diff --git a/README.md b/README.md
index a0439a8c..57fcd70c 100644
--- a/README.md
+++ b/README.md
@@ -4,67 +4,55 @@ This tutorial was designed for easily diving into TensorFlow, through examples.
It is suitable for beginners who want to find clear and concise examples about TensorFlow. Besides the traditional 'raw' TensorFlow implementations, you can also find the latest TensorFlow API practices (such as `layers`, `estimator`, `dataset`, ...).
-**Update (07/14/2019):** Added a few [TensorFlow v2 examples](tensorflow_v2)! (more coming soon).
-
-*If you are using older TensorFlow version (0.11 and under), please take a [look here](https://github.com/nebulaai/TensorFlow-Examples/tree/0.11).*
+**Update (05/16/2020):** Moving all default examples to TF2. For TF v1 examples: [check here](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1).
## Tutorial index
#### 0 - Prerequisite
-- [Introduction to Machine Learning](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/0_Prerequisite/ml_introduction.ipynb).
-- [Introduction to MNIST Dataset](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb).
-- [Tensorflow GPU Validation](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/0_Prerequisite/tensorflow_gpu_validator.ipynb).
+- [Introduction to Machine Learning](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/0_Prerequisite/ml_introduction.ipynb).
+- [Introduction to MNIST Dataset](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb).
#### 1 - Introduction
-- **Hello World** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/1_Introduction/helloworld.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/1_Introduction/helloworld.py)). Very simple example to learn how to print "hello world" using TensorFlow.
-- **Basic Operations** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/1_Introduction/basic_operations.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/1_Introduction/basic_operations.py)). A simple example that cover TensorFlow basic operations.
-- **TensorFlow Eager API basics** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/1_Introduction/basic_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/1_Introduction/basic_eager_api.py)). Get started with TensorFlow's Eager API.
+- **Hello World** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/1_Introduction/helloworld.ipynb)). Very simple example to learn how to print "hello world" using TensorFlow 2.0+.
+- **Basic Operations** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/1_Introduction/basic_operations.ipynb)). A simple example that cover TensorFlow 2.0+ basic operations.
#### 2 - Basic Models
-- **Linear Regression** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/linear_regression.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/2_BasicModels/linear_regression.py)). Implement a Linear Regression with TensorFlow.
-- **Linear Regression (eager api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/linear_regression_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/2_BasicModels/linear_regression_eager_api.py)). Implement a Linear Regression using TensorFlow's Eager API.
-- **Logistic Regression** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/logistic_regression.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/2_BasicModels/logistic_regression.py)). Implement a Logistic Regression with TensorFlow.
-- **Logistic Regression (eager api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/logistic_regression_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/2_BasicModels/logistic_regression_eager_api.py)). Implement a Logistic Regression using TensorFlow's Eager API.
-- **Nearest Neighbor** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/nearest_neighbor.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/2_BasicModels/nearest_neighbor.py)). Implement Nearest Neighbor algorithm with TensorFlow.
-- **K-Means** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/kmeans.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/2_BasicModels/kmeans.py)). Build a K-Means classifier with TensorFlow.
-- **Random Forest** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/random_forest.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/2_BasicModels/random_forest.py)). Build a Random Forest classifier with TensorFlow.
-- **Gradient Boosted Decision Tree (GBDT)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/gradient_boosted_decision_tree.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/2_BasicModels/gradient_boosted_decision_tree.py)). Build a Gradient Boosted Decision Tree (GBDT) with TensorFlow.
-- **Word2Vec (Word Embedding)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/2_BasicModels/word2vec.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/2_BasicModels/word2vec.py)). Build a Word Embedding Model (Word2Vec) from Wikipedia data, with TensorFlow.
+- **Linear Regression** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/2_BasicModels/linear_regression.ipynb)). Implement a Linear Regression with TensorFlow 2.0+.
+- **Logistic Regression** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/2_BasicModels/logistic_regression.ipynb)). Implement a Logistic Regression with TensorFlow 2.0+.
+- **Word2Vec (Word Embedding)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/2_BasicModels/word2vec.ipynb)). Build a Word Embedding Model (Word2Vec) from Wikipedia data, with TensorFlow 2.0+.
+- **GBDT (Gradient Boosted Decision Trees)** ([notebooks](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/2_BasicModels/gradient_boosted_trees.ipynb)). Implement a Gradient Boosted Decision Trees with TensorFlow 2.0+ to predict house value using Boston Housing dataset.
#### 3 - Neural Networks
##### Supervised
-- **Simple Neural Network** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/neural_network_raw.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/neural_network_raw.py)). Build a simple neural network (a.k.a Multi-layer Perceptron) to classify MNIST digits dataset. Raw TensorFlow implementation.
-- **Simple Neural Network (tf.layers/estimator api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/neural_network.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/neural_network.py)). Use TensorFlow 'layers' and 'estimator' API to build a simple neural network (a.k.a Multi-layer Perceptron) to classify MNIST digits dataset.
-- **Simple Neural Network (eager api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/neural_network_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/neural_network_eager_api.py)). Use TensorFlow Eager API to build a simple neural network (a.k.a Multi-layer Perceptron) to classify MNIST digits dataset.
-- **Convolutional Neural Network** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/convolutional_network_raw.py)). Build a convolutional neural network to classify MNIST digits dataset. Raw TensorFlow implementation.
-- **Convolutional Neural Network (tf.layers/estimator api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/convolutional_network.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/convolutional_network.py)). Use TensorFlow 'layers' and 'estimator' API to build a convolutional neural network to classify MNIST digits dataset.
-- **Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/recurrent_network.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/recurrent_network.py)). Build a recurrent neural network (LSTM) to classify MNIST digits dataset.
-- **Bi-directional Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/bidirectional_rnn.py)). Build a bi-directional recurrent neural network (LSTM) to classify MNIST digits dataset.
-- **Dynamic Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/dynamic_rnn.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/dynamic_rnn.py)). Build a recurrent neural network (LSTM) that performs dynamic calculation to classify sequences of different length.
+- **Simple Neural Network** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/3_NeuralNetworks/neural_network.ipynb)). Use TensorFlow 2.0 'layers' and 'model' API to build a simple neural network to classify MNIST digits dataset.
+- **Simple Neural Network (low-level)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/3_NeuralNetworks/neural_network_raw.ipynb)). Raw implementation of a simple neural network to classify MNIST digits dataset.
+- **Convolutional Neural Network** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/3_NeuralNetworks/convolutional_network.ipynb)). Use TensorFlow 2.0+ 'layers' and 'model' API to build a convolutional neural network to classify MNIST digits dataset.
+- **Convolutional Neural Network (low-level)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb)). Raw implementation of a convolutional neural network to classify MNIST digits dataset.
+- **Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/3_NeuralNetworks/recurrent_network.ipynb)). Build a recurrent neural network (LSTM) to classify MNIST digits dataset, using TensorFlow 2.0 'layers' and 'model' API.
+- **Bi-directional Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb)). Build a bi-directional recurrent neural network (LSTM) to classify MNIST digits dataset, using TensorFlow 2.0+ 'layers' and 'model' API.
+- **Dynamic Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/3_NeuralNetworks/dynamic_rnn.ipynb)). Build a recurrent neural network (LSTM) that performs dynamic calculation to classify sequences of variable length, using TensorFlow 2.0+ 'layers' and 'model' API.
##### Unsupervised
-- **Auto-Encoder** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/autoencoder.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/autoencoder.py)). Build an auto-encoder to encode an image to a lower dimension and re-construct it.
-- **Variational Auto-Encoder** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/variational_autoencoder.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/variational_autoencoder.py)). Build a variational auto-encoder (VAE), to encode and generate images from noise.
-- **GAN (Generative Adversarial Networks)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/gan.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/gan.py)). Build a Generative Adversarial Network (GAN) to generate images from noise.
-- **DCGAN (Deep Convolutional Generative Adversarial Networks)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/3_NeuralNetworks/dcgan.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/3_NeuralNetworks/dcgan.py)). Build a Deep Convolutional Generative Adversarial Network (DCGAN) to generate images from noise.
+- **Auto-Encoder** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/3_NeuralNetworks/autoencoder.ipynb)). Build an auto-encoder to encode an image to a lower dimension and re-construct it.
+- **DCGAN (Deep Convolutional Generative Adversarial Networks)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/3_NeuralNetworks/dcgan.ipynb)). Build a Deep Convolutional Generative Adversarial Network (DCGAN) to generate images from noise.
#### 4 - Utilities
-- **Save and Restore a model** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/4_Utils/save_restore_model.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/4_Utils/save_restore_model.py)). Save and Restore a model with TensorFlow.
-- **Tensorboard - Graph and loss visualization** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/4_Utils/tensorboard_basic.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/4_Utils/tensorboard_basic.py)). Use Tensorboard to visualize the computation Graph and plot the loss.
-- **Tensorboard - Advanced visualization** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/4_Utils/tensorboard_advanced.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/4_Utils/tensorboard_advanced.py)). Going deeper into Tensorboard; visualize the variables, gradients, and more...
+- **Save and Restore a model** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/4_Utils/save_restore_model.ipynb)). Save and Restore a model with TensorFlow 2.0+.
+- **Build Custom Layers & Modules** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/4_Utils/build_custom_layers.ipynb)). Learn how to build your own layers / modules and integrate them into TensorFlow 2.0+ Models.
+- **Tensorboard** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/4_Utils/tensorboard.ipynb)). Track and visualize neural network computation graph, metrics, weights and more using TensorFlow 2.0+ tensorboard.
#### 5 - Data Management
-- **Build an image dataset** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/5_DataManagement/build_an_image_dataset.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/5_DataManagement/build_an_image_dataset.py)). Build your own images dataset with TensorFlow data queues, from image folders or a dataset file.
-- **TensorFlow Dataset API** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/5_DataManagement/tensorflow_dataset_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/5_DataManagement/tensorflow_dataset_api.py)). Introducing TensorFlow Dataset API for optimizing the input data pipeline.
+- **Load and Parse data** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/5_DataManagement/load_data.ipynb)). Build efficient data pipeline with TensorFlow 2.0 (Numpy arrays, Images, CSV files, custom data, ...).
+- **Build and Load TFRecords** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/5_DataManagement/tfrecords.ipynb)). Convert data into TFRecords format, and load them with TensorFlow 2.0+.
+- **Image Transformation (i.e. Image Augmentation)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/5_DataManagement/image_transformation.ipynb)). Apply various image augmentation techniques with TensorFlow 2.0+, to generate distorted images for training.
-#### 6 - Multi GPU
-- **Basic Operations on multi-GPU** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/6_MultiGPU/multigpu_basics.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/6_MultiGPU/multigpu_basics.py)). A simple example to introduce multi-GPU in TensorFlow.
-- **Train a Neural Network on multi-GPU** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/6_MultiGPU/multigpu_cnn.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/examples/6_MultiGPU/multigpu_cnn.py)). A clear and simple TensorFlow implementation to train a convolutional neural network on multiple GPUs.
+#### 6 - Hardware
+- **Multi-GPU Training** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/6_Hardware/multigpu_training.ipynb)). Train a convolutional neural network with multiple GPUs on CIFAR-10 dataset.
-## TensorFlow 2.0
+## TensorFlow v1
-The tutorial index for TF v2 is available here: [TensorFlow 2.0 Examples](tensorflow_v2).
+The tutorial index for TF v1 is available here: [TensorFlow v1.15 Examples](tensorflow_v1). Or see below for a list of the examples.
## Dataset
Some examples require MNIST dataset for training and testing. Don't worry, this dataset will automatically be downloaded when running examples.
@@ -91,11 +79,64 @@ pip install tensorflow_gpu
For more details about TensorFlow installation, you can check [TensorFlow Installation Guide](https://www.tensorflow.org/install/)
-## More Examples
-The following examples are coming from [TFLearn](https://github.com/tflearn/tflearn), a library that provides a simplified interface for TensorFlow. You can have a look, there are many [examples](https://github.com/tflearn/tflearn/tree/master/examples) and [pre-built operations and layers](http://tflearn.org/doc_index/#api).
-### Tutorials
-- [TFLearn Quickstart](https://github.com/tflearn/tflearn/blob/master/tutorials/intro/quickstart.md). Learn the basics of TFLearn through a concrete machine learning task. Build and train a deep neural network classifier.
+## TensorFlow v1 Examples - Index
+
+The tutorial index for TF v1 is available here: [TensorFlow v1.15 Examples](tensorflow_v1).
+
+#### 0 - Prerequisite
+- [Introduction to Machine Learning](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/tensorflow_v1/0_Prerequisite/ml_introduction.ipynb).
+- [Introduction to MNIST Dataset](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/tensorflow_v1/0_Prerequisite/mnist_dataset_intro.ipynb).
+
+#### 1 - Introduction
+- **Hello World** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/1_Introduction/helloworld.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/1_Introduction/helloworld.py)). Very simple example to learn how to print "hello world" using TensorFlow.
+- **Basic Operations** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/tensorflow_v1/1_Introduction/basic_operations.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-examples/Examples/blob/master/tensorflow_v1/1_Introduction/basic_operations.py)). A simple example that cover TensorFlow basic operations.
+- **TensorFlow Eager API basics** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/1_Introduction/basic_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/1_Introduction/basic_eager_api.py)). Get started with TensorFlow's Eager API.
+
+#### 2 - Basic Models
+- **Linear Regression** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/linear_regression.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/linear_regression.py)). Implement a Linear Regression with TensorFlow.
+- **Linear Regression (eager api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/linear_regression_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/linear_regression_eager_api.py)). Implement a Linear Regression using TensorFlow's Eager API.
+- **Logistic Regression** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/logistic_regression.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/logistic_regression.py)). Implement a Logistic Regression with TensorFlow.
+- **Logistic Regression (eager api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/logistic_regression_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/logistic_regression_eager_api.py)). Implement a Logistic Regression using TensorFlow's Eager API.
+- **Nearest Neighbor** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/nearest_neighbor.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/nearest_neighbor.py)). Implement Nearest Neighbor algorithm with TensorFlow.
+- **K-Means** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/kmeans.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/kmeans.py)). Build a K-Means classifier with TensorFlow.
+- **Random Forest** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/random_forest.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/random_forest.py)). Build a Random Forest classifier with TensorFlow.
+- **Gradient Boosted Decision Tree (GBDT)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/gradient_boosted_decision_tree.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/gradient_boosted_decision_tree.py)). Build a Gradient Boosted Decision Tree (GBDT) with TensorFlow.
+- **Word2Vec (Word Embedding)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/word2vec.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/word2vec.py)). Build a Word Embedding Model (Word2Vec) from Wikipedia data, with TensorFlow.
+
+#### 3 - Neural Networks
+##### Supervised
+
+- **Simple Neural Network** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/3_NeuralNetworks/notebooks/neural_network_raw.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/neural_network_raw.py)). Build a simple neural network (a.k.a Multi-layer Perceptron) to classify MNIST digits dataset. Raw TensorFlow implementation.
+- **Simple Neural Network (tf.layers/estimator api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/neural_network.py)). Use TensorFlow 'layers' and 'estimator' API to build a simple neural network (a.k.a Multi-layer Perceptron) to classify MNIST digits dataset.
+- **Simple Neural Network (eager api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/neural_network_eager_api.py)). Use TensorFlow Eager API to build a simple neural network (a.k.a Multi-layer Perceptron) to classify MNIST digits dataset.
+- **Convolutional Neural Network** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/convolutional_network_raw.py)). Build a convolutional neural network to classify MNIST digits dataset. Raw TensorFlow implementation.
+- **Convolutional Neural Network (tf.layers/estimator api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/convolutional_network.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/convolutional_network.py)). Use TensorFlow 'layers' and 'estimator' API to build a convolutional neural network to classify MNIST digits dataset.
+- **Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/recurrent_network.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/recurrent_network.py)). Build a recurrent neural network (LSTM) to classify MNIST digits dataset.
+- **Bi-directional Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/bidirectional_rnn.py)). Build a bi-directional recurrent neural network (LSTM) to classify MNIST digits dataset.
+- **Dynamic Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/dynamic_rnn.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/dynamic_rnn.py)). Build a recurrent neural network (LSTM) that performs dynamic calculation to classify sequences of different length.
+
+##### Unsupervised
+- **Auto-Encoder** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/autoencoder.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/autoencoder.py)). Build an auto-encoder to encode an image to a lower dimension and re-construct it.
+- **Variational Auto-Encoder** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/variational_autoencoder.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/variational_autoencoder.py)). Build a variational auto-encoder (VAE), to encode and generate images from noise.
+- **GAN (Generative Adversarial Networks)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/gan.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/gan.py)). Build a Generative Adversarial Network (GAN) to generate images from noise.
+- **DCGAN (Deep Convolutional Generative Adversarial Networks)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/dcgan.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/dcgan.py)). Build a Deep Convolutional Generative Adversarial Network (DCGAN) to generate images from noise.
+
+#### 4 - Utilities
+- **Save and Restore a model** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/4_Utils/save_restore_model.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/4_Utils/save_restore_model.py)). Save and Restore a model with TensorFlow.
+- **Tensorboard - Graph and loss visualization** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/4_Utils/tensorboard_basic.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/4_Utils/tensorboard_basic.py)). Use Tensorboard to visualize the computation Graph and plot the loss.
+- **Tensorboard - Advanced visualization** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/4_Utils/tensorboard_advanced.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/4_Utils/tensorboard_advanced.py)). Going deeper into Tensorboard; visualize the variables, gradients, and more...
+
+#### 5 - Data Management
+- **Build an image dataset** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/5_DataManagement/build_an_image_dataset.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/5_DataManagement/build_an_image_dataset.py)). Build your own images dataset with TensorFlow data queues, from image folders or a dataset file.
+- **TensorFlow Dataset API** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/5_DataManagement/tensorflow_dataset_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/5_DataManagement/tensorflow_dataset_api.py)). Introducing TensorFlow Dataset API for optimizing the input data pipeline.
+- **Load and Parse data** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/5_DataManagement/load_data.ipynb)). Build efficient data pipeline (Numpy arrays, Images, CSV files, custom data, ...).
+- **Build and Load TFRecords** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/5_DataManagement/tfrecords.ipynb)). Convert data into TFRecords format, and load them.
+- **Image Transformation (i.e. Image Augmentation)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/5_DataManagement/image_transformation.ipynb)). Apply various image augmentation techniques, to generate distorted images for training.
+
+#### 6 - Multi GPU
+- **Basic Operations on multi-GPU** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/6_MultiGPU/multigpu_basics.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/6_MultiGPU/multigpu_basics.py)). A simple example to introduce multi-GPU in TensorFlow.
+- **Train a Neural Network on multi-GPU** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/6_MultiGPU/multigpu_cnn.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/6_MultiGPU/multigpu_cnn.py)). A clear and simple TensorFlow implementation to train a convolutional neural network on multiple GPUs.
### Examples
- [TFLearn Examples](https://github.com/tflearn/tflearn/blob/master/examples). A large collection of examples using TFLearn.
@@ -121,4 +162,4 @@ config = tf.ConfigProto()
config.gpu_options.allow_growth=True
sess = tf.Session(config=config)
```
-5. Testing pass on Nebula AI Orion Notebook.
+5. Testing pass on Nebula AI Orion Notebook.
\ No newline at end of file
diff --git a/examples/README.md b/examples/README.md
new file mode 100644
index 00000000..196ed016
--- /dev/null
+++ b/examples/README.md
@@ -0,0 +1,5 @@
+## Deprecated - Please Read
+
+Due to TensorFlow radically changing their API in v2, the examples index have been split between [v1](../tensorflow_v1) and [v2](../tensorflow_v2).
+
+The following examples are the original TF v1 examples, and will be deprecated entirely in favor of [tensorflow_v1](../tensorflow_v1) directory in a future release.
diff --git a/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb b/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb
index aa2d2458..5be58b78 100644
--- a/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb
+++ b/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb
@@ -21,7 +21,7 @@
"
\n",
"\n",
"References:\n",
- "- [Long Short Term Memory](http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf), Sepp Hochreiter & Jurgen Schmidhuber, Neural Computation 9(8): 1735-1780, 1997.\n",
+ "- [Long Short Term Memory](https://www.researchgate.net/profile/Sepp_Hochreiter/publication/13853244_Long_Short-term_Memory/links/5700e75608aea6b7746a0624/Long-Short-term-Memory.pdf), Sepp Hochreiter & Jurgen Schmidhuber, Neural Computation 9(8): 1735-1780, 1997.\n",
"\n",
"## MNIST Dataset Overview\n",
"\n",
diff --git a/notebooks/5_DataManagement/image_transformation.ipynb b/notebooks/5_DataManagement/image_transformation.ipynb
new file mode 100644
index 00000000..56cc9c2e
--- /dev/null
+++ b/notebooks/5_DataManagement/image_transformation.ipynb
@@ -0,0 +1,418 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Image Transformation (i.e. Image Augmentation)\n",
+ "\n",
+ "Learn how to apply various image augmentation techniques with TensorFlow. The transformations are meant to be applied for each image sample when training only, and each transformation will be performed with random parameters.\n",
+ "\n",
+ "**Transformations:**\n",
+ "- Random flip left-right\n",
+ "- Random contrast, brightness, saturation and hue\n",
+ "- Random distortion and crop\n",
+ "\n",
+ "For more information about loading data, see: [load_data.ipynb](load_data.ipynb)\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "from IPython.display import Image as IImage, display\n",
+ "import numpy as np\n",
+ "import PIL\n",
+ "from PIL import Image\n",
+ "import random\n",
+ "import requests\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download an image.\n",
+ "d = requests.get(\"https://www.paristoolkit.com/Images/xeffel_view.jpg.pagespeed.ic.8XcZNqpzSj.jpg\")\n",
+ "with open(\"image.jpeg\", \"wb\") as f:\n",
+ " f.write(d.content)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load image to numpy array.\n",
+ "img = PIL.Image.open('image.jpeg')\n",
+ "img.load()\n",
+ "img_array = np.array(img)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image.\n",
+ "PIL.Image.fromarray(img_array)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create TensorFlow session.\n",
+ "session = tf.Session()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly flip an image.\n",
+ "def random_flip_left_right(image):\n",
+ " return tf.image.random_flip_left_right(image)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display randomly flipped image.\n",
+ "PIL.Image.fromarray(random_flip_left_right(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image contrast.\n",
+ "def random_contrast(image, minval=0.6, maxval=1.4):\n",
+ " r = tf.random.uniform([], minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_contrast(image, contrast_factor=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different contrast.\n",
+ "PIL.Image.fromarray(random_contrast(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image brightness\n",
+ "def random_brightness(image, minval=0., maxval=.2):\n",
+ " r = tf.random.uniform([], minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_brightness(image, delta=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different brightness.\n",
+ "PIL.Image.fromarray(random_brightness(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image saturation\n",
+ "def random_saturation(image, minval=0.4, maxval=2.):\n",
+ " r = tf.random.uniform((), minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_saturation(image, saturation_factor=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different staturation.\n",
+ "PIL.Image.fromarray(random_saturation(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image hue.\n",
+ "def random_hue(image, minval=-0.04, maxval=0.08):\n",
+ " r = tf.random.uniform((), minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_hue(image, delta=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different hue.\n",
+ "PIL.Image.fromarray(random_hue(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Distort an image by cropping it with a different aspect ratio.\n",
+ "def distorted_random_crop(image,\n",
+ " min_object_covered=0.1,\n",
+ " aspect_ratio_range=(3./4., 4./3.),\n",
+ " area_range=(0.06, 1.0),\n",
+ " max_attempts=100,\n",
+ " scope=None):\n",
+ "\n",
+ " cropbox = tf.constant([0.0, 0.0, 1.0, 1.0], dtype=tf.float32, shape=[1, 1, 4])\n",
+ " sample_distorted_bounding_box = tf.image.sample_distorted_bounding_box(\n",
+ " tf.shape(image),\n",
+ " bounding_boxes=cropbox,\n",
+ " min_object_covered=min_object_covered,\n",
+ " aspect_ratio_range=aspect_ratio_range,\n",
+ " area_range=area_range,\n",
+ " max_attempts=max_attempts,\n",
+ " use_image_if_no_bounding_boxes=True)\n",
+ " bbox_begin, bbox_size, distort_bbox = sample_distorted_bounding_box\n",
+ "\n",
+ " # Crop the image to the specified bounding box.\n",
+ " cropped_image = tf.slice(image, bbox_begin, bbox_size)\n",
+ " return cropped_image"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display cropped image.\n",
+ "PIL.Image.fromarray(distorted_random_crop(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Apply all transformations to an image.\n",
+ "# That is a common image augmentation technique for image datasets, such as ImageNet.\n",
+ "def transform_image(image):\n",
+ " image = distorted_random_crop(image)\n",
+ " image = random_flip_left_right(image)\n",
+ " image = random_contrast(image)\n",
+ " image = random_brightness(image)\n",
+ " image = random_hue(image)\n",
+ " image = random_saturation(image)\n",
+ " return image"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display fully pre-processed image.\n",
+ "transformed_img = transform_image(img_array)\n",
+ "PIL.Image.fromarray(transformed_img.eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Resize transformed image to a 256x256px square image, ready for training.\n",
+ "def resize_image(image):\n",
+ " image = tf.image.resize(image, size=(256, 256), preserve_aspect_ratio=False)\n",
+ " image = tf.cast(image, tf.uint8)\n",
+ " return image"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display resized image.\n",
+ "PIL.Image.fromarray(resize_image(transformed_img).eval(session=session))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "tf1",
+ "language": "python",
+ "name": "tf1"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15+"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/notebooks/5_DataManagement/load_data.ipynb b/notebooks/5_DataManagement/load_data.ipynb
new file mode 100644
index 00000000..c71e76a0
--- /dev/null
+++ b/notebooks/5_DataManagement/load_data.ipynb
@@ -0,0 +1,577 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Load and parse data with TensorFlow\n",
+ "\n",
+ "A TensorFlow example to build input pipelines for loading data efficiently.\n",
+ "\n",
+ "\n",
+ "- Numpy Arrays\n",
+ "- Images\n",
+ "- CSV file\n",
+ "- Custom data from a Generator\n",
+ "\n",
+ "For more information about creating and loading TensorFlow's `TFRecords` data format, see: [tfrecords.ipynb](tfrecords.ipynb)\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import numpy as np\n",
+ "import random\n",
+ "import requests\n",
+ "import string\n",
+ "import tarfile\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load Numpy Arrays\n",
+ "\n",
+ "Build a data pipeline over numpy arrays."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create a toy dataset (even and odd numbers, with respective labels of 0 and 1).\n",
+ "evens = np.arange(0, 100, step=2, dtype=np.int32)\n",
+ "evens_label = np.zeros(50, dtype=np.int32)\n",
+ "odds = np.arange(1, 100, step=2, dtype=np.int32)\n",
+ "odds_label = np.ones(50, dtype=np.int32)\n",
+ "# Concatenate arrays\n",
+ "features = np.concatenate([evens, odds])\n",
+ "labels = np.concatenate([evens_label, odds_label])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with tf.Graph().as_default():\n",
+ " # Create TF session.\n",
+ " sess = tf.Session()\n",
+ " \n",
+ " # Slice the numpy arrays (each row becoming a record).\n",
+ " data = tf.data.Dataset.from_tensor_slices((features, labels))\n",
+ " # Refill data indefinitely. \n",
+ " data = data.repeat()\n",
+ " # Shuffle data.\n",
+ " data = data.shuffle(buffer_size=100)\n",
+ " # Batch data (aggregate records together).\n",
+ " data = data.batch(batch_size=4)\n",
+ " # Prefetch batch (pre-load batch for faster consumption).\n",
+ " data = data.prefetch(buffer_size=1)\n",
+ " \n",
+ " # Create an iterator over the dataset.\n",
+ " iterator = data.make_initializable_iterator()\n",
+ " # Initialize the iterator.\n",
+ " sess.run(iterator.initializer)\n",
+ "\n",
+ " # Get next data batch.\n",
+ " d = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[82 58 80 23] [0 0 0 1]\n",
+ "[16 91 74 96] [0 1 0 0]\n",
+ "[ 4 17 32 34] [0 1 0 0]\n",
+ "[16 8 77 21] [0 0 1 1]\n",
+ "[20 99 48 18] [0 1 0 0]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Display data.\n",
+ "for i in range(5):\n",
+ " x, y = sess.run(d)\n",
+ " print(x, y)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load CSV files\n",
+ "\n",
+ "Build a data pipeline from features stored in a CSV file. For this example, Titanic dataset will be used as a toy dataset stored in CSV format."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Titanic Dataset\n",
+ "\n",
+ "\n",
+ "\n",
+ "survived|pclass|name|sex|age|sibsp|parch|ticket|fare\n",
+ "--------|------|----|---|---|-----|-----|------|----\n",
+ "1|1|\"Allen, Miss. Elisabeth Walton\"|female|29|0|0|24160|211.3375\n",
+ "1|1|\"Allison, Master. Hudson Trevor\"|male|0.9167|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Miss. Helen Loraine\"|female|2|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Mr. Hudson Joshua Creighton\"|male|30|1|2|113781|151.5500\n",
+ "...|...|...|...|...|...|...|...|..."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download Titanic dataset (in csv format).\n",
+ "d = requests.get(\"https://raw.githubusercontent.com/tflearn/tflearn.github.io/master/resources/titanic_dataset.csv\")\n",
+ "with open(\"titanic_dataset.csv\", \"wb\") as f:\n",
+ " f.write(d.content)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load Titanic dataset.\n",
+ "# Original features: survived,pclass,name,sex,age,sibsp,parch,ticket,fare\n",
+ "# Select specific columns: survived,pclass,name,sex,age,fare\n",
+ "column_to_use = [0, 1, 2, 3, 4, 8]\n",
+ "record_defaults = [tf.int32, tf.int32, tf.string, tf.string, tf.float32, tf.float32]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with tf.Graph().as_default():\n",
+ " # Create TF session.\n",
+ " sess = tf.Session()\n",
+ " \n",
+ " # Load the whole dataset file, and slice each line.\n",
+ " data = tf.data.experimental.CsvDataset(\"titanic_dataset.csv\", record_defaults, header=True, select_cols=column_to_use)\n",
+ " # Refill data indefinitely. \n",
+ " data = data.repeat()\n",
+ " # Shuffle data.\n",
+ " data = data.shuffle(buffer_size=1000)\n",
+ " # Batch data (aggregate records together).\n",
+ " data = data.batch(batch_size=2)\n",
+ " # Prefetch batch (pre-load batch for faster consumption).\n",
+ " data = data.prefetch(buffer_size=1)\n",
+ " \n",
+ " # Create an iterator over the dataset.\n",
+ " iterator = data.make_initializable_iterator()\n",
+ " # Initialize the iterator.\n",
+ " sess.run(iterator.initializer)\n",
+ "\n",
+ " # Get next data batch.\n",
+ " d = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[1 0]\n",
+ "[3 1]\n",
+ "['Lam, Mr. Ali' 'Widener, Mr. Harry Elkins']\n",
+ "['male' 'male']\n",
+ "[ 0. 27.]\n",
+ "[ 56.4958 211.5 ]\n",
+ "\n",
+ "[0 1]\n",
+ "[1 1]\n",
+ "['Baumann, Mr. John D' 'Daly, Mr. Peter Denis ']\n",
+ "['male' 'male']\n",
+ "[ 0. 51.]\n",
+ "[25.925 26.55 ]\n",
+ "\n",
+ "[0 1]\n",
+ "[3 1]\n",
+ "['Assam, Mr. Ali' 'Newell, Miss. Madeleine']\n",
+ "['male' 'female']\n",
+ "[23. 31.]\n",
+ "[ 7.05 113.275]\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Display data.\n",
+ "for i in range(3):\n",
+ " survived, pclass, name, sex, age, fare = sess.run(d)\n",
+ " print(survived)\n",
+ " print(pclass)\n",
+ " print(name)\n",
+ " print(sex)\n",
+ " print(age)\n",
+ " print(fare)\n",
+ " print(\"\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load Images\n",
+ "\n",
+ "Build a data pipeline by loading images from disk. For this example, Oxford Flowers dataset will be used."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download Oxford 17 flowers dataset.\n",
+ "d = requests.get(\"http://www.robots.ox.ac.uk/~vgg/data/flowers/17/17flowers.tgz\")\n",
+ "with open(\"17flowers.tgz\", \"wb\") as f:\n",
+ " f.write(d.content)\n",
+ "# Extract archive.\n",
+ "with tarfile.open(\"17flowers.tgz\") as t:\n",
+ " t.extractall()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create a file to list all images path and their corresponding label.\n",
+ "with open('jpg/dataset.csv', 'w') as f:\n",
+ " c = 0\n",
+ " for i in range(1360):\n",
+ " f.write(\"jpg/image_%04i.jpg,%i\\n\" % (i+1, c))\n",
+ " if (i+1) % 80 == 0:\n",
+ " c += 1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with tf.Graph().as_default():\n",
+ " \n",
+ " # Load Images.\n",
+ " with open(\"jpg/dataset.csv\") as f:\n",
+ " dataset_file = f.read().splitlines()\n",
+ " \n",
+ " # Create TF session.\n",
+ " sess = tf.Session()\n",
+ "\n",
+ " # Load the whole dataset file, and slice each line.\n",
+ " data = tf.data.Dataset.from_tensor_slices(dataset_file)\n",
+ " # Refill data indefinitely.\n",
+ " data = data.repeat()\n",
+ " # Shuffle data.\n",
+ " data = data.shuffle(buffer_size=1000)\n",
+ "\n",
+ " # Load and pre-process images.\n",
+ " def load_image(path):\n",
+ " # Read image from path.\n",
+ " image = tf.io.read_file(path)\n",
+ " # Decode the jpeg image to array [0, 255].\n",
+ " image = tf.image.decode_jpeg(image)\n",
+ " # Resize images to a common size of 256x256.\n",
+ " image = tf.image.resize(image, [256, 256])\n",
+ " # Rescale values to [-1, 1].\n",
+ " image = 1. - image / 127.5\n",
+ " return image\n",
+ " # Decode each line from the dataset file.\n",
+ " def parse_records(line):\n",
+ " # File is in csv format: \"image_path,label_id\".\n",
+ " # TensorFlow requires a default value, but it will never be used.\n",
+ " image_path, image_label = tf.io.decode_csv(line, [\"\", 0])\n",
+ " # Apply the function to load images.\n",
+ " image = load_image(image_path)\n",
+ " return image, image_label\n",
+ " # Use 'map' to apply the above functions in parallel.\n",
+ " data = data.map(parse_records, num_parallel_calls=4)\n",
+ "\n",
+ " # Batch data (aggregate images-array together).\n",
+ " data = data.batch(batch_size=2)\n",
+ " # Prefetch batch (pre-load batch for faster consumption).\n",
+ " data = data.prefetch(buffer_size=1)\n",
+ " \n",
+ " # Create an iterator over the dataset.\n",
+ " iterator = data.make_initializable_iterator()\n",
+ " # Initialize the iterator.\n",
+ " sess.run(iterator.initializer)\n",
+ "\n",
+ " # Get next data batch.\n",
+ " d = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[[[[ 0.1294117 0.05098033 0.46666664]\n",
+ " [ 0.1368872 0.05098033 0.48909312]\n",
+ " [ 0.0931372 0.0068627 0.46029407]\n",
+ " ...\n",
+ " [ 0.23480386 0.0522058 0.6102941 ]\n",
+ " [ 0.12696075 -0.05416667 0.38063723]\n",
+ " [-0.10024512 -0.28848052 0.10367644]]\n",
+ "\n",
+ " [[ 0.04120708 -0.06118262 0.36256123]\n",
+ " [ 0.08009624 -0.02229345 0.41640145]\n",
+ " [ 0.06797445 -0.04132879 0.41923058]\n",
+ " ...\n",
+ " [ 0.2495715 0.06697345 0.6251221 ]\n",
+ " [ 0.12058818 -0.06094813 0.37577546]\n",
+ " [-0.05184889 -0.24009418 0.16777915]]\n",
+ "\n",
+ " [[-0.09234071 -0.22738981 0.20484066]\n",
+ " [-0.03100491 -0.17312062 0.2811274 ]\n",
+ " [ 0.01051998 -0.13237214 0.3376838 ]\n",
+ " ...\n",
+ " [ 0.27787983 0.07494056 0.64203525]\n",
+ " [ 0.11533964 -0.09005249 0.3869906 ]\n",
+ " [-0.02704227 -0.23958337 0.19454747]]\n",
+ "\n",
+ " ...\n",
+ "\n",
+ " [[ 0.07913595 -0.13069856 0.29874384]\n",
+ " [ 0.10140878 -0.09445572 0.35912937]\n",
+ " [ 0.08869672 -0.08415675 0.41446364]\n",
+ " ...\n",
+ " [ 0.25821072 0.22463232 0.69197303]\n",
+ " [ 0.31636214 0.25750512 0.79362744]\n",
+ " [ 0.09552741 0.01709598 0.57395875]]\n",
+ "\n",
+ " [[ 0.09019601 -0.12156868 0.3098039 ]\n",
+ " [ 0.17446858 -0.02271283 0.43218917]\n",
+ " [ 0.06583172 -0.10818791 0.39230233]\n",
+ " ...\n",
+ " [ 0.27021956 0.23664117 0.70269513]\n",
+ " [ 0.19560927 0.1385014 0.6740407 ]\n",
+ " [ 0.04364848 -0.03478289 0.5220798 ]]\n",
+ "\n",
+ " [[ 0.02830875 -0.18345594 0.24791664]\n",
+ " [ 0.12937105 -0.06781042 0.38709164]\n",
+ " [ 0.01120263 -0.162817 0.33767325]\n",
+ " ...\n",
+ " [ 0.25989532 0.22631687 0.69237083]\n",
+ " [ 0.1200884 0.06298059 0.5985198 ]\n",
+ " [ 0.05961001 -0.01882136 0.53804135]]]\n",
+ "\n",
+ "\n",
+ " [[[ 0.3333333 0.25490195 0.05882347]\n",
+ " [ 0.3333333 0.25490195 0.05882347]\n",
+ " [ 0.3340686 0.24705875 0.03039211]\n",
+ " ...\n",
+ " [-0.5215688 -0.4599266 -0.14632356]\n",
+ " [-0.5100491 -0.47083342 -0.03725493]\n",
+ " [-0.43419123 -0.39497554 0.05992639]]\n",
+ "\n",
+ " [[ 0.34117645 0.26274508 0.0666666 ]\n",
+ " [ 0.35646445 0.2630821 0.0744791 ]\n",
+ " [ 0.3632046 0.2548713 0.04384762]\n",
+ " ...\n",
+ " [-0.9210479 -0.84267783 -0.4540485 ]\n",
+ " [-0.9017464 -0.8390626 -0.3507018 ]\n",
+ " [-0.83339334 -0.7632048 -0.2534927 ]]\n",
+ "\n",
+ " [[ 0.3646446 0.2706495 0.06678915]\n",
+ " [ 0.37248772 0.27837008 0.07445425]\n",
+ " [ 0.38033658 0.27053267 0.05950326]\n",
+ " ...\n",
+ " [-0.94302344 -0.84222686 -0.30278325]\n",
+ " [-0.91017747 -0.8090074 -0.18615782]\n",
+ " [-0.83437514 -0.7402575 -0.08192408]]\n",
+ "\n",
+ " ...\n",
+ "\n",
+ " [[ 0.64705884 0.654902 0.67058825]\n",
+ " [ 0.6318321 0.63967526 0.65536153]\n",
+ " [ 0.63128924 0.6391324 0.65481865]\n",
+ " ...\n",
+ " [ 0.6313726 0.57647055 0.51372546]\n",
+ " [ 0.6078431 0.53725487 0.4823529 ]\n",
+ " [ 0.6078431 0.53725487 0.4823529 ]]\n",
+ "\n",
+ " [[ 0.654902 0.654902 0.6704657 ]\n",
+ " [ 0.654902 0.654902 0.6704657 ]\n",
+ " [ 0.64778835 0.64778835 0.6492474 ]\n",
+ " ...\n",
+ " [ 0.6392157 0.5843137 0.5215686 ]\n",
+ " [ 0.6393325 0.56874424 0.5138422 ]\n",
+ " [ 0.63106614 0.5604779 0.50557595]]\n",
+ "\n",
+ " [[ 0.654902 0.64705884 0.6313726 ]\n",
+ " [ 0.6548728 0.64702964 0.63134336]\n",
+ " [ 0.64705884 0.63210785 0.6377451 ]\n",
+ " ...\n",
+ " [ 0.63244915 0.5775472 0.5148021 ]\n",
+ " [ 0.6698529 0.5992647 0.5443627 ]\n",
+ " [ 0.6545358 0.5839475 0.5290455 ]]]] [5 9]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Display data.\n",
+ "for i in range(1):\n",
+ " batch_x, batch_y = sess.run(d)\n",
+ " print(batch_x, batch_y)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load data from a Generator\n",
+ "\n",
+ "Build a data pipeline from a custom generator. For this example, a toy generator yielding random string, vector and it is used."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create a dummy generator.\n",
+ "def generate_features():\n",
+ " # Function to generate a random string.\n",
+ " def random_string(length):\n",
+ " return ''.join(random.choice(string.ascii_letters) for m in xrange(length))\n",
+ " # Return a random string, a random vector, and a random int.\n",
+ " yield random_string(4), np.random.uniform(size=4), random.randint(0, 10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with tf.Graph().as_default():\n",
+ "\n",
+ " # Create TF session.\n",
+ " sess = tf.Session()\n",
+ "\n",
+ " # Create TF dataset from the generator.\n",
+ " data = tf.data.Dataset.from_generator(generate_features, output_types=(tf.string, tf.float32, tf.int32))\n",
+ " # Refill data indefinitely.\n",
+ " data = data.repeat()\n",
+ " # Shuffle data.\n",
+ " data = data.shuffle(buffer_size=100)\n",
+ " # Batch data (aggregate records together).\n",
+ " data = data.batch(batch_size=4)\n",
+ " # Prefetch batch (pre-load batch for faster consumption).\n",
+ " data = data.prefetch(buffer_size=1)\n",
+ "\n",
+ " # Create an iterator over the dataset.\n",
+ " iterator = data.make_initializable_iterator()\n",
+ " # Initialize the iterator.\n",
+ " sess.run(iterator.initializer)\n",
+ "\n",
+ " # Get next data batch.\n",
+ " d = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['AvCS' 'kAaI' 'QwGX' 'IWOI'] [[0.6096093 0.32192084 0.26622605 0.70250475]\n",
+ " [0.72534287 0.7637426 0.19977213 0.74121326]\n",
+ " [0.6930984 0.09409562 0.4063325 0.5002103 ]\n",
+ " [0.05160935 0.59411395 0.276416 0.98264974]] [1 3 5 6]\n",
+ "['EXjS' 'brvx' 'kwNz' 'eFOb'] [[0.34355283 0.26881003 0.70575935 0.7503411 ]\n",
+ " [0.9584373 0.27466875 0.27802315 0.9563204 ]\n",
+ " [0.19129485 0.07014314 0.0932724 0.20726128]\n",
+ " [0.28744072 0.81736153 0.37507302 0.8984588 ]] [1 9 7 0]\n",
+ "['vpSa' 'UuqW' 'xaTO' 'milw'] [[0.2942028 0.8228986 0.5793326 0.16651365]\n",
+ " [0.28259405 0.599063 0.2922477 0.95071274]\n",
+ " [0.23645316 0.00258607 0.06772221 0.7291911 ]\n",
+ " [0.12861755 0.31435087 0.576638 0.7333119 ]] [3 5 8 4]\n",
+ "['UBBb' 'MUXs' 'nLJB' 'OBGl'] [[0.2677402 0.17931737 0.02607645 0.85898155]\n",
+ " [0.58647937 0.727203 0.13329858 0.8898983 ]\n",
+ " [0.13872191 0.47390288 0.7061665 0.08478573]\n",
+ " [0.3786016 0.22002582 0.91989636 0.45837343]] [ 5 8 0 10]\n",
+ "['kiiz' 'bQYG' 'WpUU' 'AuIY'] [[0.74781317 0.13744462 0.9236441 0.63558507]\n",
+ " [0.23649399 0.35303807 0.0951511 0.03541444]\n",
+ " [0.33599988 0.6906629 0.97166294 0.55850506]\n",
+ " [0.90997607 0.5545979 0.43635726 0.9127501 ]] [8 1 4 4]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Display data.\n",
+ "for i in range(5):\n",
+ " batch_str, batch_vector, batch_int = sess.run(d)\n",
+ " print(batch_str, batch_vector, batch_int)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "tf1",
+ "language": "python",
+ "name": "tf1"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15+"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/notebooks/5_DataManagement/tfrecords.ipynb b/notebooks/5_DataManagement/tfrecords.ipynb
new file mode 100644
index 00000000..a801b2f7
--- /dev/null
+++ b/notebooks/5_DataManagement/tfrecords.ipynb
@@ -0,0 +1,261 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Create and Load TFRecords\n",
+ "\n",
+ "A simple TensorFlow example to parse a dataset into TFRecord format, and then read that dataset.\n",
+ "\n",
+ "In this example, the Titanic Dataset (in CSV format) will be used as a toy dataset, for parsing all the dataset features into TFRecord format, and then building an input pipeline that can be used for training models.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Titanic Dataset\n",
+ "\n",
+ "The titanic dataset is a popular dataset for ML that provides a list of all passengers onboard the Titanic, along with various features such as their age, sex, class (1st, 2nd, 3rd)... And if the passenger survived the disaster or not.\n",
+ "\n",
+ "It can be used to see that even though some luck was involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class...\n",
+ "\n",
+ "#### Overview\n",
+ "survived|pclass|name|sex|age|sibsp|parch|ticket|fare\n",
+ "--------|------|----|---|---|-----|-----|------|----\n",
+ "1|1|\"Allen, Miss. Elisabeth Walton\"|female|29|0|0|24160|211.3375\n",
+ "1|1|\"Allison, Master. Hudson Trevor\"|male|0.9167|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Miss. Helen Loraine\"|female|2|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Mr. Hudson Joshua Creighton\"|male|30|1|2|113781|151.5500\n",
+ "...|...|...|...|...|...|...|...|...\n",
+ "\n",
+ "\n",
+ "#### Variable Descriptions\n",
+ "```\n",
+ "survived Survived\n",
+ " (0 = No; 1 = Yes)\n",
+ "pclass Passenger Class\n",
+ " (1 = 1st; 2 = 2nd; 3 = 3rd)\n",
+ "name Name\n",
+ "sex Sex\n",
+ "age Age\n",
+ "sibsp Number of Siblings/Spouses Aboard\n",
+ "parch Number of Parents/Children Aboard\n",
+ "ticket Ticket Number\n",
+ "fare Passenger Fare\n",
+ "```"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import csv\n",
+ "import requests\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download Titanic dataset (in csv format).\n",
+ "d = requests.get(\"https://raw.githubusercontent.com/tflearn/tflearn.github.io/master/resources/titanic_dataset.csv\")\n",
+ "with open(\"titanic_dataset.csv\", \"wb\") as f:\n",
+ " f.write(d.content)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Create TFRecords"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Generate Integer Features.\n",
+ "def build_int64_feature(data):\n",
+ " return tf.train.Feature(int64_list=tf.train.Int64List(value=[data]))\n",
+ "\n",
+ "# Generate Float Features.\n",
+ "def build_float_feature(data):\n",
+ " return tf.train.Feature(float_list=tf.train.FloatList(value=[data]))\n",
+ "\n",
+ "# Generate String Features.\n",
+ "def build_string_feature(data):\n",
+ " return tf.train.Feature(bytes_list=tf.train.BytesList(value=[data]))\n",
+ "\n",
+ "# Generate a TF `Example`, parsing all features of the dataset.\n",
+ "def convert_to_tfexample(survived, pclass, name, sex, age, sibsp, parch, ticket, fare):\n",
+ " return tf.train.Example(\n",
+ " features=tf.train.Features(\n",
+ " feature={\n",
+ " 'survived': build_int64_feature(survived),\n",
+ " 'pclass': build_int64_feature(pclass),\n",
+ " 'name': build_string_feature(name),\n",
+ " 'sex': build_string_feature(sex),\n",
+ " 'age': build_float_feature(age),\n",
+ " 'sibsp': build_int64_feature(sibsp),\n",
+ " 'parch': build_int64_feature(parch),\n",
+ " 'ticket': build_string_feature(ticket),\n",
+ " 'fare': build_float_feature(fare),\n",
+ " })\n",
+ " )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Open dataset file.\n",
+ "with open(\"titanic_dataset.csv\") as f:\n",
+ " # Output TFRecord file.\n",
+ " with tf.io.TFRecordWriter(\"titanic_dataset.tfrecord\") as w:\n",
+ " # Generate a TF Example for all row in our dataset.\n",
+ " # CSV reader will read and parse all rows.\n",
+ " reader = csv.reader(f, skipinitialspace=True)\n",
+ " for i, record in enumerate(reader):\n",
+ " # Skip header.\n",
+ " if i == 0:\n",
+ " continue\n",
+ " survived, pclass, name, sex, age, sibsp, parch, ticket, fare = record\n",
+ " # Parse each csv row to TF Example using the above functions.\n",
+ " example = convert_to_tfexample(int(survived), int(pclass), name, sex, float(age), int(sibsp), int(parch), ticket, float(fare))\n",
+ " # Serialize each TF Example to string, and write to TFRecord file.\n",
+ " w.write(example.SerializeToString())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load TFRecords"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Build features template, with types.\n",
+ "features = {\n",
+ " 'survived': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'pclass': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'name': tf.io.FixedLenFeature([], tf.string),\n",
+ " 'sex': tf.io.FixedLenFeature([], tf.string),\n",
+ " 'age': tf.io.FixedLenFeature([], tf.float32),\n",
+ " 'sibsp': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'parch': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'ticket': tf.io.FixedLenFeature([], tf.string),\n",
+ " 'fare': tf.io.FixedLenFeature([], tf.float32),\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create TensorFlow session.\n",
+ "sess = tf.Session()\n",
+ "\n",
+ "# Load TFRecord data.\n",
+ "filenames = [\"titanic_dataset.tfrecord\"]\n",
+ "data = tf.data.TFRecordDataset(filenames)\n",
+ "\n",
+ "# Parse features, using the above template.\n",
+ "def parse_record(record):\n",
+ " return tf.io.parse_single_example(record, features=features)\n",
+ "# Apply the parsing to each record from the dataset.\n",
+ "data = data.map(parse_record)\n",
+ "\n",
+ "# Refill data indefinitely.\n",
+ "data = data.repeat()\n",
+ "# Shuffle data.\n",
+ "data = data.shuffle(buffer_size=1000)\n",
+ "# Batch data (aggregate records together).\n",
+ "data = data.batch(batch_size=4)\n",
+ "# Prefetch batch (pre-load batch for faster consumption).\n",
+ "data = data.prefetch(buffer_size=1)\n",
+ "\n",
+ "# Create an iterator over the dataset.\n",
+ "iterator = data.make_initializable_iterator()\n",
+ "# Initialize the iterator.\n",
+ "sess.run(iterator.initializer)\n",
+ "\n",
+ "# Get next data batch.\n",
+ "x = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "{'fare': array([ 35.5 , 73.5 , 133.65 , 19.2583], dtype=float32), 'name': array(['Sloper, Mr. William Thompson', 'Davies, Mr. Charles Henry',\n",
+ " 'Frauenthal, Dr. Henry William', 'Baclini, Miss. Marie Catherine'],\n",
+ " dtype=object), 'age': array([28., 18., 50., 5.], dtype=float32), 'parch': array([0, 0, 0, 1]), 'pclass': array([1, 2, 1, 3]), 'sex': array(['male', 'male', 'male', 'female'], dtype=object), 'survived': array([1, 0, 1, 1]), 'sibsp': array([0, 0, 2, 2]), 'ticket': array(['113788', 'S.O.C. 14879', 'PC 17611', '2666'], dtype=object)}\n",
+ "\n",
+ "{'fare': array([ 18.75 , 106.425, 78.85 , 90. ], dtype=float32), 'name': array(['Richards, Mrs. Sidney (Emily Hocking)', 'LeRoy, Miss. Bertha',\n",
+ " 'Cavendish, Mrs. Tyrell William (Julia Florence Siegel)',\n",
+ " 'Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby)'], dtype=object), 'age': array([24., 30., 76., 35.], dtype=float32), 'parch': array([3, 0, 0, 0]), 'pclass': array([2, 1, 1, 1]), 'sex': array(['female', 'female', 'female', 'female'], dtype=object), 'survived': array([1, 1, 1, 1]), 'sibsp': array([2, 0, 1, 1]), 'ticket': array(['29106', 'PC 17761', '19877', '19943'], dtype=object)}\n",
+ "\n",
+ "{'fare': array([19.9667, 15.5 , 15.0458, 66.6 ], dtype=float32), 'name': array(['Hagland, Mr. Konrad Mathias Reiersen', 'Lennon, Miss. Mary',\n",
+ " 'Richard, Mr. Emile', 'Pears, Mr. Thomas Clinton'], dtype=object), 'age': array([ 0., 0., 23., 29.], dtype=float32), 'parch': array([0, 0, 0, 0]), 'pclass': array([3, 3, 2, 1]), 'sex': array(['male', 'female', 'male', 'male'], dtype=object), 'survived': array([0, 0, 0, 0]), 'sibsp': array([1, 1, 0, 1]), 'ticket': array(['65304', '370371', 'SC/PARIS 2133', '113776'], dtype=object)}\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Dequeue data and display.\n",
+ "for i in range(3):\n",
+ " print(sess.run(x))\n",
+ " print(\"\")"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "tf1",
+ "language": "python",
+ "name": "tf1"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15+"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/notebooks/README.md b/notebooks/README.md
new file mode 100644
index 00000000..196ed016
--- /dev/null
+++ b/notebooks/README.md
@@ -0,0 +1,5 @@
+## Deprecated - Please Read
+
+Due to TensorFlow radically changing their API in v2, the examples index have been split between [v1](../tensorflow_v1) and [v2](../tensorflow_v2).
+
+The following examples are the original TF v1 examples, and will be deprecated entirely in favor of [tensorflow_v1](../tensorflow_v1) directory in a future release.
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diff --git a/tensorflow_v1/README.md b/tensorflow_v1/README.md
new file mode 100644
index 00000000..8d60ff56
--- /dev/null
+++ b/tensorflow_v1/README.md
@@ -0,0 +1,93 @@
+# TensorFlow v1 Examples
+
+All the following examples are the original TF v1 examples.
+
+*If you are using older TensorFlow version (0.11 and under), please take a [look here](https://github.com/nebulaai/TensorFlow-Examples/tree/0.11).*
+
+#### 0 - Prerequisite
+- [Introduction to Machine Learning](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/0_Prerequisite/ml_introduction.ipynb).
+- [Introduction to MNIST Dataset](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb).
+
+#### 1 - Introduction
+- **Hello World** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/1_Introduction/helloworld.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/1_Introduction/helloworld.py)). Very simple example to learn how to print "hello world" using TensorFlow.
+- **Basic Operations** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/1_Introduction/basic_operations.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/1_Introduction/basic_operations.py)). A simple example that cover TensorFlow basic operations.
+- **TensorFlow Eager API basics** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/1_Introduction/basic_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/1_Introduction/basic_eager_api.py)). Get started with TensorFlow's Eager API.
+
+#### 2 - Basic Models
+- **Linear Regression** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/linear_regression.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/linear_regression.py)). Implement a Linear Regression with TensorFlow.
+- **Linear Regression (eager api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/linear_regression_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/linear_regression_eager_api.py)). Implement a Linear Regression using TensorFlow's Eager API.
+- **Logistic Regression** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/logistic_regression.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/logistic_regression.py)). Implement a Logistic Regression with TensorFlow.
+- **Logistic Regression (eager api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/logistic_regression_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/logistic_regression_eager_api.py)). Implement a Logistic Regression using TensorFlow's Eager API.
+- **Nearest Neighbor** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/nearest_neighbor.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/nearest_neighbor.py)). Implement Nearest Neighbor algorithm with TensorFlow.
+- **K-Means** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/kmeans.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/kmeans.py)). Build a K-Means classifier with TensorFlow.
+- **Random Forest** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/random_forest.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/random_forest.py)). Build a Random Forest classifier with TensorFlow.
+- **Gradient Boosted Decision Tree (GBDT)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/gradient_boosted_decision_tree.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/gradient_boosted_decision_tree.py)). Build a Gradient Boosted Decision Tree (GBDT) with TensorFlow.
+- **Word2Vec (Word Embedding)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/2_BasicModels/word2vec.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/2_BasicModels/word2vec.py)). Build a Word Embedding Model (Word2Vec) from Wikipedia data, with TensorFlow.
+
+#### 3 - Neural Networks
+##### Supervised
+
+- **Simple Neural Network** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network_raw.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/neural_network_raw.py)). Build a simple neural network (a.k.a Multi-layer Perceptron) to classify MNIST digits dataset. Raw TensorFlow implementation.
+- **Simple Neural Network (tf.layers/estimator api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/neural_network.py)). Use TensorFlow 'layers' and 'estimator' API to build a simple neural network (a.k.a Multi-layer Perceptron) to classify MNIST digits dataset.
+- **Simple Neural Network (eager api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network_eager_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/neural_network_eager_api.py)). Use TensorFlow Eager API to build a simple neural network (a.k.a Multi-layer Perceptron) to classify MNIST digits dataset.
+- **Convolutional Neural Network** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/convolutional_network_raw.py)). Build a convolutional neural network to classify MNIST digits dataset. Raw TensorFlow implementation.
+- **Convolutional Neural Network (tf.layers/estimator api)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/convolutional_network.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/convolutional_network.py)). Use TensorFlow 'layers' and 'estimator' API to build a convolutional neural network to classify MNIST digits dataset.
+- **Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/recurrent_network.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/recurrent_network.py)). Build a recurrent neural network (LSTM) to classify MNIST digits dataset.
+- **Bi-directional Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/bidirectional_rnn.py)). Build a bi-directional recurrent neural network (LSTM) to classify MNIST digits dataset.
+- **Dynamic Recurrent Neural Network (LSTM)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/dynamic_rnn.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/dynamic_rnn.py)). Build a recurrent neural network (LSTM) that performs dynamic calculation to classify sequences of different length.
+
+##### Unsupervised
+- **Auto-Encoder** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/autoencoder.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/autoencoder.py)). Build an auto-encoder to encode an image to a lower dimension and re-construct it.
+- **Variational Auto-Encoder** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/variational_autoencoder.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/variational_autoencoder.py)). Build a variational auto-encoder (VAE), to encode and generate images from noise.
+- **GAN (Generative Adversarial Networks)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/gan.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/gan.py)). Build a Generative Adversarial Network (GAN) to generate images from noise.
+- **DCGAN (Deep Convolutional Generative Adversarial Networks)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/3_NeuralNetworks/dcgan.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/3_NeuralNetworks/dcgan.py)). Build a Deep Convolutional Generative Adversarial Network (DCGAN) to generate images from noise.
+
+#### 4 - Utilities
+- **Save and Restore a model** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/4_Utils/save_restore_model.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/4_Utils/save_restore_model.py)). Save and Restore a model with TensorFlow.
+- **Tensorboard - Graph and loss visualization** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/4_Utils/tensorboard_basic.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/4_Utils/tensorboard_basic.py)). Use Tensorboard to visualize the computation Graph and plot the loss.
+- **Tensorboard - Advanced visualization** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/4_Utils/tensorboard_advanced.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/4_Utils/tensorboard_advanced.py)). Going deeper into Tensorboard; visualize the variables, gradients, and more...
+
+#### 5 - Data Management
+- **Build an image dataset** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/5_DataManagement/build_an_image_dataset.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/5_DataManagement/build_an_image_dataset.py)). Build your own images dataset with TensorFlow data queues, from image folders or a dataset file.
+- **TensorFlow Dataset API** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/5_DataManagement/tensorflow_dataset_api.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/5_DataManagement/tensorflow_dataset_api.py)). Introducing TensorFlow Dataset API for optimizing the input data pipeline.
+- **Load and Parse data** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/5_DataManagement/load_data.ipynb)). Build efficient data pipeline (Numpy arrays, Images, CSV files, custom data, ...).
+- **Build and Load TFRecords** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/5_DataManagement/tfrecords.ipynb)). Convert data into TFRecords format, and load them.
+- **Image Transformation (i.e. Image Augmentation)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/5_DataManagement/image_transformation.ipynb)). Apply various image augmentation techniques, to generate distorted images for training.
+
+#### 6 - Multi GPU
+- **Basic Operations on multi-GPU** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/6_MultiGPU/multigpu_basics.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/6_MultiGPU/multigpu_basics.py)). A simple example to introduce multi-GPU in TensorFlow.
+- **Train a Neural Network on multi-GPU** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/notebooks/6_MultiGPU/multigpu_cnn.ipynb)) ([code](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v1/examples/6_MultiGPU/multigpu_cnn.py)). A clear and simple TensorFlow implementation to train a convolutional neural network on multiple GPUs.
+
+## Installation
+
+To download all the examples, simply clone this repository:
+```
+git clone https://github.com/nebulaai/TensorFlow-Examples
+```
+
+To run them, you also need the latest version of TensorFlow. To install it:
+```
+pip install tensorflow==1.15.0
+```
+
+or (with GPU support):
+```
+pip install tensorflow_gpu==1.15.0
+```
+
+For more details about TensorFlow installation, you can check [TensorFlow Installation Guide](https://www.tensorflow.org/install/)
+
+## Dataset
+Some examples require MNIST dataset for training and testing. Don't worry, this dataset will automatically be downloaded when running examples.
+MNIST is a database of handwritten digits, for a quick description of that dataset, you can check [this notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb).
+
+Official Website: [http://yann.lecun.com/exdb/mnist/](http://yann.lecun.com/exdb/mnist/).
+
+## More Examples
+The following examples are coming from [TFLearn](https://github.com/tflearn/tflearn), a library that provides a simplified interface for TensorFlow. You can have a look, there are many [examples](https://github.com/tflearn/tflearn/tree/master/examples) and [pre-built operations and layers](http://tflearn.org/doc_index/#api).
+
+### Tutorials
+- [TFLearn Quickstart](https://github.com/tflearn/tflearn/blob/master/tutorials/intro/quickstart.md). Learn the basics of TFLearn through a concrete machine learning task. Build and train a deep neural network classifier.
+
+### Examples
+- [TFLearn Examples](https://github.com/tflearn/tflearn/blob/master/examples). A large collection of examples using TFLearn.
diff --git a/tensorflow_v1/examples/1_Introduction/basic_eager_api.py b/tensorflow_v1/examples/1_Introduction/basic_eager_api.py
new file mode 100644
index 00000000..abb3cd8d
--- /dev/null
+++ b/tensorflow_v1/examples/1_Introduction/basic_eager_api.py
@@ -0,0 +1,68 @@
+'''
+Basic introduction to TensorFlow's Eager API.
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+
+What is Eager API?
+" Eager execution is an imperative, define-by-run interface where operations are
+executed immediately as they are called from Python. This makes it easier to
+get started with TensorFlow, and can make research and development more
+intuitive. A vast majority of the TensorFlow API remains the same whether eager
+execution is enabled or not. As a result, the exact same code that constructs
+TensorFlow graphs (e.g. using the layers API) can be executed imperatively
+by using eager execution. Conversely, most models written with Eager enabled
+can be converted to a graph that can be further optimized and/or extracted
+for deployment in production without changing code. " - Rajat Monga
+
+'''
+from __future__ import absolute_import, division, print_function
+
+import numpy as np
+import tensorflow as tf
+import tensorflow.contrib.eager as tfe
+
+# Set Eager API
+print("Setting Eager mode...")
+tfe.enable_eager_execution()
+
+# Define constant tensors
+print("Define constant tensors")
+a = tf.constant(2)
+print("a = %i" % a)
+b = tf.constant(3)
+print("b = %i" % b)
+
+# Run the operation without the need for tf.Session
+print("Running operations, without tf.Session")
+c = a + b
+print("a + b = %i" % c)
+d = a * b
+print("a * b = %i" % d)
+
+
+# Full compatibility with Numpy
+print("Mixing operations with Tensors and Numpy Arrays")
+
+# Define constant tensors
+a = tf.constant([[2., 1.],
+ [1., 0.]], dtype=tf.float32)
+print("Tensor:\n a = %s" % a)
+b = np.array([[3., 0.],
+ [5., 1.]], dtype=np.float32)
+print("NumpyArray:\n b = %s" % b)
+
+# Run the operation without the need for tf.Session
+print("Running operations, without tf.Session")
+
+c = a + b
+print("a + b = %s" % c)
+
+d = tf.matmul(a, b)
+print("a * b = %s" % d)
+
+print("Iterate through Tensor 'a':")
+for i in range(a.shape[0]):
+ for j in range(a.shape[1]):
+ print(a[i][j])
+
diff --git a/tensorflow_v1/examples/1_Introduction/basic_operations.py b/tensorflow_v1/examples/1_Introduction/basic_operations.py
new file mode 100644
index 00000000..bda09d0f
--- /dev/null
+++ b/tensorflow_v1/examples/1_Introduction/basic_operations.py
@@ -0,0 +1,75 @@
+'''
+Basic Operations example using TensorFlow library.
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+
+from __future__ import print_function
+
+import tensorflow as tf
+
+# Basic constant operations
+# The value returned by the constructor represents the output
+# of the Constant op.
+a = tf.constant(2)
+b = tf.constant(3)
+
+# Launch the default graph.
+with tf.Session() as sess:
+ print("a=2, b=3")
+ print("Addition with constants: %i" % sess.run(a+b))
+ print("Multiplication with constants: %i" % sess.run(a*b))
+
+# Basic Operations with variable as graph input
+# The value returned by the constructor represents the output
+# of the Variable op. (define as input when running session)
+# tf Graph input
+a = tf.placeholder(tf.int16)
+b = tf.placeholder(tf.int16)
+
+# Define some operations
+add = tf.add(a, b)
+mul = tf.multiply(a, b)
+
+# Launch the default graph.
+with tf.Session() as sess:
+ # Run every operation with variable input
+ print("Addition with variables: %i" % sess.run(add, feed_dict={a: 2, b: 3}))
+ print("Multiplication with variables: %i" % sess.run(mul, feed_dict={a: 2, b: 3}))
+
+
+# ----------------
+# More in details:
+# Matrix Multiplication from TensorFlow official tutorial
+
+# Create a Constant op that produces a 1x2 matrix. The op is
+# added as a node to the default graph.
+#
+# The value returned by the constructor represents the output
+# of the Constant op.
+matrix1 = tf.constant([[3., 3.]])
+
+# Create another Constant that produces a 2x1 matrix.
+matrix2 = tf.constant([[2.],[2.]])
+
+# Create a Matmul op that takes 'matrix1' and 'matrix2' as inputs.
+# The returned value, 'product', represents the result of the matrix
+# multiplication.
+product = tf.matmul(matrix1, matrix2)
+
+# To run the matmul op we call the session 'run()' method, passing 'product'
+# which represents the output of the matmul op. This indicates to the call
+# that we want to get the output of the matmul op back.
+#
+# All inputs needed by the op are run automatically by the session. They
+# typically are run in parallel.
+#
+# The call 'run(product)' thus causes the execution of threes ops in the
+# graph: the two constants and matmul.
+#
+# The output of the op is returned in 'result' as a numpy `ndarray` object.
+with tf.Session() as sess:
+ result = sess.run(product)
+ print(result)
+ # ==> [[ 12.]]
diff --git a/tensorflow_v1/examples/1_Introduction/helloworld.py b/tensorflow_v1/examples/1_Introduction/helloworld.py
new file mode 100644
index 00000000..e6f41af6
--- /dev/null
+++ b/tensorflow_v1/examples/1_Introduction/helloworld.py
@@ -0,0 +1,25 @@
+'''
+HelloWorld example using TensorFlow library.
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+
+from __future__ import print_function
+
+import tensorflow as tf
+
+# Simple hello world using TensorFlow
+
+# Create a Constant op
+# The op is added as a node to the default graph.
+#
+# The value returned by the constructor represents the output
+# of the Constant op.
+hello = tf.constant('Hello, TensorFlow!')
+
+# Start tf session
+sess = tf.Session()
+
+# Run the op
+print(sess.run(hello))
diff --git a/tensorflow_v1/examples/2_BasicModels/gradient_boosted_decision_tree.py b/tensorflow_v1/examples/2_BasicModels/gradient_boosted_decision_tree.py
new file mode 100644
index 00000000..5eeae4d4
--- /dev/null
+++ b/tensorflow_v1/examples/2_BasicModels/gradient_boosted_decision_tree.py
@@ -0,0 +1,85 @@
+""" Gradient Boosted Decision Tree (GBDT).
+
+Implement a Gradient Boosted Decision tree with TensorFlow to classify
+handwritten digit images. This example is using the MNIST database of
+handwritten digits as training samples (http://yann.lecun.com/exdb/mnist/).
+
+Links:
+ [MNIST Dataset](http://yann.lecun.com/exdb/mnist/).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import print_function
+
+import tensorflow as tf
+from tensorflow.contrib.boosted_trees.estimator_batch.estimator import GradientBoostedDecisionTreeClassifier
+from tensorflow.contrib.boosted_trees.proto import learner_pb2 as gbdt_learner
+
+# Ignore all GPUs (current TF GBDT does not support GPU).
+import os
+os.environ["CUDA_VISIBLE_DEVICES"] = ""
+
+# Import MNIST data
+# Set verbosity to display errors only (Remove this line for showing warnings)
+tf.logging.set_verbosity(tf.logging.ERROR)
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=False,
+ source_url='http://yann.lecun.com/exdb/mnist/')
+
+# Parameters
+batch_size = 4096 # The number of samples per batch
+num_classes = 10 # The 10 digits
+num_features = 784 # Each image is 28x28 pixels
+max_steps = 10000
+
+# GBDT Parameters
+learning_rate = 0.1
+l1_regul = 0.
+l2_regul = 1.
+examples_per_layer = 1000
+num_trees = 10
+max_depth = 16
+
+# Fill GBDT parameters into the config proto
+learner_config = gbdt_learner.LearnerConfig()
+learner_config.learning_rate_tuner.fixed.learning_rate = learning_rate
+learner_config.regularization.l1 = l1_regul
+learner_config.regularization.l2 = l2_regul / examples_per_layer
+learner_config.constraints.max_tree_depth = max_depth
+growing_mode = gbdt_learner.LearnerConfig.LAYER_BY_LAYER
+learner_config.growing_mode = growing_mode
+run_config = tf.contrib.learn.RunConfig(save_checkpoints_secs=300)
+learner_config.multi_class_strategy = (
+ gbdt_learner.LearnerConfig.DIAGONAL_HESSIAN)\
+
+# Create a TensorFlor GBDT Estimator
+gbdt_model = GradientBoostedDecisionTreeClassifier(
+ model_dir=None, # No save directory specified
+ learner_config=learner_config,
+ n_classes=num_classes,
+ examples_per_layer=examples_per_layer,
+ num_trees=num_trees,
+ center_bias=False,
+ config=run_config)
+
+# Display TF info logs
+tf.logging.set_verbosity(tf.logging.INFO)
+
+# Define the input function for training
+input_fn = tf.estimator.inputs.numpy_input_fn(
+ x={'images': mnist.train.images}, y=mnist.train.labels,
+ batch_size=batch_size, num_epochs=None, shuffle=True)
+# Train the Model
+gbdt_model.fit(input_fn=input_fn, max_steps=max_steps)
+
+# Evaluate the Model
+# Define the input function for evaluating
+input_fn = tf.estimator.inputs.numpy_input_fn(
+ x={'images': mnist.test.images}, y=mnist.test.labels,
+ batch_size=batch_size, shuffle=False)
+# Use the Estimator 'evaluate' method
+e = gbdt_model.evaluate(input_fn=input_fn)
+
+print("Testing Accuracy:", e['accuracy'])
diff --git a/tensorflow_v1/examples/2_BasicModels/kmeans.py b/tensorflow_v1/examples/2_BasicModels/kmeans.py
new file mode 100644
index 00000000..59a25374
--- /dev/null
+++ b/tensorflow_v1/examples/2_BasicModels/kmeans.py
@@ -0,0 +1,93 @@
+""" K-Means.
+
+Implement K-Means algorithm with TensorFlow, and apply it to classify
+handwritten digit images. This example is using the MNIST database of
+handwritten digits as training samples (http://yann.lecun.com/exdb/mnist/).
+
+Note: This example requires TensorFlow v1.1.0 or over.
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import print_function
+
+import numpy as np
+import tensorflow as tf
+from tensorflow.contrib.factorization import KMeans
+
+# Ignore all GPUs, tf k-means does not benefit from it.
+import os
+os.environ["CUDA_VISIBLE_DEVICES"] = ""
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+full_data_x = mnist.train.images
+
+# Parameters
+num_steps = 50 # Total steps to train
+batch_size = 1024 # The number of samples per batch
+k = 25 # The number of clusters
+num_classes = 10 # The 10 digits
+num_features = 784 # Each image is 28x28 pixels
+
+# Input images
+X = tf.placeholder(tf.float32, shape=[None, num_features])
+# Labels (for assigning a label to a centroid and testing)
+Y = tf.placeholder(tf.float32, shape=[None, num_classes])
+
+# K-Means Parameters
+kmeans = KMeans(inputs=X, num_clusters=k, distance_metric='cosine',
+ use_mini_batch=True)
+
+# Build KMeans graph
+training_graph = kmeans.training_graph()
+
+if len(training_graph) > 6: # Tensorflow 1.4+
+ (all_scores, cluster_idx, scores, cluster_centers_initialized,
+ cluster_centers_var, init_op, train_op) = training_graph
+else:
+ (all_scores, cluster_idx, scores, cluster_centers_initialized,
+ init_op, train_op) = training_graph
+
+cluster_idx = cluster_idx[0] # fix for cluster_idx being a tuple
+avg_distance = tf.reduce_mean(scores)
+
+# Initialize the variables (i.e. assign their default value)
+init_vars = tf.global_variables_initializer()
+
+# Start TensorFlow session
+sess = tf.Session()
+
+# Run the initializer
+sess.run(init_vars, feed_dict={X: full_data_x})
+sess.run(init_op, feed_dict={X: full_data_x})
+
+# Training
+for i in range(1, num_steps + 1):
+ _, d, idx = sess.run([train_op, avg_distance, cluster_idx],
+ feed_dict={X: full_data_x})
+ if i % 10 == 0 or i == 1:
+ print("Step %i, Avg Distance: %f" % (i, d))
+
+# Assign a label to each centroid
+# Count total number of labels per centroid, using the label of each training
+# sample to their closest centroid (given by 'idx')
+counts = np.zeros(shape=(k, num_classes))
+for i in range(len(idx)):
+ counts[idx[i]] += mnist.train.labels[i]
+# Assign the most frequent label to the centroid
+labels_map = [np.argmax(c) for c in counts]
+labels_map = tf.convert_to_tensor(labels_map)
+
+# Evaluation ops
+# Lookup: centroid_id -> label
+cluster_label = tf.nn.embedding_lookup(labels_map, cluster_idx)
+# Compute accuracy
+correct_prediction = tf.equal(cluster_label, tf.cast(tf.argmax(Y, 1), tf.int32))
+accuracy_op = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
+
+# Test Model
+test_x, test_y = mnist.test.images, mnist.test.labels
+print("Test Accuracy:", sess.run(accuracy_op, feed_dict={X: test_x, Y: test_y}))
diff --git a/tensorflow_v1/examples/2_BasicModels/linear_regression.py b/tensorflow_v1/examples/2_BasicModels/linear_regression.py
new file mode 100644
index 00000000..07cdead7
--- /dev/null
+++ b/tensorflow_v1/examples/2_BasicModels/linear_regression.py
@@ -0,0 +1,89 @@
+'''
+A linear regression learning algorithm example using TensorFlow library.
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+
+from __future__ import print_function
+
+import tensorflow as tf
+import numpy
+import matplotlib.pyplot as plt
+rng = numpy.random
+
+# Parameters
+learning_rate = 0.01
+training_epochs = 1000
+display_step = 50
+
+# Training Data
+train_X = numpy.asarray([3.3,4.4,5.5,6.71,6.93,4.168,9.779,6.182,7.59,2.167,
+ 7.042,10.791,5.313,7.997,5.654,9.27,3.1])
+train_Y = numpy.asarray([1.7,2.76,2.09,3.19,1.694,1.573,3.366,2.596,2.53,1.221,
+ 2.827,3.465,1.65,2.904,2.42,2.94,1.3])
+n_samples = train_X.shape[0]
+
+# tf Graph Input
+X = tf.placeholder("float")
+Y = tf.placeholder("float")
+
+# Set model weights
+W = tf.Variable(rng.randn(), name="weight")
+b = tf.Variable(rng.randn(), name="bias")
+
+# Construct a linear model
+pred = tf.add(tf.multiply(X, W), b)
+
+# Mean squared error
+cost = tf.reduce_sum(tf.pow(pred-Y, 2))/(2*n_samples)
+# Gradient descent
+# Note, minimize() knows to modify W and b because Variable objects are trainable=True by default
+optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ # Fit all training data
+ for epoch in range(training_epochs):
+ for (x, y) in zip(train_X, train_Y):
+ sess.run(optimizer, feed_dict={X: x, Y: y})
+
+ # Display logs per epoch step
+ if (epoch+1) % display_step == 0:
+ c = sess.run(cost, feed_dict={X: train_X, Y:train_Y})
+ print("Epoch:", '%04d' % (epoch+1), "cost=", "{:.9f}".format(c), \
+ "W=", sess.run(W), "b=", sess.run(b))
+
+ print("Optimization Finished!")
+ training_cost = sess.run(cost, feed_dict={X: train_X, Y: train_Y})
+ print("Training cost=", training_cost, "W=", sess.run(W), "b=", sess.run(b), '\n')
+
+ # Graphic display
+ plt.plot(train_X, train_Y, 'ro', label='Original data')
+ plt.plot(train_X, sess.run(W) * train_X + sess.run(b), label='Fitted line')
+ plt.legend()
+ plt.show()
+
+ # Testing example, as requested (Issue #2)
+ test_X = numpy.asarray([6.83, 4.668, 8.9, 7.91, 5.7, 8.7, 3.1, 2.1])
+ test_Y = numpy.asarray([1.84, 2.273, 3.2, 2.831, 2.92, 3.24, 1.35, 1.03])
+
+ print("Testing... (Mean square loss Comparison)")
+ testing_cost = sess.run(
+ tf.reduce_sum(tf.pow(pred - Y, 2)) / (2 * test_X.shape[0]),
+ feed_dict={X: test_X, Y: test_Y}) # same function as cost above
+ print("Testing cost=", testing_cost)
+ print("Absolute mean square loss difference:", abs(
+ training_cost - testing_cost))
+
+ plt.plot(test_X, test_Y, 'bo', label='Testing data')
+ plt.plot(train_X, sess.run(W) * train_X + sess.run(b), label='Fitted line')
+ plt.legend()
+ plt.show()
diff --git a/tensorflow_v1/examples/2_BasicModels/linear_regression_eager_api.py b/tensorflow_v1/examples/2_BasicModels/linear_regression_eager_api.py
new file mode 100644
index 00000000..f8f873bd
--- /dev/null
+++ b/tensorflow_v1/examples/2_BasicModels/linear_regression_eager_api.py
@@ -0,0 +1,69 @@
+''' Linear Regression with Eager API.
+
+A linear regression learning algorithm example using TensorFlow's Eager API.
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+from __future__ import absolute_import, division, print_function
+
+import matplotlib.pyplot as plt
+import numpy as np
+import tensorflow as tf
+
+# Set Eager API
+tf.enable_eager_execution()
+tfe = tf.contrib.eager
+
+# Training Data
+train_X = [3.3, 4.4, 5.5, 6.71, 6.93, 4.168, 9.779, 6.182, 7.59, 2.167,
+ 7.042, 10.791, 5.313, 7.997, 5.654, 9.27, 3.1]
+train_Y = [1.7, 2.76, 2.09, 3.19, 1.694, 1.573, 3.366, 2.596, 2.53, 1.221,
+ 2.827, 3.465, 1.65, 2.904, 2.42, 2.94, 1.3]
+n_samples = len(train_X)
+
+# Parameters
+learning_rate = 0.01
+display_step = 100
+num_steps = 1000
+
+# Weight and Bias
+W = tfe.Variable(np.random.randn())
+b = tfe.Variable(np.random.randn())
+
+
+# Linear regression (Wx + b)
+def linear_regression(inputs):
+ return inputs * W + b
+
+
+# Mean square error
+def mean_square_fn(model_fn, inputs, labels):
+ return tf.reduce_sum(tf.pow(model_fn(inputs) - labels, 2)) / (2 * n_samples)
+
+
+# SGD Optimizer
+optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)
+# Compute gradients
+grad = tfe.implicit_gradients(mean_square_fn)
+
+# Initial cost, before optimizing
+print("Initial cost= {:.9f}".format(
+ mean_square_fn(linear_regression, train_X, train_Y)),
+ "W=", W.numpy(), "b=", b.numpy())
+
+# Training
+for step in range(num_steps):
+
+ optimizer.apply_gradients(grad(linear_regression, train_X, train_Y))
+
+ if (step + 1) % display_step == 0 or step == 0:
+ print("Epoch:", '%04d' % (step + 1), "cost=",
+ "{:.9f}".format(mean_square_fn(linear_regression, train_X, train_Y)),
+ "W=", W.numpy(), "b=", b.numpy())
+
+# Graphic display
+plt.plot(train_X, train_Y, 'ro', label='Original data')
+plt.plot(train_X, np.array(W * train_X + b), label='Fitted line')
+plt.legend()
+plt.show()
diff --git a/tensorflow_v1/examples/2_BasicModels/logistic_regression.py b/tensorflow_v1/examples/2_BasicModels/logistic_regression.py
new file mode 100644
index 00000000..a83fd1a9
--- /dev/null
+++ b/tensorflow_v1/examples/2_BasicModels/logistic_regression.py
@@ -0,0 +1,71 @@
+'''
+A logistic regression learning algorithm example using TensorFlow library.
+This example is using the MNIST database of handwritten digits
+(http://yann.lecun.com/exdb/mnist/)
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+
+from __future__ import print_function
+
+import tensorflow as tf
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# Parameters
+learning_rate = 0.01
+training_epochs = 25
+batch_size = 100
+display_step = 1
+
+# tf Graph Input
+x = tf.placeholder(tf.float32, [None, 784]) # mnist data image of shape 28*28=784
+y = tf.placeholder(tf.float32, [None, 10]) # 0-9 digits recognition => 10 classes
+
+# Set model weights
+W = tf.Variable(tf.zeros([784, 10]))
+b = tf.Variable(tf.zeros([10]))
+
+# Construct model
+pred = tf.nn.softmax(tf.matmul(x, W) + b) # Softmax
+
+# Minimize error using cross entropy
+cost = tf.reduce_mean(-tf.reduce_sum(y*tf.log(pred), reduction_indices=1))
+# Gradient Descent
+optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ # Training cycle
+ for epoch in range(training_epochs):
+ avg_cost = 0.
+ total_batch = int(mnist.train.num_examples/batch_size)
+ # Loop over all batches
+ for i in range(total_batch):
+ batch_xs, batch_ys = mnist.train.next_batch(batch_size)
+ # Run optimization op (backprop) and cost op (to get loss value)
+ _, c = sess.run([optimizer, cost], feed_dict={x: batch_xs,
+ y: batch_ys})
+ # Compute average loss
+ avg_cost += c / total_batch
+ # Display logs per epoch step
+ if (epoch+1) % display_step == 0:
+ print("Epoch:", '%04d' % (epoch+1), "cost=", "{:.9f}".format(avg_cost))
+
+ print("Optimization Finished!")
+
+ # Test model
+ correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))
+ # Calculate accuracy
+ accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
+ print("Accuracy:", accuracy.eval({x: mnist.test.images, y: mnist.test.labels}))
diff --git a/tensorflow_v1/examples/2_BasicModels/logistic_regression_eager_api.py b/tensorflow_v1/examples/2_BasicModels/logistic_regression_eager_api.py
new file mode 100644
index 00000000..98a811cc
--- /dev/null
+++ b/tensorflow_v1/examples/2_BasicModels/logistic_regression_eager_api.py
@@ -0,0 +1,105 @@
+''' Logistic Regression with Eager API.
+
+A logistic regression learning algorithm example using TensorFlow's Eager API.
+This example is using the MNIST database of handwritten digits
+(http://yann.lecun.com/exdb/mnist/)
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+from __future__ import absolute_import, division, print_function
+
+import tensorflow as tf
+
+# Set Eager API
+tf.enable_eager_execution()
+tfe = tf.contrib.eager
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=False)
+
+# Parameters
+learning_rate = 0.1
+batch_size = 128
+num_steps = 1000
+display_step = 100
+
+dataset = tf.data.Dataset.from_tensor_slices(
+ (mnist.train.images, mnist.train.labels))
+dataset = dataset.repeat().batch(batch_size).prefetch(batch_size)
+dataset_iter = tfe.Iterator(dataset)
+
+# Variables
+W = tfe.Variable(tf.zeros([784, 10]), name='weights')
+b = tfe.Variable(tf.zeros([10]), name='bias')
+
+
+# Logistic regression (Wx + b)
+def logistic_regression(inputs):
+ return tf.matmul(inputs, W) + b
+
+
+# Cross-Entropy loss function
+def loss_fn(inference_fn, inputs, labels):
+ # Using sparse_softmax cross entropy
+ return tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(
+ logits=inference_fn(inputs), labels=labels))
+
+
+# Calculate accuracy
+def accuracy_fn(inference_fn, inputs, labels):
+ prediction = tf.nn.softmax(inference_fn(inputs))
+ correct_pred = tf.equal(tf.argmax(prediction, 1), labels)
+ return tf.reduce_mean(tf.cast(correct_pred, tf.float32))
+
+
+# SGD Optimizer
+optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)
+# Compute gradients
+grad = tfe.implicit_gradients(loss_fn)
+
+# Training
+average_loss = 0.
+average_acc = 0.
+for step in range(num_steps):
+
+ # Iterate through the dataset
+ d = dataset_iter.next()
+
+ # Images
+ x_batch = d[0]
+ # Labels
+ y_batch = tf.cast(d[1], dtype=tf.int64)
+
+ # Compute the batch loss
+ batch_loss = loss_fn(logistic_regression, x_batch, y_batch)
+ average_loss += batch_loss
+ # Compute the batch accuracy
+ batch_accuracy = accuracy_fn(logistic_regression, x_batch, y_batch)
+ average_acc += batch_accuracy
+
+ if step == 0:
+ # Display the initial cost, before optimizing
+ print("Initial loss= {:.9f}".format(average_loss))
+
+ # Update the variables following gradients info
+ optimizer.apply_gradients(grad(logistic_regression, x_batch, y_batch))
+
+ # Display info
+ if (step + 1) % display_step == 0 or step == 0:
+ if step > 0:
+ average_loss /= display_step
+ average_acc /= display_step
+ print("Step:", '%04d' % (step + 1), " loss=",
+ "{:.9f}".format(average_loss), " accuracy=",
+ "{:.4f}".format(average_acc))
+ average_loss = 0.
+ average_acc = 0.
+
+# Evaluate model on the test image set
+testX = mnist.test.images
+testY = mnist.test.labels
+
+test_acc = accuracy_fn(logistic_regression, testX, testY)
+print("Testset Accuracy: {:.4f}".format(test_acc))
diff --git a/tensorflow_v1/examples/2_BasicModels/nearest_neighbor.py b/tensorflow_v1/examples/2_BasicModels/nearest_neighbor.py
new file mode 100644
index 00000000..72540774
--- /dev/null
+++ b/tensorflow_v1/examples/2_BasicModels/nearest_neighbor.py
@@ -0,0 +1,55 @@
+'''
+A nearest neighbor learning algorithm example using TensorFlow library.
+This example is using the MNIST database of handwritten digits
+(http://yann.lecun.com/exdb/mnist/)
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+
+from __future__ import print_function
+
+import numpy as np
+import tensorflow as tf
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# In this example, we limit mnist data
+Xtr, Ytr = mnist.train.next_batch(5000) #5000 for training (nn candidates)
+Xte, Yte = mnist.test.next_batch(200) #200 for testing
+
+# tf Graph Input
+xtr = tf.placeholder("float", [None, 784])
+xte = tf.placeholder("float", [784])
+
+# Nearest Neighbor calculation using L1 Distance
+# Calculate L1 Distance
+distance = tf.reduce_sum(tf.abs(tf.add(xtr, tf.negative(xte))), reduction_indices=1)
+# Prediction: Get min distance index (Nearest neighbor)
+pred = tf.arg_min(distance, 0)
+
+accuracy = 0.
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ # loop over test data
+ for i in range(len(Xte)):
+ # Get nearest neighbor
+ nn_index = sess.run(pred, feed_dict={xtr: Xtr, xte: Xte[i, :]})
+ # Get nearest neighbor class label and compare it to its true label
+ print("Test", i, "Prediction:", np.argmax(Ytr[nn_index]), \
+ "True Class:", np.argmax(Yte[i]))
+ # Calculate accuracy
+ if np.argmax(Ytr[nn_index]) == np.argmax(Yte[i]):
+ accuracy += 1./len(Xte)
+ print("Done!")
+ print("Accuracy:", accuracy)
diff --git a/tensorflow_v1/examples/2_BasicModels/random_forest.py b/tensorflow_v1/examples/2_BasicModels/random_forest.py
new file mode 100644
index 00000000..0ac6919b
--- /dev/null
+++ b/tensorflow_v1/examples/2_BasicModels/random_forest.py
@@ -0,0 +1,77 @@
+""" Random Forest.
+
+Implement Random Forest algorithm with TensorFlow, and apply it to classify
+handwritten digit images. This example is using the MNIST database of
+handwritten digits as training samples (http://yann.lecun.com/exdb/mnist/).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import print_function
+
+import tensorflow as tf
+from tensorflow.contrib.tensor_forest.python import tensor_forest
+from tensorflow.python.ops import resources
+
+# Ignore all GPUs, tf random forest does not benefit from it.
+import os
+os.environ["CUDA_VISIBLE_DEVICES"] = ""
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=False)
+
+# Parameters
+num_steps = 500 # Total steps to train
+batch_size = 1024 # The number of samples per batch
+num_classes = 10 # The 10 digits
+num_features = 784 # Each image is 28x28 pixels
+num_trees = 10
+max_nodes = 1000
+
+# Input and Target data
+X = tf.placeholder(tf.float32, shape=[None, num_features])
+# For random forest, labels must be integers (the class id)
+Y = tf.placeholder(tf.int32, shape=[None])
+
+# Random Forest Parameters
+hparams = tensor_forest.ForestHParams(num_classes=num_classes,
+ num_features=num_features,
+ num_trees=num_trees,
+ max_nodes=max_nodes).fill()
+
+# Build the Random Forest
+forest_graph = tensor_forest.RandomForestGraphs(hparams)
+# Get training graph and loss
+train_op = forest_graph.training_graph(X, Y)
+loss_op = forest_graph.training_loss(X, Y)
+
+# Measure the accuracy
+infer_op, _, _ = forest_graph.inference_graph(X)
+correct_prediction = tf.equal(tf.argmax(infer_op, 1), tf.cast(Y, tf.int64))
+accuracy_op = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))
+
+# Initialize the variables (i.e. assign their default value) and forest resources
+init_vars = tf.group(tf.global_variables_initializer(),
+ resources.initialize_resources(resources.shared_resources()))
+
+# Start TensorFlow session
+sess = tf.Session()
+
+# Run the initializer
+sess.run(init_vars)
+
+# Training
+for i in range(1, num_steps + 1):
+ # Prepare Data
+ # Get the next batch of MNIST data (only images are needed, not labels)
+ batch_x, batch_y = mnist.train.next_batch(batch_size)
+ _, l = sess.run([train_op, loss_op], feed_dict={X: batch_x, Y: batch_y})
+ if i % 50 == 0 or i == 1:
+ acc = sess.run(accuracy_op, feed_dict={X: batch_x, Y: batch_y})
+ print('Step %i, Loss: %f, Acc: %f' % (i, l, acc))
+
+# Test Model
+test_x, test_y = mnist.test.images, mnist.test.labels
+print("Test Accuracy:", sess.run(accuracy_op, feed_dict={X: test_x, Y: test_y}))
diff --git a/tensorflow_v1/examples/2_BasicModels/word2vec.py b/tensorflow_v1/examples/2_BasicModels/word2vec.py
new file mode 100644
index 00000000..3d59acab
--- /dev/null
+++ b/tensorflow_v1/examples/2_BasicModels/word2vec.py
@@ -0,0 +1,195 @@
+""" Word2Vec.
+
+Implement Word2Vec algorithm to compute vector representations of words.
+This example is using a small chunk of Wikipedia articles to train from.
+
+References:
+ - Mikolov, Tomas et al. "Efficient Estimation of Word Representations
+ in Vector Space.", 2013.
+
+Links:
+ - [Word2Vec] https://arxiv.org/pdf/1301.3781.pdf
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+from __future__ import division, print_function, absolute_import
+
+import collections
+import os
+import random
+import urllib
+import zipfile
+
+import numpy as np
+import tensorflow as tf
+
+# Training Parameters
+learning_rate = 0.1
+batch_size = 128
+num_steps = 3000000
+display_step = 10000
+eval_step = 200000
+
+# Evaluation Parameters
+eval_words = ['five', 'of', 'going', 'hardware', 'american', 'britain']
+
+# Word2Vec Parameters
+embedding_size = 200 # Dimension of the embedding vector
+max_vocabulary_size = 50000 # Total number of different words in the vocabulary
+min_occurrence = 10 # Remove all words that does not appears at least n times
+skip_window = 3 # How many words to consider left and right
+num_skips = 2 # How many times to reuse an input to generate a label
+num_sampled = 64 # Number of negative examples to sample
+
+
+# Download a small chunk of Wikipedia articles collection
+url = 'http://mattmahoney.net/dc/text8.zip'
+data_path = 'text8.zip'
+if not os.path.exists(data_path):
+ print("Downloading the dataset... (It may take some time)")
+ filename, _ = urllib.urlretrieve(url, data_path)
+ print("Done!")
+# Unzip the dataset file. Text has already been processed
+with zipfile.ZipFile(data_path) as f:
+ text_words = f.read(f.namelist()[0]).lower().split()
+
+# Build the dictionary and replace rare words with UNK token
+count = [('UNK', -1)]
+# Retrieve the most common words
+count.extend(collections.Counter(text_words).most_common(max_vocabulary_size - 1))
+# Remove samples with less than 'min_occurrence' occurrences
+for i in range(len(count) - 1, -1, -1):
+ if count[i][1] < min_occurrence:
+ count.pop(i)
+ else:
+ # The collection is ordered, so stop when 'min_occurrence' is reached
+ break
+# Compute the vocabulary size
+vocabulary_size = len(count)
+# Assign an id to each word
+word2id = dict()
+for i, (word, _)in enumerate(count):
+ word2id[word] = i
+
+data = list()
+unk_count = 0
+for word in text_words:
+ # Retrieve a word id, or assign it index 0 ('UNK') if not in dictionary
+ index = word2id.get(word, 0)
+ if index == 0:
+ unk_count += 1
+ data.append(index)
+count[0] = ('UNK', unk_count)
+id2word = dict(zip(word2id.values(), word2id.keys()))
+
+print("Words count:", len(text_words))
+print("Unique words:", len(set(text_words)))
+print("Vocabulary size:", vocabulary_size)
+print("Most common words:", count[:10])
+
+data_index = 0
+# Generate training batch for the skip-gram model
+def next_batch(batch_size, num_skips, skip_window):
+ global data_index
+ assert batch_size % num_skips == 0
+ assert num_skips <= 2 * skip_window
+ batch = np.ndarray(shape=(batch_size), dtype=np.int32)
+ labels = np.ndarray(shape=(batch_size, 1), dtype=np.int32)
+ # get window size (words left and right + current one)
+ span = 2 * skip_window + 1
+ buffer = collections.deque(maxlen=span)
+ if data_index + span > len(data):
+ data_index = 0
+ buffer.extend(data[data_index:data_index + span])
+ data_index += span
+ for i in range(batch_size // num_skips):
+ context_words = [w for w in range(span) if w != skip_window]
+ words_to_use = random.sample(context_words, num_skips)
+ for j, context_word in enumerate(words_to_use):
+ batch[i * num_skips + j] = buffer[skip_window]
+ labels[i * num_skips + j, 0] = buffer[context_word]
+ if data_index == len(data):
+ buffer.extend(data[0:span])
+ data_index = span
+ else:
+ buffer.append(data[data_index])
+ data_index += 1
+ # Backtrack a little bit to avoid skipping words in the end of a batch
+ data_index = (data_index + len(data) - span) % len(data)
+ return batch, labels
+
+
+# Input data
+X = tf.placeholder(tf.int32, shape=[None])
+# Input label
+Y = tf.placeholder(tf.int32, shape=[None, 1])
+
+# Ensure the following ops & var are assigned on CPU
+# (some ops are not compatible on GPU)
+with tf.device('/cpu:0'):
+ # Create the embedding variable (each row represent a word embedding vector)
+ embedding = tf.Variable(tf.random_normal([vocabulary_size, embedding_size]))
+ # Lookup the corresponding embedding vectors for each sample in X
+ X_embed = tf.nn.embedding_lookup(embedding, X)
+
+ # Construct the variables for the NCE loss
+ nce_weights = tf.Variable(tf.random_normal([vocabulary_size, embedding_size]))
+ nce_biases = tf.Variable(tf.zeros([vocabulary_size]))
+
+# Compute the average NCE loss for the batch
+loss_op = tf.reduce_mean(
+ tf.nn.nce_loss(weights=nce_weights,
+ biases=nce_biases,
+ labels=Y,
+ inputs=X_embed,
+ num_sampled=num_sampled,
+ num_classes=vocabulary_size))
+
+# Define the optimizer
+optimizer = tf.train.GradientDescentOptimizer(learning_rate)
+train_op = optimizer.minimize(loss_op)
+
+# Evaluation
+# Compute the cosine similarity between input data embedding and every embedding vectors
+X_embed_norm = X_embed / tf.sqrt(tf.reduce_sum(tf.square(X_embed)))
+embedding_norm = embedding / tf.sqrt(tf.reduce_sum(tf.square(embedding), 1, keepdims=True))
+cosine_sim_op = tf.matmul(X_embed_norm, embedding_norm, transpose_b=True)
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ # Testing data
+ x_test = np.array([word2id[w] for w in eval_words])
+
+ average_loss = 0
+ for step in xrange(1, num_steps + 1):
+ # Get a new batch of data
+ batch_x, batch_y = next_batch(batch_size, num_skips, skip_window)
+ # Run training op
+ _, loss = sess.run([train_op, loss_op], feed_dict={X: batch_x, Y: batch_y})
+ average_loss += loss
+
+ if step % display_step == 0 or step == 1:
+ if step > 1:
+ average_loss /= display_step
+ print("Step " + str(step) + ", Average Loss= " + \
+ "{:.4f}".format(average_loss))
+ average_loss = 0
+
+ # Evaluation
+ if step % eval_step == 0 or step == 1:
+ print("Evaluation...")
+ sim = sess.run(cosine_sim_op, feed_dict={X: x_test})
+ for i in xrange(len(eval_words)):
+ top_k = 8 # number of nearest neighbors
+ nearest = (-sim[i, :]).argsort()[1:top_k + 1]
+ log_str = '"%s" nearest neighbors:' % eval_words[i]
+ for k in xrange(top_k):
+ log_str = '%s %s,' % (log_str, id2word[nearest[k]])
+ print(log_str)
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/autoencoder.py b/tensorflow_v1/examples/3_NeuralNetworks/autoencoder.py
new file mode 100644
index 00000000..a58473fe
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/autoencoder.py
@@ -0,0 +1,142 @@
+""" Auto Encoder Example.
+
+Build a 2 layers auto-encoder with TensorFlow to compress images to a
+lower latent space and then reconstruct them.
+
+References:
+ Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. "Gradient-based
+ learning applied to document recognition." Proceedings of the IEEE,
+ 86(11):2278-2324, November 1998.
+
+Links:
+ [MNIST Dataset] http://yann.lecun.com/exdb/mnist/
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+from __future__ import division, print_function, absolute_import
+
+import tensorflow as tf
+import numpy as np
+import matplotlib.pyplot as plt
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# Training Parameters
+learning_rate = 0.01
+num_steps = 30000
+batch_size = 256
+
+display_step = 1000
+examples_to_show = 10
+
+# Network Parameters
+num_hidden_1 = 256 # 1st layer num features
+num_hidden_2 = 128 # 2nd layer num features (the latent dim)
+num_input = 784 # MNIST data input (img shape: 28*28)
+
+# tf Graph input (only pictures)
+X = tf.placeholder("float", [None, num_input])
+
+weights = {
+ 'encoder_h1': tf.Variable(tf.random_normal([num_input, num_hidden_1])),
+ 'encoder_h2': tf.Variable(tf.random_normal([num_hidden_1, num_hidden_2])),
+ 'decoder_h1': tf.Variable(tf.random_normal([num_hidden_2, num_hidden_1])),
+ 'decoder_h2': tf.Variable(tf.random_normal([num_hidden_1, num_input])),
+}
+biases = {
+ 'encoder_b1': tf.Variable(tf.random_normal([num_hidden_1])),
+ 'encoder_b2': tf.Variable(tf.random_normal([num_hidden_2])),
+ 'decoder_b1': tf.Variable(tf.random_normal([num_hidden_1])),
+ 'decoder_b2': tf.Variable(tf.random_normal([num_input])),
+}
+
+# Building the encoder
+def encoder(x):
+ # Encoder Hidden layer with sigmoid activation #1
+ layer_1 = tf.nn.sigmoid(tf.add(tf.matmul(x, weights['encoder_h1']),
+ biases['encoder_b1']))
+ # Encoder Hidden layer with sigmoid activation #2
+ layer_2 = tf.nn.sigmoid(tf.add(tf.matmul(layer_1, weights['encoder_h2']),
+ biases['encoder_b2']))
+ return layer_2
+
+
+# Building the decoder
+def decoder(x):
+ # Decoder Hidden layer with sigmoid activation #1
+ layer_1 = tf.nn.sigmoid(tf.add(tf.matmul(x, weights['decoder_h1']),
+ biases['decoder_b1']))
+ # Decoder Hidden layer with sigmoid activation #2
+ layer_2 = tf.nn.sigmoid(tf.add(tf.matmul(layer_1, weights['decoder_h2']),
+ biases['decoder_b2']))
+ return layer_2
+
+# Construct model
+encoder_op = encoder(X)
+decoder_op = decoder(encoder_op)
+
+# Prediction
+y_pred = decoder_op
+# Targets (Labels) are the input data.
+y_true = X
+
+# Define loss and optimizer, minimize the squared error
+loss = tf.reduce_mean(tf.pow(y_true - y_pred, 2))
+optimizer = tf.train.RMSPropOptimizer(learning_rate).minimize(loss)
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start Training
+# Start a new TF session
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ # Training
+ for i in range(1, num_steps+1):
+ # Prepare Data
+ # Get the next batch of MNIST data (only images are needed, not labels)
+ batch_x, _ = mnist.train.next_batch(batch_size)
+
+ # Run optimization op (backprop) and cost op (to get loss value)
+ _, l = sess.run([optimizer, loss], feed_dict={X: batch_x})
+ # Display logs per step
+ if i % display_step == 0 or i == 1:
+ print('Step %i: Minibatch Loss: %f' % (i, l))
+
+ # Testing
+ # Encode and decode images from test set and visualize their reconstruction.
+ n = 4
+ canvas_orig = np.empty((28 * n, 28 * n))
+ canvas_recon = np.empty((28 * n, 28 * n))
+ for i in range(n):
+ # MNIST test set
+ batch_x, _ = mnist.test.next_batch(n)
+ # Encode and decode the digit image
+ g = sess.run(decoder_op, feed_dict={X: batch_x})
+
+ # Display original images
+ for j in range(n):
+ # Draw the original digits
+ canvas_orig[i * 28:(i + 1) * 28, j * 28:(j + 1) * 28] = \
+ batch_x[j].reshape([28, 28])
+ # Display reconstructed images
+ for j in range(n):
+ # Draw the reconstructed digits
+ canvas_recon[i * 28:(i + 1) * 28, j * 28:(j + 1) * 28] = \
+ g[j].reshape([28, 28])
+
+ print("Original Images")
+ plt.figure(figsize=(n, n))
+ plt.imshow(canvas_orig, origin="upper", cmap="gray")
+ plt.show()
+
+ print("Reconstructed Images")
+ plt.figure(figsize=(n, n))
+ plt.imshow(canvas_recon, origin="upper", cmap="gray")
+ plt.show()
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/bidirectional_rnn.py b/tensorflow_v1/examples/3_NeuralNetworks/bidirectional_rnn.py
new file mode 100644
index 00000000..6117e7cd
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/bidirectional_rnn.py
@@ -0,0 +1,126 @@
+""" Bi-directional Recurrent Neural Network.
+
+A Bi-directional Recurrent Neural Network (LSTM) implementation example using
+TensorFlow library. This example is using the MNIST database of handwritten
+digits (http://yann.lecun.com/exdb/mnist/)
+
+Links:
+ [Long Short Term Memory](http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf)
+ [MNIST Dataset](http://yann.lecun.com/exdb/mnist/).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import print_function
+
+import tensorflow as tf
+from tensorflow.contrib import rnn
+import numpy as np
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+'''
+To classify images using a bidirectional recurrent neural network, we consider
+every image row as a sequence of pixels. Because MNIST image shape is 28*28px,
+we will then handle 28 sequences of 28 steps for every sample.
+'''
+
+# Training Parameters
+learning_rate = 0.001
+training_steps = 10000
+batch_size = 128
+display_step = 200
+
+# Network Parameters
+num_input = 28 # MNIST data input (img shape: 28*28)
+timesteps = 28 # timesteps
+num_hidden = 128 # hidden layer num of features
+num_classes = 10 # MNIST total classes (0-9 digits)
+
+# tf Graph input
+X = tf.placeholder("float", [None, timesteps, num_input])
+Y = tf.placeholder("float", [None, num_classes])
+
+# Define weights
+weights = {
+ # Hidden layer weights => 2*n_hidden because of forward + backward cells
+ 'out': tf.Variable(tf.random_normal([2*num_hidden, num_classes]))
+}
+biases = {
+ 'out': tf.Variable(tf.random_normal([num_classes]))
+}
+
+
+def BiRNN(x, weights, biases):
+
+ # Prepare data shape to match `rnn` function requirements
+ # Current data input shape: (batch_size, timesteps, n_input)
+ # Required shape: 'timesteps' tensors list of shape (batch_size, num_input)
+
+ # Unstack to get a list of 'timesteps' tensors of shape (batch_size, num_input)
+ x = tf.unstack(x, timesteps, 1)
+
+ # Define lstm cells with tensorflow
+ # Forward direction cell
+ lstm_fw_cell = rnn.BasicLSTMCell(num_hidden, forget_bias=1.0)
+ # Backward direction cell
+ lstm_bw_cell = rnn.BasicLSTMCell(num_hidden, forget_bias=1.0)
+
+ # Get lstm cell output
+ try:
+ outputs, _, _ = rnn.static_bidirectional_rnn(lstm_fw_cell, lstm_bw_cell, x,
+ dtype=tf.float32)
+ except Exception: # Old TensorFlow version only returns outputs not states
+ outputs = rnn.static_bidirectional_rnn(lstm_fw_cell, lstm_bw_cell, x,
+ dtype=tf.float32)
+
+ # Linear activation, using rnn inner loop last output
+ return tf.matmul(outputs[-1], weights['out']) + biases['out']
+
+logits = BiRNN(X, weights, biases)
+prediction = tf.nn.softmax(logits)
+
+# Define loss and optimizer
+loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(
+ logits=logits, labels=Y))
+optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)
+train_op = optimizer.minimize(loss_op)
+
+# Evaluate model (with test logits, for dropout to be disabled)
+correct_pred = tf.equal(tf.argmax(prediction, 1), tf.argmax(Y, 1))
+accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ for step in range(1, training_steps+1):
+ batch_x, batch_y = mnist.train.next_batch(batch_size)
+ # Reshape data to get 28 seq of 28 elements
+ batch_x = batch_x.reshape((batch_size, timesteps, num_input))
+ # Run optimization op (backprop)
+ sess.run(train_op, feed_dict={X: batch_x, Y: batch_y})
+ if step % display_step == 0 or step == 1:
+ # Calculate batch loss and accuracy
+ loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,
+ Y: batch_y})
+ print("Step " + str(step) + ", Minibatch Loss= " + \
+ "{:.4f}".format(loss) + ", Training Accuracy= " + \
+ "{:.3f}".format(acc))
+
+ print("Optimization Finished!")
+
+ # Calculate accuracy for 128 mnist test images
+ test_len = 128
+ test_data = mnist.test.images[:test_len].reshape((-1, timesteps, num_input))
+ test_label = mnist.test.labels[:test_len]
+ print("Testing Accuracy:", \
+ sess.run(accuracy, feed_dict={X: test_data, Y: test_label}))
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/convolutional_network.py b/tensorflow_v1/examples/3_NeuralNetworks/convolutional_network.py
new file mode 100644
index 00000000..63b6de16
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/convolutional_network.py
@@ -0,0 +1,125 @@
+""" Convolutional Neural Network.
+
+Build and train a convolutional neural network with TensorFlow.
+This example is using the MNIST database of handwritten digits
+(http://yann.lecun.com/exdb/mnist/)
+
+This example is using TensorFlow layers API, see 'convolutional_network_raw'
+example for a raw implementation with variables.
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+from __future__ import division, print_function, absolute_import
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=False)
+
+import tensorflow as tf
+
+# Training Parameters
+learning_rate = 0.001
+num_steps = 2000
+batch_size = 128
+
+# Network Parameters
+num_input = 784 # MNIST data input (img shape: 28*28)
+num_classes = 10 # MNIST total classes (0-9 digits)
+dropout = 0.25 # Dropout, probability to drop a unit
+
+
+# Create the neural network
+def conv_net(x_dict, n_classes, dropout, reuse, is_training):
+ # Define a scope for reusing the variables
+ with tf.variable_scope('ConvNet', reuse=reuse):
+ # TF Estimator input is a dict, in case of multiple inputs
+ x = x_dict['images']
+
+ # MNIST data input is a 1-D vector of 784 features (28*28 pixels)
+ # Reshape to match picture format [Height x Width x Channel]
+ # Tensor input become 4-D: [Batch Size, Height, Width, Channel]
+ x = tf.reshape(x, shape=[-1, 28, 28, 1])
+
+ # Convolution Layer with 32 filters and a kernel size of 5
+ conv1 = tf.layers.conv2d(x, 32, 5, activation=tf.nn.relu)
+ # Max Pooling (down-sampling) with strides of 2 and kernel size of 2
+ conv1 = tf.layers.max_pooling2d(conv1, 2, 2)
+
+ # Convolution Layer with 64 filters and a kernel size of 3
+ conv2 = tf.layers.conv2d(conv1, 64, 3, activation=tf.nn.relu)
+ # Max Pooling (down-sampling) with strides of 2 and kernel size of 2
+ conv2 = tf.layers.max_pooling2d(conv2, 2, 2)
+
+ # Flatten the data to a 1-D vector for the fully connected layer
+ fc1 = tf.contrib.layers.flatten(conv2)
+
+ # Fully connected layer (in tf contrib folder for now)
+ fc1 = tf.layers.dense(fc1, 1024)
+ # Apply Dropout (if is_training is False, dropout is not applied)
+ fc1 = tf.layers.dropout(fc1, rate=dropout, training=is_training)
+
+ # Output layer, class prediction
+ out = tf.layers.dense(fc1, n_classes)
+
+ return out
+
+
+# Define the model function (following TF Estimator Template)
+def model_fn(features, labels, mode):
+ # Build the neural network
+ # Because Dropout have different behavior at training and prediction time, we
+ # need to create 2 distinct computation graphs that still share the same weights.
+ logits_train = conv_net(features, num_classes, dropout, reuse=False,
+ is_training=True)
+ logits_test = conv_net(features, num_classes, dropout, reuse=True,
+ is_training=False)
+
+ # Predictions
+ pred_classes = tf.argmax(logits_test, axis=1)
+ pred_probas = tf.nn.softmax(logits_test)
+
+ # If prediction mode, early return
+ if mode == tf.estimator.ModeKeys.PREDICT:
+ return tf.estimator.EstimatorSpec(mode, predictions=pred_classes)
+
+ # Define loss and optimizer
+ loss_op = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(
+ logits=logits_train, labels=tf.cast(labels, dtype=tf.int32)))
+ optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
+ train_op = optimizer.minimize(loss_op,
+ global_step=tf.train.get_global_step())
+
+ # Evaluate the accuracy of the model
+ acc_op = tf.metrics.accuracy(labels=labels, predictions=pred_classes)
+
+ # TF Estimators requires to return a EstimatorSpec, that specify
+ # the different ops for training, evaluating, ...
+ estim_specs = tf.estimator.EstimatorSpec(
+ mode=mode,
+ predictions=pred_classes,
+ loss=loss_op,
+ train_op=train_op,
+ eval_metric_ops={'accuracy': acc_op})
+
+ return estim_specs
+
+# Build the Estimator
+model = tf.estimator.Estimator(model_fn)
+
+# Define the input function for training
+input_fn = tf.estimator.inputs.numpy_input_fn(
+ x={'images': mnist.train.images}, y=mnist.train.labels,
+ batch_size=batch_size, num_epochs=None, shuffle=True)
+# Train the Model
+model.train(input_fn, steps=num_steps)
+
+# Evaluate the Model
+# Define the input function for evaluating
+input_fn = tf.estimator.inputs.numpy_input_fn(
+ x={'images': mnist.test.images}, y=mnist.test.labels,
+ batch_size=batch_size, shuffle=False)
+# Use the Estimator 'evaluate' method
+e = model.evaluate(input_fn)
+
+print("Testing Accuracy:", e['accuracy'])
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/convolutional_network_raw.py b/tensorflow_v1/examples/3_NeuralNetworks/convolutional_network_raw.py
new file mode 100644
index 00000000..4fa6c863
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/convolutional_network_raw.py
@@ -0,0 +1,141 @@
+""" Convolutional Neural Network.
+
+Build and train a convolutional neural network with TensorFlow.
+This example is using the MNIST database of handwritten digits
+(http://yann.lecun.com/exdb/mnist/)
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import division, print_function, absolute_import
+
+import tensorflow as tf
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# Training Parameters
+learning_rate = 0.001
+num_steps = 200
+batch_size = 128
+display_step = 10
+
+# Network Parameters
+num_input = 784 # MNIST data input (img shape: 28*28)
+num_classes = 10 # MNIST total classes (0-9 digits)
+dropout = 0.75 # Dropout, probability to keep units
+
+# tf Graph input
+X = tf.placeholder(tf.float32, [None, num_input])
+Y = tf.placeholder(tf.float32, [None, num_classes])
+keep_prob = tf.placeholder(tf.float32) # dropout (keep probability)
+
+
+# Create some wrappers for simplicity
+def conv2d(x, W, b, strides=1):
+ # Conv2D wrapper, with bias and relu activation
+ x = tf.nn.conv2d(x, W, strides=[1, strides, strides, 1], padding='SAME')
+ x = tf.nn.bias_add(x, b)
+ return tf.nn.relu(x)
+
+
+def maxpool2d(x, k=2):
+ # MaxPool2D wrapper
+ return tf.nn.max_pool(x, ksize=[1, k, k, 1], strides=[1, k, k, 1],
+ padding='SAME')
+
+
+# Create model
+def conv_net(x, weights, biases, dropout):
+ # MNIST data input is a 1-D vector of 784 features (28*28 pixels)
+ # Reshape to match picture format [Height x Width x Channel]
+ # Tensor input become 4-D: [Batch Size, Height, Width, Channel]
+ x = tf.reshape(x, shape=[-1, 28, 28, 1])
+
+ # Convolution Layer
+ conv1 = conv2d(x, weights['wc1'], biases['bc1'])
+ # Max Pooling (down-sampling)
+ conv1 = maxpool2d(conv1, k=2)
+
+ # Convolution Layer
+ conv2 = conv2d(conv1, weights['wc2'], biases['bc2'])
+ # Max Pooling (down-sampling)
+ conv2 = maxpool2d(conv2, k=2)
+
+ # Fully connected layer
+ # Reshape conv2 output to fit fully connected layer input
+ fc1 = tf.reshape(conv2, [-1, weights['wd1'].get_shape().as_list()[0]])
+ fc1 = tf.add(tf.matmul(fc1, weights['wd1']), biases['bd1'])
+ fc1 = tf.nn.relu(fc1)
+ # Apply Dropout
+ fc1 = tf.nn.dropout(fc1, dropout)
+
+ # Output, class prediction
+ out = tf.add(tf.matmul(fc1, weights['out']), biases['out'])
+ return out
+
+# Store layers weight & bias
+weights = {
+ # 5x5 conv, 1 input, 32 outputs
+ 'wc1': tf.Variable(tf.random_normal([5, 5, 1, 32])),
+ # 5x5 conv, 32 inputs, 64 outputs
+ 'wc2': tf.Variable(tf.random_normal([5, 5, 32, 64])),
+ # fully connected, 7*7*64 inputs, 1024 outputs
+ 'wd1': tf.Variable(tf.random_normal([7*7*64, 1024])),
+ # 1024 inputs, 10 outputs (class prediction)
+ 'out': tf.Variable(tf.random_normal([1024, num_classes]))
+}
+
+biases = {
+ 'bc1': tf.Variable(tf.random_normal([32])),
+ 'bc2': tf.Variable(tf.random_normal([64])),
+ 'bd1': tf.Variable(tf.random_normal([1024])),
+ 'out': tf.Variable(tf.random_normal([num_classes]))
+}
+
+# Construct model
+logits = conv_net(X, weights, biases, keep_prob)
+prediction = tf.nn.softmax(logits)
+
+# Define loss and optimizer
+loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(
+ logits=logits, labels=Y))
+optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
+train_op = optimizer.minimize(loss_op)
+
+
+# Evaluate model
+correct_pred = tf.equal(tf.argmax(prediction, 1), tf.argmax(Y, 1))
+accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ for step in range(1, num_steps+1):
+ batch_x, batch_y = mnist.train.next_batch(batch_size)
+ # Run optimization op (backprop)
+ sess.run(train_op, feed_dict={X: batch_x, Y: batch_y, keep_prob: 0.8})
+ if step % display_step == 0 or step == 1:
+ # Calculate batch loss and accuracy
+ loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,
+ Y: batch_y,
+ keep_prob: 1.0})
+ print("Step " + str(step) + ", Minibatch Loss= " + \
+ "{:.4f}".format(loss) + ", Training Accuracy= " + \
+ "{:.3f}".format(acc))
+
+ print("Optimization Finished!")
+
+ # Calculate accuracy for 256 MNIST test images
+ print("Testing Accuracy:", \
+ sess.run(accuracy, feed_dict={X: mnist.test.images[:256],
+ Y: mnist.test.labels[:256],
+ keep_prob: 1.0}))
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/dcgan.py b/tensorflow_v1/examples/3_NeuralNetworks/dcgan.py
new file mode 100644
index 00000000..07bb4536
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/dcgan.py
@@ -0,0 +1,167 @@
+""" Deep Convolutional Generative Adversarial Network (DCGAN).
+
+Using deep convolutional generative adversarial networks (DCGAN) to generate
+digit images from a noise distribution.
+
+References:
+ - Unsupervised representation learning with deep convolutional generative
+ adversarial networks. A Radford, L Metz, S Chintala. arXiv:1511.06434.
+
+Links:
+ - [DCGAN Paper](https://arxiv.org/abs/1511.06434).
+ - [MNIST Dataset](http://yann.lecun.com/exdb/mnist/).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import division, print_function, absolute_import
+
+import matplotlib.pyplot as plt
+import numpy as np
+import tensorflow as tf
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# Training Params
+num_steps = 20000
+batch_size = 32
+
+# Network Params
+image_dim = 784 # 28*28 pixels * 1 channel
+gen_hidden_dim = 256
+disc_hidden_dim = 256
+noise_dim = 200 # Noise data points
+
+
+# Generator Network
+# Input: Noise, Output: Image
+def generator(x, reuse=False):
+ with tf.variable_scope('Generator', reuse=reuse):
+ # TensorFlow Layers automatically create variables and calculate their
+ # shape, based on the input.
+ x = tf.layers.dense(x, units=6 * 6 * 128)
+ x = tf.nn.tanh(x)
+ # Reshape to a 4-D array of images: (batch, height, width, channels)
+ # New shape: (batch, 6, 6, 128)
+ x = tf.reshape(x, shape=[-1, 6, 6, 128])
+ # Deconvolution, image shape: (batch, 14, 14, 64)
+ x = tf.layers.conv2d_transpose(x, 64, 4, strides=2)
+ # Deconvolution, image shape: (batch, 28, 28, 1)
+ x = tf.layers.conv2d_transpose(x, 1, 2, strides=2)
+ # Apply sigmoid to clip values between 0 and 1
+ x = tf.nn.sigmoid(x)
+ return x
+
+
+# Discriminator Network
+# Input: Image, Output: Prediction Real/Fake Image
+def discriminator(x, reuse=False):
+ with tf.variable_scope('Discriminator', reuse=reuse):
+ # Typical convolutional neural network to classify images.
+ x = tf.layers.conv2d(x, 64, 5)
+ x = tf.nn.tanh(x)
+ x = tf.layers.average_pooling2d(x, 2, 2)
+ x = tf.layers.conv2d(x, 128, 5)
+ x = tf.nn.tanh(x)
+ x = tf.layers.average_pooling2d(x, 2, 2)
+ x = tf.contrib.layers.flatten(x)
+ x = tf.layers.dense(x, 1024)
+ x = tf.nn.tanh(x)
+ # Output 2 classes: Real and Fake images
+ x = tf.layers.dense(x, 2)
+ return x
+
+# Build Networks
+# Network Inputs
+noise_input = tf.placeholder(tf.float32, shape=[None, noise_dim])
+real_image_input = tf.placeholder(tf.float32, shape=[None, 28, 28, 1])
+
+# Build Generator Network
+gen_sample = generator(noise_input)
+
+# Build 2 Discriminator Networks (one from real image input, one from generated samples)
+disc_real = discriminator(real_image_input)
+disc_fake = discriminator(gen_sample, reuse=True)
+disc_concat = tf.concat([disc_real, disc_fake], axis=0)
+
+# Build the stacked generator/discriminator
+stacked_gan = discriminator(gen_sample, reuse=True)
+
+# Build Targets (real or fake images)
+disc_target = tf.placeholder(tf.int32, shape=[None])
+gen_target = tf.placeholder(tf.int32, shape=[None])
+
+# Build Loss
+disc_loss = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(
+ logits=disc_concat, labels=disc_target))
+gen_loss = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(
+ logits=stacked_gan, labels=gen_target))
+
+# Build Optimizers
+optimizer_gen = tf.train.AdamOptimizer(learning_rate=0.001)
+optimizer_disc = tf.train.AdamOptimizer(learning_rate=0.001)
+
+# Training Variables for each optimizer
+# By default in TensorFlow, all variables are updated by each optimizer, so we
+# need to precise for each one of them the specific variables to update.
+# Generator Network Variables
+gen_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope='Generator')
+# Discriminator Network Variables
+disc_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope='Discriminator')
+
+# Create training operations
+train_gen = optimizer_gen.minimize(gen_loss, var_list=gen_vars)
+train_disc = optimizer_disc.minimize(disc_loss, var_list=disc_vars)
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ for i in range(1, num_steps+1):
+
+ # Prepare Input Data
+ # Get the next batch of MNIST data (only images are needed, not labels)
+ batch_x, _ = mnist.train.next_batch(batch_size)
+ batch_x = np.reshape(batch_x, newshape=[-1, 28, 28, 1])
+ # Generate noise to feed to the generator
+ z = np.random.uniform(-1., 1., size=[batch_size, noise_dim])
+
+ # Prepare Targets (Real image: 1, Fake image: 0)
+ # The first half of data fed to the discriminator are real images,
+ # the other half are fake images (coming from the generator).
+ batch_disc_y = np.concatenate(
+ [np.ones([batch_size]), np.zeros([batch_size])], axis=0)
+ # Generator tries to fool the discriminator, thus targets are 1.
+ batch_gen_y = np.ones([batch_size])
+
+ # Training
+ feed_dict = {real_image_input: batch_x, noise_input: z,
+ disc_target: batch_disc_y, gen_target: batch_gen_y}
+ _, _, gl, dl = sess.run([train_gen, train_disc, gen_loss, disc_loss],
+ feed_dict=feed_dict)
+ if i % 100 == 0 or i == 1:
+ print('Step %i: Generator Loss: %f, Discriminator Loss: %f' % (i, gl, dl))
+
+ # Generate images from noise, using the generator network.
+ f, a = plt.subplots(4, 10, figsize=(10, 4))
+ for i in range(10):
+ # Noise input.
+ z = np.random.uniform(-1., 1., size=[4, noise_dim])
+ g = sess.run(gen_sample, feed_dict={noise_input: z})
+ for j in range(4):
+ # Generate image from noise. Extend to 3 channels for matplot figure.
+ img = np.reshape(np.repeat(g[j][:, :, np.newaxis], 3, axis=2),
+ newshape=(28, 28, 3))
+ a[j][i].imshow(img)
+
+ f.show()
+ plt.draw()
+ plt.waitforbuttonpress()
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/dynamic_rnn.py b/tensorflow_v1/examples/3_NeuralNetworks/dynamic_rnn.py
new file mode 100644
index 00000000..b9cf063b
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/dynamic_rnn.py
@@ -0,0 +1,193 @@
+""" Dynamic Recurrent Neural Network.
+
+TensorFlow implementation of a Recurrent Neural Network (LSTM) that performs
+dynamic computation over sequences with variable length. This example is using
+a toy dataset to classify linear sequences. The generated sequences have
+variable length.
+
+Links:
+ [Long Short Term Memory](http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf)
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import print_function
+
+import tensorflow as tf
+import random
+
+
+# ====================
+# TOY DATA GENERATOR
+# ====================
+class ToySequenceData(object):
+ """ Generate sequence of data with dynamic length.
+ This class generate samples for training:
+ - Class 0: linear sequences (i.e. [0, 1, 2, 3,...])
+ - Class 1: random sequences (i.e. [1, 3, 10, 7,...])
+
+ NOTICE:
+ We have to pad each sequence to reach 'max_seq_len' for TensorFlow
+ consistency (we cannot feed a numpy array with inconsistent
+ dimensions). The dynamic calculation will then be perform thanks to
+ 'seqlen' attribute that records every actual sequence length.
+ """
+ def __init__(self, n_samples=1000, max_seq_len=20, min_seq_len=3,
+ max_value=1000):
+ self.data = []
+ self.labels = []
+ self.seqlen = []
+ for i in range(n_samples):
+ # Random sequence length
+ len = random.randint(min_seq_len, max_seq_len)
+ # Monitor sequence length for TensorFlow dynamic calculation
+ self.seqlen.append(len)
+ # Add a random or linear int sequence (50% prob)
+ if random.random() < .5:
+ # Generate a linear sequence
+ rand_start = random.randint(0, max_value - len)
+ s = [[float(i)/max_value] for i in
+ range(rand_start, rand_start + len)]
+ # Pad sequence for dimension consistency
+ s += [[0.] for i in range(max_seq_len - len)]
+ self.data.append(s)
+ self.labels.append([1., 0.])
+ else:
+ # Generate a random sequence
+ s = [[float(random.randint(0, max_value))/max_value]
+ for i in range(len)]
+ # Pad sequence for dimension consistency
+ s += [[0.] for i in range(max_seq_len - len)]
+ self.data.append(s)
+ self.labels.append([0., 1.])
+ self.batch_id = 0
+
+ def next(self, batch_size):
+ """ Return a batch of data. When dataset end is reached, start over.
+ """
+ if self.batch_id == len(self.data):
+ self.batch_id = 0
+ batch_data = (self.data[self.batch_id:min(self.batch_id +
+ batch_size, len(self.data))])
+ batch_labels = (self.labels[self.batch_id:min(self.batch_id +
+ batch_size, len(self.data))])
+ batch_seqlen = (self.seqlen[self.batch_id:min(self.batch_id +
+ batch_size, len(self.data))])
+ self.batch_id = min(self.batch_id + batch_size, len(self.data))
+ return batch_data, batch_labels, batch_seqlen
+
+
+# ==========
+# MODEL
+# ==========
+
+# Parameters
+learning_rate = 0.01
+training_steps = 10000
+batch_size = 128
+display_step = 200
+
+# Network Parameters
+seq_max_len = 20 # Sequence max length
+n_hidden = 64 # hidden layer num of features
+n_classes = 2 # linear sequence or not
+
+trainset = ToySequenceData(n_samples=1000, max_seq_len=seq_max_len)
+testset = ToySequenceData(n_samples=500, max_seq_len=seq_max_len)
+
+# tf Graph input
+x = tf.placeholder("float", [None, seq_max_len, 1])
+y = tf.placeholder("float", [None, n_classes])
+# A placeholder for indicating each sequence length
+seqlen = tf.placeholder(tf.int32, [None])
+
+# Define weights
+weights = {
+ 'out': tf.Variable(tf.random_normal([n_hidden, n_classes]))
+}
+biases = {
+ 'out': tf.Variable(tf.random_normal([n_classes]))
+}
+
+
+def dynamicRNN(x, seqlen, weights, biases):
+
+ # Prepare data shape to match `rnn` function requirements
+ # Current data input shape: (batch_size, n_steps, n_input)
+ # Required shape: 'n_steps' tensors list of shape (batch_size, n_input)
+
+ # Unstack to get a list of 'n_steps' tensors of shape (batch_size, n_input)
+ x = tf.unstack(x, seq_max_len, 1)
+
+ # Define a lstm cell with tensorflow
+ lstm_cell = tf.contrib.rnn.BasicLSTMCell(n_hidden)
+
+ # Get lstm cell output, providing 'sequence_length' will perform dynamic
+ # calculation.
+ outputs, states = tf.contrib.rnn.static_rnn(lstm_cell, x, dtype=tf.float32,
+ sequence_length=seqlen)
+
+ # When performing dynamic calculation, we must retrieve the last
+ # dynamically computed output, i.e., if a sequence length is 10, we need
+ # to retrieve the 10th output.
+ # However TensorFlow doesn't support advanced indexing yet, so we build
+ # a custom op that for each sample in batch size, get its length and
+ # get the corresponding relevant output.
+
+ # 'outputs' is a list of output at every timestep, we pack them in a Tensor
+ # and change back dimension to [batch_size, n_step, n_input]
+ outputs = tf.stack(outputs)
+ outputs = tf.transpose(outputs, [1, 0, 2])
+
+ # Hack to build the indexing and retrieve the right output.
+ batch_size = tf.shape(outputs)[0]
+ # Start indices for each sample
+ index = tf.range(0, batch_size) * seq_max_len + (seqlen - 1)
+ # Indexing
+ outputs = tf.gather(tf.reshape(outputs, [-1, n_hidden]), index)
+
+ # Linear activation, using outputs computed above
+ return tf.matmul(outputs, weights['out']) + biases['out']
+
+pred = dynamicRNN(x, seqlen, weights, biases)
+
+# Define loss and optimizer
+cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=pred, labels=y))
+optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate).minimize(cost)
+
+# Evaluate model
+correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))
+accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ for step in range(1, training_steps + 1):
+ batch_x, batch_y, batch_seqlen = trainset.next(batch_size)
+ # Run optimization op (backprop)
+ sess.run(optimizer, feed_dict={x: batch_x, y: batch_y,
+ seqlen: batch_seqlen})
+ if step % display_step == 0 or step == 1:
+ # Calculate batch accuracy & loss
+ acc, loss = sess.run([accuracy, cost], feed_dict={x: batch_x, y: batch_y,
+ seqlen: batch_seqlen})
+ print("Step " + str(step*batch_size) + ", Minibatch Loss= " + \
+ "{:.6f}".format(loss) + ", Training Accuracy= " + \
+ "{:.5f}".format(acc))
+
+ print("Optimization Finished!")
+
+ # Calculate accuracy
+ test_data = testset.data
+ test_label = testset.labels
+ test_seqlen = testset.seqlen
+ print("Testing Accuracy:", \
+ sess.run(accuracy, feed_dict={x: test_data, y: test_label,
+ seqlen: test_seqlen}))
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/gan.py b/tensorflow_v1/examples/3_NeuralNetworks/gan.py
new file mode 100644
index 00000000..9f51db9d
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/gan.py
@@ -0,0 +1,157 @@
+""" Generative Adversarial Networks (GAN).
+
+Using generative adversarial networks (GAN) to generate digit images from a
+noise distribution.
+
+References:
+ - Generative adversarial nets. I Goodfellow, J Pouget-Abadie, M Mirza,
+ B Xu, D Warde-Farley, S Ozair, Y. Bengio. Advances in neural information
+ processing systems, 2672-2680.
+ - Understanding the difficulty of training deep feedforward neural networks.
+ X Glorot, Y Bengio. Aistats 9, 249-256
+
+Links:
+ - [GAN Paper](https://arxiv.org/pdf/1406.2661.pdf).
+ - [MNIST Dataset](http://yann.lecun.com/exdb/mnist/).
+ - [Xavier Glorot Init](www.cs.cmu.edu/~bhiksha/courses/deeplearning/Fall.../AISTATS2010_Glorot.pdf).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import division, print_function, absolute_import
+
+import matplotlib.pyplot as plt
+import numpy as np
+import tensorflow as tf
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# Training Params
+num_steps = 100000
+batch_size = 128
+learning_rate = 0.0002
+
+# Network Params
+image_dim = 784 # 28*28 pixels
+gen_hidden_dim = 256
+disc_hidden_dim = 256
+noise_dim = 100 # Noise data points
+
+# A custom initialization (see Xavier Glorot init)
+def glorot_init(shape):
+ return tf.random_normal(shape=shape, stddev=1. / tf.sqrt(shape[0] / 2.))
+
+# Store layers weight & bias
+weights = {
+ 'gen_hidden1': tf.Variable(glorot_init([noise_dim, gen_hidden_dim])),
+ 'gen_out': tf.Variable(glorot_init([gen_hidden_dim, image_dim])),
+ 'disc_hidden1': tf.Variable(glorot_init([image_dim, disc_hidden_dim])),
+ 'disc_out': tf.Variable(glorot_init([disc_hidden_dim, 1])),
+}
+biases = {
+ 'gen_hidden1': tf.Variable(tf.zeros([gen_hidden_dim])),
+ 'gen_out': tf.Variable(tf.zeros([image_dim])),
+ 'disc_hidden1': tf.Variable(tf.zeros([disc_hidden_dim])),
+ 'disc_out': tf.Variable(tf.zeros([1])),
+}
+
+
+# Generator
+def generator(x):
+ hidden_layer = tf.matmul(x, weights['gen_hidden1'])
+ hidden_layer = tf.add(hidden_layer, biases['gen_hidden1'])
+ hidden_layer = tf.nn.relu(hidden_layer)
+ out_layer = tf.matmul(hidden_layer, weights['gen_out'])
+ out_layer = tf.add(out_layer, biases['gen_out'])
+ out_layer = tf.nn.sigmoid(out_layer)
+ return out_layer
+
+
+# Discriminator
+def discriminator(x):
+ hidden_layer = tf.matmul(x, weights['disc_hidden1'])
+ hidden_layer = tf.add(hidden_layer, biases['disc_hidden1'])
+ hidden_layer = tf.nn.relu(hidden_layer)
+ out_layer = tf.matmul(hidden_layer, weights['disc_out'])
+ out_layer = tf.add(out_layer, biases['disc_out'])
+ out_layer = tf.nn.sigmoid(out_layer)
+ return out_layer
+
+# Build Networks
+# Network Inputs
+gen_input = tf.placeholder(tf.float32, shape=[None, noise_dim], name='input_noise')
+disc_input = tf.placeholder(tf.float32, shape=[None, image_dim], name='disc_input')
+
+# Build Generator Network
+gen_sample = generator(gen_input)
+
+# Build 2 Discriminator Networks (one from noise input, one from generated samples)
+disc_real = discriminator(disc_input)
+disc_fake = discriminator(gen_sample)
+
+# Build Loss
+gen_loss = -tf.reduce_mean(tf.log(disc_fake))
+disc_loss = -tf.reduce_mean(tf.log(disc_real) + tf.log(1. - disc_fake))
+
+# Build Optimizers
+optimizer_gen = tf.train.AdamOptimizer(learning_rate=learning_rate)
+optimizer_disc = tf.train.AdamOptimizer(learning_rate=learning_rate)
+
+# Training Variables for each optimizer
+# By default in TensorFlow, all variables are updated by each optimizer, so we
+# need to precise for each one of them the specific variables to update.
+# Generator Network Variables
+gen_vars = [weights['gen_hidden1'], weights['gen_out'],
+ biases['gen_hidden1'], biases['gen_out']]
+# Discriminator Network Variables
+disc_vars = [weights['disc_hidden1'], weights['disc_out'],
+ biases['disc_hidden1'], biases['disc_out']]
+
+# Create training operations
+train_gen = optimizer_gen.minimize(gen_loss, var_list=gen_vars)
+train_disc = optimizer_disc.minimize(disc_loss, var_list=disc_vars)
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ for i in range(1, num_steps+1):
+ # Prepare Data
+ # Get the next batch of MNIST data (only images are needed, not labels)
+ batch_x, _ = mnist.train.next_batch(batch_size)
+ # Generate noise to feed to the generator
+ z = np.random.uniform(-1., 1., size=[batch_size, noise_dim])
+
+ # Train
+ feed_dict = {disc_input: batch_x, gen_input: z}
+ _, _, gl, dl = sess.run([train_gen, train_disc, gen_loss, disc_loss],
+ feed_dict=feed_dict)
+ if i % 1000 == 0 or i == 1:
+ print('Step %i: Generator Loss: %f, Discriminator Loss: %f' % (i, gl, dl))
+
+ # Generate images from noise, using the generator network.
+ f, a = plt.subplots(4, 10, figsize=(10, 4))
+ for i in range(10):
+ # Noise input.
+ z = np.random.uniform(-1., 1., size=[4, noise_dim])
+ g = sess.run([gen_sample], feed_dict={gen_input: z})
+ g = np.reshape(g, newshape=(4, 28, 28, 1))
+ # Reverse colours for better display
+ g = -1 * (g - 1)
+ for j in range(4):
+ # Generate image from noise. Extend to 3 channels for matplot figure.
+ img = np.reshape(np.repeat(g[j][:, :, np.newaxis], 3, axis=2),
+ newshape=(28, 28, 3))
+ a[j][i].imshow(img)
+
+ f.show()
+ plt.draw()
+ plt.waitforbuttonpress()
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/multilayer_perceptron.py b/tensorflow_v1/examples/3_NeuralNetworks/multilayer_perceptron.py
new file mode 100644
index 00000000..8929682a
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/multilayer_perceptron.py
@@ -0,0 +1,104 @@
+""" Multilayer Perceptron.
+
+A Multilayer Perceptron (Neural Network) implementation example using
+TensorFlow library. This example is using the MNIST database of handwritten
+digits (http://yann.lecun.com/exdb/mnist/).
+
+Links:
+ [MNIST Dataset](http://yann.lecun.com/exdb/mnist/).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+# ------------------------------------------------------------------
+#
+# THIS EXAMPLE HAS BEEN RENAMED 'neural_network.py', FOR SIMPLICITY.
+#
+# ------------------------------------------------------------------
+
+
+from __future__ import print_function
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+import tensorflow as tf
+
+# Parameters
+learning_rate = 0.001
+training_epochs = 15
+batch_size = 100
+display_step = 1
+
+# Network Parameters
+n_hidden_1 = 256 # 1st layer number of neurons
+n_hidden_2 = 256 # 2nd layer number of neurons
+n_input = 784 # MNIST data input (img shape: 28*28)
+n_classes = 10 # MNIST total classes (0-9 digits)
+
+# tf Graph input
+X = tf.placeholder("float", [None, n_input])
+Y = tf.placeholder("float", [None, n_classes])
+
+# Store layers weight & bias
+weights = {
+ 'h1': tf.Variable(tf.random_normal([n_input, n_hidden_1])),
+ 'h2': tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2])),
+ 'out': tf.Variable(tf.random_normal([n_hidden_2, n_classes]))
+}
+biases = {
+ 'b1': tf.Variable(tf.random_normal([n_hidden_1])),
+ 'b2': tf.Variable(tf.random_normal([n_hidden_2])),
+ 'out': tf.Variable(tf.random_normal([n_classes]))
+}
+
+
+# Create model
+def multilayer_perceptron(x):
+ # Hidden fully connected layer with 256 neurons
+ layer_1 = tf.add(tf.matmul(x, weights['h1']), biases['b1'])
+ # Hidden fully connected layer with 256 neurons
+ layer_2 = tf.add(tf.matmul(layer_1, weights['h2']), biases['b2'])
+ # Output fully connected layer with a neuron for each class
+ out_layer = tf.matmul(layer_2, weights['out']) + biases['out']
+ return out_layer
+
+# Construct model
+logits = multilayer_perceptron(X)
+
+# Define loss and optimizer
+loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(
+ logits=logits, labels=Y))
+optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
+train_op = optimizer.minimize(loss_op)
+# Initializing the variables
+init = tf.global_variables_initializer()
+
+with tf.Session() as sess:
+ sess.run(init)
+
+ # Training cycle
+ for epoch in range(training_epochs):
+ avg_cost = 0.
+ total_batch = int(mnist.train.num_examples/batch_size)
+ # Loop over all batches
+ for i in range(total_batch):
+ batch_x, batch_y = mnist.train.next_batch(batch_size)
+ # Run optimization op (backprop) and cost op (to get loss value)
+ _, c = sess.run([train_op, loss_op], feed_dict={X: batch_x,
+ Y: batch_y})
+ # Compute average loss
+ avg_cost += c / total_batch
+ # Display logs per epoch step
+ if epoch % display_step == 0:
+ print("Epoch:", '%04d' % (epoch+1), "cost={:.9f}".format(avg_cost))
+ print("Optimization Finished!")
+
+ # Test model
+ pred = tf.nn.softmax(logits) # Apply softmax to logits
+ correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(Y, 1))
+ # Calculate accuracy
+ accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
+ print("Accuracy:", accuracy.eval({X: mnist.test.images, Y: mnist.test.labels}))
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/neural_network.py b/tensorflow_v1/examples/3_NeuralNetworks/neural_network.py
new file mode 100644
index 00000000..b7d0fa82
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/neural_network.py
@@ -0,0 +1,103 @@
+""" Neural Network.
+
+A 2-Hidden Layers Fully Connected Neural Network (a.k.a Multilayer Perceptron)
+implementation with TensorFlow. This example is using the MNIST database
+of handwritten digits (http://yann.lecun.com/exdb/mnist/).
+
+This example is using TensorFlow layers, see 'neural_network_raw' example for
+a raw implementation with variables.
+
+Links:
+ [MNIST Dataset](http://yann.lecun.com/exdb/mnist/).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import print_function
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=False)
+
+import tensorflow as tf
+
+# Parameters
+learning_rate = 0.1
+num_steps = 1000
+batch_size = 128
+display_step = 100
+
+# Network Parameters
+n_hidden_1 = 256 # 1st layer number of neurons
+n_hidden_2 = 256 # 2nd layer number of neurons
+num_input = 784 # MNIST data input (img shape: 28*28)
+num_classes = 10 # MNIST total classes (0-9 digits)
+
+
+# Define the neural network
+def neural_net(x_dict):
+ # TF Estimator input is a dict, in case of multiple inputs
+ x = x_dict['images']
+ # Hidden fully connected layer with 256 neurons
+ layer_1 = tf.layers.dense(x, n_hidden_1)
+ # Hidden fully connected layer with 256 neurons
+ layer_2 = tf.layers.dense(layer_1, n_hidden_2)
+ # Output fully connected layer with a neuron for each class
+ out_layer = tf.layers.dense(layer_2, num_classes)
+ return out_layer
+
+
+# Define the model function (following TF Estimator Template)
+def model_fn(features, labels, mode):
+ # Build the neural network
+ logits = neural_net(features)
+
+ # Predictions
+ pred_classes = tf.argmax(logits, axis=1)
+ pred_probas = tf.nn.softmax(logits)
+
+ # If prediction mode, early return
+ if mode == tf.estimator.ModeKeys.PREDICT:
+ return tf.estimator.EstimatorSpec(mode, predictions=pred_classes)
+
+ # Define loss and optimizer
+ loss_op = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(
+ logits=logits, labels=tf.cast(labels, dtype=tf.int32)))
+ optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)
+ train_op = optimizer.minimize(loss_op,
+ global_step=tf.train.get_global_step())
+
+ # Evaluate the accuracy of the model
+ acc_op = tf.metrics.accuracy(labels=labels, predictions=pred_classes)
+
+ # TF Estimators requires to return a EstimatorSpec, that specify
+ # the different ops for training, evaluating, ...
+ estim_specs = tf.estimator.EstimatorSpec(
+ mode=mode,
+ predictions=pred_classes,
+ loss=loss_op,
+ train_op=train_op,
+ eval_metric_ops={'accuracy': acc_op})
+
+ return estim_specs
+
+# Build the Estimator
+model = tf.estimator.Estimator(model_fn)
+
+# Define the input function for training
+input_fn = tf.estimator.inputs.numpy_input_fn(
+ x={'images': mnist.train.images}, y=mnist.train.labels,
+ batch_size=batch_size, num_epochs=None, shuffle=True)
+# Train the Model
+model.train(input_fn, steps=num_steps)
+
+# Evaluate the Model
+# Define the input function for evaluating
+input_fn = tf.estimator.inputs.numpy_input_fn(
+ x={'images': mnist.test.images}, y=mnist.test.labels,
+ batch_size=batch_size, shuffle=False)
+# Use the Estimator 'evaluate' method
+e = model.evaluate(input_fn)
+
+print("Testing Accuracy:", e['accuracy'])
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/neural_network_eager_api.py b/tensorflow_v1/examples/3_NeuralNetworks/neural_network_eager_api.py
new file mode 100644
index 00000000..fe0714f6
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/neural_network_eager_api.py
@@ -0,0 +1,133 @@
+""" Neural Network with Eager API.
+
+A 2-Hidden Layers Fully Connected Neural Network (a.k.a Multilayer Perceptron)
+implementation with TensorFlow's Eager API. This example is using the MNIST database
+of handwritten digits (http://yann.lecun.com/exdb/mnist/).
+
+This example is using TensorFlow layers, see 'neural_network_raw' example for
+a raw implementation with variables.
+
+Links:
+ [MNIST Dataset](http://yann.lecun.com/exdb/mnist/).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+from __future__ import print_function
+
+import tensorflow as tf
+
+# Set Eager API
+tf.enable_eager_execution()
+tfe = tf.contrib.eager
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=False)
+
+# Parameters
+learning_rate = 0.001
+num_steps = 1000
+batch_size = 128
+display_step = 100
+
+# Network Parameters
+n_hidden_1 = 256 # 1st layer number of neurons
+n_hidden_2 = 256 # 2nd layer number of neurons
+num_input = 784 # MNIST data input (img shape: 28*28)
+num_classes = 10 # MNIST total classes (0-9 digits)
+
+# Using TF Dataset to split data into batches
+dataset = tf.data.Dataset.from_tensor_slices(
+ (mnist.train.images, mnist.train.labels))
+dataset = dataset.repeat().batch(batch_size).prefetch(batch_size)
+dataset_iter = tfe.Iterator(dataset)
+
+
+# Define the neural network. To use eager API and tf.layers API together,
+# we must instantiate a tfe.Network class as follow:
+class NeuralNet(tfe.Network):
+ def __init__(self):
+ # Define each layer
+ super(NeuralNet, self).__init__()
+ # Hidden fully connected layer with 256 neurons
+ self.layer1 = self.track_layer(
+ tf.layers.Dense(n_hidden_1, activation=tf.nn.relu))
+ # Hidden fully connected layer with 256 neurons
+ self.layer2 = self.track_layer(
+ tf.layers.Dense(n_hidden_2, activation=tf.nn.relu))
+ # Output fully connected layer with a neuron for each class
+ self.out_layer = self.track_layer(tf.layers.Dense(num_classes))
+
+ def call(self, x):
+ x = self.layer1(x)
+ x = self.layer2(x)
+ return self.out_layer(x)
+
+
+neural_net = NeuralNet()
+
+
+# Cross-Entropy loss function
+def loss_fn(inference_fn, inputs, labels):
+ # Using sparse_softmax cross entropy
+ return tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(
+ logits=inference_fn(inputs), labels=labels))
+
+
+# Calculate accuracy
+def accuracy_fn(inference_fn, inputs, labels):
+ prediction = tf.nn.softmax(inference_fn(inputs))
+ correct_pred = tf.equal(tf.argmax(prediction, 1), labels)
+ return tf.reduce_mean(tf.cast(correct_pred, tf.float32))
+
+
+# SGD Optimizer
+optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
+# Compute gradients
+grad = tfe.implicit_gradients(loss_fn)
+
+# Training
+average_loss = 0.
+average_acc = 0.
+for step in range(num_steps):
+
+ # Iterate through the dataset
+ d = dataset_iter.next()
+
+ # Images
+ x_batch = d[0]
+ # Labels
+ y_batch = tf.cast(d[1], dtype=tf.int64)
+
+ # Compute the batch loss
+ batch_loss = loss_fn(neural_net, x_batch, y_batch)
+ average_loss += batch_loss
+ # Compute the batch accuracy
+ batch_accuracy = accuracy_fn(neural_net, x_batch, y_batch)
+ average_acc += batch_accuracy
+
+ if step == 0:
+ # Display the initial cost, before optimizing
+ print("Initial loss= {:.9f}".format(average_loss))
+
+ # Update the variables following gradients info
+ optimizer.apply_gradients(grad(neural_net, x_batch, y_batch))
+
+ # Display info
+ if (step + 1) % display_step == 0 or step == 0:
+ if step > 0:
+ average_loss /= display_step
+ average_acc /= display_step
+ print("Step:", '%04d' % (step + 1), " loss=",
+ "{:.9f}".format(average_loss), " accuracy=",
+ "{:.4f}".format(average_acc))
+ average_loss = 0.
+ average_acc = 0.
+
+# Evaluate model on the test image set
+testX = mnist.test.images
+testY = mnist.test.labels
+
+test_acc = accuracy_fn(neural_net, testX, testY)
+print("Testset Accuracy: {:.4f}".format(test_acc))
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/neural_network_raw.py b/tensorflow_v1/examples/3_NeuralNetworks/neural_network_raw.py
new file mode 100644
index 00000000..a5bf25ca
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/neural_network_raw.py
@@ -0,0 +1,101 @@
+""" Neural Network.
+
+A 2-Hidden Layers Fully Connected Neural Network (a.k.a Multilayer Perceptron)
+implementation with TensorFlow. This example is using the MNIST database
+of handwritten digits (http://yann.lecun.com/exdb/mnist/).
+
+Links:
+ [MNIST Dataset](http://yann.lecun.com/exdb/mnist/).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import print_function
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+import tensorflow as tf
+
+# Parameters
+learning_rate = 0.1
+num_steps = 500
+batch_size = 128
+display_step = 100
+
+# Network Parameters
+n_hidden_1 = 256 # 1st layer number of neurons
+n_hidden_2 = 256 # 2nd layer number of neurons
+num_input = 784 # MNIST data input (img shape: 28*28)
+num_classes = 10 # MNIST total classes (0-9 digits)
+
+# tf Graph input
+X = tf.placeholder("float", [None, num_input])
+Y = tf.placeholder("float", [None, num_classes])
+
+# Store layers weight & bias
+weights = {
+ 'h1': tf.Variable(tf.random_normal([num_input, n_hidden_1])),
+ 'h2': tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2])),
+ 'out': tf.Variable(tf.random_normal([n_hidden_2, num_classes]))
+}
+biases = {
+ 'b1': tf.Variable(tf.random_normal([n_hidden_1])),
+ 'b2': tf.Variable(tf.random_normal([n_hidden_2])),
+ 'out': tf.Variable(tf.random_normal([num_classes]))
+}
+
+
+# Create model
+def neural_net(x):
+ # Hidden fully connected layer with 256 neurons
+ layer_1 = tf.add(tf.matmul(x, weights['h1']), biases['b1'])
+ # Hidden fully connected layer with 256 neurons
+ layer_2 = tf.add(tf.matmul(layer_1, weights['h2']), biases['b2'])
+ # Output fully connected layer with a neuron for each class
+ out_layer = tf.matmul(layer_2, weights['out']) + biases['out']
+ return out_layer
+
+# Construct model
+logits = neural_net(X)
+prediction = tf.nn.softmax(logits)
+
+# Define loss and optimizer
+loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(
+ logits=logits, labels=Y))
+optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
+train_op = optimizer.minimize(loss_op)
+
+# Evaluate model
+correct_pred = tf.equal(tf.argmax(prediction, 1), tf.argmax(Y, 1))
+accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ for step in range(1, num_steps+1):
+ batch_x, batch_y = mnist.train.next_batch(batch_size)
+ # Run optimization op (backprop)
+ sess.run(train_op, feed_dict={X: batch_x, Y: batch_y})
+ if step % display_step == 0 or step == 1:
+ # Calculate batch loss and accuracy
+ loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,
+ Y: batch_y})
+ print("Step " + str(step) + ", Minibatch Loss= " + \
+ "{:.4f}".format(loss) + ", Training Accuracy= " + \
+ "{:.3f}".format(acc))
+
+ print("Optimization Finished!")
+
+ # Calculate accuracy for MNIST test images
+ print("Testing Accuracy:", \
+ sess.run(accuracy, feed_dict={X: mnist.test.images,
+ Y: mnist.test.labels}))
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/recurrent_network.py b/tensorflow_v1/examples/3_NeuralNetworks/recurrent_network.py
new file mode 100644
index 00000000..2c93c087
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/recurrent_network.py
@@ -0,0 +1,115 @@
+""" Recurrent Neural Network.
+
+A Recurrent Neural Network (LSTM) implementation example using TensorFlow library.
+This example is using the MNIST database of handwritten digits (http://yann.lecun.com/exdb/mnist/)
+
+Links:
+ [Long Short Term Memory](http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf)
+ [MNIST Dataset](http://yann.lecun.com/exdb/mnist/).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+
+from __future__ import print_function
+
+import tensorflow as tf
+from tensorflow.contrib import rnn
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+'''
+To classify images using a recurrent neural network, we consider every image
+row as a sequence of pixels. Because MNIST image shape is 28*28px, we will then
+handle 28 sequences of 28 steps for every sample.
+'''
+
+# Training Parameters
+learning_rate = 0.001
+training_steps = 10000
+batch_size = 128
+display_step = 200
+
+# Network Parameters
+num_input = 28 # MNIST data input (img shape: 28*28)
+timesteps = 28 # timesteps
+num_hidden = 128 # hidden layer num of features
+num_classes = 10 # MNIST total classes (0-9 digits)
+
+# tf Graph input
+X = tf.placeholder("float", [None, timesteps, num_input])
+Y = tf.placeholder("float", [None, num_classes])
+
+# Define weights
+weights = {
+ 'out': tf.Variable(tf.random_normal([num_hidden, num_classes]))
+}
+biases = {
+ 'out': tf.Variable(tf.random_normal([num_classes]))
+}
+
+
+def RNN(x, weights, biases):
+
+ # Prepare data shape to match `rnn` function requirements
+ # Current data input shape: (batch_size, timesteps, n_input)
+ # Required shape: 'timesteps' tensors list of shape (batch_size, n_input)
+
+ # Unstack to get a list of 'timesteps' tensors of shape (batch_size, n_input)
+ x = tf.unstack(x, timesteps, 1)
+
+ # Define a lstm cell with tensorflow
+ lstm_cell = rnn.BasicLSTMCell(num_hidden, forget_bias=1.0)
+
+ # Get lstm cell output
+ outputs, states = rnn.static_rnn(lstm_cell, x, dtype=tf.float32)
+
+ # Linear activation, using rnn inner loop last output
+ return tf.matmul(outputs[-1], weights['out']) + biases['out']
+
+logits = RNN(X, weights, biases)
+prediction = tf.nn.softmax(logits)
+
+# Define loss and optimizer
+loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(
+ logits=logits, labels=Y))
+optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)
+train_op = optimizer.minimize(loss_op)
+
+# Evaluate model (with test logits, for dropout to be disabled)
+correct_pred = tf.equal(tf.argmax(prediction, 1), tf.argmax(Y, 1))
+accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ for step in range(1, training_steps+1):
+ batch_x, batch_y = mnist.train.next_batch(batch_size)
+ # Reshape data to get 28 seq of 28 elements
+ batch_x = batch_x.reshape((batch_size, timesteps, num_input))
+ # Run optimization op (backprop)
+ sess.run(train_op, feed_dict={X: batch_x, Y: batch_y})
+ if step % display_step == 0 or step == 1:
+ # Calculate batch loss and accuracy
+ loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,
+ Y: batch_y})
+ print("Step " + str(step) + ", Minibatch Loss= " + \
+ "{:.4f}".format(loss) + ", Training Accuracy= " + \
+ "{:.3f}".format(acc))
+
+ print("Optimization Finished!")
+
+ # Calculate accuracy for 128 mnist test images
+ test_len = 128
+ test_data = mnist.test.images[:test_len].reshape((-1, timesteps, num_input))
+ test_label = mnist.test.labels[:test_len]
+ print("Testing Accuracy:", \
+ sess.run(accuracy, feed_dict={X: test_data, Y: test_label}))
diff --git a/tensorflow_v1/examples/3_NeuralNetworks/variational_autoencoder.py b/tensorflow_v1/examples/3_NeuralNetworks/variational_autoencoder.py
new file mode 100644
index 00000000..322690f6
--- /dev/null
+++ b/tensorflow_v1/examples/3_NeuralNetworks/variational_autoencoder.py
@@ -0,0 +1,143 @@
+""" Variational Auto-Encoder Example.
+
+Using a variational auto-encoder to generate digits images from noise.
+MNIST handwritten digits are used as training examples.
+
+References:
+ - Auto-Encoding Variational Bayes The International Conference on Learning
+ Representations (ICLR), Banff, 2014. D.P. Kingma, M. Welling
+ - Understanding the difficulty of training deep feedforward neural networks.
+ X Glorot, Y Bengio. Aistats 9, 249-256
+ - Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. "Gradient-based
+ learning applied to document recognition." Proceedings of the IEEE,
+ 86(11):2278-2324, November 1998.
+
+Links:
+ - [VAE Paper] https://arxiv.org/abs/1312.6114
+ - [Xavier Glorot Init](www.cs.cmu.edu/~bhiksha/courses/deeplearning/Fall.../AISTATS2010_Glorot.pdf).
+ - [MNIST Dataset] http://yann.lecun.com/exdb/mnist/
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+from __future__ import division, print_function, absolute_import
+
+import numpy as np
+import matplotlib.pyplot as plt
+from scipy.stats import norm
+import tensorflow as tf
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# Parameters
+learning_rate = 0.001
+num_steps = 30000
+batch_size = 64
+
+# Network Parameters
+image_dim = 784 # MNIST images are 28x28 pixels
+hidden_dim = 512
+latent_dim = 2
+
+# A custom initialization (see Xavier Glorot init)
+def glorot_init(shape):
+ return tf.random_normal(shape=shape, stddev=1. / tf.sqrt(shape[0] / 2.))
+
+# Variables
+weights = {
+ 'encoder_h1': tf.Variable(glorot_init([image_dim, hidden_dim])),
+ 'z_mean': tf.Variable(glorot_init([hidden_dim, latent_dim])),
+ 'z_std': tf.Variable(glorot_init([hidden_dim, latent_dim])),
+ 'decoder_h1': tf.Variable(glorot_init([latent_dim, hidden_dim])),
+ 'decoder_out': tf.Variable(glorot_init([hidden_dim, image_dim]))
+}
+biases = {
+ 'encoder_b1': tf.Variable(glorot_init([hidden_dim])),
+ 'z_mean': tf.Variable(glorot_init([latent_dim])),
+ 'z_std': tf.Variable(glorot_init([latent_dim])),
+ 'decoder_b1': tf.Variable(glorot_init([hidden_dim])),
+ 'decoder_out': tf.Variable(glorot_init([image_dim]))
+}
+
+# Building the encoder
+input_image = tf.placeholder(tf.float32, shape=[None, image_dim])
+encoder = tf.matmul(input_image, weights['encoder_h1']) + biases['encoder_b1']
+encoder = tf.nn.tanh(encoder)
+z_mean = tf.matmul(encoder, weights['z_mean']) + biases['z_mean']
+z_std = tf.matmul(encoder, weights['z_std']) + biases['z_std']
+
+# Sampler: Normal (gaussian) random distribution
+eps = tf.random_normal(tf.shape(z_std), dtype=tf.float32, mean=0., stddev=1.0,
+ name='epsilon')
+z = z_mean + tf.exp(z_std / 2) * eps
+
+# Building the decoder (with scope to re-use these layers later)
+decoder = tf.matmul(z, weights['decoder_h1']) + biases['decoder_b1']
+decoder = tf.nn.tanh(decoder)
+decoder = tf.matmul(decoder, weights['decoder_out']) + biases['decoder_out']
+decoder = tf.nn.sigmoid(decoder)
+
+
+# Define VAE Loss
+def vae_loss(x_reconstructed, x_true):
+ # Reconstruction loss
+ encode_decode_loss = x_true * tf.log(1e-10 + x_reconstructed) \
+ + (1 - x_true) * tf.log(1e-10 + 1 - x_reconstructed)
+ encode_decode_loss = -tf.reduce_sum(encode_decode_loss, 1)
+ # KL Divergence loss
+ kl_div_loss = 1 + z_std - tf.square(z_mean) - tf.exp(z_std)
+ kl_div_loss = -0.5 * tf.reduce_sum(kl_div_loss, 1)
+ return tf.reduce_mean(encode_decode_loss + kl_div_loss)
+
+loss_op = vae_loss(decoder, input_image)
+optimizer = tf.train.RMSPropOptimizer(learning_rate=learning_rate)
+train_op = optimizer.minimize(loss_op)
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ for i in range(1, num_steps+1):
+ # Prepare Data
+ # Get the next batch of MNIST data (only images are needed, not labels)
+ batch_x, _ = mnist.train.next_batch(batch_size)
+
+ # Train
+ feed_dict = {input_image: batch_x}
+ _, l = sess.run([train_op, loss_op], feed_dict=feed_dict)
+ if i % 1000 == 0 or i == 1:
+ print('Step %i, Loss: %f' % (i, l))
+
+ # Testing
+ # Generator takes noise as input
+ noise_input = tf.placeholder(tf.float32, shape=[None, latent_dim])
+ # Rebuild the decoder to create image from noise
+ decoder = tf.matmul(noise_input, weights['decoder_h1']) + biases['decoder_b1']
+ decoder = tf.nn.tanh(decoder)
+ decoder = tf.matmul(decoder, weights['decoder_out']) + biases['decoder_out']
+ decoder = tf.nn.sigmoid(decoder)
+
+ # Building a manifold of generated digits
+ n = 20
+ x_axis = np.linspace(-3, 3, n)
+ y_axis = np.linspace(-3, 3, n)
+
+ canvas = np.empty((28 * n, 28 * n))
+ for i, yi in enumerate(x_axis):
+ for j, xi in enumerate(y_axis):
+ z_mu = np.array([[xi, yi]] * batch_size)
+ x_mean = sess.run(decoder, feed_dict={noise_input: z_mu})
+ canvas[(n - i - 1) * 28:(n - i) * 28, j * 28:(j + 1) * 28] = \
+ x_mean[0].reshape(28, 28)
+
+ plt.figure(figsize=(8, 10))
+ Xi, Yi = np.meshgrid(x_axis, y_axis)
+ plt.imshow(canvas, origin="upper", cmap="gray")
+ plt.show()
diff --git a/tensorflow_v1/examples/4_Utils/save_restore_model.py b/tensorflow_v1/examples/4_Utils/save_restore_model.py
new file mode 100644
index 00000000..cee2cba0
--- /dev/null
+++ b/tensorflow_v1/examples/4_Utils/save_restore_model.py
@@ -0,0 +1,140 @@
+'''
+Save and Restore a model using TensorFlow.
+This example is using the MNIST database of handwritten digits
+(http://yann.lecun.com/exdb/mnist/)
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+
+from __future__ import print_function
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("MNIST_data/", one_hot=True)
+
+import tensorflow as tf
+
+# Parameters
+learning_rate = 0.001
+batch_size = 100
+display_step = 1
+model_path = "/tmp/model.ckpt"
+
+# Network Parameters
+n_hidden_1 = 256 # 1st layer number of features
+n_hidden_2 = 256 # 2nd layer number of features
+n_input = 784 # MNIST data input (img shape: 28*28)
+n_classes = 10 # MNIST total classes (0-9 digits)
+
+# tf Graph input
+x = tf.placeholder("float", [None, n_input])
+y = tf.placeholder("float", [None, n_classes])
+
+
+# Create model
+def multilayer_perceptron(x, weights, biases):
+ # Hidden layer with RELU activation
+ layer_1 = tf.add(tf.matmul(x, weights['h1']), biases['b1'])
+ layer_1 = tf.nn.relu(layer_1)
+ # Hidden layer with RELU activation
+ layer_2 = tf.add(tf.matmul(layer_1, weights['h2']), biases['b2'])
+ layer_2 = tf.nn.relu(layer_2)
+ # Output layer with linear activation
+ out_layer = tf.matmul(layer_2, weights['out']) + biases['out']
+ return out_layer
+
+# Store layers weight & bias
+weights = {
+ 'h1': tf.Variable(tf.random_normal([n_input, n_hidden_1])),
+ 'h2': tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2])),
+ 'out': tf.Variable(tf.random_normal([n_hidden_2, n_classes]))
+}
+biases = {
+ 'b1': tf.Variable(tf.random_normal([n_hidden_1])),
+ 'b2': tf.Variable(tf.random_normal([n_hidden_2])),
+ 'out': tf.Variable(tf.random_normal([n_classes]))
+}
+
+# Construct model
+pred = multilayer_perceptron(x, weights, biases)
+
+# Define loss and optimizer
+cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=pred, labels=y))
+optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate).minimize(cost)
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# 'Saver' op to save and restore all the variables
+saver = tf.train.Saver()
+
+# Running first session
+print("Starting 1st session...")
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ # Training cycle
+ for epoch in range(3):
+ avg_cost = 0.
+ total_batch = int(mnist.train.num_examples/batch_size)
+ # Loop over all batches
+ for i in range(total_batch):
+ batch_x, batch_y = mnist.train.next_batch(batch_size)
+ # Run optimization op (backprop) and cost op (to get loss value)
+ _, c = sess.run([optimizer, cost], feed_dict={x: batch_x,
+ y: batch_y})
+ # Compute average loss
+ avg_cost += c / total_batch
+ # Display logs per epoch step
+ if epoch % display_step == 0:
+ print("Epoch:", '%04d' % (epoch+1), "cost=", \
+ "{:.9f}".format(avg_cost))
+ print("First Optimization Finished!")
+
+ # Test model
+ correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))
+ # Calculate accuracy
+ accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
+ print("Accuracy:", accuracy.eval({x: mnist.test.images, y: mnist.test.labels}))
+
+ # Save model weights to disk
+ save_path = saver.save(sess, model_path)
+ print("Model saved in file: %s" % save_path)
+
+# Running a new session
+print("Starting 2nd session...")
+with tf.Session() as sess:
+ # Initialize variables
+ sess.run(init)
+
+ # Restore model weights from previously saved model
+ saver.restore(sess, model_path)
+ print("Model restored from file: %s" % save_path)
+
+ # Resume training
+ for epoch in range(7):
+ avg_cost = 0.
+ total_batch = int(mnist.train.num_examples / batch_size)
+ # Loop over all batches
+ for i in range(total_batch):
+ batch_x, batch_y = mnist.train.next_batch(batch_size)
+ # Run optimization op (backprop) and cost op (to get loss value)
+ _, c = sess.run([optimizer, cost], feed_dict={x: batch_x,
+ y: batch_y})
+ # Compute average loss
+ avg_cost += c / total_batch
+ # Display logs per epoch step
+ if epoch % display_step == 0:
+ print("Epoch:", '%04d' % (epoch + 1), "cost=", \
+ "{:.9f}".format(avg_cost))
+ print("Second Optimization Finished!")
+
+ # Test model
+ correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))
+ # Calculate accuracy
+ accuracy = tf.reduce_mean(tf.cast(correct_prediction, "float"))
+ print("Accuracy:", accuracy.eval(
+ {x: mnist.test.images, y: mnist.test.labels}))
diff --git a/tensorflow_v1/examples/4_Utils/tensorboard_advanced.py b/tensorflow_v1/examples/4_Utils/tensorboard_advanced.py
new file mode 100644
index 00000000..d9a150c2
--- /dev/null
+++ b/tensorflow_v1/examples/4_Utils/tensorboard_advanced.py
@@ -0,0 +1,143 @@
+'''
+Graph and Loss visualization using Tensorboard.
+This example is using the MNIST database of handwritten digits
+(http://yann.lecun.com/exdb/mnist/)
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+
+from __future__ import print_function
+
+import tensorflow as tf
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# Parameters
+learning_rate = 0.01
+training_epochs = 25
+batch_size = 100
+display_step = 1
+logs_path = '/tmp/tensorflow_logs/example/'
+
+# Network Parameters
+n_hidden_1 = 256 # 1st layer number of features
+n_hidden_2 = 256 # 2nd layer number of features
+n_input = 784 # MNIST data input (img shape: 28*28)
+n_classes = 10 # MNIST total classes (0-9 digits)
+
+# tf Graph Input
+# mnist data image of shape 28*28=784
+x = tf.placeholder(tf.float32, [None, 784], name='InputData')
+# 0-9 digits recognition => 10 classes
+y = tf.placeholder(tf.float32, [None, 10], name='LabelData')
+
+
+# Create model
+def multilayer_perceptron(x, weights, biases):
+ # Hidden layer with RELU activation
+ layer_1 = tf.add(tf.matmul(x, weights['w1']), biases['b1'])
+ layer_1 = tf.nn.relu(layer_1)
+ # Create a summary to visualize the first layer ReLU activation
+ tf.summary.histogram("relu1", layer_1)
+ # Hidden layer with RELU activation
+ layer_2 = tf.add(tf.matmul(layer_1, weights['w2']), biases['b2'])
+ layer_2 = tf.nn.relu(layer_2)
+ # Create another summary to visualize the second layer ReLU activation
+ tf.summary.histogram("relu2", layer_2)
+ # Output layer
+ out_layer = tf.add(tf.matmul(layer_2, weights['w3']), biases['b3'])
+ return out_layer
+
+# Store layers weight & bias
+weights = {
+ 'w1': tf.Variable(tf.random_normal([n_input, n_hidden_1]), name='W1'),
+ 'w2': tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2]), name='W2'),
+ 'w3': tf.Variable(tf.random_normal([n_hidden_2, n_classes]), name='W3')
+}
+biases = {
+ 'b1': tf.Variable(tf.random_normal([n_hidden_1]), name='b1'),
+ 'b2': tf.Variable(tf.random_normal([n_hidden_2]), name='b2'),
+ 'b3': tf.Variable(tf.random_normal([n_classes]), name='b3')
+}
+
+# Encapsulating all ops into scopes, making Tensorboard's Graph
+# Visualization more convenient
+with tf.name_scope('Model'):
+ # Build model
+ pred = multilayer_perceptron(x, weights, biases)
+
+with tf.name_scope('Loss'):
+ # Softmax Cross entropy (cost function)
+ loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=pred, labels=y))
+
+with tf.name_scope('SGD'):
+ # Gradient Descent
+ optimizer = tf.train.GradientDescentOptimizer(learning_rate)
+ # Op to calculate every variable gradient
+ grads = tf.gradients(loss, tf.trainable_variables())
+ grads = list(zip(grads, tf.trainable_variables()))
+ # Op to update all variables according to their gradient
+ apply_grads = optimizer.apply_gradients(grads_and_vars=grads)
+
+with tf.name_scope('Accuracy'):
+ # Accuracy
+ acc = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))
+ acc = tf.reduce_mean(tf.cast(acc, tf.float32))
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Create a summary to monitor cost tensor
+tf.summary.scalar("loss", loss)
+# Create a summary to monitor accuracy tensor
+tf.summary.scalar("accuracy", acc)
+# Create summaries to visualize weights
+for var in tf.trainable_variables():
+ tf.summary.histogram(var.name, var)
+# Summarize all gradients
+for grad, var in grads:
+ tf.summary.histogram(var.name + '/gradient', grad)
+# Merge all summaries into a single op
+merged_summary_op = tf.summary.merge_all()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ # op to write logs to Tensorboard
+ summary_writer = tf.summary.FileWriter(logs_path,
+ graph=tf.get_default_graph())
+
+ # Training cycle
+ for epoch in range(training_epochs):
+ avg_cost = 0.
+ total_batch = int(mnist.train.num_examples/batch_size)
+ # Loop over all batches
+ for i in range(total_batch):
+ batch_xs, batch_ys = mnist.train.next_batch(batch_size)
+ # Run optimization op (backprop), cost op (to get loss value)
+ # and summary nodes
+ _, c, summary = sess.run([apply_grads, loss, merged_summary_op],
+ feed_dict={x: batch_xs, y: batch_ys})
+ # Write logs at every iteration
+ summary_writer.add_summary(summary, epoch * total_batch + i)
+ # Compute average loss
+ avg_cost += c / total_batch
+ # Display logs per epoch step
+ if (epoch+1) % display_step == 0:
+ print("Epoch:", '%04d' % (epoch+1), "cost=", "{:.9f}".format(avg_cost))
+
+ print("Optimization Finished!")
+
+ # Test model
+ # Calculate accuracy
+ print("Accuracy:", acc.eval({x: mnist.test.images, y: mnist.test.labels}))
+
+ print("Run the command line:\n" \
+ "--> tensorboard --logdir=/tmp/tensorflow_logs " \
+ "\nThen open http://0.0.0.0:6006/ into your web browser")
diff --git a/tensorflow_v1/examples/4_Utils/tensorboard_basic.py b/tensorflow_v1/examples/4_Utils/tensorboard_basic.py
new file mode 100644
index 00000000..cbc485b7
--- /dev/null
+++ b/tensorflow_v1/examples/4_Utils/tensorboard_basic.py
@@ -0,0 +1,97 @@
+'''
+Graph and Loss visualization using Tensorboard.
+This example is using the MNIST database of handwritten digits
+(http://yann.lecun.com/exdb/mnist/)
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+
+from __future__ import print_function
+
+import tensorflow as tf
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# Parameters
+learning_rate = 0.01
+training_epochs = 25
+batch_size = 100
+display_epoch = 1
+logs_path = '/tmp/tensorflow_logs/example/'
+
+# tf Graph Input
+# mnist data image of shape 28*28=784
+x = tf.placeholder(tf.float32, [None, 784], name='InputData')
+# 0-9 digits recognition => 10 classes
+y = tf.placeholder(tf.float32, [None, 10], name='LabelData')
+
+# Set model weights
+W = tf.Variable(tf.zeros([784, 10]), name='Weights')
+b = tf.Variable(tf.zeros([10]), name='Bias')
+
+# Construct model and encapsulating all ops into scopes, making
+# Tensorboard's Graph visualization more convenient
+with tf.name_scope('Model'):
+ # Model
+ pred = tf.nn.softmax(tf.matmul(x, W) + b) # Softmax
+with tf.name_scope('Loss'):
+ # Minimize error using cross entropy
+ cost = tf.reduce_mean(-tf.reduce_sum(y*tf.log(pred), reduction_indices=1))
+with tf.name_scope('SGD'):
+ # Gradient Descent
+ optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)
+with tf.name_scope('Accuracy'):
+ # Accuracy
+ acc = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))
+ acc = tf.reduce_mean(tf.cast(acc, tf.float32))
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Create a summary to monitor cost tensor
+tf.summary.scalar("loss", cost)
+# Create a summary to monitor accuracy tensor
+tf.summary.scalar("accuracy", acc)
+# Merge all summaries into a single op
+merged_summary_op = tf.summary.merge_all()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ # op to write logs to Tensorboard
+ summary_writer = tf.summary.FileWriter(logs_path, graph=tf.get_default_graph())
+
+ # Training cycle
+ for epoch in range(training_epochs):
+ avg_cost = 0.
+ total_batch = int(mnist.train.num_examples/batch_size)
+ # Loop over all batches
+ for i in range(total_batch):
+ batch_xs, batch_ys = mnist.train.next_batch(batch_size)
+ # Run optimization op (backprop), cost op (to get loss value)
+ # and summary nodes
+ _, c, summary = sess.run([optimizer, cost, merged_summary_op],
+ feed_dict={x: batch_xs, y: batch_ys})
+ # Write logs at every iteration
+ summary_writer.add_summary(summary, epoch * total_batch + i)
+ # Compute average loss
+ avg_cost += c / total_batch
+ # Display logs per epoch step
+ if (epoch+1) % display_epoch == 0:
+ print("Epoch:", '%04d' % (epoch+1), "cost=", "{:.9f}".format(avg_cost))
+
+ print("Optimization Finished!")
+
+ # Test model
+ # Calculate accuracy
+ print("Accuracy:", acc.eval({x: mnist.test.images, y: mnist.test.labels}))
+
+ print("Run the command line:\n" \
+ "--> tensorboard --logdir=/tmp/tensorflow_logs " \
+ "\nThen open http://0.0.0.0:6006/ into your web browser")
diff --git a/tensorflow_v1/examples/5_DataManagement/build_an_image_dataset.py b/tensorflow_v1/examples/5_DataManagement/build_an_image_dataset.py
new file mode 100644
index 00000000..ebeaf337
--- /dev/null
+++ b/tensorflow_v1/examples/5_DataManagement/build_an_image_dataset.py
@@ -0,0 +1,212 @@
+""" Build an Image Dataset in TensorFlow.
+
+For this example, you need to make your own set of images (JPEG).
+We will show 2 different ways to build that dataset:
+
+- From a root folder, that will have a sub-folder containing images for each class
+ ```
+ ROOT_FOLDER
+ |-------- SUBFOLDER (CLASS 0)
+ | |
+ | | ----- image1.jpg
+ | | ----- image2.jpg
+ | | ----- etc...
+ |
+ |-------- SUBFOLDER (CLASS 1)
+ | |
+ | | ----- image1.jpg
+ | | ----- image2.jpg
+ | | ----- etc...
+ ```
+
+- From a plain text file, that will list all images with their class ID:
+ ```
+ /path/to/image/1.jpg CLASS_ID
+ /path/to/image/2.jpg CLASS_ID
+ /path/to/image/3.jpg CLASS_ID
+ /path/to/image/4.jpg CLASS_ID
+ etc...
+ ```
+
+Below, there are some parameters that you need to change (Marked 'CHANGE HERE'),
+such as the dataset path.
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+from __future__ import print_function
+
+import tensorflow as tf
+import os
+
+# Dataset Parameters - CHANGE HERE
+MODE = 'folder' # or 'file', if you choose a plain text file (see above).
+DATASET_PATH = '/path/to/dataset/' # the dataset file or root folder path.
+
+# Image Parameters
+N_CLASSES = 2 # CHANGE HERE, total number of classes
+IMG_HEIGHT = 64 # CHANGE HERE, the image height to be resized to
+IMG_WIDTH = 64 # CHANGE HERE, the image width to be resized to
+CHANNELS = 3 # The 3 color channels, change to 1 if grayscale
+
+
+# Reading the dataset
+# 2 modes: 'file' or 'folder'
+def read_images(dataset_path, mode, batch_size):
+ imagepaths, labels = list(), list()
+ if mode == 'file':
+ # Read dataset file
+ with open(dataset_path) as f:
+ data = f.read().splitlines()
+ for d in data:
+ imagepaths.append(d.split(' ')[0])
+ labels.append(int(d.split(' ')[1]))
+ elif mode == 'folder':
+ # An ID will be affected to each sub-folders by alphabetical order
+ label = 0
+ # List the directory
+ try: # Python 2
+ classes = sorted(os.walk(dataset_path).next()[1])
+ except Exception: # Python 3
+ classes = sorted(os.walk(dataset_path).__next__()[1])
+ # List each sub-directory (the classes)
+ for c in classes:
+ c_dir = os.path.join(dataset_path, c)
+ try: # Python 2
+ walk = os.walk(c_dir).next()
+ except Exception: # Python 3
+ walk = os.walk(c_dir).__next__()
+ # Add each image to the training set
+ for sample in walk[2]:
+ # Only keeps jpeg images
+ if sample.endswith('.jpg') or sample.endswith('.jpeg'):
+ imagepaths.append(os.path.join(c_dir, sample))
+ labels.append(label)
+ label += 1
+ else:
+ raise Exception("Unknown mode.")
+
+ # Convert to Tensor
+ imagepaths = tf.convert_to_tensor(imagepaths, dtype=tf.string)
+ labels = tf.convert_to_tensor(labels, dtype=tf.int32)
+ # Build a TF Queue, shuffle data
+ image, label = tf.train.slice_input_producer([imagepaths, labels],
+ shuffle=True)
+
+ # Read images from disk
+ image = tf.read_file(image)
+ image = tf.image.decode_jpeg(image, channels=CHANNELS)
+
+ # Resize images to a common size
+ image = tf.image.resize_images(image, [IMG_HEIGHT, IMG_WIDTH])
+
+ # Normalize
+ image = image * 1.0/127.5 - 1.0
+
+ # Create batches
+ X, Y = tf.train.batch([image, label], batch_size=batch_size,
+ capacity=batch_size * 8,
+ num_threads=4)
+
+ return X, Y
+
+# -----------------------------------------------
+# THIS IS A CLASSIC CNN (see examples, section 3)
+# -----------------------------------------------
+# Note that a few elements have changed (usage of queues).
+
+# Parameters
+learning_rate = 0.001
+num_steps = 10000
+batch_size = 128
+display_step = 100
+
+# Network Parameters
+dropout = 0.75 # Dropout, probability to keep units
+
+# Build the data input
+X, Y = read_images(DATASET_PATH, MODE, batch_size)
+
+
+# Create model
+def conv_net(x, n_classes, dropout, reuse, is_training):
+ # Define a scope for reusing the variables
+ with tf.variable_scope('ConvNet', reuse=reuse):
+
+ # Convolution Layer with 32 filters and a kernel size of 5
+ conv1 = tf.layers.conv2d(x, 32, 5, activation=tf.nn.relu)
+ # Max Pooling (down-sampling) with strides of 2 and kernel size of 2
+ conv1 = tf.layers.max_pooling2d(conv1, 2, 2)
+
+ # Convolution Layer with 32 filters and a kernel size of 5
+ conv2 = tf.layers.conv2d(conv1, 64, 3, activation=tf.nn.relu)
+ # Max Pooling (down-sampling) with strides of 2 and kernel size of 2
+ conv2 = tf.layers.max_pooling2d(conv2, 2, 2)
+
+ # Flatten the data to a 1-D vector for the fully connected layer
+ fc1 = tf.contrib.layers.flatten(conv2)
+
+ # Fully connected layer (in contrib folder for now)
+ fc1 = tf.layers.dense(fc1, 1024)
+ # Apply Dropout (if is_training is False, dropout is not applied)
+ fc1 = tf.layers.dropout(fc1, rate=dropout, training=is_training)
+
+ # Output layer, class prediction
+ out = tf.layers.dense(fc1, n_classes)
+ # Because 'softmax_cross_entropy_with_logits' already apply softmax,
+ # we only apply softmax to testing network
+ out = tf.nn.softmax(out) if not is_training else out
+
+ return out
+
+
+# Because Dropout have different behavior at training and prediction time, we
+# need to create 2 distinct computation graphs that share the same weights.
+
+# Create a graph for training
+logits_train = conv_net(X, N_CLASSES, dropout, reuse=False, is_training=True)
+# Create another graph for testing that reuse the same weights
+logits_test = conv_net(X, N_CLASSES, dropout, reuse=True, is_training=False)
+
+# Define loss and optimizer (with train logits, for dropout to take effect)
+loss_op = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(
+ logits=logits_train, labels=Y))
+optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
+train_op = optimizer.minimize(loss_op)
+
+# Evaluate model (with test logits, for dropout to be disabled)
+correct_pred = tf.equal(tf.argmax(logits_test, 1), tf.cast(Y, tf.int64))
+accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Saver object
+saver = tf.train.Saver()
+
+# Start training
+with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ # Start the data queue
+ tf.train.start_queue_runners()
+
+ # Training cycle
+ for step in range(1, num_steps+1):
+
+ if step % display_step == 0:
+ # Run optimization and calculate batch loss and accuracy
+ _, loss, acc = sess.run([train_op, loss_op, accuracy])
+ print("Step " + str(step) + ", Minibatch Loss= " + \
+ "{:.4f}".format(loss) + ", Training Accuracy= " + \
+ "{:.3f}".format(acc))
+ else:
+ # Only run the optimization op (backprop)
+ sess.run(train_op)
+
+ print("Optimization Finished!")
+
+ # Save your model
+ saver.save(sess, 'my_tf_model')
diff --git a/tensorflow_v1/examples/5_DataManagement/tensorflow_dataset_api.py b/tensorflow_v1/examples/5_DataManagement/tensorflow_dataset_api.py
new file mode 100644
index 00000000..3a47e021
--- /dev/null
+++ b/tensorflow_v1/examples/5_DataManagement/tensorflow_dataset_api.py
@@ -0,0 +1,130 @@
+""" TensorFlow Dataset API.
+
+In this example, we will show how to load numpy array data into the new
+TensorFlow 'Dataset' API. The Dataset API implements an optimized data pipeline
+with queues, that make data processing and training faster (especially on GPU).
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+"""
+from __future__ import print_function
+
+import tensorflow as tf
+
+# Import MNIST data (Numpy format)
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# Parameters
+learning_rate = 0.001
+num_steps = 2000
+batch_size = 128
+display_step = 100
+
+# Network Parameters
+n_input = 784 # MNIST data input (img shape: 28*28)
+n_classes = 10 # MNIST total classes (0-9 digits)
+dropout = 0.75 # Dropout, probability to keep units
+
+sess = tf.Session()
+
+# Create a dataset tensor from the images and the labels
+dataset = tf.data.Dataset.from_tensor_slices(
+ (mnist.train.images, mnist.train.labels))
+# Automatically refill the data queue when empty
+dataset = dataset.repeat()
+# Create batches of data
+dataset = dataset.batch(batch_size)
+# Prefetch data for faster consumption
+dataset = dataset.prefetch(batch_size)
+
+# Create an iterator over the dataset
+iterator = dataset.make_initializable_iterator()
+# Initialize the iterator
+sess.run(iterator.initializer)
+
+# Neural Net Input (images, labels)
+X, Y = iterator.get_next()
+
+
+# -----------------------------------------------
+# THIS IS A CLASSIC CNN (see examples, section 3)
+# -----------------------------------------------
+# Note that a few elements have changed (usage of sess run).
+
+# Create model
+def conv_net(x, n_classes, dropout, reuse, is_training):
+ # Define a scope for reusing the variables
+ with tf.variable_scope('ConvNet', reuse=reuse):
+ # MNIST data input is a 1-D vector of 784 features (28*28 pixels)
+ # Reshape to match picture format [Height x Width x Channel]
+ # Tensor input become 4-D: [Batch Size, Height, Width, Channel]
+ x = tf.reshape(x, shape=[-1, 28, 28, 1])
+
+ # Convolution Layer with 32 filters and a kernel size of 5
+ conv1 = tf.layers.conv2d(x, 32, 5, activation=tf.nn.relu)
+ # Max Pooling (down-sampling) with strides of 2 and kernel size of 2
+ conv1 = tf.layers.max_pooling2d(conv1, 2, 2)
+
+ # Convolution Layer with 32 filters and a kernel size of 5
+ conv2 = tf.layers.conv2d(conv1, 64, 3, activation=tf.nn.relu)
+ # Max Pooling (down-sampling) with strides of 2 and kernel size of 2
+ conv2 = tf.layers.max_pooling2d(conv2, 2, 2)
+
+ # Flatten the data to a 1-D vector for the fully connected layer
+ fc1 = tf.contrib.layers.flatten(conv2)
+
+ # Fully connected layer (in contrib folder for now)
+ fc1 = tf.layers.dense(fc1, 1024)
+ # Apply Dropout (if is_training is False, dropout is not applied)
+ fc1 = tf.layers.dropout(fc1, rate=dropout, training=is_training)
+
+ # Output layer, class prediction
+ out = tf.layers.dense(fc1, n_classes)
+ # Because 'softmax_cross_entropy_with_logits' already apply softmax,
+ # we only apply softmax to testing network
+ out = tf.nn.softmax(out) if not is_training else out
+
+ return out
+
+
+# Because Dropout have different behavior at training and prediction time, we
+# need to create 2 distinct computation graphs that share the same weights.
+
+# Create a graph for training
+logits_train = conv_net(X, n_classes, dropout, reuse=False, is_training=True)
+# Create another graph for testing that reuse the same weights, but has
+# different behavior for 'dropout' (not applied).
+logits_test = conv_net(X, n_classes, dropout, reuse=True, is_training=False)
+
+# Define loss and optimizer (with train logits, for dropout to take effect)
+loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(
+ logits=logits_train, labels=Y))
+optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
+train_op = optimizer.minimize(loss_op)
+
+# Evaluate model (with test logits, for dropout to be disabled)
+correct_pred = tf.equal(tf.argmax(logits_test, 1), tf.argmax(Y, 1))
+accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
+
+# Initialize the variables (i.e. assign their default value)
+init = tf.global_variables_initializer()
+
+# Run the initializer
+sess.run(init)
+
+# Training cycle
+for step in range(1, num_steps + 1):
+
+ # Run optimization
+ sess.run(train_op)
+
+ if step % display_step == 0 or step == 1:
+ # Calculate batch loss and accuracy
+ # (note that this consume a new batch of data)
+ loss, acc = sess.run([loss_op, accuracy])
+ print("Step " + str(step) + ", Minibatch Loss= " + \
+ "{:.4f}".format(loss) + ", Training Accuracy= " + \
+ "{:.3f}".format(acc))
+
+print("Optimization Finished!")
diff --git a/tensorflow_v1/examples/6_MultiGPU/multigpu_basics.py b/tensorflow_v1/examples/6_MultiGPU/multigpu_basics.py
new file mode 100644
index 00000000..5e255ad5
--- /dev/null
+++ b/tensorflow_v1/examples/6_MultiGPU/multigpu_basics.py
@@ -0,0 +1,94 @@
+from __future__ import print_function
+'''
+Basic Multi GPU computation example using TensorFlow library.
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+
+'''
+This tutorial requires your machine to have 2 GPUs
+"/cpu:0": The CPU of your machine.
+"/gpu:0": The first GPU of your machine
+"/gpu:1": The second GPU of your machine
+'''
+
+
+
+import numpy as np
+import tensorflow as tf
+import datetime
+
+# Processing Units logs
+log_device_placement = True
+
+# Num of multiplications to perform
+n = 10
+
+'''
+Example: compute A^n + B^n on 2 GPUs
+Results on 8 cores with 2 GTX-980:
+ * Single GPU computation time: 0:00:11.277449
+ * Multi GPU computation time: 0:00:07.131701
+'''
+# Create random large matrix
+A = np.random.rand(10000, 10000).astype('float32')
+B = np.random.rand(10000, 10000).astype('float32')
+
+# Create a graph to store results
+c1 = []
+c2 = []
+
+def matpow(M, n):
+ if n < 1: #Abstract cases where n < 1
+ return M
+ else:
+ return tf.matmul(M, matpow(M, n-1))
+
+'''
+Single GPU computing
+'''
+with tf.device('/gpu:0'):
+ a = tf.placeholder(tf.float32, [10000, 10000])
+ b = tf.placeholder(tf.float32, [10000, 10000])
+ # Compute A^n and B^n and store results in c1
+ c1.append(matpow(a, n))
+ c1.append(matpow(b, n))
+
+with tf.device('/cpu:0'):
+ sum = tf.add_n(c1) #Addition of all elements in c1, i.e. A^n + B^n
+
+t1_1 = datetime.datetime.now()
+with tf.Session(config=tf.ConfigProto(log_device_placement=log_device_placement)) as sess:
+ # Run the op.
+ sess.run(sum, {a:A, b:B})
+t2_1 = datetime.datetime.now()
+
+
+'''
+Multi GPU computing
+'''
+# GPU:0 computes A^n
+with tf.device('/gpu:0'):
+ # Compute A^n and store result in c2
+ a = tf.placeholder(tf.float32, [10000, 10000])
+ c2.append(matpow(a, n))
+
+# GPU:1 computes B^n
+with tf.device('/gpu:1'):
+ # Compute B^n and store result in c2
+ b = tf.placeholder(tf.float32, [10000, 10000])
+ c2.append(matpow(b, n))
+
+with tf.device('/cpu:0'):
+ sum = tf.add_n(c2) #Addition of all elements in c2, i.e. A^n + B^n
+
+t1_2 = datetime.datetime.now()
+with tf.Session(config=tf.ConfigProto(log_device_placement=log_device_placement)) as sess:
+ # Run the op.
+ sess.run(sum, {a:A, b:B})
+t2_2 = datetime.datetime.now()
+
+
+print("Single GPU computation time: " + str(t2_1-t1_1))
+print("Multi GPU computation time: " + str(t2_2-t1_2))
diff --git a/tensorflow_v1/examples/6_MultiGPU/multigpu_cnn.py b/tensorflow_v1/examples/6_MultiGPU/multigpu_cnn.py
new file mode 100644
index 00000000..e2e2d9eb
--- /dev/null
+++ b/tensorflow_v1/examples/6_MultiGPU/multigpu_cnn.py
@@ -0,0 +1,198 @@
+''' Multi-GPU Training Example.
+
+Train a convolutional neural network on multiple GPU with TensorFlow.
+
+This example is using TensorFlow layers, see 'convolutional_network_raw' example
+for a raw TensorFlow implementation with variables.
+
+This example is using the MNIST database of handwritten digits
+(http://yann.lecun.com/exdb/mnist/)
+
+Author: Aymeric Damien
+Project: https://github.com/nebulaai/TensorFlow-Examples/
+'''
+
+from __future__ import division, print_function, absolute_import
+
+import numpy as np
+import tensorflow as tf
+import time
+
+# Import MNIST data
+from tensorflow.examples.tutorials.mnist import input_data
+mnist = input_data.read_data_sets("/tmp/data/", one_hot=True)
+
+# Training Parameters
+num_gpus = 2
+num_steps = 200
+learning_rate = 0.001
+batch_size = 1024
+display_step = 10
+
+# Network Parameters
+num_input = 784 # MNIST data input (img shape: 28*28)
+num_classes = 10 # MNIST total classes (0-9 digits)
+dropout = 0.75 # Dropout, probability to keep units
+
+
+# Build a convolutional neural network
+def conv_net(x, n_classes, dropout, reuse, is_training):
+ # Define a scope for reusing the variables
+ with tf.variable_scope('ConvNet', reuse=reuse):
+ # MNIST data input is a 1-D vector of 784 features (28*28 pixels)
+ # Reshape to match picture format [Height x Width x Channel]
+ # Tensor input become 4-D: [Batch Size, Height, Width, Channel]
+ x = tf.reshape(x, shape=[-1, 28, 28, 1])
+
+ # Convolution Layer with 64 filters and a kernel size of 5
+ x = tf.layers.conv2d(x, 64, 5, activation=tf.nn.relu)
+ # Max Pooling (down-sampling) with strides of 2 and kernel size of 2
+ x = tf.layers.max_pooling2d(x, 2, 2)
+
+ # Convolution Layer with 256 filters and a kernel size of 5
+ x = tf.layers.conv2d(x, 256, 3, activation=tf.nn.relu)
+ # Convolution Layer with 512 filters and a kernel size of 5
+ x = tf.layers.conv2d(x, 512, 3, activation=tf.nn.relu)
+ # Max Pooling (down-sampling) with strides of 2 and kernel size of 2
+ x = tf.layers.max_pooling2d(x, 2, 2)
+
+ # Flatten the data to a 1-D vector for the fully connected layer
+ x = tf.contrib.layers.flatten(x)
+
+ # Fully connected layer (in contrib folder for now)
+ x = tf.layers.dense(x, 2048)
+ # Apply Dropout (if is_training is False, dropout is not applied)
+ x = tf.layers.dropout(x, rate=dropout, training=is_training)
+
+ # Fully connected layer (in contrib folder for now)
+ x = tf.layers.dense(x, 1024)
+ # Apply Dropout (if is_training is False, dropout is not applied)
+ x = tf.layers.dropout(x, rate=dropout, training=is_training)
+
+ # Output layer, class prediction
+ out = tf.layers.dense(x, n_classes)
+ # Because 'softmax_cross_entropy_with_logits' loss already apply
+ # softmax, we only apply softmax to testing network
+ out = tf.nn.softmax(out) if not is_training else out
+
+ return out
+
+
+def average_gradients(tower_grads):
+ average_grads = []
+ for grad_and_vars in zip(*tower_grads):
+ # Note that each grad_and_vars looks like the following:
+ # ((grad0_gpu0, var0_gpu0), ... , (grad0_gpuN, var0_gpuN))
+ grads = []
+ for g, _ in grad_and_vars:
+ # Add 0 dimension to the gradients to represent the tower.
+ expanded_g = tf.expand_dims(g, 0)
+
+ # Append on a 'tower' dimension which we will average over below.
+ grads.append(expanded_g)
+
+ # Average over the 'tower' dimension.
+ grad = tf.concat(grads, 0)
+ grad = tf.reduce_mean(grad, 0)
+
+ # Keep in mind that the Variables are redundant because they are shared
+ # across towers. So .. we will just return the first tower's pointer to
+ # the Variable.
+ v = grad_and_vars[0][1]
+ grad_and_var = (grad, v)
+ average_grads.append(grad_and_var)
+ return average_grads
+
+
+# By default, all variables will be placed on '/gpu:0'
+# So we need a custom device function, to assign all variables to '/cpu:0'
+# Note: If GPUs are peered, '/gpu:0' can be a faster option
+PS_OPS = ['Variable', 'VariableV2', 'AutoReloadVariable']
+
+def assign_to_device(device, ps_device='/cpu:0'):
+ def _assign(op):
+ node_def = op if isinstance(op, tf.NodeDef) else op.node_def
+ if node_def.op in PS_OPS:
+ return "/" + ps_device
+ else:
+ return device
+
+ return _assign
+
+
+# Place all ops on CPU by default
+with tf.device('/cpu:0'):
+ tower_grads = []
+ reuse_vars = False
+
+ # tf Graph input
+ X = tf.placeholder(tf.float32, [None, num_input])
+ Y = tf.placeholder(tf.float32, [None, num_classes])
+
+ # Loop over all GPUs and construct their own computation graph
+ for i in range(num_gpus):
+ with tf.device(assign_to_device('/gpu:{}'.format(i), ps_device='/cpu:0')):
+
+ # Split data between GPUs
+ _x = X[i * batch_size: (i+1) * batch_size]
+ _y = Y[i * batch_size: (i+1) * batch_size]
+
+ # Because Dropout have different behavior at training and prediction time, we
+ # need to create 2 distinct computation graphs that share the same weights.
+
+ # Create a graph for training
+ logits_train = conv_net(_x, num_classes, dropout,
+ reuse=reuse_vars, is_training=True)
+ # Create another graph for testing that reuse the same weights
+ logits_test = conv_net(_x, num_classes, dropout,
+ reuse=True, is_training=False)
+
+ # Define loss and optimizer (with train logits, for dropout to take effect)
+ loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(
+ logits=logits_train, labels=_y))
+ optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
+ grads = optimizer.compute_gradients(loss_op)
+
+ # Only first GPU compute accuracy
+ if i == 0:
+ # Evaluate model (with test logits, for dropout to be disabled)
+ correct_pred = tf.equal(tf.argmax(logits_test, 1), tf.argmax(_y, 1))
+ accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))
+
+ reuse_vars = True
+ tower_grads.append(grads)
+
+ tower_grads = average_gradients(tower_grads)
+ train_op = optimizer.apply_gradients(tower_grads)
+
+ # Initialize the variables (i.e. assign their default value)
+ init = tf.global_variables_initializer()
+
+ # Start Training
+ with tf.Session() as sess:
+
+ # Run the initializer
+ sess.run(init)
+
+ # Keep training until reach max iterations
+ for step in range(1, num_steps + 1):
+ # Get a batch for each GPU
+ batch_x, batch_y = mnist.train.next_batch(batch_size * num_gpus)
+ # Run optimization op (backprop)
+ ts = time.time()
+ sess.run(train_op, feed_dict={X: batch_x, Y: batch_y})
+ te = time.time() - ts
+ if step % display_step == 0 or step == 1:
+ # Calculate batch loss and accuracy
+ loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,
+ Y: batch_y})
+ print("Step " + str(step) + ": Minibatch Loss= " + \
+ "{:.4f}".format(loss) + ", Training Accuracy= " + \
+ "{:.3f}".format(acc) + ", %i Examples/sec" % int(len(batch_x)/te))
+ step += 1
+ print("Optimization Finished!")
+
+ # Calculate accuracy for MNIST test images
+ print("Testing Accuracy:", \
+ np.mean([sess.run(accuracy, feed_dict={X: mnist.test.images[i:i+batch_size],
+ Y: mnist.test.labels[i:i+batch_size]}) for i in range(0, len(mnist.test.images), batch_size)]))
diff --git a/tensorflow_v1/notebooks/0_Prerequisite/ml_introduction.ipynb b/tensorflow_v1/notebooks/0_Prerequisite/ml_introduction.ipynb
new file mode 100644
index 00000000..fe84ef52
--- /dev/null
+++ b/tensorflow_v1/notebooks/0_Prerequisite/ml_introduction.ipynb
@@ -0,0 +1,48 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Machine Learning\n",
+ "\n",
+ "Prior to start browsing the examples, it may be useful that you get familiar with machine learning, as TensorFlow is mostly used for machine learning tasks (especially Neural Networks). You can find below a list of useful links, that can give you the basic knowledge required for this TensorFlow Tutorial.\n",
+ "\n",
+ "## Machine Learning\n",
+ "\n",
+ "- [An Introduction to Machine Learning Theory and Its Applications: A Visual Tutorial with Examples](https://www.toptal.com/machine-learning/machine-learning-theory-an-introductory-primer)\n",
+ "- [A Gentle Guide to Machine Learning](https://blog.monkeylearn.com/a-gentle-guide-to-machine-learning/)\n",
+ "- [A Visual Introduction to Machine Learning](http://www.r2d3.us/visual-intro-to-machine-learning-part-1/)\n",
+ "- [Introduction to Machine Learning](http://alex.smola.org/drafts/thebook.pdf)\n",
+ "\n",
+ "## Deep Learning & Neural Networks\n",
+ "\n",
+ "- [An Introduction to Neural Networks](http://www.cs.stir.ac.uk/~lss/NNIntro/InvSlides.html)\n",
+ "- [An Introduction to Image Recognition with Deep Learning](https://medium.com/@ageitgey/machine-learning-is-fun-part-3-deep-learning-and-convolutional-neural-networks-f40359318721)\n",
+ "- [Neural Networks and Deep Learning](http://neuralnetworksanddeeplearning.com/index.html)\n",
+ "\n"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "IPython (Python 2.7)",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.11"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb b/tensorflow_v1/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb
new file mode 100644
index 00000000..6b96dc0f
--- /dev/null
+++ b/tensorflow_v1/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb
@@ -0,0 +1,94 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "# MNIST Dataset Introduction\n",
+ "\n",
+ "Most examples are using MNIST dataset of handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flatten and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "## Overview\n",
+ "\n",
+ "\n",
+ "\n",
+ "## Usage\n",
+ "In our examples, we are using TensorFlow [input_data.py](https://github.com/tensorflow/tensorflow/blob/r0.7/tensorflow/examples/tutorials/mnist/input_data.py) script to load that dataset.\n",
+ "It is quite useful for managing our data, and handle:\n",
+ "\n",
+ "- Dataset downloading\n",
+ "\n",
+ "- Loading the entire dataset into numpy array: \n",
+ "\n",
+ "\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Import MNIST\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)\n",
+ "\n",
+ "# Load data\n",
+ "X_train = mnist.train.images\n",
+ "Y_train = mnist.train.labels\n",
+ "X_test = mnist.test.images\n",
+ "Y_test = mnist.test.labels"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "- A `next_batch` function that can iterate over the whole dataset and return only the desired fraction of the dataset samples (in order to save memory and avoid to load the entire dataset)."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Get the next 64 images array and labels\n",
+ "batch_X, batch_Y = mnist.train.next_batch(64)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "Link: http://yann.lecun.com/exdb/mnist/"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.13"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/1_Introduction/basic_eager_api.ipynb b/tensorflow_v1/notebooks/1_Introduction/basic_eager_api.ipynb
new file mode 100644
index 00000000..ef6ce407
--- /dev/null
+++ b/tensorflow_v1/notebooks/1_Introduction/basic_eager_api.ipynb
@@ -0,0 +1,238 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Basic introduction to TensorFlow's Eager API\n",
+ "\n",
+ "A simple introduction to get started with TensorFlow's Eager API.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### What is TensorFlow's Eager API ?\n",
+ "\n",
+ "*Eager execution is an imperative, define-by-run interface where operations are\n",
+ "executed immediately as they are called from Python. This makes it easier to\n",
+ "get started with TensorFlow, and can make research and development more\n",
+ "intuitive. A vast majority of the TensorFlow API remains the same whether eager\n",
+ "execution is enabled or not. As a result, the exact same code that constructs\n",
+ "TensorFlow graphs (e.g. using the layers API) can be executed imperatively\n",
+ "by using eager execution. Conversely, most models written with Eager enabled\n",
+ "can be converted to a graph that can be further optimized and/or extracted\n",
+ "for deployment in production without changing code. - Rajat Monga*\n",
+ "\n",
+ "More info: https://research.googleblog.com/2017/10/eager-execution-imperative-define-by.html"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import numpy as np\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Setting Eager mode...\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Set Eager API\n",
+ "print(\"Setting Eager mode...\")\n",
+ "tf.enable_eager_execution()\n",
+ "tfe = tf.contrib.eager"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Define constant tensors\n",
+ "a = 2\n",
+ "b = 3\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Define constant tensors\n",
+ "print(\"Define constant tensors\")\n",
+ "a = tf.constant(2)\n",
+ "print(\"a = %i\" % a)\n",
+ "b = tf.constant(3)\n",
+ "print(\"b = %i\" % b)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Running operations, without tf.Session\n",
+ "a + b = 5\n",
+ "a * b = 6\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Run the operation without the need for tf.Session\n",
+ "print(\"Running operations, without tf.Session\")\n",
+ "c = a + b\n",
+ "print(\"a + b = %i\" % c)\n",
+ "d = a * b\n",
+ "print(\"a * b = %i\" % d)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Mixing operations with Tensors and Numpy Arrays\n",
+ "Tensor:\n",
+ " a = tf.Tensor(\n",
+ "[[2. 1.]\n",
+ " [1. 0.]], shape=(2, 2), dtype=float32)\n",
+ "NumpyArray:\n",
+ " b = [[3. 0.]\n",
+ " [5. 1.]]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Full compatibility with Numpy\n",
+ "print(\"Mixing operations with Tensors and Numpy Arrays\")\n",
+ "\n",
+ "# Define constant tensors\n",
+ "a = tf.constant([[2., 1.],\n",
+ " [1., 0.]], dtype=tf.float32)\n",
+ "print(\"Tensor:\\n a = %s\" % a)\n",
+ "b = np.array([[3., 0.],\n",
+ " [5., 1.]], dtype=np.float32)\n",
+ "print(\"NumpyArray:\\n b = %s\" % b)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Running operations, without tf.Session\n",
+ "a + b = tf.Tensor(\n",
+ "[[5. 1.]\n",
+ " [6. 1.]], shape=(2, 2), dtype=float32)\n",
+ "a * b = tf.Tensor(\n",
+ "[[11. 1.]\n",
+ " [ 3. 0.]], shape=(2, 2), dtype=float32)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Run the operation without the need for tf.Session\n",
+ "print(\"Running operations, without tf.Session\")\n",
+ "\n",
+ "c = a + b\n",
+ "print(\"a + b = %s\" % c)\n",
+ "\n",
+ "d = tf.matmul(a, b)\n",
+ "print(\"a * b = %s\" % d)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Iterate through Tensor 'a':\n",
+ "tf.Tensor(2.0, shape=(), dtype=float32)\n",
+ "tf.Tensor(1.0, shape=(), dtype=float32)\n",
+ "tf.Tensor(1.0, shape=(), dtype=float32)\n",
+ "tf.Tensor(0.0, shape=(), dtype=float32)\n"
+ ]
+ }
+ ],
+ "source": [
+ "print(\"Iterate through Tensor 'a':\")\n",
+ "for i in range(a.shape[0]):\n",
+ " for j in range(a.shape[1]):\n",
+ " print(a[i][j])"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/1_Introduction/basic_operations.ipynb b/tensorflow_v1/notebooks/1_Introduction/basic_operations.ipynb
new file mode 100644
index 00000000..577517bd
--- /dev/null
+++ b/tensorflow_v1/notebooks/1_Introduction/basic_operations.ipynb
@@ -0,0 +1,220 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Basic Operations example using TensorFlow library.\n",
+ "# Author: Aymeric Damien\n",
+ "# Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Basic constant operations\n",
+ "# The value returned by the constructor represents the output\n",
+ "# of the Constant op.\n",
+ "a = tf.constant(2)\n",
+ "b = tf.constant(3)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "a=2, b=3\n",
+ "Addition with constants: 5\n",
+ "Multiplication with constants: 6\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Launch the default graph.\n",
+ "with tf.Session() as sess:\n",
+ " print \"a: %i\" % sess.run(a), \"b: %i\" % sess.run(b)\n",
+ " print \"Addition with constants: %i\" % sess.run(a+b)\n",
+ " print \"Multiplication with constants: %i\" % sess.run(a*b)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Basic Operations with variable as graph input\n",
+ "# The value returned by the constructor represents the output\n",
+ "# of the Variable op. (define as input when running session)\n",
+ "# tf Graph input\n",
+ "a = tf.placeholder(tf.int16)\n",
+ "b = tf.placeholder(tf.int16)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Define some operations\n",
+ "add = tf.add(a, b)\n",
+ "mul = tf.multiply(a, b)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Addition with variables: 5\n",
+ "Multiplication with variables: 6\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Launch the default graph.\n",
+ "with tf.Session() as sess:\n",
+ " # Run every operation with variable input\n",
+ " print \"Addition with variables: %i\" % sess.run(add, feed_dict={a: 2, b: 3})\n",
+ " print \"Multiplication with variables: %i\" % sess.run(mul, feed_dict={a: 2, b: 3})"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# ----------------\n",
+ "# More in details:\n",
+ "# Matrix Multiplication from TensorFlow official tutorial\n",
+ "\n",
+ "# Create a Constant op that produces a 1x2 matrix. The op is\n",
+ "# added as a node to the default graph.\n",
+ "#\n",
+ "# The value returned by the constructor represents the output\n",
+ "# of the Constant op.\n",
+ "matrix1 = tf.constant([[3., 3.]])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Create another Constant that produces a 2x1 matrix.\n",
+ "matrix2 = tf.constant([[2.],[2.]])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Create a Matmul op that takes 'matrix1' and 'matrix2' as inputs.\n",
+ "# The returned value, 'product', represents the result of the matrix\n",
+ "# multiplication.\n",
+ "product = tf.matmul(matrix1, matrix2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[[ 12.]]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# To run the matmul op we call the session 'run()' method, passing 'product'\n",
+ "# which represents the output of the matmul op. This indicates to the call\n",
+ "# that we want to get the output of the matmul op back.\n",
+ "#\n",
+ "# All inputs needed by the op are run automatically by the session. They\n",
+ "# typically are run in parallel.\n",
+ "#\n",
+ "# The call 'run(product)' thus causes the execution of threes ops in the\n",
+ "# graph: the two constants and matmul.\n",
+ "#\n",
+ "# The output of the op is returned in 'result' as a numpy `ndarray` object.\n",
+ "with tf.Session() as sess:\n",
+ " result = sess.run(product)\n",
+ " print result"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "IPython (Python 2.7)",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2.0
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.8"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/1_Introduction/helloworld.ipynb b/tensorflow_v1/notebooks/1_Introduction/helloworld.ipynb
new file mode 100644
index 00000000..9d7f0ace
--- /dev/null
+++ b/tensorflow_v1/notebooks/1_Introduction/helloworld.ipynb
@@ -0,0 +1,87 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Simple hello world using TensorFlow\n",
+ "\n",
+ "# Create a Constant op\n",
+ "# The op is added as a node to the default graph.\n",
+ "#\n",
+ "# The value returned by the constructor represents the output\n",
+ "# of the Constant op.\n",
+ "\n",
+ "hello = tf.constant('Hello, TensorFlow!')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Start tf session\n",
+ "sess = tf.Session()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Hello, TensorFlow!\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Run graph\n",
+ "print(sess.run(hello))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "IPython (Python 2.7)",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2.0
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.8"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/2_BasicModels/gradient_boosted_decision_tree.ipynb b/tensorflow_v1/notebooks/2_BasicModels/gradient_boosted_decision_tree.ipynb
new file mode 100644
index 00000000..6e8b9a51
--- /dev/null
+++ b/tensorflow_v1/notebooks/2_BasicModels/gradient_boosted_decision_tree.ipynb
@@ -0,0 +1,266 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Gradient Boosted Decision Tree\n",
+ "\n",
+ "Implement a Gradient Boosted Decision tree (GBDT) with TensorFlow to classify\n",
+ "handwritten digit images. This example is using the MNIST database of\n",
+ "handwritten digits as training samples (http://yann.lecun.com/exdb/mnist/).\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "from tensorflow.contrib.boosted_trees.estimator_batch.estimator import GradientBoostedDecisionTreeClassifier\n",
+ "from tensorflow.contrib.boosted_trees.proto import learner_pb2 as gbdt_learner\n",
+ "\n",
+ "# Ignore all GPUs (current TF GBDT does not support GPU).\n",
+ "import os\n",
+ "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Import MNIST data\n",
+ "# Set verbosity to display errors only (Remove this line for showing warnings)\n",
+ "tf.logging.set_verbosity(tf.logging.ERROR)\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=False,\n",
+ " source_url='http://yann.lecun.com/exdb/mnist/')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "batch_size = 4096 # The number of samples per batch\n",
+ "num_classes = 10 # The 10 digits\n",
+ "num_features = 784 # Each image is 28x28 pixels\n",
+ "max_steps = 10000\n",
+ "\n",
+ "# GBDT Parameters\n",
+ "learning_rate = 0.1\n",
+ "l1_regul = 0.\n",
+ "l2_regul = 1.\n",
+ "examples_per_layer = 1000\n",
+ "num_trees = 10\n",
+ "max_depth = 16"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Fill GBDT parameters into the config proto\n",
+ "learner_config = gbdt_learner.LearnerConfig()\n",
+ "learner_config.learning_rate_tuner.fixed.learning_rate = learning_rate\n",
+ "learner_config.regularization.l1 = l1_regul\n",
+ "learner_config.regularization.l2 = l2_regul / examples_per_layer\n",
+ "learner_config.constraints.max_tree_depth = max_depth\n",
+ "growing_mode = gbdt_learner.LearnerConfig.LAYER_BY_LAYER\n",
+ "learner_config.growing_mode = growing_mode\n",
+ "run_config = tf.contrib.learn.RunConfig(save_checkpoints_secs=300)\n",
+ "learner_config.multi_class_strategy = (\n",
+ " gbdt_learner.LearnerConfig.DIAGONAL_HESSIAN)\\\n",
+ "\n",
+ "# Create a TensorFlor GBDT Estimator\n",
+ "gbdt_model = GradientBoostedDecisionTreeClassifier(\n",
+ " model_dir=None, # No save directory specified\n",
+ " learner_config=learner_config,\n",
+ " n_classes=num_classes,\n",
+ " examples_per_layer=examples_per_layer,\n",
+ " num_trees=num_trees,\n",
+ " center_bias=False,\n",
+ " config=run_config)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Active Feature Columns: ['images_0', 'images_1', 'images_2', 'images_3', 'images_4', 'images_5', 'images_6', 'images_7', 'images_8', 'images_9', 'images_10', 'images_11', 'images_12', 'images_13', 'images_14', 'images_15', 'images_16', 'images_17', 'images_18', 'images_19', 'images_20', 'images_21', 'images_22', 'images_23', 'images_24', 'images_25', 'images_26', 'images_27', 'images_28', 'images_29', 'images_30', 'images_31', 'images_32', 'images_33', 'images_34', 'images_35', 'images_36', 'images_37', 'images_38', 'images_39', 'images_40', 'images_41', 'images_42', 'images_43', 'images_44', 'images_45', 'images_46', 'images_47', 'images_48', 'images_49', 'images_50', 'images_51', 'images_52', 'images_53', 'images_54', 'images_55', 'images_56', 'images_57', 'images_58', 'images_59', 'images_60', 'images_61', 'images_62', 'images_63', 'images_64', 'images_65', 'images_66', 'images_67', 'images_68', 'images_69', 'images_70', 'images_71', 'images_72', 'images_73', 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'images_715', 'images_716', 'images_717', 'images_718', 'images_719', 'images_720', 'images_721', 'images_722', 'images_723', 'images_724', 'images_725', 'images_726', 'images_727', 'images_728', 'images_729', 'images_730', 'images_731', 'images_732', 'images_733', 'images_734', 'images_735', 'images_736', 'images_737', 'images_738', 'images_739', 'images_740', 'images_741', 'images_742', 'images_743', 'images_744', 'images_745', 'images_746', 'images_747', 'images_748', 'images_749', 'images_750', 'images_751', 'images_752', 'images_753', 'images_754', 'images_755', 'images_756', 'images_757', 'images_758', 'images_759', 'images_760', 'images_761', 'images_762', 'images_763', 'images_764', 'images_765', 'images_766', 'images_767', 'images_768', 'images_769', 'images_770', 'images_771', 'images_772', 'images_773', 'images_774', 'images_775', 'images_776', 'images_777', 'images_778', 'images_779', 'images_780', 'images_781', 'images_782', 'images_783']\n",
+ "WARNING:tensorflow:From /Users/aymeric.damien/anaconda2/lib/python2.7/site-packages/tensorflow/contrib/learn/python/learn/estimators/head.py:678: __new__ (from tensorflow.contrib.learn.python.learn.estimators.model_fn) is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "When switching to tf.estimator.Estimator, use tf.estimator.EstimatorSpec. You can use the `estimator_spec` method to create an equivalent one.\n",
+ "INFO:tensorflow:Create CheckpointSaverHook.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Graph was finalized.\n",
+ "INFO:tensorflow:Running local_init_op.\n",
+ "INFO:tensorflow:Done running local_init_op.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Saving checkpoints for 0 into /var/folders/p7/9nxn5g_s5kv636j86zdg2hrr0000gr/T/tmpE_8oiQ/model.ckpt.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:loss = 2.3025992, step = 1\n",
+ "INFO:tensorflow:Saving checkpoints for 2 into /var/folders/p7/9nxn5g_s5kv636j86zdg2hrr0000gr/T/tmpE_8oiQ/model.ckpt.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Saving checkpoints for 94 into /var/folders/p7/9nxn5g_s5kv636j86zdg2hrr0000gr/T/tmpE_8oiQ/model.ckpt.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:global_step/sec: 0.199624\n",
+ "INFO:tensorflow:loss = 0.32783023, step = 101 (500.943 sec)\n",
+ "INFO:tensorflow:Requesting stop since we have reached 10 trees.\n",
+ "INFO:tensorflow:Saving checkpoints for 161 into /var/folders/p7/9nxn5g_s5kv636j86zdg2hrr0000gr/T/tmpE_8oiQ/model.ckpt.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Loss for final step: 0.21336032.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "GradientBoostedDecisionTreeClassifier(params={'head': , 'weight_column_name': None, 'feature_columns': None, 'center_bias': False, 'num_trees': 10, 'logits_modifier_function': None, 'use_core_libs': False, 'learner_config': num_classes: 10\n",
+ "regularization {\n",
+ " l2: 0.0010000000475\n",
+ "}\n",
+ "constraints {\n",
+ " max_tree_depth: 16\n",
+ "}\n",
+ "learning_rate_tuner {\n",
+ " fixed {\n",
+ " learning_rate: 0.10000000149\n",
+ " }\n",
+ "}\n",
+ "pruning_mode: POST_PRUNE\n",
+ "growing_mode: LAYER_BY_LAYER\n",
+ "multi_class_strategy: DIAGONAL_HESSIAN\n",
+ ", 'examples_per_layer': 1000})"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display TF info logs\n",
+ "tf.logging.set_verbosity(tf.logging.INFO)\n",
+ "\n",
+ "# Define the input function for training\n",
+ "input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+ " x={'images': mnist.train.images}, y=mnist.train.labels,\n",
+ " batch_size=batch_size, num_epochs=None, shuffle=True)\n",
+ "\n",
+ "# Train the Model\n",
+ "gbdt_model.fit(input_fn=input_fn, max_steps=max_steps)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Active Feature Columns: ['images_0', 'images_1', 'images_2', 'images_3', 'images_4', 'images_5', 'images_6', 'images_7', 'images_8', 'images_9', 'images_10', 'images_11', 'images_12', 'images_13', 'images_14', 'images_15', 'images_16', 'images_17', 'images_18', 'images_19', 'images_20', 'images_21', 'images_22', 'images_23', 'images_24', 'images_25', 'images_26', 'images_27', 'images_28', 'images_29', 'images_30', 'images_31', 'images_32', 'images_33', 'images_34', 'images_35', 'images_36', 'images_37', 'images_38', 'images_39', 'images_40', 'images_41', 'images_42', 'images_43', 'images_44', 'images_45', 'images_46', 'images_47', 'images_48', 'images_49', 'images_50', 'images_51', 'images_52', 'images_53', 'images_54', 'images_55', 'images_56', 'images_57', 'images_58', 'images_59', 'images_60', 'images_61', 'images_62', 'images_63', 'images_64', 'images_65', 'images_66', 'images_67', 'images_68', 'images_69', 'images_70', 'images_71', 'images_72', 'images_73', 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'images_715', 'images_716', 'images_717', 'images_718', 'images_719', 'images_720', 'images_721', 'images_722', 'images_723', 'images_724', 'images_725', 'images_726', 'images_727', 'images_728', 'images_729', 'images_730', 'images_731', 'images_732', 'images_733', 'images_734', 'images_735', 'images_736', 'images_737', 'images_738', 'images_739', 'images_740', 'images_741', 'images_742', 'images_743', 'images_744', 'images_745', 'images_746', 'images_747', 'images_748', 'images_749', 'images_750', 'images_751', 'images_752', 'images_753', 'images_754', 'images_755', 'images_756', 'images_757', 'images_758', 'images_759', 'images_760', 'images_761', 'images_762', 'images_763', 'images_764', 'images_765', 'images_766', 'images_767', 'images_768', 'images_769', 'images_770', 'images_771', 'images_772', 'images_773', 'images_774', 'images_775', 'images_776', 'images_777', 'images_778', 'images_779', 'images_780', 'images_781', 'images_782', 'images_783']\n",
+ "INFO:tensorflow:Starting evaluation at 2018-07-26-01:00:06\n",
+ "INFO:tensorflow:Graph was finalized.\n",
+ "INFO:tensorflow:Restoring parameters from /var/folders/p7/9nxn5g_s5kv636j86zdg2hrr0000gr/T/tmpE_8oiQ/model.ckpt-161\n",
+ "INFO:tensorflow:Running local_init_op.\n",
+ "INFO:tensorflow:Done running local_init_op.\n",
+ "INFO:tensorflow:Finished evaluation at 2018-07-26-01:00:07\n",
+ "INFO:tensorflow:Saving dict for global step 161: accuracy = 0.9273, global_step = 161, loss = 0.23841818\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "Testing Accuracy: 0.9273\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Evaluate the Model\n",
+ "# Define the input function for evaluating\n",
+ "input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+ " x={'images': mnist.test.images}, y=mnist.test.labels,\n",
+ " batch_size=batch_size, shuffle=False)\n",
+ "\n",
+ "# Use the Estimator 'evaluate' method\n",
+ "e = gbdt_model.evaluate(input_fn=input_fn)\n",
+ "print(\"Testing Accuracy:\", e['accuracy'])"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/2_BasicModels/kmeans.ipynb b/tensorflow_v1/notebooks/2_BasicModels/kmeans.ipynb
new file mode 100644
index 00000000..99f685e7
--- /dev/null
+++ b/tensorflow_v1/notebooks/2_BasicModels/kmeans.ipynb
@@ -0,0 +1,226 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# K-Means Example\n",
+ "\n",
+ "Implement K-Means algorithm with TensorFlow, and apply it to classify\n",
+ "handwritten digit images. This example is using the MNIST database of\n",
+ "handwritten digits as training samples (http://yann.lecun.com/exdb/mnist/).\n",
+ "\n",
+ "Note: This example requires TensorFlow v1.1.0 or over.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import numpy as np\n",
+ "import tensorflow as tf\n",
+ "from tensorflow.contrib.factorization import KMeans\n",
+ "\n",
+ "# Ignore all GPUs, tf random forest does not benefit from it.\n",
+ "import os\n",
+ "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)\n",
+ "full_data_x = mnist.train.images"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "num_steps = 50 # Total steps to train\n",
+ "batch_size = 1024 # The number of samples per batch\n",
+ "k = 25 # The number of clusters\n",
+ "num_classes = 10 # The 10 digits\n",
+ "num_features = 784 # Each image is 28x28 pixels\n",
+ "\n",
+ "# Input images\n",
+ "X = tf.placeholder(tf.float32, shape=[None, num_features])\n",
+ "# Labels (for assigning a label to a centroid and testing)\n",
+ "Y = tf.placeholder(tf.float32, shape=[None, num_classes])\n",
+ "\n",
+ "# K-Means Parameters\n",
+ "kmeans = KMeans(inputs=X, num_clusters=k, distance_metric='cosine',\n",
+ " use_mini_batch=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Build KMeans graph\n",
+ "(all_scores, cluster_idx, scores, cluster_centers_initialized, \n",
+ " cluster_centers_vars,init_op,train_op) = kmeans.training_graph()\n",
+ "cluster_idx = cluster_idx[0] # fix for cluster_idx being a tuple\n",
+ "avg_distance = tf.reduce_mean(scores)\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init_vars = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1, Avg Distance: 0.341471\n",
+ "Step 10, Avg Distance: 0.221609\n",
+ "Step 20, Avg Distance: 0.220328\n",
+ "Step 30, Avg Distance: 0.219776\n",
+ "Step 40, Avg Distance: 0.219419\n",
+ "Step 50, Avg Distance: 0.219154\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start TensorFlow session\n",
+ "sess = tf.Session()\n",
+ "\n",
+ "# Run the initializer\n",
+ "sess.run(init_vars, feed_dict={X: full_data_x})\n",
+ "sess.run(init_op, feed_dict={X: full_data_x})\n",
+ "\n",
+ "# Training\n",
+ "for i in range(1, num_steps + 1):\n",
+ " _, d, idx = sess.run([train_op, avg_distance, cluster_idx],\n",
+ " feed_dict={X: full_data_x})\n",
+ " if i % 10 == 0 or i == 1:\n",
+ " print(\"Step %i, Avg Distance: %f\" % (i, d))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Test Accuracy: 0.7127\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Assign a label to each centroid\n",
+ "# Count total number of labels per centroid, using the label of each training\n",
+ "# sample to their closest centroid (given by 'idx')\n",
+ "counts = np.zeros(shape=(k, num_classes))\n",
+ "for i in range(len(idx)):\n",
+ " counts[idx[i]] += mnist.train.labels[i]\n",
+ "# Assign the most frequent label to the centroid\n",
+ "labels_map = [np.argmax(c) for c in counts]\n",
+ "labels_map = tf.convert_to_tensor(labels_map)\n",
+ "\n",
+ "# Evaluation ops\n",
+ "# Lookup: centroid_id -> label\n",
+ "cluster_label = tf.nn.embedding_lookup(labels_map, cluster_idx)\n",
+ "# Compute accuracy\n",
+ "correct_prediction = tf.equal(cluster_label, tf.cast(tf.argmax(Y, 1), tf.int32))\n",
+ "accuracy_op = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))\n",
+ "\n",
+ "# Test Model\n",
+ "test_x, test_y = mnist.test.images, mnist.test.labels\n",
+ "print(\"Test Accuracy:\", sess.run(accuracy_op, feed_dict={X: test_x, Y: test_y}))"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ },
+ "varInspector": {
+ "cols": {
+ "lenName": 16,
+ "lenType": 16,
+ "lenVar": 40
+ },
+ "kernels_config": {
+ "python": {
+ "delete_cmd_postfix": "",
+ "delete_cmd_prefix": "del ",
+ "library": "var_list.py",
+ "varRefreshCmd": "print(var_dic_list())"
+ },
+ "r": {
+ "delete_cmd_postfix": ") ",
+ "delete_cmd_prefix": "rm(",
+ "library": "var_list.r",
+ "varRefreshCmd": "cat(var_dic_list()) "
+ }
+ },
+ "types_to_exclude": [
+ "module",
+ "function",
+ "builtin_function_or_method",
+ "instance",
+ "_Feature"
+ ],
+ "window_display": false
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/2_BasicModels/linear_regression.ipynb b/tensorflow_v1/notebooks/2_BasicModels/linear_regression.ipynb
new file mode 100644
index 00000000..f0d8cff9
--- /dev/null
+++ b/tensorflow_v1/notebooks/2_BasicModels/linear_regression.ipynb
@@ -0,0 +1,236 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": false
+ },
+ "source": [
+ "# Linear Regression Example\n",
+ "\n",
+ "A linear regression learning algorithm example using TensorFlow library.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "import tensorflow as tf\n",
+ "import numpy\n",
+ "import matplotlib.pyplot as plt\n",
+ "rng = numpy.random"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.01\n",
+ "training_epochs = 1000\n",
+ "display_step = 50"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Training Data\n",
+ "train_X = numpy.asarray([3.3,4.4,5.5,6.71,6.93,4.168,9.779,6.182,7.59,2.167,\n",
+ " 7.042,10.791,5.313,7.997,5.654,9.27,3.1])\n",
+ "train_Y = numpy.asarray([1.7,2.76,2.09,3.19,1.694,1.573,3.366,2.596,2.53,1.221,\n",
+ " 2.827,3.465,1.65,2.904,2.42,2.94,1.3])\n",
+ "n_samples = train_X.shape[0]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# tf Graph Input\n",
+ "X = tf.placeholder(\"float\")\n",
+ "Y = tf.placeholder(\"float\")\n",
+ "\n",
+ "# Set model weights\n",
+ "W = tf.Variable(rng.randn(), name=\"weight\")\n",
+ "b = tf.Variable(rng.randn(), name=\"bias\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Construct a linear model\n",
+ "pred = tf.add(tf.multiply(X, W), b)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Mean squared error\n",
+ "cost = tf.reduce_sum(tf.pow(pred-Y, 2))/(2*n_samples)\n",
+ "# Gradient descent\n",
+ "optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Epoch: 0050 cost= 0.195095107 W= 0.441748 b= -0.580876\n",
+ "Epoch: 0100 cost= 0.181448311 W= 0.430319 b= -0.498661\n",
+ "Epoch: 0150 cost= 0.169377610 W= 0.419571 b= -0.421336\n",
+ "Epoch: 0200 cost= 0.158700854 W= 0.409461 b= -0.348611\n",
+ "Epoch: 0250 cost= 0.149257123 W= 0.399953 b= -0.28021\n",
+ "Epoch: 0300 cost= 0.140904188 W= 0.391011 b= -0.215878\n",
+ "Epoch: 0350 cost= 0.133515999 W= 0.3826 b= -0.155372\n",
+ "Epoch: 0400 cost= 0.126981199 W= 0.374689 b= -0.0984639\n",
+ "Epoch: 0450 cost= 0.121201262 W= 0.367249 b= -0.0449408\n",
+ "Epoch: 0500 cost= 0.116088994 W= 0.360252 b= 0.00539905\n",
+ "Epoch: 0550 cost= 0.111567356 W= 0.35367 b= 0.052745\n",
+ "Epoch: 0600 cost= 0.107568085 W= 0.34748 b= 0.0972751\n",
+ "Epoch: 0650 cost= 0.104030922 W= 0.341659 b= 0.139157\n",
+ "Epoch: 0700 cost= 0.100902475 W= 0.336183 b= 0.178547\n",
+ "Epoch: 0750 cost= 0.098135538 W= 0.331033 b= 0.215595\n",
+ "Epoch: 0800 cost= 0.095688373 W= 0.32619 b= 0.25044\n",
+ "Epoch: 0850 cost= 0.093524046 W= 0.321634 b= 0.283212\n",
+ "Epoch: 0900 cost= 0.091609895 W= 0.317349 b= 0.314035\n",
+ "Epoch: 0950 cost= 0.089917004 W= 0.31332 b= 0.343025\n",
+ "Epoch: 1000 cost= 0.088419855 W= 0.30953 b= 0.370291\n",
+ "Optimization Finished!\n",
+ "Training cost= 0.0884199 W= 0.30953 b= 0.370291 \n",
+ "\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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5eOSRR3a731//+ld8Ph8rVqxoaJs4cSIHHXRQokPMeEoSREQ6kAULFuDz+SK+Gq+I6PP5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\n4IFd2wUFsFqprIh0YKrdIB3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+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Start training\n",
+ "with tf.Session() as sess:\n",
+ " sess.run(init)\n",
+ "\n",
+ " # Fit all training data\n",
+ " for epoch in range(training_epochs):\n",
+ " for (x, y) in zip(train_X, train_Y):\n",
+ " sess.run(optimizer, feed_dict={X: x, Y: y})\n",
+ "\n",
+ " #Display logs per epoch step\n",
+ " if (epoch+1) % display_step == 0:\n",
+ " c = sess.run(cost, feed_dict={X: train_X, Y:train_Y})\n",
+ " print \"Epoch:\", '%04d' % (epoch+1), \"cost=\", \"{:.9f}\".format(c), \\\n",
+ " \"W=\", sess.run(W), \"b=\", sess.run(b)\n",
+ "\n",
+ " print \"Optimization Finished!\"\n",
+ " training_cost = sess.run(cost, feed_dict={X: train_X, Y: train_Y})\n",
+ " print \"Training cost=\", training_cost, \"W=\", sess.run(W), \"b=\", sess.run(b), '\\n'\n",
+ "\n",
+ " #Graphic display\n",
+ " plt.plot(train_X, train_Y, 'ro', label='Original data')\n",
+ " plt.plot(train_X, sess.run(W) * train_X + sess.run(b), label='Fitted line')\n",
+ " plt.legend()\n",
+ " plt.show()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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OVIcOHbR3714tXLhQmzdv1jPPPKOoqChJ0pQpU5Senq7t27dX3Nqwf//++uUv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\nWrlyZbVfV1RUpCuuuEKtWrXStGnTdOjQIU2fPl1ffvmlPB6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+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 1,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Regression result"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/2_BasicModels/linear_regression_eager_api.ipynb b/tensorflow_v1/notebooks/2_BasicModels/linear_regression_eager_api.ipynb
new file mode 100644
index 00000000..8e8ea2b8
--- /dev/null
+++ b/tensorflow_v1/notebooks/2_BasicModels/linear_regression_eager_api.ipynb
@@ -0,0 +1,181 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Linear Regression with Eager API\n",
+ "\n",
+ "A linear regression implemented using TensorFlow's Eager API.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Set Eager API\n",
+ "tf.enable_eager_execution()\n",
+ "tfe = tf.contrib.eager"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Training Data\n",
+ "train_X = [3.3, 4.4, 5.5, 6.71, 6.93, 4.168, 9.779, 6.182, 7.59, 2.167,\n",
+ " 7.042, 10.791, 5.313, 7.997, 5.654, 9.27, 3.1]\n",
+ "train_Y = [1.7, 2.76, 2.09, 3.19, 1.694, 1.573, 3.366, 2.596, 2.53, 1.221,\n",
+ " 2.827, 3.465, 1.65, 2.904, 2.42, 2.94, 1.3]\n",
+ "n_samples = len(train_X)\n",
+ "\n",
+ "# Parameters\n",
+ "learning_rate = 0.01\n",
+ "display_step = 100\n",
+ "num_steps = 1000"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Weight and Bias\n",
+ "W = tfe.Variable(np.random.randn())\n",
+ "b = tfe.Variable(np.random.randn())\n",
+ "\n",
+ "# Linear regression (Wx + b)\n",
+ "def linear_regression(inputs):\n",
+ " return inputs * W + b\n",
+ "\n",
+ "# Mean square error\n",
+ "def mean_square_fn(model_fn, inputs, labels):\n",
+ " return tf.reduce_sum(tf.pow(model_fn(inputs) - labels, 2)) / (2 * n_samples)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# SGD Optimizer\n",
+ "optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)\n",
+ "\n",
+ "# Compute gradients\n",
+ "grad = tfe.implicit_gradients(mean_square_fn)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Initial cost= 31.307329178 W= -0.7870768 b= -0.2507985\n",
+ "Epoch: 0001 cost= 9.502781868 W= -0.26173288 b= -0.17560114\n",
+ "Epoch: 0100 cost= 0.114994615 W= 0.36224815 b= 0.014603348\n",
+ "Epoch: 0200 cost= 0.106785327 W= 0.34959725 b= 0.104292504\n",
+ "Epoch: 0300 cost= 0.100346453 W= 0.33839324 b= 0.1837239\n",
+ "Epoch: 0400 cost= 0.095296182 W= 0.32847065 b= 0.25407064\n",
+ "Epoch: 0500 cost= 0.091335081 W= 0.3196829 b= 0.3163719\n",
+ "Epoch: 0600 cost= 0.088228233 W= 0.31190023 b= 0.37154746\n",
+ "Epoch: 0700 cost= 0.085791394 W= 0.30500764 b= 0.42041263\n",
+ "Epoch: 0800 cost= 0.083880097 W= 0.2989034 b= 0.46368918\n",
+ "Epoch: 0900 cost= 0.082380980 W= 0.2934973 b= 0.50201607\n",
+ "Epoch: 1000 cost= 0.081205189 W= 0.28870946 b= 0.5359594\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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U83hXoHvtyc651Wb2fWAmMBn4BLjAOdf4jgcREWmhhQthRKNl7Hbvhv3396ee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\nzI7yu65omdnFZvammW2p+VliZiP8ris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+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Initial cost, before optimizing\n",
+ "print(\"Initial cost= {:.9f}\".format(\n",
+ " mean_square_fn(linear_regression, train_X, train_Y)),\n",
+ " \"W=\", W.numpy(), \"b=\", b.numpy())\n",
+ "\n",
+ "# Training\n",
+ "for step in range(num_steps):\n",
+ "\n",
+ " optimizer.apply_gradients(grad(linear_regression, train_X, train_Y))\n",
+ "\n",
+ " if (step + 1) % display_step == 0 or step == 0:\n",
+ " print(\"Epoch:\", '%04d' % (step + 1), \"cost=\",\n",
+ " \"{:.9f}\".format(mean_square_fn(linear_regression, train_X, train_Y)),\n",
+ " \"W=\", W.numpy(), \"b=\", b.numpy())\n",
+ "\n",
+ "# Graphic display\n",
+ "plt.plot(train_X, train_Y, 'ro', label='Original data')\n",
+ "plt.plot(train_X, np.array(W * train_X + b), label='Fitted line')\n",
+ "plt.legend()\n",
+ "plt.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/2_BasicModels/logistic_regression.ipynb b/tensorflow_v1/notebooks/2_BasicModels/logistic_regression.ipynb
new file mode 100644
index 00000000..1636016f
--- /dev/null
+++ b/tensorflow_v1/notebooks/2_BasicModels/logistic_regression.ipynb
@@ -0,0 +1,174 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Logistic Regression Example\n",
+ "\n",
+ "A logistic regression learning algorithm example using TensorFlow library.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting MNIST_data/train-images-idx3-ubyte.gz\n",
+ "Extracting MNIST_data/train-labels-idx1-ubyte.gz\n",
+ "Extracting MNIST_data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting MNIST_data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "import tensorflow as tf\n",
+ "\n",
+ "# Import MINST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.01\n",
+ "training_epochs = 25\n",
+ "batch_size = 100\n",
+ "display_step = 1\n",
+ "\n",
+ "# tf Graph Input\n",
+ "x = tf.placeholder(tf.float32, [None, 784]) # mnist data image of shape 28*28=784\n",
+ "y = tf.placeholder(tf.float32, [None, 10]) # 0-9 digits recognition => 10 classes\n",
+ "\n",
+ "# Set model weights\n",
+ "W = tf.Variable(tf.zeros([784, 10]))\n",
+ "b = tf.Variable(tf.zeros([10]))\n",
+ "\n",
+ "# Construct model\n",
+ "pred = tf.nn.softmax(tf.matmul(x, W) + b) # Softmax\n",
+ "\n",
+ "# Minimize error using cross entropy\n",
+ "cost = tf.reduce_mean(-tf.reduce_sum(y*tf.log(pred), reduction_indices=1))\n",
+ "# Gradient Descent\n",
+ "optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Epoch: 0001 cost= 1.182138959\n",
+ "Epoch: 0002 cost= 0.664778162\n",
+ "Epoch: 0003 cost= 0.552686284\n",
+ "Epoch: 0004 cost= 0.498628905\n",
+ "Epoch: 0005 cost= 0.465469866\n",
+ "Epoch: 0006 cost= 0.442537872\n",
+ "Epoch: 0007 cost= 0.425462044\n",
+ "Epoch: 0008 cost= 0.412185303\n",
+ "Epoch: 0009 cost= 0.401311587\n",
+ "Epoch: 0010 cost= 0.392326203\n",
+ "Epoch: 0011 cost= 0.384736038\n",
+ "Epoch: 0012 cost= 0.378137191\n",
+ "Epoch: 0013 cost= 0.372363752\n",
+ "Epoch: 0014 cost= 0.367308579\n",
+ "Epoch: 0015 cost= 0.362704660\n",
+ "Epoch: 0016 cost= 0.358588599\n",
+ "Epoch: 0017 cost= 0.354823110\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start training\n",
+ "with tf.Session() as sess:\n",
+ " sess.run(init)\n",
+ "\n",
+ " # Training cycle\n",
+ " for epoch in range(training_epochs):\n",
+ " avg_cost = 0.\n",
+ " total_batch = int(mnist.train.num_examples/batch_size)\n",
+ " # Loop over all batches\n",
+ " for i in range(total_batch):\n",
+ " batch_xs, batch_ys = mnist.train.next_batch(batch_size)\n",
+ " # Fit training using batch data\n",
+ " _, c = sess.run([optimizer, cost], feed_dict={x: batch_xs,\n",
+ " y: batch_ys})\n",
+ " # Compute average loss\n",
+ " avg_cost += c / total_batch\n",
+ " # Display logs per epoch step\n",
+ " if (epoch+1) % display_step == 0:\n",
+ " print \"Epoch:\", '%04d' % (epoch+1), \"cost=\", \"{:.9f}\".format(avg_cost)\n",
+ "\n",
+ " print \"Optimization Finished!\"\n",
+ "\n",
+ " # Test model\n",
+ " correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))\n",
+ " # Calculate accuracy for 3000 examples\n",
+ " accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))\n",
+ " print \"Accuracy:\", accuracy.eval({x: mnist.test.images[:3000], y: mnist.test.labels[:3000]})"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/2_BasicModels/logistic_regression_eager_api.ipynb b/tensorflow_v1/notebooks/2_BasicModels/logistic_regression_eager_api.ipynb
new file mode 100644
index 00000000..be3256c9
--- /dev/null
+++ b/tensorflow_v1/notebooks/2_BasicModels/logistic_regression_eager_api.ipynb
@@ -0,0 +1,258 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Logistic Regression with Eager API\n",
+ "\n",
+ "A logistic regression implemented using TensorFlow's Eager API.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Set Eager API\n",
+ "tf.enable_eager_execution()\n",
+ "tfe = tf.contrib.eager"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=False)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.1\n",
+ "batch_size = 128\n",
+ "num_steps = 1000\n",
+ "display_step = 100"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Iterator for the dataset\n",
+ "dataset = tf.data.Dataset.from_tensor_slices(\n",
+ " (mnist.train.images, mnist.train.labels))\n",
+ "dataset = dataset.repeat().batch(batch_size).prefetch(batch_size)\n",
+ "dataset_iter = tfe.Iterator(dataset)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Variables\n",
+ "W = tfe.Variable(tf.zeros([784, 10]), name='weights')\n",
+ "b = tfe.Variable(tf.zeros([10]), name='bias')\n",
+ "\n",
+ "# Logistic regression (Wx + b)\n",
+ "def logistic_regression(inputs):\n",
+ " return tf.matmul(inputs, W) + b\n",
+ "\n",
+ "# Cross-Entropy loss function\n",
+ "def loss_fn(inference_fn, inputs, labels):\n",
+ " # Using sparse_softmax cross entropy\n",
+ " return tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(\n",
+ " logits=inference_fn(inputs), labels=labels))\n",
+ "\n",
+ "# Calculate accuracy\n",
+ "def accuracy_fn(inference_fn, inputs, labels):\n",
+ " prediction = tf.nn.softmax(inference_fn(inputs))\n",
+ " correct_pred = tf.equal(tf.argmax(prediction, 1), labels)\n",
+ " return tf.reduce_mean(tf.cast(correct_pred, tf.float32))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# SGD Optimizer\n",
+ "optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)\n",
+ "\n",
+ "# Compute gradients\n",
+ "grad = tfe.implicit_gradients(loss_fn)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Initial loss= 2.302584887\n",
+ "Step: 0001 loss= 2.302584887 accuracy= 0.1172\n",
+ "Step: 0100 loss= 0.952338457 accuracy= 0.7955\n",
+ "Step: 0200 loss= 0.535867393 accuracy= 0.8712\n",
+ "Step: 0300 loss= 0.485415280 accuracy= 0.8757\n",
+ "Step: 0400 loss= 0.433947206 accuracy= 0.8843\n",
+ "Step: 0500 loss= 0.381990731 accuracy= 0.8971\n",
+ "Step: 0600 loss= 0.394154936 accuracy= 0.8947\n",
+ "Step: 0700 loss= 0.391497582 accuracy= 0.8905\n",
+ "Step: 0800 loss= 0.386373103 accuracy= 0.8945\n",
+ "Step: 0900 loss= 0.332039326 accuracy= 0.9096\n",
+ "Step: 1000 loss= 0.358993769 accuracy= 0.9002\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Training\n",
+ "average_loss = 0.\n",
+ "average_acc = 0.\n",
+ "for step in range(num_steps):\n",
+ "\n",
+ " # Iterate through the dataset\n",
+ " d = dataset_iter.next()\n",
+ "\n",
+ " # Images\n",
+ " x_batch = d[0]\n",
+ " # Labels\n",
+ " y_batch = tf.cast(d[1], dtype=tf.int64)\n",
+ "\n",
+ " # Compute the batch loss\n",
+ " batch_loss = loss_fn(logistic_regression, x_batch, y_batch)\n",
+ " average_loss += batch_loss\n",
+ " # Compute the batch accuracy\n",
+ " batch_accuracy = accuracy_fn(logistic_regression, x_batch, y_batch)\n",
+ " average_acc += batch_accuracy\n",
+ "\n",
+ " if step == 0:\n",
+ " # Display the initial cost, before optimizing\n",
+ " print(\"Initial loss= {:.9f}\".format(average_loss))\n",
+ "\n",
+ " # Update the variables following gradients info\n",
+ " optimizer.apply_gradients(grad(logistic_regression, x_batch, y_batch))\n",
+ "\n",
+ " # Display info\n",
+ " if (step + 1) % display_step == 0 or step == 0:\n",
+ " if step > 0:\n",
+ " average_loss /= display_step\n",
+ " average_acc /= display_step\n",
+ " print(\"Step:\", '%04d' % (step + 1), \" loss=\",\n",
+ " \"{:.9f}\".format(average_loss), \" accuracy=\",\n",
+ " \"{:.4f}\".format(average_acc))\n",
+ " average_loss = 0.\n",
+ " average_acc = 0."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Testset Accuracy: 0.9083\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Evaluate model on the test image set\n",
+ "testX = mnist.test.images\n",
+ "testY = mnist.test.labels\n",
+ "\n",
+ "test_acc = accuracy_fn(logistic_regression, testX, testY)\n",
+ "print(\"Testset Accuracy: {:.4f}\".format(test_acc))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.14"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/2_BasicModels/nearest_neighbor.ipynb b/tensorflow_v1/notebooks/2_BasicModels/nearest_neighbor.ipynb
new file mode 100644
index 00000000..a8608d82
--- /dev/null
+++ b/tensorflow_v1/notebooks/2_BasicModels/nearest_neighbor.ipynb
@@ -0,0 +1,332 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Nearest Neighbor Example\n",
+ "\n",
+ "A nearest neighbor learning algorithm example using TensorFlow library.\n",
+ "This example is using the MNIST database of handwritten digits (http://yann.lecun.com/exdb/mnist/)\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting MNIST_data/train-images-idx3-ubyte.gz\n",
+ "Extracting MNIST_data/train-labels-idx1-ubyte.gz\n",
+ "Extracting MNIST_data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting MNIST_data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "import numpy as np\n",
+ "import tensorflow as tf\n",
+ "\n",
+ "# Import MINST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# In this example, we limit mnist data\n",
+ "Xtr, Ytr = mnist.train.next_batch(5000) #5000 for training (nn candidates)\n",
+ "Xte, Yte = mnist.test.next_batch(200) #200 for testing\n",
+ "\n",
+ "# tf Graph Input\n",
+ "xtr = tf.placeholder(\"float\", [None, 784])\n",
+ "xte = tf.placeholder(\"float\", [784])\n",
+ "\n",
+ "# Nearest Neighbor calculation using L1 Distance\n",
+ "# Calculate L1 Distance\n",
+ "distance = tf.reduce_sum(tf.abs(tf.add(xtr, tf.negative(xte))), reduction_indices=1)\n",
+ "# Prediction: Get min distance index (Nearest neighbor)\n",
+ "pred = tf.argmin(distance, 0)\n",
+ "\n",
+ "accuracy = 0.\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Test 0 Prediction: 7 True Class: 7\n",
+ "Test 1 Prediction: 2 True Class: 2\n",
+ "Test 2 Prediction: 1 True Class: 1\n",
+ "Test 3 Prediction: 0 True Class: 0\n",
+ "Test 4 Prediction: 4 True Class: 4\n",
+ "Test 5 Prediction: 1 True Class: 1\n",
+ "Test 6 Prediction: 4 True Class: 4\n",
+ "Test 7 Prediction: 9 True Class: 9\n",
+ "Test 8 Prediction: 8 True Class: 5\n",
+ "Test 9 Prediction: 9 True Class: 9\n",
+ "Test 10 Prediction: 0 True Class: 0\n",
+ "Test 11 Prediction: 0 True Class: 6\n",
+ "Test 12 Prediction: 9 True Class: 9\n",
+ "Test 13 Prediction: 0 True Class: 0\n",
+ "Test 14 Prediction: 1 True Class: 1\n",
+ "Test 15 Prediction: 5 True Class: 5\n",
+ "Test 16 Prediction: 4 True Class: 9\n",
+ "Test 17 Prediction: 7 True Class: 7\n",
+ "Test 18 Prediction: 3 True Class: 3\n",
+ "Test 19 Prediction: 4 True Class: 4\n",
+ "Test 20 Prediction: 9 True Class: 9\n",
+ "Test 21 Prediction: 6 True Class: 6\n",
+ "Test 22 Prediction: 6 True Class: 6\n",
+ "Test 23 Prediction: 5 True Class: 5\n",
+ "Test 24 Prediction: 4 True Class: 4\n",
+ "Test 25 Prediction: 0 True Class: 0\n",
+ "Test 26 Prediction: 7 True Class: 7\n",
+ "Test 27 Prediction: 4 True Class: 4\n",
+ "Test 28 Prediction: 0 True Class: 0\n",
+ "Test 29 Prediction: 1 True Class: 1\n",
+ "Test 30 Prediction: 3 True Class: 3\n",
+ "Test 31 Prediction: 1 True Class: 1\n",
+ "Test 32 Prediction: 3 True Class: 3\n",
+ "Test 33 Prediction: 4 True Class: 4\n",
+ "Test 34 Prediction: 7 True Class: 7\n",
+ "Test 35 Prediction: 2 True Class: 2\n",
+ "Test 36 Prediction: 7 True Class: 7\n",
+ "Test 37 Prediction: 1 True Class: 1\n",
+ "Test 38 Prediction: 2 True Class: 2\n",
+ "Test 39 Prediction: 1 True Class: 1\n",
+ "Test 40 Prediction: 1 True Class: 1\n",
+ "Test 41 Prediction: 7 True Class: 7\n",
+ "Test 42 Prediction: 4 True Class: 4\n",
+ "Test 43 Prediction: 1 True Class: 2\n",
+ "Test 44 Prediction: 3 True Class: 3\n",
+ "Test 45 Prediction: 5 True Class: 5\n",
+ "Test 46 Prediction: 1 True Class: 1\n",
+ "Test 47 Prediction: 2 True Class: 2\n",
+ "Test 48 Prediction: 4 True Class: 4\n",
+ "Test 49 Prediction: 4 True Class: 4\n",
+ "Test 50 Prediction: 6 True Class: 6\n",
+ "Test 51 Prediction: 3 True Class: 3\n",
+ "Test 52 Prediction: 5 True Class: 5\n",
+ "Test 53 Prediction: 5 True Class: 5\n",
+ "Test 54 Prediction: 6 True Class: 6\n",
+ "Test 55 Prediction: 0 True Class: 0\n",
+ "Test 56 Prediction: 4 True Class: 4\n",
+ "Test 57 Prediction: 1 True Class: 1\n",
+ "Test 58 Prediction: 9 True Class: 9\n",
+ "Test 59 Prediction: 5 True Class: 5\n",
+ "Test 60 Prediction: 7 True Class: 7\n",
+ "Test 61 Prediction: 8 True Class: 8\n",
+ "Test 62 Prediction: 9 True Class: 9\n",
+ "Test 63 Prediction: 3 True Class: 3\n",
+ "Test 64 Prediction: 7 True Class: 7\n",
+ "Test 65 Prediction: 4 True Class: 4\n",
+ "Test 66 Prediction: 6 True Class: 6\n",
+ "Test 67 Prediction: 4 True Class: 4\n",
+ "Test 68 Prediction: 3 True Class: 3\n",
+ "Test 69 Prediction: 0 True Class: 0\n",
+ "Test 70 Prediction: 7 True Class: 7\n",
+ "Test 71 Prediction: 0 True Class: 0\n",
+ "Test 72 Prediction: 2 True Class: 2\n",
+ "Test 73 Prediction: 7 True Class: 9\n",
+ "Test 74 Prediction: 1 True Class: 1\n",
+ "Test 75 Prediction: 7 True Class: 7\n",
+ "Test 76 Prediction: 3 True Class: 3\n",
+ "Test 77 Prediction: 7 True Class: 2\n",
+ "Test 78 Prediction: 9 True Class: 9\n",
+ "Test 79 Prediction: 7 True Class: 7\n",
+ "Test 80 Prediction: 7 True Class: 7\n",
+ "Test 81 Prediction: 6 True Class: 6\n",
+ "Test 82 Prediction: 2 True Class: 2\n",
+ "Test 83 Prediction: 7 True Class: 7\n",
+ "Test 84 Prediction: 8 True Class: 8\n",
+ "Test 85 Prediction: 4 True Class: 4\n",
+ "Test 86 Prediction: 7 True Class: 7\n",
+ "Test 87 Prediction: 3 True Class: 3\n",
+ "Test 88 Prediction: 6 True Class: 6\n",
+ "Test 89 Prediction: 1 True Class: 1\n",
+ "Test 90 Prediction: 3 True Class: 3\n",
+ "Test 91 Prediction: 6 True Class: 6\n",
+ "Test 92 Prediction: 9 True Class: 9\n",
+ "Test 93 Prediction: 3 True Class: 3\n",
+ "Test 94 Prediction: 1 True Class: 1\n",
+ "Test 95 Prediction: 4 True Class: 4\n",
+ "Test 96 Prediction: 1 True Class: 1\n",
+ "Test 97 Prediction: 7 True Class: 7\n",
+ "Test 98 Prediction: 6 True Class: 6\n",
+ "Test 99 Prediction: 9 True Class: 9\n",
+ "Test 100 Prediction: 6 True Class: 6\n",
+ "Test 101 Prediction: 0 True Class: 0\n",
+ "Test 102 Prediction: 5 True Class: 5\n",
+ "Test 103 Prediction: 4 True Class: 4\n",
+ "Test 104 Prediction: 9 True Class: 9\n",
+ "Test 105 Prediction: 9 True Class: 9\n",
+ "Test 106 Prediction: 2 True Class: 2\n",
+ "Test 107 Prediction: 1 True Class: 1\n",
+ "Test 108 Prediction: 9 True Class: 9\n",
+ "Test 109 Prediction: 4 True Class: 4\n",
+ "Test 110 Prediction: 8 True Class: 8\n",
+ "Test 111 Prediction: 7 True Class: 7\n",
+ "Test 112 Prediction: 3 True Class: 3\n",
+ "Test 113 Prediction: 9 True Class: 9\n",
+ "Test 114 Prediction: 7 True Class: 7\n",
+ "Test 115 Prediction: 9 True Class: 4\n",
+ "Test 116 Prediction: 9 True Class: 4\n",
+ "Test 117 Prediction: 4 True Class: 4\n",
+ "Test 118 Prediction: 9 True Class: 9\n",
+ "Test 119 Prediction: 7 True Class: 2\n",
+ "Test 120 Prediction: 5 True Class: 5\n",
+ "Test 121 Prediction: 4 True Class: 4\n",
+ "Test 122 Prediction: 7 True Class: 7\n",
+ "Test 123 Prediction: 6 True Class: 6\n",
+ "Test 124 Prediction: 7 True Class: 7\n",
+ "Test 125 Prediction: 9 True Class: 9\n",
+ "Test 126 Prediction: 0 True Class: 0\n",
+ "Test 127 Prediction: 5 True Class: 5\n",
+ "Test 128 Prediction: 8 True Class: 8\n",
+ "Test 129 Prediction: 5 True Class: 5\n",
+ "Test 130 Prediction: 6 True Class: 6\n",
+ "Test 131 Prediction: 6 True Class: 6\n",
+ "Test 132 Prediction: 5 True Class: 5\n",
+ "Test 133 Prediction: 7 True Class: 7\n",
+ "Test 134 Prediction: 8 True Class: 8\n",
+ "Test 135 Prediction: 1 True Class: 1\n",
+ "Test 136 Prediction: 0 True Class: 0\n",
+ "Test 137 Prediction: 1 True Class: 1\n",
+ "Test 138 Prediction: 6 True Class: 6\n",
+ "Test 139 Prediction: 4 True Class: 4\n",
+ "Test 140 Prediction: 6 True Class: 6\n",
+ "Test 141 Prediction: 7 True Class: 7\n",
+ "Test 142 Prediction: 2 True Class: 3\n",
+ "Test 143 Prediction: 1 True Class: 1\n",
+ "Test 144 Prediction: 7 True Class: 7\n",
+ "Test 145 Prediction: 1 True Class: 1\n",
+ "Test 146 Prediction: 8 True Class: 8\n",
+ "Test 147 Prediction: 2 True Class: 2\n",
+ "Test 148 Prediction: 0 True Class: 0\n",
+ "Test 149 Prediction: 1 True Class: 2\n",
+ "Test 150 Prediction: 9 True Class: 9\n",
+ "Test 151 Prediction: 9 True Class: 9\n",
+ "Test 152 Prediction: 5 True Class: 5\n",
+ "Test 153 Prediction: 5 True Class: 5\n",
+ "Test 154 Prediction: 1 True Class: 1\n",
+ "Test 155 Prediction: 5 True Class: 5\n",
+ "Test 156 Prediction: 6 True Class: 6\n",
+ "Test 157 Prediction: 0 True Class: 0\n",
+ "Test 158 Prediction: 3 True Class: 3\n",
+ "Test 159 Prediction: 4 True Class: 4\n",
+ "Test 160 Prediction: 4 True Class: 4\n",
+ "Test 161 Prediction: 6 True Class: 6\n",
+ "Test 162 Prediction: 5 True Class: 5\n",
+ "Test 163 Prediction: 4 True Class: 4\n",
+ "Test 164 Prediction: 6 True Class: 6\n",
+ "Test 165 Prediction: 5 True Class: 5\n",
+ "Test 166 Prediction: 4 True Class: 4\n",
+ "Test 167 Prediction: 5 True Class: 5\n",
+ "Test 168 Prediction: 1 True Class: 1\n",
+ "Test 169 Prediction: 4 True Class: 4\n",
+ "Test 170 Prediction: 9 True Class: 4\n",
+ "Test 171 Prediction: 7 True Class: 7\n",
+ "Test 172 Prediction: 2 True Class: 2\n",
+ "Test 173 Prediction: 3 True Class: 3\n",
+ "Test 174 Prediction: 2 True Class: 2\n",
+ "Test 175 Prediction: 1 True Class: 7\n",
+ "Test 176 Prediction: 1 True Class: 1\n",
+ "Test 177 Prediction: 8 True Class: 8\n",
+ "Test 178 Prediction: 1 True Class: 1\n",
+ "Test 179 Prediction: 8 True Class: 8\n",
+ "Test 180 Prediction: 1 True Class: 1\n",
+ "Test 181 Prediction: 8 True Class: 8\n",
+ "Test 182 Prediction: 5 True Class: 5\n",
+ "Test 183 Prediction: 0 True Class: 0\n",
+ "Test 184 Prediction: 2 True Class: 8\n",
+ "Test 185 Prediction: 9 True Class: 9\n",
+ "Test 186 Prediction: 2 True Class: 2\n",
+ "Test 187 Prediction: 5 True Class: 5\n",
+ "Test 188 Prediction: 0 True Class: 0\n",
+ "Test 189 Prediction: 1 True Class: 1\n",
+ "Test 190 Prediction: 1 True Class: 1\n",
+ "Test 191 Prediction: 1 True Class: 1\n",
+ "Test 192 Prediction: 0 True Class: 0\n",
+ "Test 193 Prediction: 4 True Class: 9\n",
+ "Test 194 Prediction: 0 True Class: 0\n",
+ "Test 195 Prediction: 1 True Class: 3\n",
+ "Test 196 Prediction: 1 True Class: 1\n",
+ "Test 197 Prediction: 6 True Class: 6\n",
+ "Test 198 Prediction: 4 True Class: 4\n",
+ "Test 199 Prediction: 2 True Class: 2\n",
+ "Done!\n",
+ "Accuracy: 0.92\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start training\n",
+ "with tf.Session() as sess:\n",
+ " sess.run(init)\n",
+ "\n",
+ " # loop over test data\n",
+ " for i in range(len(Xte)):\n",
+ " # Get nearest neighbor\n",
+ " nn_index = sess.run(pred, feed_dict={xtr: Xtr, xte: Xte[i, :]})\n",
+ " # Get nearest neighbor class label and compare it to its true label\n",
+ " print \"Test\", i, \"Prediction:\", np.argmax(Ytr[nn_index]), \\\n",
+ " \"True Class:\", np.argmax(Yte[i])\n",
+ " # Calculate accuracy\n",
+ " if np.argmax(Ytr[nn_index]) == np.argmax(Yte[i]):\n",
+ " accuracy += 1./len(Xte)\n",
+ " print \"Done!\"\n",
+ " print \"Accuracy:\", accuracy"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/2_BasicModels/random_forest.ipynb b/tensorflow_v1/notebooks/2_BasicModels/random_forest.ipynb
new file mode 100644
index 00000000..a3c26f4a
--- /dev/null
+++ b/tensorflow_v1/notebooks/2_BasicModels/random_forest.ipynb
@@ -0,0 +1,229 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Random Forest Example\n",
+ "\n",
+ "Implement Random Forest algorithm with TensorFlow, and apply it to classify \n",
+ "handwritten digit images. This example is using the MNIST database of \n",
+ "handwritten digits as training samples (http://yann.lecun.com/exdb/mnist/).\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "from tensorflow.python.ops import resources\n",
+ "from tensorflow.contrib.tensor_forest.python import tensor_forest\n",
+ "\n",
+ "# Ignore all GPUs, tf random forest does not benefit from it.\n",
+ "import os\n",
+ "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\""
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.\n",
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=False)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "num_steps = 500 # Total steps to train\n",
+ "batch_size = 1024 # The number of samples per batch\n",
+ "num_classes = 10 # The 10 digits\n",
+ "num_features = 784 # Each image is 28x28 pixels\n",
+ "num_trees = 10\n",
+ "max_nodes = 1000\n",
+ "\n",
+ "# Input and Target data\n",
+ "X = tf.placeholder(tf.float32, shape=[None, num_features])\n",
+ "# For random forest, labels must be integers (the class id)\n",
+ "Y = tf.placeholder(tf.int32, shape=[None])\n",
+ "\n",
+ "# Random Forest Parameters\n",
+ "hparams = tensor_forest.ForestHParams(num_classes=num_classes,\n",
+ " num_features=num_features,\n",
+ " num_trees=num_trees,\n",
+ " max_nodes=max_nodes).fill()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Constructing forest with params = \n",
+ "INFO:tensorflow:{'valid_leaf_threshold': 1, 'split_after_samples': 250, 'num_output_columns': 11, 'feature_bagging_fraction': 1.0, 'split_initializations_per_input': 3, 'bagged_features': None, 'min_split_samples': 5, 'max_nodes': 1000, 'num_features': 784, 'num_trees': 10, 'num_splits_to_consider': 784, 'base_random_seed': 0, 'num_outputs': 1, 'dominate_fraction': 0.99, 'max_fertile_nodes': 500, 'bagged_num_features': 784, 'dominate_method': 'bootstrap', 'bagging_fraction': 1.0, 'regression': False, 'num_classes': 10}\n",
+ "INFO:tensorflow:training graph for tree: 0\n",
+ "INFO:tensorflow:training graph for tree: 1\n",
+ "INFO:tensorflow:training graph for tree: 2\n",
+ "INFO:tensorflow:training graph for tree: 3\n",
+ "INFO:tensorflow:training graph for tree: 4\n",
+ "INFO:tensorflow:training graph for tree: 5\n",
+ "INFO:tensorflow:training graph for tree: 6\n",
+ "INFO:tensorflow:training graph for tree: 7\n",
+ "INFO:tensorflow:training graph for tree: 8\n",
+ "INFO:tensorflow:training graph for tree: 9\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Build the Random Forest\n",
+ "forest_graph = tensor_forest.RandomForestGraphs(hparams)\n",
+ "# Get training graph and loss\n",
+ "train_op = forest_graph.training_graph(X, Y)\n",
+ "loss_op = forest_graph.training_loss(X, Y)\n",
+ "\n",
+ "# Measure the accuracy\n",
+ "infer_op, _, _ = forest_graph.inference_graph(X)\n",
+ "correct_prediction = tf.equal(tf.argmax(infer_op, 1), tf.cast(Y, tf.int64))\n",
+ "accuracy_op = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value) and forest resources\n",
+ "init_vars = tf.group(tf.global_variables_initializer(),\n",
+ " resources.initialize_resources(resources.shared_resources()))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1, Loss: -0.000000, Acc: 0.112305\n",
+ "Step 50, Loss: -123.800003, Acc: 0.863281\n",
+ "Step 100, Loss: -274.200012, Acc: 0.863281\n",
+ "Step 150, Loss: -425.399994, Acc: 0.872070\n",
+ "Step 200, Loss: -582.799988, Acc: 0.917969\n",
+ "Step 250, Loss: -740.200012, Acc: 0.912109\n",
+ "Step 300, Loss: -895.799988, Acc: 0.939453\n",
+ "Step 350, Loss: -998.000000, Acc: 0.924805\n",
+ "Step 400, Loss: -998.000000, Acc: 0.940430\n",
+ "Step 450, Loss: -998.000000, Acc: 0.914062\n",
+ "Step 500, Loss: -998.000000, Acc: 0.927734\n",
+ "Test Accuracy: 0.9204\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start TensorFlow session\n",
+ "sess = tf.train.MonitoredSession()\n",
+ "\n",
+ "# Run the initializer\n",
+ "sess.run(init_vars)\n",
+ "\n",
+ "# Training\n",
+ "for i in range(1, num_steps + 1):\n",
+ " # Prepare Data\n",
+ " # Get the next batch of MNIST data (only images are needed, not labels)\n",
+ " batch_x, batch_y = mnist.train.next_batch(batch_size)\n",
+ " _, l = sess.run([train_op, loss_op], feed_dict={X: batch_x, Y: batch_y})\n",
+ " if i % 50 == 0 or i == 1:\n",
+ " acc = sess.run(accuracy_op, feed_dict={X: batch_x, Y: batch_y})\n",
+ " print('Step %i, Loss: %f, Acc: %f' % (i, l, acc))\n",
+ "\n",
+ "# Test Model\n",
+ "test_x, test_y = mnist.test.images, mnist.test.labels\n",
+ "print(\"Test Accuracy:\", sess.run(accuracy_op, feed_dict={X: test_x, Y: test_y}))"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ },
+ "varInspector": {
+ "cols": {
+ "lenName": 16.0,
+ "lenType": 16.0,
+ "lenVar": 40.0
+ },
+ "kernels_config": {
+ "python": {
+ "delete_cmd_postfix": "",
+ "delete_cmd_prefix": "del ",
+ "library": "var_list.py",
+ "varRefreshCmd": "print(var_dic_list())"
+ },
+ "r": {
+ "delete_cmd_postfix": ") ",
+ "delete_cmd_prefix": "rm(",
+ "library": "var_list.r",
+ "varRefreshCmd": "cat(var_dic_list()) "
+ }
+ },
+ "types_to_exclude": [
+ "module",
+ "function",
+ "builtin_function_or_method",
+ "instance",
+ "_Feature"
+ ],
+ "window_display": false
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/2_BasicModels/word2vec.ipynb b/tensorflow_v1/notebooks/2_BasicModels/word2vec.ipynb
new file mode 100644
index 00000000..c96b1ba9
--- /dev/null
+++ b/tensorflow_v1/notebooks/2_BasicModels/word2vec.ipynb
@@ -0,0 +1,724 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Word2Vec (Word Embedding)\n",
+ "\n",
+ "Implement Word2Vec algorithm to compute vector representations of words.\n",
+ "This example is using a small chunk of Wikipedia articles to train from.\n",
+ "\n",
+ "More info: [Mikolov, Tomas et al. \"Efficient Estimation of Word Representations in Vector Space.\", 2013](https://arxiv.org/pdf/1301.3781.pdf)\n",
+ "\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import division, print_function, absolute_import\n",
+ "\n",
+ "import collections\n",
+ "import os\n",
+ "import random\n",
+ "import urllib\n",
+ "import zipfile\n",
+ "\n",
+ "import numpy as np\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Training Parameters\n",
+ "learning_rate = 0.1\n",
+ "batch_size = 128\n",
+ "num_steps = 3000000\n",
+ "display_step = 10000\n",
+ "eval_step = 200000\n",
+ "\n",
+ "# Evaluation Parameters\n",
+ "eval_words = ['five', 'of', 'going', 'hardware', 'american', 'britain']\n",
+ "\n",
+ "# Word2Vec Parameters\n",
+ "embedding_size = 200 # Dimension of the embedding vector\n",
+ "max_vocabulary_size = 50000 # Total number of different words in the vocabulary\n",
+ "min_occurrence = 10 # Remove all words that does not appears at least n times\n",
+ "skip_window = 3 # How many words to consider left and right\n",
+ "num_skips = 2 # How many times to reuse an input to generate a label\n",
+ "num_sampled = 64 # Number of negative examples to sample"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Downloading the dataset... (It may take some time)\n",
+ "Done!\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Download a small chunk of Wikipedia articles collection\n",
+ "url = 'http://mattmahoney.net/dc/text8.zip'\n",
+ "data_path = 'text8.zip'\n",
+ "if not os.path.exists(data_path):\n",
+ " print(\"Downloading the dataset... (It may take some time)\")\n",
+ " filename, _ = urllib.urlretrieve(url, data_path)\n",
+ " print(\"Done!\")\n",
+ "# Unzip the dataset file. Text has already been processed\n",
+ "with zipfile.ZipFile(data_path) as f:\n",
+ " text_words = f.read(f.namelist()[0]).lower().split()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Words count: 17005207\n",
+ "Unique words: 253854\n",
+ "Vocabulary size: 50000\n",
+ "Most common words: [('UNK', 418391), ('the', 1061396), ('of', 593677), ('and', 416629), ('one', 411764), ('in', 372201), ('a', 325873), ('to', 316376), ('zero', 264975), ('nine', 250430)]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Build the dictionary and replace rare words with UNK token\n",
+ "count = [('UNK', -1)]\n",
+ "# Retrieve the most common words\n",
+ "count.extend(collections.Counter(text_words).most_common(max_vocabulary_size - 1))\n",
+ "# Remove samples with less than 'min_occurrence' occurrences\n",
+ "for i in range(len(count) - 1, -1, -1):\n",
+ " if count[i][1] < min_occurrence:\n",
+ " count.pop(i)\n",
+ " else:\n",
+ " # The collection is ordered, so stop when 'min_occurrence' is reached\n",
+ " break\n",
+ "# Compute the vocabulary size\n",
+ "vocabulary_size = len(count)\n",
+ "# Assign an id to each word\n",
+ "word2id = dict()\n",
+ "for i, (word, _)in enumerate(count):\n",
+ " word2id[word] = i\n",
+ "\n",
+ "data = list()\n",
+ "unk_count = 0\n",
+ "for word in text_words:\n",
+ " # Retrieve a word id, or assign it index 0 ('UNK') if not in dictionary\n",
+ " index = word2id.get(word, 0)\n",
+ " if index == 0:\n",
+ " unk_count += 1\n",
+ " data.append(index)\n",
+ "count[0] = ('UNK', unk_count)\n",
+ "id2word = dict(zip(word2id.values(), word2id.keys()))\n",
+ "\n",
+ "print(\"Words count:\", len(text_words))\n",
+ "print(\"Unique words:\", len(set(text_words)))\n",
+ "print(\"Vocabulary size:\", vocabulary_size)\n",
+ "print(\"Most common words:\", count[:10])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "data_index = 0\n",
+ "# Generate training batch for the skip-gram model\n",
+ "def next_batch(batch_size, num_skips, skip_window):\n",
+ " global data_index\n",
+ " assert batch_size % num_skips == 0\n",
+ " assert num_skips <= 2 * skip_window\n",
+ " batch = np.ndarray(shape=(batch_size), dtype=np.int32)\n",
+ " labels = np.ndarray(shape=(batch_size, 1), dtype=np.int32)\n",
+ " # get window size (words left and right + current one)\n",
+ " span = 2 * skip_window + 1\n",
+ " buffer = collections.deque(maxlen=span)\n",
+ " if data_index + span > len(data):\n",
+ " data_index = 0\n",
+ " buffer.extend(data[data_index:data_index + span])\n",
+ " data_index += span\n",
+ " for i in range(batch_size // num_skips):\n",
+ " context_words = [w for w in range(span) if w != skip_window]\n",
+ " words_to_use = random.sample(context_words, num_skips)\n",
+ " for j, context_word in enumerate(words_to_use):\n",
+ " batch[i * num_skips + j] = buffer[skip_window]\n",
+ " labels[i * num_skips + j, 0] = buffer[context_word]\n",
+ " if data_index == len(data):\n",
+ " buffer.extend(data[0:span])\n",
+ " data_index = span\n",
+ " else:\n",
+ " buffer.append(data[data_index])\n",
+ " data_index += 1\n",
+ " # Backtrack a little bit to avoid skipping words in the end of a batch\n",
+ " data_index = (data_index + len(data) - span) % len(data)\n",
+ " return batch, labels"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Input data\n",
+ "X = tf.placeholder(tf.int32, shape=[None])\n",
+ "# Input label\n",
+ "Y = tf.placeholder(tf.int32, shape=[None, 1])\n",
+ "\n",
+ "# Ensure the following ops & var are assigned on CPU\n",
+ "# (some ops are not compatible on GPU)\n",
+ "with tf.device('/cpu:0'):\n",
+ " # Create the embedding variable (each row represent a word embedding vector)\n",
+ " embedding = tf.Variable(tf.random_normal([vocabulary_size, embedding_size]))\n",
+ " # Lookup the corresponding embedding vectors for each sample in X\n",
+ " X_embed = tf.nn.embedding_lookup(embedding, X)\n",
+ "\n",
+ " # Construct the variables for the NCE loss\n",
+ " nce_weights = tf.Variable(tf.random_normal([vocabulary_size, embedding_size]))\n",
+ " nce_biases = tf.Variable(tf.zeros([vocabulary_size]))\n",
+ "\n",
+ "# Compute the average NCE loss for the batch\n",
+ "loss_op = tf.reduce_mean(\n",
+ " tf.nn.nce_loss(weights=nce_weights,\n",
+ " biases=nce_biases,\n",
+ " labels=Y,\n",
+ " inputs=X_embed,\n",
+ " num_sampled=num_sampled,\n",
+ " num_classes=vocabulary_size))\n",
+ "\n",
+ "# Define the optimizer\n",
+ "optimizer = tf.train.GradientDescentOptimizer(learning_rate)\n",
+ "train_op = optimizer.minimize(loss_op)\n",
+ "\n",
+ "# Evaluation\n",
+ "# Compute the cosine similarity between input data embedding and every embedding vectors\n",
+ "X_embed_norm = X_embed / tf.sqrt(tf.reduce_sum(tf.square(X_embed)))\n",
+ "embedding_norm = embedding / tf.sqrt(tf.reduce_sum(tf.square(embedding), 1, keepdims=True))\n",
+ "cosine_sim_op = tf.matmul(X_embed_norm, embedding_norm, transpose_b=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1, Average Loss= 520.3188\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: brothers, swinging, dissemination, fruitful, trichloride, dll, timur, torre,\n",
+ "\"of\" nearest neighbors: malting, vaginal, cecil, xiaoping, arrangers, hydras, exhibits, splits,\n",
+ "\"going\" nearest neighbors: besht, xps, sdtv, mississippi, frequencies, tora, reciprocating, tursiops,\n",
+ "\"hardware\" nearest neighbors: burgh, residences, mares, attested, whirlwind, isomerism, admiration, ties,\n",
+ "\"american\" nearest neighbors: tensile, months, baffling, cricket, kodak, risky, nicomedia, jura,\n",
+ "\"britain\" nearest neighbors: superstring, interpretations, genealogical, munition, boer, occasional, psychologists, turbofan,\n",
+ "Step 10000, Average Loss= 202.2640\n",
+ "Step 20000, Average Loss= 96.5149\n",
+ "Step 30000, Average Loss= 67.2858\n",
+ "Step 40000, Average Loss= 52.5055\n",
+ "Step 50000, Average Loss= 42.6301\n",
+ "Step 60000, Average Loss= 37.3644\n",
+ "Step 70000, Average Loss= 33.1220\n",
+ "Step 80000, Average Loss= 30.5835\n",
+ "Step 90000, Average Loss= 28.2243\n",
+ "Step 100000, Average Loss= 25.5532\n",
+ "Step 110000, Average Loss= 24.0891\n",
+ "Step 120000, Average Loss= 21.8576\n",
+ "Step 130000, Average Loss= 21.2192\n",
+ "Step 140000, Average Loss= 19.8834\n",
+ "Step 150000, Average Loss= 19.3362\n",
+ "Step 160000, Average Loss= 18.3129\n",
+ "Step 170000, Average Loss= 17.4952\n",
+ "Step 180000, Average Loss= 16.8531\n",
+ "Step 190000, Average Loss= 15.9615\n",
+ "Step 200000, Average Loss= 15.0718\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, eight, six, seven, two, nine, one,\n",
+ "\"of\" nearest neighbors: the, is, a, was, with, in, and, on,\n",
+ "\"going\" nearest neighbors: time, military, called, with, used, state, most, new,\n",
+ "\"hardware\" nearest neighbors: deaths, system, three, at, zero, two, s, UNK,\n",
+ "\"american\" nearest neighbors: UNK, and, s, about, in, when, from, after,\n",
+ "\"britain\" nearest neighbors: years, were, from, both, of, these, is, many,\n",
+ "Step 210000, Average Loss= 14.9267\n",
+ "Step 220000, Average Loss= 15.4700\n",
+ "Step 230000, Average Loss= 14.0867\n",
+ "Step 240000, Average Loss= 14.5337\n",
+ "Step 250000, Average Loss= 13.2458\n",
+ "Step 260000, Average Loss= 13.2944\n",
+ "Step 270000, Average Loss= 13.0396\n",
+ "Step 280000, Average Loss= 12.1902\n",
+ "Step 290000, Average Loss= 11.7444\n",
+ "Step 300000, Average Loss= 11.8473\n",
+ "Step 310000, Average Loss= 11.1306\n",
+ "Step 320000, Average Loss= 11.1699\n",
+ "Step 330000, Average Loss= 10.8638\n",
+ "Step 340000, Average Loss= 10.7910\n",
+ "Step 350000, Average Loss= 11.0721\n",
+ "Step 360000, Average Loss= 10.6309\n",
+ "Step 370000, Average Loss= 10.4836\n",
+ "Step 380000, Average Loss= 10.3482\n",
+ "Step 390000, Average Loss= 10.0679\n",
+ "Step 400000, Average Loss= 10.0070\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, seven, eight, two, one, zero,\n",
+ "\"of\" nearest neighbors: and, in, the, a, for, by, is, while,\n",
+ "\"going\" nearest neighbors: name, called, made, military, music, people, city, was,\n",
+ "\"hardware\" nearest neighbors: power, a, john, the, has, see, and, system,\n",
+ "\"american\" nearest neighbors: s, british, UNK, john, in, during, and, from,\n",
+ "\"britain\" nearest neighbors: from, general, are, before, first, after, history, was,\n",
+ "Step 410000, Average Loss= 10.1151\n",
+ "Step 420000, Average Loss= 9.5719\n",
+ "Step 430000, Average Loss= 9.8267\n",
+ "Step 440000, Average Loss= 9.4704\n",
+ "Step 450000, Average Loss= 9.5561\n",
+ "Step 460000, Average Loss= 9.1479\n",
+ "Step 470000, Average Loss= 8.8914\n",
+ "Step 480000, Average Loss= 9.0281\n",
+ "Step 490000, Average Loss= 9.3139\n",
+ "Step 500000, Average Loss= 9.1559\n",
+ "Step 510000, Average Loss= 8.8257\n",
+ "Step 520000, Average Loss= 8.9081\n",
+ "Step 530000, Average Loss= 8.8572\n",
+ "Step 540000, Average Loss= 8.5835\n",
+ "Step 550000, Average Loss= 8.4495\n",
+ "Step 560000, Average Loss= 8.4193\n",
+ "Step 570000, Average Loss= 8.3399\n",
+ "Step 580000, Average Loss= 8.1633\n",
+ "Step 590000, Average Loss= 8.2914\n",
+ "Step 600000, Average Loss= 8.0268\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, six, two, seven, eight, one, zero,\n",
+ "\"of\" nearest neighbors: and, the, in, including, with, for, on, or,\n",
+ "\"going\" nearest neighbors: popular, king, his, music, and, time, name, being,\n",
+ "\"hardware\" nearest neighbors: power, over, then, than, became, at, less, for,\n",
+ "\"american\" nearest neighbors: english, s, german, in, french, since, john, between,\n",
+ "\"britain\" nearest neighbors: however, were, state, first, group, general, from, second,\n",
+ "Step 610000, Average Loss= 8.1733\n",
+ "Step 620000, Average Loss= 8.2522\n",
+ "Step 630000, Average Loss= 8.0434\n",
+ "Step 640000, Average Loss= 8.0930\n",
+ "Step 650000, Average Loss= 7.8770\n",
+ "Step 660000, Average Loss= 7.9221\n",
+ "Step 670000, Average Loss= 7.7645\n",
+ "Step 680000, Average Loss= 7.9534\n",
+ "Step 690000, Average Loss= 7.7507\n",
+ "Step 700000, Average Loss= 7.7499\n",
+ "Step 710000, Average Loss= 7.6629\n",
+ "Step 720000, Average Loss= 7.6055\n",
+ "Step 730000, Average Loss= 7.4779\n",
+ "Step 740000, Average Loss= 7.3182\n",
+ "Step 750000, Average Loss= 7.6399\n",
+ "Step 760000, Average Loss= 7.4364\n",
+ "Step 770000, Average Loss= 7.6509\n",
+ "Step 780000, Average Loss= 7.3204\n",
+ "Step 790000, Average Loss= 7.4101\n",
+ "Step 800000, Average Loss= 7.4354\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, six, seven, eight, two, one, nine,\n",
+ "\"of\" nearest neighbors: and, the, its, a, with, at, in, for,\n",
+ "\"going\" nearest neighbors: were, man, music, now, great, support, popular, her,\n",
+ "\"hardware\" nearest neighbors: power, system, then, military, high, against, since, international,\n",
+ "\"american\" nearest neighbors: english, british, born, b, john, french, d, german,\n",
+ "\"britain\" nearest neighbors: government, second, before, from, state, several, the, at,\n",
+ "Step 810000, Average Loss= 7.2603\n",
+ "Step 820000, Average Loss= 7.1646\n",
+ "Step 830000, Average Loss= 7.3155\n",
+ "Step 840000, Average Loss= 7.1274\n",
+ "Step 850000, Average Loss= 7.1237\n",
+ "Step 860000, Average Loss= 7.1528\n",
+ "Step 870000, Average Loss= 7.0673\n",
+ "Step 880000, Average Loss= 7.2167\n",
+ "Step 890000, Average Loss= 7.1359\n",
+ "Step 900000, Average Loss= 7.0940\n",
+ "Step 910000, Average Loss= 7.1114\n",
+ "Step 920000, Average Loss= 6.9328\n",
+ "Step 930000, Average Loss= 7.0108\n",
+ "Step 940000, Average Loss= 7.0630\n",
+ "Step 950000, Average Loss= 6.8371\n",
+ "Step 960000, Average Loss= 7.0466\n",
+ "Step 970000, Average Loss= 6.8331\n",
+ "Step 980000, Average Loss= 6.9670\n",
+ "Step 990000, Average Loss= 6.7357\n",
+ "Step 1000000, Average Loss= 6.6453\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, eight, seven, two, nine, zero,\n",
+ "\"of\" nearest neighbors: the, became, including, first, second, from, following, and,\n",
+ "\"going\" nearest neighbors: near, music, popular, made, while, his, works, most,\n",
+ "\"hardware\" nearest neighbors: power, system, before, its, using, for, thus, an,\n",
+ "\"american\" nearest neighbors: b, born, d, UNK, nine, john, english, seven,\n",
+ "\"britain\" nearest neighbors: of, following, government, home, from, state, end, several,\n",
+ "Step 1010000, Average Loss= 6.7193\n",
+ "Step 1020000, Average Loss= 6.9297\n",
+ "Step 1030000, Average Loss= 6.7905\n",
+ "Step 1040000, Average Loss= 6.7709\n",
+ "Step 1050000, Average Loss= 6.7337\n",
+ "Step 1060000, Average Loss= 6.7617\n",
+ "Step 1070000, Average Loss= 6.7489\n",
+ "Step 1080000, Average Loss= 6.6259\n",
+ "Step 1090000, Average Loss= 6.6415\n",
+ "Step 1100000, Average Loss= 6.7209\n",
+ "Step 1110000, Average Loss= 6.5471\n",
+ "Step 1120000, Average Loss= 6.6508\n",
+ "Step 1130000, Average Loss= 6.5184\n",
+ "Step 1140000, Average Loss= 6.6202\n",
+ "Step 1150000, Average Loss= 6.7205\n",
+ "Step 1160000, Average Loss= 6.5821\n",
+ "Step 1170000, Average Loss= 6.6200\n",
+ "Step 1180000, Average Loss= 6.5089\n",
+ "Step 1190000, Average Loss= 6.5587\n",
+ "Step 1200000, Average Loss= 6.4930\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, six, seven, eight, two, nine, zero,\n",
+ "\"of\" nearest neighbors: the, and, including, in, first, with, following, from,\n",
+ "\"going\" nearest neighbors: near, popular, works, today, large, now, when, both,\n",
+ "\"hardware\" nearest neighbors: power, system, computer, its, both, for, using, which,\n",
+ "\"american\" nearest neighbors: born, d, john, german, b, UNK, english, s,\n",
+ "\"britain\" nearest neighbors: state, following, government, home, became, people, were, the,\n",
+ "Step 1210000, Average Loss= 6.5985\n",
+ "Step 1220000, Average Loss= 6.4534\n",
+ "Step 1230000, Average Loss= 6.5083\n",
+ "Step 1240000, Average Loss= 6.4913\n",
+ "Step 1250000, Average Loss= 6.4326\n",
+ "Step 1260000, Average Loss= 6.3891\n",
+ "Step 1270000, Average Loss= 6.1601\n",
+ "Step 1280000, Average Loss= 6.4479\n",
+ "Step 1290000, Average Loss= 6.3813\n",
+ "Step 1300000, Average Loss= 6.5335\n",
+ "Step 1310000, Average Loss= 6.2971\n",
+ "Step 1320000, Average Loss= 6.3723\n",
+ "Step 1330000, Average Loss= 6.4234\n",
+ "Step 1340000, Average Loss= 6.3130\n",
+ "Step 1350000, Average Loss= 6.2867\n",
+ "Step 1360000, Average Loss= 6.3505\n",
+ "Step 1370000, Average Loss= 6.2990\n",
+ "Step 1380000, Average Loss= 6.3012\n",
+ "Step 1390000, Average Loss= 6.3112\n",
+ "Step 1400000, Average Loss= 6.2680\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, two, seven, eight, one, zero,\n",
+ "\"of\" nearest neighbors: the, its, and, including, in, with, see, for,\n",
+ "\"going\" nearest neighbors: near, great, like, today, began, called, an, another,\n",
+ "\"hardware\" nearest neighbors: power, computer, system, for, program, high, control, small,\n",
+ "\"american\" nearest neighbors: english, german, french, born, john, british, s, references,\n",
+ "\"britain\" nearest neighbors: state, great, government, people, following, became, along, home,\n",
+ "Step 1410000, Average Loss= 6.3157\n",
+ "Step 1420000, Average Loss= 6.3466\n",
+ "Step 1430000, Average Loss= 6.3090\n",
+ "Step 1440000, Average Loss= 6.3330\n",
+ "Step 1450000, Average Loss= 6.2072\n",
+ "Step 1460000, Average Loss= 6.2363\n",
+ "Step 1470000, Average Loss= 6.2736\n",
+ "Step 1480000, Average Loss= 6.1793\n",
+ "Step 1490000, Average Loss= 6.2977\n",
+ "Step 1500000, Average Loss= 6.1899\n",
+ "Step 1510000, Average Loss= 6.2381\n",
+ "Step 1520000, Average Loss= 6.1027\n",
+ "Step 1530000, Average Loss= 6.0046\n",
+ "Step 1540000, Average Loss= 6.0747\n",
+ "Step 1550000, Average Loss= 6.2524\n",
+ "Step 1560000, Average Loss= 6.1247\n",
+ "Step 1570000, Average Loss= 6.1937\n",
+ "Step 1580000, Average Loss= 6.0450\n",
+ "Step 1590000, Average Loss= 6.1556\n",
+ "Step 1600000, Average Loss= 6.1765\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, six, two, seven, eight, one, zero,\n",
+ "\"of\" nearest neighbors: the, and, its, for, from, modern, in, part,\n",
+ "\"going\" nearest neighbors: great, today, once, now, while, her, like, by,\n",
+ "\"hardware\" nearest neighbors: power, system, high, program, control, computer, typically, making,\n",
+ "\"american\" nearest neighbors: born, english, british, german, john, french, b, d,\n",
+ "\"britain\" nearest neighbors: country, state, home, government, first, following, during, from,\n",
+ "Step 1610000, Average Loss= 6.1029\n",
+ "Step 1620000, Average Loss= 6.0501\n",
+ "Step 1630000, Average Loss= 6.1536\n",
+ "Step 1640000, Average Loss= 6.0483\n",
+ "Step 1650000, Average Loss= 6.1197\n",
+ "Step 1660000, Average Loss= 6.0261\n",
+ "Step 1670000, Average Loss= 6.1012\n",
+ "Step 1680000, Average Loss= 6.1795\n",
+ "Step 1690000, Average Loss= 6.1224\n",
+ "Step 1700000, Average Loss= 6.0896\n",
+ "Step 1710000, Average Loss= 6.0418\n",
+ "Step 1720000, Average Loss= 6.0626\n",
+ "Step 1730000, Average Loss= 6.0214\n",
+ "Step 1740000, Average Loss= 6.1206\n",
+ "Step 1750000, Average Loss= 5.9721\n",
+ "Step 1760000, Average Loss= 6.0782\n",
+ "Step 1770000, Average Loss= 6.0291\n",
+ "Step 1780000, Average Loss= 6.0187\n",
+ "Step 1790000, Average Loss= 5.9761\n",
+ "Step 1800000, Average Loss= 5.7518\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, seven, eight, nine, two, zero,\n",
+ "\"of\" nearest neighbors: the, from, in, became, and, second, first, including,\n",
+ "\"going\" nearest neighbors: today, which, once, little, made, before, now, etc,\n",
+ "\"hardware\" nearest neighbors: computer, power, program, system, high, typically, current, eventually,\n",
+ "\"american\" nearest neighbors: b, d, born, actor, UNK, robert, william, english,\n",
+ "\"britain\" nearest neighbors: government, state, country, from, world, great, of, in,\n",
+ "Step 1810000, Average Loss= 5.9839\n",
+ "Step 1820000, Average Loss= 5.9931\n",
+ "Step 1830000, Average Loss= 6.0794\n",
+ "Step 1840000, Average Loss= 5.9072\n",
+ "Step 1850000, Average Loss= 5.9831\n",
+ "Step 1860000, Average Loss= 6.0023\n",
+ "Step 1870000, Average Loss= 5.9375\n",
+ "Step 1880000, Average Loss= 5.9250\n",
+ "Step 1890000, Average Loss= 5.9422\n",
+ "Step 1900000, Average Loss= 5.9339\n",
+ "Step 1910000, Average Loss= 5.9235\n",
+ "Step 1920000, Average Loss= 5.9692\n",
+ "Step 1930000, Average Loss= 5.9022\n",
+ "Step 1940000, Average Loss= 5.9599\n",
+ "Step 1950000, Average Loss= 6.0174\n",
+ "Step 1960000, Average Loss= 5.9530\n",
+ "Step 1970000, Average Loss= 5.9479\n",
+ "Step 1980000, Average Loss= 5.8870\n",
+ "Step 1990000, Average Loss= 5.9271\n",
+ "Step 2000000, Average Loss= 5.8774\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, seven, eight, two, nine, zero,\n",
+ "\"of\" nearest neighbors: and, the, from, in, within, first, including, with,\n",
+ "\"going\" nearest neighbors: today, before, another, little, work, etc, now, him,\n",
+ "\"hardware\" nearest neighbors: computer, program, system, both, making, designed, power, simple,\n",
+ "\"american\" nearest neighbors: actor, born, d, robert, john, b, german, writer,\n",
+ "\"britain\" nearest neighbors: government, state, following, great, england, became, country, from,\n",
+ "Step 2010000, Average Loss= 5.9373\n",
+ "Step 2020000, Average Loss= 5.9113\n",
+ "Step 2030000, Average Loss= 5.9158\n",
+ "Step 2040000, Average Loss= 5.9020\n",
+ "Step 2050000, Average Loss= 5.8608\n",
+ "Step 2060000, Average Loss= 5.7379\n",
+ "Step 2070000, Average Loss= 5.7143\n",
+ "Step 2080000, Average Loss= 5.9379\n",
+ "Step 2090000, Average Loss= 5.8201\n",
+ "Step 2100000, Average Loss= 5.9390\n",
+ "Step 2110000, Average Loss= 5.7295\n",
+ "Step 2120000, Average Loss= 5.8290\n",
+ "Step 2130000, Average Loss= 5.9042\n",
+ "Step 2140000, Average Loss= 5.8367\n",
+ "Step 2150000, Average Loss= 5.7760\n",
+ "Step 2160000, Average Loss= 5.8664\n",
+ "Step 2170000, Average Loss= 5.7974\n",
+ "Step 2180000, Average Loss= 5.8523\n",
+ "Step 2190000, Average Loss= 5.8047\n",
+ "Step 2200000, Average Loss= 5.8172\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, six, eight, two, seven, one, zero,\n",
+ "\"of\" nearest neighbors: the, with, group, in, its, and, from, including,\n",
+ "\"going\" nearest neighbors: produced, when, today, while, little, before, had, like,\n",
+ "\"hardware\" nearest neighbors: computer, system, power, technology, program, simple, for, designed,\n",
+ "\"american\" nearest neighbors: english, canadian, german, french, author, british, film, born,\n",
+ "\"britain\" nearest neighbors: government, great, state, established, british, england, country, army,\n",
+ "Step 2210000, Average Loss= 5.8847\n",
+ "Step 2220000, Average Loss= 5.8622\n",
+ "Step 2230000, Average Loss= 5.8295\n",
+ "Step 2240000, Average Loss= 5.8484\n",
+ "Step 2250000, Average Loss= 5.7917\n",
+ "Step 2260000, Average Loss= 5.7846\n",
+ "Step 2270000, Average Loss= 5.8307\n",
+ "Step 2280000, Average Loss= 5.7341\n",
+ "Step 2290000, Average Loss= 5.8519\n",
+ "Step 2300000, Average Loss= 5.7792\n",
+ "Step 2310000, Average Loss= 5.8277\n",
+ "Step 2320000, Average Loss= 5.7196\n",
+ "Step 2330000, Average Loss= 5.5469\n",
+ "Step 2340000, Average Loss= 5.7177\n",
+ "Step 2350000, Average Loss= 5.8139\n",
+ "Step 2360000, Average Loss= 5.7849\n",
+ "Step 2370000, Average Loss= 5.7022\n",
+ "Step 2380000, Average Loss= 5.7447\n",
+ "Step 2390000, Average Loss= 5.7667\n",
+ "Step 2400000, Average Loss= 5.7625\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, six, seven, two, eight, zero, nine,\n",
+ "\"of\" nearest neighbors: the, and, from, part, in, following, within, including,\n",
+ "\"going\" nearest neighbors: where, once, little, now, again, while, off, produced,\n",
+ "\"hardware\" nearest neighbors: system, computer, high, power, using, designed, systems, simple,\n",
+ "\"american\" nearest neighbors: author, actor, english, born, writer, british, b, d,\n",
+ "\"britain\" nearest neighbors: great, established, government, england, country, state, army, former,\n",
+ "Step 2410000, Average Loss= 5.6953\n",
+ "Step 2420000, Average Loss= 5.7413\n",
+ "Step 2430000, Average Loss= 5.7242\n",
+ "Step 2440000, Average Loss= 5.7397\n",
+ "Step 2450000, Average Loss= 5.7755\n",
+ "Step 2460000, Average Loss= 5.6881\n",
+ "Step 2470000, Average Loss= 5.7471\n",
+ "Step 2480000, Average Loss= 5.8159\n",
+ "Step 2490000, Average Loss= 5.7452\n",
+ "Step 2500000, Average Loss= 5.7547\n",
+ "Step 2510000, Average Loss= 5.6945\n",
+ "Step 2520000, Average Loss= 5.7318\n",
+ "Step 2530000, Average Loss= 5.6682\n",
+ "Step 2540000, Average Loss= 5.7660\n",
+ "Step 2550000, Average Loss= 5.6956\n",
+ "Step 2560000, Average Loss= 5.7307\n",
+ "Step 2570000, Average Loss= 5.7015\n",
+ "Step 2580000, Average Loss= 5.6932\n",
+ "Step 2590000, Average Loss= 5.6386\n",
+ "Step 2600000, Average Loss= 5.4734\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, seven, eight, nine, two, zero,\n",
+ "\"of\" nearest neighbors: the, and, in, from, became, including, for, with,\n",
+ "\"going\" nearest neighbors: little, again, just, a, now, where, to, for,\n",
+ "\"hardware\" nearest neighbors: computer, program, system, software, designed, systems, technology, current,\n",
+ "\"american\" nearest neighbors: actor, d, writer, b, born, singer, author, robert,\n",
+ "\"britain\" nearest neighbors: great, established, government, england, country, in, from, state,\n",
+ "Step 2610000, Average Loss= 5.7291\n",
+ "Step 2620000, Average Loss= 5.6412\n",
+ "Step 2630000, Average Loss= 5.7485\n",
+ "Step 2640000, Average Loss= 5.5833\n",
+ "Step 2650000, Average Loss= 5.6548\n",
+ "Step 2660000, Average Loss= 5.7159\n",
+ "Step 2670000, Average Loss= 5.6569\n",
+ "Step 2680000, Average Loss= 5.6080\n",
+ "Step 2690000, Average Loss= 5.7037\n",
+ "Step 2700000, Average Loss= 5.6360\n",
+ "Step 2710000, Average Loss= 5.6707\n",
+ "Step 2720000, Average Loss= 5.6811\n",
+ "Step 2730000, Average Loss= 5.6237\n",
+ "Step 2740000, Average Loss= 5.7050\n",
+ "Step 2750000, Average Loss= 5.6991\n",
+ "Step 2760000, Average Loss= 5.6691\n",
+ "Step 2770000, Average Loss= 5.7057\n",
+ "Step 2780000, Average Loss= 5.6162\n",
+ "Step 2790000, Average Loss= 5.6484\n",
+ "Step 2800000, Average Loss= 5.6627\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, six, three, seven, eight, nine, two, one,\n",
+ "\"of\" nearest neighbors: the, in, following, including, part, and, from, under,\n",
+ "\"going\" nearest neighbors: again, before, little, away, once, when, eventually, then,\n",
+ "\"hardware\" nearest neighbors: computer, system, software, program, systems, designed, for, design,\n",
+ "\"american\" nearest neighbors: actor, writer, singer, author, born, robert, d, john,\n",
+ "\"britain\" nearest neighbors: established, england, great, government, france, army, the, throughout,\n",
+ "Step 2810000, Average Loss= 5.5900\n",
+ "Step 2820000, Average Loss= 5.7053\n",
+ "Step 2830000, Average Loss= 5.6064\n",
+ "Step 2840000, Average Loss= 5.6891\n",
+ "Step 2850000, Average Loss= 5.5571\n",
+ "Step 2860000, Average Loss= 5.4490\n",
+ "Step 2870000, Average Loss= 5.5428\n",
+ "Step 2880000, Average Loss= 5.6832\n",
+ "Step 2890000, Average Loss= 5.5973\n",
+ "Step 2900000, Average Loss= 5.5816\n",
+ "Step 2910000, Average Loss= 5.5647\n",
+ "Step 2920000, Average Loss= 5.6001\n",
+ "Step 2930000, Average Loss= 5.6459\n",
+ "Step 2940000, Average Loss= 5.5622\n",
+ "Step 2950000, Average Loss= 5.5707\n",
+ "Step 2960000, Average Loss= 5.6492\n",
+ "Step 2970000, Average Loss= 5.5633\n",
+ "Step 2980000, Average Loss= 5.6323\n",
+ "Step 2990000, Average Loss= 5.5440\n",
+ "Step 3000000, Average Loss= 5.6209\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, eight, seven, two, zero, one,\n",
+ "\"of\" nearest neighbors: the, in, and, including, group, includes, part, from,\n",
+ "\"going\" nearest neighbors: once, again, when, quickly, before, eventually, little, had,\n",
+ "\"hardware\" nearest neighbors: computer, system, software, designed, program, simple, systems, sound,\n",
+ "\"american\" nearest neighbors: canadian, english, author, german, french, british, irish, australian,\n",
+ "\"britain\" nearest neighbors: established, england, great, government, throughout, france, british, northern,\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()\n",
+ "\n",
+ "with tf.Session() as sess:\n",
+ "\n",
+ " # Run the initializer\n",
+ " sess.run(init)\n",
+ "\n",
+ " # Testing data\n",
+ " x_test = np.array([word2id[w] for w in eval_words])\n",
+ "\n",
+ " average_loss = 0\n",
+ " for step in xrange(1, num_steps + 1):\n",
+ " # Get a new batch of data\n",
+ " batch_x, batch_y = next_batch(batch_size, num_skips, skip_window)\n",
+ " # Run training op\n",
+ " _, loss = sess.run([train_op, loss_op], feed_dict={X: batch_x, Y: batch_y})\n",
+ " average_loss += loss\n",
+ "\n",
+ " if step % display_step == 0 or step == 1:\n",
+ " if step > 1:\n",
+ " average_loss /= display_step\n",
+ " print(\"Step \" + str(step) + \", Average Loss= \" + \\\n",
+ " \"{:.4f}\".format(average_loss))\n",
+ " average_loss = 0\n",
+ "\n",
+ " # Evaluation\n",
+ " if step % eval_step == 0 or step == 1:\n",
+ " print(\"Evaluation...\")\n",
+ " sim = sess.run(cosine_sim_op, feed_dict={X: x_test})\n",
+ " for i in xrange(len(eval_words)):\n",
+ " top_k = 8 # number of nearest neighbors\n",
+ " nearest = (-sim[i, :]).argsort()[1:top_k + 1]\n",
+ " log_str = '\"%s\" nearest neighbors:' % eval_words[i]\n",
+ " for k in xrange(top_k):\n",
+ " log_str = '%s %s,' % (log_str, id2word[nearest[k]])\n",
+ " print(log_str)\n"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/autoencoder.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/autoencoder.ipynb
new file mode 100644
index 00000000..0c5e8ed0
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/autoencoder.ipynb
@@ -0,0 +1,310 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Auto-Encoder Example\n",
+ "\n",
+ "Build a 2 layers auto-encoder with TensorFlow to compress images to a lower latent space and then reconstruct them.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Auto-Encoder Overview\n",
+ "\n",
+ "
\n",
+ "\n",
+ "References:\n",
+ "- [Gradient-based learning applied to document recognition](http://yann.lecun.com/exdb/publis/pdf/lecun-01a.pdf). Y. LeCun, L. Bottou, Y. Bengio, and P. Haffner. Proceedings of the IEEE, 86(11):2278-2324, November 1998.\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import division, print_function, absolute_import\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Training Parameters\n",
+ "learning_rate = 0.01\n",
+ "num_steps = 30000\n",
+ "batch_size = 256\n",
+ "\n",
+ "display_step = 1000\n",
+ "examples_to_show = 10\n",
+ "\n",
+ "# Network Parameters\n",
+ "num_hidden_1 = 256 # 1st layer num features\n",
+ "num_hidden_2 = 128 # 2nd layer num features (the latent dim)\n",
+ "num_input = 784 # MNIST data input (img shape: 28*28)\n",
+ "\n",
+ "# tf Graph input (only pictures)\n",
+ "X = tf.placeholder(\"float\", [None, num_input])\n",
+ "\n",
+ "weights = {\n",
+ " 'encoder_h1': tf.Variable(tf.random_normal([num_input, num_hidden_1])),\n",
+ " 'encoder_h2': tf.Variable(tf.random_normal([num_hidden_1, num_hidden_2])),\n",
+ " 'decoder_h1': tf.Variable(tf.random_normal([num_hidden_2, num_hidden_1])),\n",
+ " 'decoder_h2': tf.Variable(tf.random_normal([num_hidden_1, num_input])),\n",
+ "}\n",
+ "biases = {\n",
+ " 'encoder_b1': tf.Variable(tf.random_normal([num_hidden_1])),\n",
+ " 'encoder_b2': tf.Variable(tf.random_normal([num_hidden_2])),\n",
+ " 'decoder_b1': tf.Variable(tf.random_normal([num_hidden_1])),\n",
+ " 'decoder_b2': tf.Variable(tf.random_normal([num_input])),\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Building the encoder\n",
+ "def encoder(x):\n",
+ " # Encoder Hidden layer with sigmoid activation #1\n",
+ " layer_1 = tf.nn.sigmoid(tf.add(tf.matmul(x, weights['encoder_h1']),\n",
+ " biases['encoder_b1']))\n",
+ " # Encoder Hidden layer with sigmoid activation #2\n",
+ " layer_2 = tf.nn.sigmoid(tf.add(tf.matmul(layer_1, weights['encoder_h2']),\n",
+ " biases['encoder_b2']))\n",
+ " return layer_2\n",
+ "\n",
+ "\n",
+ "# Building the decoder\n",
+ "def decoder(x):\n",
+ " # Decoder Hidden layer with sigmoid activation #1\n",
+ " layer_1 = tf.nn.sigmoid(tf.add(tf.matmul(x, weights['decoder_h1']),\n",
+ " biases['decoder_b1']))\n",
+ " # Decoder Hidden layer with sigmoid activation #2\n",
+ " layer_2 = tf.nn.sigmoid(tf.add(tf.matmul(layer_1, weights['decoder_h2']),\n",
+ " biases['decoder_b2']))\n",
+ " return layer_2\n",
+ "\n",
+ "# Construct model\n",
+ "encoder_op = encoder(X)\n",
+ "decoder_op = decoder(encoder_op)\n",
+ "\n",
+ "# Prediction\n",
+ "y_pred = decoder_op\n",
+ "# Targets (Labels) are the input data.\n",
+ "y_true = X\n",
+ "\n",
+ "# Define loss and optimizer, minimize the squared error\n",
+ "loss = tf.reduce_mean(tf.pow(y_true - y_pred, 2))\n",
+ "optimizer = tf.train.RMSPropOptimizer(learning_rate).minimize(loss)\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1: Minibatch Loss: 0.438300\n",
+ "Step 1000: Minibatch Loss: 0.146586\n",
+ "Step 2000: Minibatch Loss: 0.130722\n",
+ "Step 3000: Minibatch Loss: 0.117178\n",
+ "Step 4000: Minibatch Loss: 0.109027\n",
+ "Step 5000: Minibatch Loss: 0.102582\n",
+ "Step 6000: Minibatch Loss: 0.099183\n",
+ "Step 7000: Minibatch Loss: 0.095619\n",
+ "Step 8000: Minibatch Loss: 0.089006\n",
+ "Step 9000: Minibatch Loss: 0.087125\n",
+ "Step 10000: Minibatch Loss: 0.083930\n",
+ "Step 11000: Minibatch Loss: 0.077512\n",
+ "Step 12000: Minibatch Loss: 0.077137\n",
+ "Step 13000: Minibatch Loss: 0.073983\n",
+ "Step 14000: Minibatch Loss: 0.074218\n",
+ "Step 15000: Minibatch Loss: 0.074492\n",
+ "Step 16000: Minibatch Loss: 0.074374\n",
+ "Step 17000: Minibatch Loss: 0.070909\n",
+ "Step 18000: Minibatch Loss: 0.069438\n",
+ "Step 19000: Minibatch Loss: 0.068245\n",
+ "Step 20000: Minibatch Loss: 0.068402\n",
+ "Step 21000: Minibatch Loss: 0.067113\n",
+ "Step 22000: Minibatch Loss: 0.068241\n",
+ "Step 23000: Minibatch Loss: 0.062454\n",
+ "Step 24000: Minibatch Loss: 0.059754\n",
+ "Step 25000: Minibatch Loss: 0.058687\n",
+ "Step 26000: Minibatch Loss: 0.059107\n",
+ "Step 27000: Minibatch Loss: 0.055788\n",
+ "Step 28000: Minibatch Loss: 0.057263\n",
+ "Step 29000: Minibatch Loss: 0.056391\n",
+ "Step 30000: Minibatch Loss: 0.057672\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start Training\n",
+ "# Start a new TF session\n",
+ "sess = tf.Session()\n",
+ "\n",
+ "# Run the initializer\n",
+ "sess.run(init)\n",
+ "\n",
+ "# Training\n",
+ "for i in range(1, num_steps+1):\n",
+ " # Prepare Data\n",
+ " # Get the next batch of MNIST data (only images are needed, not labels)\n",
+ " batch_x, _ = mnist.train.next_batch(batch_size)\n",
+ "\n",
+ " # Run optimization op (backprop) and cost op (to get loss value)\n",
+ " _, l = sess.run([optimizer, loss], feed_dict={X: batch_x})\n",
+ " # Display logs per step\n",
+ " if i % display_step == 0 or i == 1:\n",
+ " print('Step %i: Minibatch Loss: %f' % (i, l))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Original Images\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Reconstructed Images\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": 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ITCEgICCCpohTGDBggJ02bVrVO5uackqiDho0CCjEGEi/fv755wEX3adXFdiQ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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Testing\n",
+ "# Encode and decode images from test set and visualize their reconstruction.\n",
+ "n = 4\n",
+ "canvas_orig = np.empty((28 * n, 28 * n))\n",
+ "canvas_recon = np.empty((28 * n, 28 * n))\n",
+ "for i in range(n):\n",
+ " # MNIST test set\n",
+ " batch_x, _ = mnist.test.next_batch(n)\n",
+ " # Encode and decode the digit image\n",
+ " g = sess.run(decoder_op, feed_dict={X: batch_x})\n",
+ " \n",
+ " # Display original images\n",
+ " for j in range(n):\n",
+ " # Draw the generated digits\n",
+ " canvas_orig[i * 28:(i + 1) * 28, j * 28:(j + 1) * 28] = batch_x[j].reshape([28, 28])\n",
+ " # Display reconstructed images\n",
+ " for j in range(n):\n",
+ " # Draw the generated digits\n",
+ " canvas_recon[i * 28:(i + 1) * 28, j * 28:(j + 1) * 28] = g[j].reshape([28, 28])\n",
+ "\n",
+ "print(\"Original Images\") \n",
+ "plt.figure(figsize=(n, n))\n",
+ "plt.imshow(canvas_orig, origin=\"upper\", cmap=\"gray\")\n",
+ "plt.show()\n",
+ "\n",
+ "print(\"Reconstructed Images\")\n",
+ "plt.figure(figsize=(n, n))\n",
+ "plt.imshow(canvas_recon, origin=\"upper\", cmap=\"gray\")\n",
+ "plt.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2.0
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
\ No newline at end of file
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb
new file mode 100644
index 00000000..f2771b97
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/bidirectional_rnn.ipynb
@@ -0,0 +1,301 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Bi-directional Recurrent Neural Network Example\n",
+ "\n",
+ "Build a bi-directional recurrent neural network (LSTM) with TensorFlow.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## BiRNN Overview\n",
+ "\n",
+ "
\n",
+ "\n",
+ "References:\n",
+ "- [Long Short Term Memory](http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf), Sepp Hochreiter & Jurgen Schmidhuber, Neural Computation 9(8): 1735-1780, 1997.\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "To classify images using a recurrent neural network, we consider every image row as a sequence of pixels. Because MNIST image shape is 28*28px, we will then handle 28 sequences of 28 timesteps for every sample.\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "from tensorflow.contrib import rnn\n",
+ "import numpy as np\n",
+ "\n",
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Training Parameters\n",
+ "learning_rate = 0.001\n",
+ "training_steps = 10000\n",
+ "batch_size = 128\n",
+ "display_step = 200\n",
+ "\n",
+ "# Network Parameters\n",
+ "num_input = 28 # MNIST data input (img shape: 28*28)\n",
+ "timesteps = 28 # timesteps\n",
+ "num_hidden = 128 # hidden layer num of features\n",
+ "num_classes = 10 # MNIST total classes (0-9 digits)\n",
+ "\n",
+ "# tf Graph input\n",
+ "X = tf.placeholder(\"float\", [None, timesteps, num_input])\n",
+ "Y = tf.placeholder(\"float\", [None, num_classes])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Define weights\n",
+ "weights = {\n",
+ " # Hidden layer weights => 2*n_hidden because of forward + backward cells\n",
+ " 'out': tf.Variable(tf.random_normal([2*num_hidden, num_classes]))\n",
+ "}\n",
+ "biases = {\n",
+ " 'out': tf.Variable(tf.random_normal([num_classes]))\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "def BiRNN(x, weights, biases):\n",
+ "\n",
+ " # Prepare data shape to match `rnn` function requirements\n",
+ " # Current data input shape: (batch_size, timesteps, n_input)\n",
+ " # Required shape: 'timesteps' tensors list of shape (batch_size, num_input)\n",
+ "\n",
+ " # Unstack to get a list of 'timesteps' tensors of shape (batch_size, num_input)\n",
+ " x = tf.unstack(x, timesteps, 1)\n",
+ "\n",
+ " # Define lstm cells with tensorflow\n",
+ " # Forward direction cell\n",
+ " lstm_fw_cell = rnn.BasicLSTMCell(num_hidden, forget_bias=1.0)\n",
+ " # Backward direction cell\n",
+ " lstm_bw_cell = rnn.BasicLSTMCell(num_hidden, forget_bias=1.0)\n",
+ "\n",
+ " # Get lstm cell output\n",
+ " try:\n",
+ " outputs, _, _ = rnn.static_bidirectional_rnn(lstm_fw_cell, lstm_bw_cell, x,\n",
+ " dtype=tf.float32)\n",
+ " except Exception: # Old TensorFlow version only returns outputs not states\n",
+ " outputs = rnn.static_bidirectional_rnn(lstm_fw_cell, lstm_bw_cell, x,\n",
+ " dtype=tf.float32)\n",
+ "\n",
+ " # Linear activation, using rnn inner loop last output\n",
+ " return tf.matmul(outputs[-1], weights['out']) + biases['out']"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "logits = BiRNN(X, weights, biases)\n",
+ "prediction = tf.nn.softmax(logits)\n",
+ "\n",
+ "# Define loss and optimizer\n",
+ "loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(\n",
+ " logits=logits, labels=Y))\n",
+ "optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)\n",
+ "train_op = optimizer.minimize(loss_op)\n",
+ "\n",
+ "# Evaluate model (with test logits, for dropout to be disabled)\n",
+ "correct_pred = tf.equal(tf.argmax(prediction, 1), tf.argmax(Y, 1))\n",
+ "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1, Minibatch Loss= 2.6218, Training Accuracy= 0.086\n",
+ "Step 200, Minibatch Loss= 2.1900, Training Accuracy= 0.211\n",
+ "Step 400, Minibatch Loss= 2.0144, Training Accuracy= 0.375\n",
+ "Step 600, Minibatch Loss= 1.8729, Training Accuracy= 0.445\n",
+ "Step 800, Minibatch Loss= 1.8000, Training Accuracy= 0.469\n",
+ "Step 1000, Minibatch Loss= 1.7244, Training Accuracy= 0.453\n",
+ "Step 1200, Minibatch Loss= 1.5657, Training Accuracy= 0.523\n",
+ "Step 1400, Minibatch Loss= 1.5473, Training Accuracy= 0.547\n",
+ "Step 1600, Minibatch Loss= 1.5288, Training Accuracy= 0.500\n",
+ "Step 1800, Minibatch Loss= 1.4203, Training Accuracy= 0.555\n",
+ "Step 2000, Minibatch Loss= 1.2525, Training Accuracy= 0.641\n",
+ "Step 2200, Minibatch Loss= 1.2696, Training Accuracy= 0.594\n",
+ "Step 2400, Minibatch Loss= 1.2000, Training Accuracy= 0.664\n",
+ "Step 2600, Minibatch Loss= 1.1017, Training Accuracy= 0.625\n",
+ "Step 2800, Minibatch Loss= 1.2656, Training Accuracy= 0.578\n",
+ "Step 3000, Minibatch Loss= 1.0830, Training Accuracy= 0.656\n",
+ "Step 3200, Minibatch Loss= 1.1522, Training Accuracy= 0.633\n",
+ "Step 3400, Minibatch Loss= 0.9484, Training Accuracy= 0.680\n",
+ "Step 3600, Minibatch Loss= 1.0470, Training Accuracy= 0.641\n",
+ "Step 3800, Minibatch Loss= 1.0609, Training Accuracy= 0.586\n",
+ "Step 4000, Minibatch Loss= 1.1853, Training Accuracy= 0.648\n",
+ "Step 4200, Minibatch Loss= 0.9438, Training Accuracy= 0.750\n",
+ "Step 4400, Minibatch Loss= 0.7986, Training Accuracy= 0.766\n",
+ "Step 4600, Minibatch Loss= 0.8070, Training Accuracy= 0.750\n",
+ "Step 4800, Minibatch Loss= 0.8382, Training Accuracy= 0.734\n",
+ "Step 5000, Minibatch Loss= 0.7397, Training Accuracy= 0.766\n",
+ "Step 5200, Minibatch Loss= 0.7870, Training Accuracy= 0.727\n",
+ "Step 5400, Minibatch Loss= 0.6380, Training Accuracy= 0.828\n",
+ "Step 5600, Minibatch Loss= 0.7975, Training Accuracy= 0.719\n",
+ "Step 5800, Minibatch Loss= 0.7934, Training Accuracy= 0.766\n",
+ "Step 6000, Minibatch Loss= 0.6628, Training Accuracy= 0.805\n",
+ "Step 6200, Minibatch Loss= 0.7958, Training Accuracy= 0.672\n",
+ "Step 6400, Minibatch Loss= 0.6582, Training Accuracy= 0.773\n",
+ "Step 6600, Minibatch Loss= 0.5908, Training Accuracy= 0.812\n",
+ "Step 6800, Minibatch Loss= 0.6182, Training Accuracy= 0.820\n",
+ "Step 7000, Minibatch Loss= 0.5513, Training Accuracy= 0.812\n",
+ "Step 7200, Minibatch Loss= 0.6683, Training Accuracy= 0.789\n",
+ "Step 7400, Minibatch Loss= 0.5337, Training Accuracy= 0.828\n",
+ "Step 7600, Minibatch Loss= 0.6428, Training Accuracy= 0.805\n",
+ "Step 7800, Minibatch Loss= 0.6708, Training Accuracy= 0.797\n",
+ "Step 8000, Minibatch Loss= 0.4664, Training Accuracy= 0.852\n",
+ "Step 8200, Minibatch Loss= 0.4249, Training Accuracy= 0.859\n",
+ "Step 8400, Minibatch Loss= 0.7723, Training Accuracy= 0.773\n",
+ "Step 8600, Minibatch Loss= 0.4706, Training Accuracy= 0.859\n",
+ "Step 8800, Minibatch Loss= 0.4800, Training Accuracy= 0.867\n",
+ "Step 9000, Minibatch Loss= 0.4636, Training Accuracy= 0.891\n",
+ "Step 9200, Minibatch Loss= 0.5734, Training Accuracy= 0.828\n",
+ "Step 9400, Minibatch Loss= 0.5548, Training Accuracy= 0.875\n",
+ "Step 9600, Minibatch Loss= 0.3575, Training Accuracy= 0.922\n",
+ "Step 9800, Minibatch Loss= 0.4566, Training Accuracy= 0.844\n",
+ "Step 10000, Minibatch Loss= 0.5125, Training Accuracy= 0.844\n",
+ "Optimization Finished!\n",
+ "Testing Accuracy: 0.890625\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start training\n",
+ "with tf.Session() as sess:\n",
+ "\n",
+ " # Run the initializer\n",
+ " sess.run(init)\n",
+ "\n",
+ " for step in range(1, training_steps+1):\n",
+ " batch_x, batch_y = mnist.train.next_batch(batch_size)\n",
+ " # Reshape data to get 28 seq of 28 elements\n",
+ " batch_x = batch_x.reshape((batch_size, timesteps, num_input))\n",
+ " # Run optimization op (backprop)\n",
+ " sess.run(train_op, feed_dict={X: batch_x, Y: batch_y})\n",
+ " if step % display_step == 0 or step == 1:\n",
+ " # Calculate batch loss and accuracy\n",
+ " loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,\n",
+ " Y: batch_y})\n",
+ " print(\"Step \" + str(step) + \", Minibatch Loss= \" + \\\n",
+ " \"{:.4f}\".format(loss) + \", Training Accuracy= \" + \\\n",
+ " \"{:.3f}\".format(acc))\n",
+ "\n",
+ " print(\"Optimization Finished!\")\n",
+ "\n",
+ " # Calculate accuracy for 128 mnist test images\n",
+ " test_len = 128\n",
+ " test_data = mnist.test.images[:test_len].reshape((-1, timesteps, num_input))\n",
+ " test_label = mnist.test.labels[:test_len]\n",
+ " print(\"Testing Accuracy:\", \\\n",
+ " sess.run(accuracy, feed_dict={X: test_data, Y: test_label}))\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.13"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/convolutional_network.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/convolutional_network.ipynb
new file mode 100644
index 00000000..32c5daf8
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/convolutional_network.ipynb
@@ -0,0 +1,423 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Convolutional Neural Network Example\n",
+ "\n",
+ "Build a convolutional neural network with TensorFlow.\n",
+ "\n",
+ "This example is using TensorFlow layers API, see 'convolutional_network_raw' example\n",
+ "for a raw TensorFlow implementation with variables.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## CNN Overview\n",
+ "\n",
+ "\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "from __future__ import division, print_function, absolute_import\n",
+ "\n",
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=False)\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Training Parameters\n",
+ "learning_rate = 0.001\n",
+ "num_steps = 2000\n",
+ "batch_size = 128\n",
+ "\n",
+ "# Network Parameters\n",
+ "num_input = 784 # MNIST data input (img shape: 28*28)\n",
+ "num_classes = 10 # MNIST total classes (0-9 digits)\n",
+ "dropout = 0.25 # Dropout, probability to drop a unit"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Create the neural network\n",
+ "def conv_net(x_dict, n_classes, dropout, reuse, is_training):\n",
+ " \n",
+ " # Define a scope for reusing the variables\n",
+ " with tf.variable_scope('ConvNet', reuse=reuse):\n",
+ " # TF Estimator input is a dict, in case of multiple inputs\n",
+ " x = x_dict['images']\n",
+ "\n",
+ " # MNIST data input is a 1-D vector of 784 features (28*28 pixels)\n",
+ " # Reshape to match picture format [Height x Width x Channel]\n",
+ " # Tensor input become 4-D: [Batch Size, Height, Width, Channel]\n",
+ " x = tf.reshape(x, shape=[-1, 28, 28, 1])\n",
+ "\n",
+ " # Convolution Layer with 32 filters and a kernel size of 5\n",
+ " conv1 = tf.layers.conv2d(x, 32, 5, activation=tf.nn.relu)\n",
+ " # Max Pooling (down-sampling) with strides of 2 and kernel size of 2\n",
+ " conv1 = tf.layers.max_pooling2d(conv1, 2, 2)\n",
+ "\n",
+ " # Convolution Layer with 64 filters and a kernel size of 3\n",
+ " conv2 = tf.layers.conv2d(conv1, 64, 3, activation=tf.nn.relu)\n",
+ " # Max Pooling (down-sampling) with strides of 2 and kernel size of 2\n",
+ " conv2 = tf.layers.max_pooling2d(conv2, 2, 2)\n",
+ "\n",
+ " # Flatten the data to a 1-D vector for the fully connected layer\n",
+ " fc1 = tf.contrib.layers.flatten(conv2)\n",
+ "\n",
+ " # Fully connected layer (in tf contrib folder for now)\n",
+ " fc1 = tf.layers.dense(fc1, 1024)\n",
+ " # Apply Dropout (if is_training is False, dropout is not applied)\n",
+ " fc1 = tf.layers.dropout(fc1, rate=dropout, training=is_training)\n",
+ "\n",
+ " # Output layer, class prediction\n",
+ " out = tf.layers.dense(fc1, n_classes)\n",
+ "\n",
+ " return out"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Define the model function (following TF Estimator Template)\n",
+ "def model_fn(features, labels, mode):\n",
+ " \n",
+ " # Build the neural network\n",
+ " # Because Dropout have different behavior at training and prediction time, we\n",
+ " # need to create 2 distinct computation graphs that still share the same weights.\n",
+ " logits_train = conv_net(features, num_classes, dropout, reuse=False, is_training=True)\n",
+ " logits_test = conv_net(features, num_classes, dropout, reuse=True, is_training=False)\n",
+ " \n",
+ " # Predictions\n",
+ " pred_classes = tf.argmax(logits_test, axis=1)\n",
+ " pred_probas = tf.nn.softmax(logits_test)\n",
+ " \n",
+ " # If prediction mode, early return\n",
+ " if mode == tf.estimator.ModeKeys.PREDICT:\n",
+ " return tf.estimator.EstimatorSpec(mode, predictions=pred_classes) \n",
+ " \n",
+ " # Define loss and optimizer\n",
+ " loss_op = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(\n",
+ " logits=logits_train, labels=tf.cast(labels, dtype=tf.int32)))\n",
+ " optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
+ " train_op = optimizer.minimize(loss_op, global_step=tf.train.get_global_step())\n",
+ " \n",
+ " # Evaluate the accuracy of the model\n",
+ " acc_op = tf.metrics.accuracy(labels=labels, predictions=pred_classes)\n",
+ " \n",
+ " # TF Estimators requires to return a EstimatorSpec, that specify\n",
+ " # the different ops for training, evaluating, ...\n",
+ " estim_specs = tf.estimator.EstimatorSpec(\n",
+ " mode=mode,\n",
+ " predictions=pred_classes,\n",
+ " loss=loss_op,\n",
+ " train_op=train_op,\n",
+ " eval_metric_ops={'accuracy': acc_op})\n",
+ "\n",
+ " return estim_specs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Using default config.\n",
+ "WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmpdhd6F4\n",
+ "INFO:tensorflow:Using config: {'_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_tf_random_seed': 1, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_save_checkpoints_steps': None, '_model_dir': '/tmp/tmpdhd6F4', '_save_summary_steps': 100}\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Build the Estimator\n",
+ "model = tf.estimator.Estimator(model_fn)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Create CheckpointSaverHook.\n",
+ "INFO:tensorflow:Saving checkpoints for 1 into /tmp/tmpdhd6F4/model.ckpt.\n",
+ "INFO:tensorflow:loss = 2.39026, step = 1\n",
+ "INFO:tensorflow:global_step/sec: 238.314\n",
+ "INFO:tensorflow:loss = 0.237997, step = 101 (0.421 sec)\n",
+ "INFO:tensorflow:global_step/sec: 255.312\n",
+ "INFO:tensorflow:loss = 0.0954537, step = 201 (0.392 sec)\n",
+ "INFO:tensorflow:global_step/sec: 257.194\n",
+ "INFO:tensorflow:loss = 0.121477, step = 301 (0.389 sec)\n",
+ "INFO:tensorflow:global_step/sec: 255.018\n",
+ "INFO:tensorflow:loss = 0.0539927, step = 401 (0.392 sec)\n",
+ "INFO:tensorflow:global_step/sec: 254.293\n",
+ "INFO:tensorflow:loss = 0.0440369, step = 501 (0.393 sec)\n",
+ "INFO:tensorflow:global_step/sec: 256.501\n",
+ "INFO:tensorflow:loss = 0.0247431, step = 601 (0.390 sec)\n",
+ "INFO:tensorflow:global_step/sec: 252.956\n",
+ "INFO:tensorflow:loss = 0.0738082, step = 701 (0.395 sec)\n",
+ "INFO:tensorflow:global_step/sec: 253.222\n",
+ "INFO:tensorflow:loss = 0.134998, step = 801 (0.395 sec)\n",
+ "INFO:tensorflow:global_step/sec: 255.606\n",
+ "INFO:tensorflow:loss = 0.00438448, step = 901 (0.391 sec)\n",
+ "INFO:tensorflow:global_step/sec: 256.306\n",
+ "INFO:tensorflow:loss = 0.0471991, step = 1001 (0.390 sec)\n",
+ "INFO:tensorflow:global_step/sec: 255.352\n",
+ "INFO:tensorflow:loss = 0.0371172, step = 1101 (0.392 sec)\n",
+ "INFO:tensorflow:global_step/sec: 253.277\n",
+ "INFO:tensorflow:loss = 0.0129522, step = 1201 (0.395 sec)\n",
+ "INFO:tensorflow:global_step/sec: 252.49\n",
+ "INFO:tensorflow:loss = 0.039862, step = 1301 (0.396 sec)\n",
+ "INFO:tensorflow:global_step/sec: 253.902\n",
+ "INFO:tensorflow:loss = 0.0520571, step = 1401 (0.394 sec)\n",
+ "INFO:tensorflow:global_step/sec: 255.572\n",
+ "INFO:tensorflow:loss = 0.0307549, step = 1501 (0.392 sec)\n",
+ "INFO:tensorflow:global_step/sec: 254.32\n",
+ "INFO:tensorflow:loss = 0.0108862, step = 1601 (0.393 sec)\n",
+ "INFO:tensorflow:global_step/sec: 255.62\n",
+ "INFO:tensorflow:loss = 0.0294434, step = 1701 (0.391 sec)\n",
+ "INFO:tensorflow:global_step/sec: 254.349\n",
+ "INFO:tensorflow:loss = 0.0179781, step = 1801 (0.393 sec)\n",
+ "INFO:tensorflow:global_step/sec: 255.508\n",
+ "INFO:tensorflow:loss = 0.0375271, step = 1901 (0.391 sec)\n",
+ "INFO:tensorflow:Saving checkpoints for 2000 into /tmp/tmpdhd6F4/model.ckpt.\n",
+ "INFO:tensorflow:Loss for final step: 0.00440777.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Define the input function for training\n",
+ "input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+ " x={'images': mnist.train.images}, y=mnist.train.labels,\n",
+ " batch_size=batch_size, num_epochs=None, shuffle=True)\n",
+ "# Train the Model\n",
+ "model.train(input_fn, steps=num_steps)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Starting evaluation at 2017-08-21-14:25:29\n",
+ "INFO:tensorflow:Restoring parameters from /tmp/tmpdhd6F4/model.ckpt-2000\n",
+ "INFO:tensorflow:Finished evaluation at 2017-08-21-14:25:29\n",
+ "INFO:tensorflow:Saving dict for global step 2000: accuracy = 0.9908, global_step = 2000, loss = 0.0382241\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "{'accuracy': 0.99080002, 'global_step': 2000, 'loss': 0.038224086}"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Evaluate the Model\n",
+ "# Define the input function for evaluating\n",
+ "input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+ " x={'images': mnist.test.images}, y=mnist.test.labels,\n",
+ " batch_size=batch_size, shuffle=False)\n",
+ "# Use the Estimator 'evaluate' method\n",
+ "model.evaluate(input_fn)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Restoring parameters from /tmp/tmpdhd6F4/model.ckpt-2000\n"
+ ]
+ },
+ {
+ "data": {
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+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Model prediction: 7\n"
+ ]
+ },
+ {
+ "data": {
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+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Model prediction: 2\n"
+ ]
+ },
+ {
+ "data": {
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+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Model prediction: 1\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nZZUAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Model prediction: 0\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Predict single images\n",
+ "n_images = 4\n",
+ "# Get images from test set\n",
+ "test_images = mnist.test.images[:n_images]\n",
+ "# Prepare the input data\n",
+ "input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+ " x={'images': test_images}, shuffle=False)\n",
+ "# Use the model to predict the images class\n",
+ "preds = list(model.predict(input_fn))\n",
+ "\n",
+ "# Display\n",
+ "for i in range(n_images):\n",
+ " plt.imshow(np.reshape(test_images[i], [28, 28]), cmap='gray')\n",
+ " plt.show()\n",
+ " print(\"Model prediction:\", preds[i])"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb
new file mode 100644
index 00000000..63765e1d
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb
@@ -0,0 +1,303 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Convolutional Neural Network Example\n",
+ "\n",
+ "Build a convolutional neural network with TensorFlow.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## CNN Overview\n",
+ "\n",
+ "\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "from __future__ import division, print_function, absolute_import\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "\n",
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Training Parameters\n",
+ "learning_rate = 0.001\n",
+ "num_steps = 500\n",
+ "batch_size = 128\n",
+ "display_step = 10\n",
+ "\n",
+ "# Network Parameters\n",
+ "num_input = 784 # MNIST data input (img shape: 28*28)\n",
+ "num_classes = 10 # MNIST total classes (0-9 digits)\n",
+ "dropout = 0.75 # Dropout, probability to keep units\n",
+ "\n",
+ "# tf Graph input\n",
+ "X = tf.placeholder(tf.float32, [None, num_input])\n",
+ "Y = tf.placeholder(tf.float32, [None, num_classes])\n",
+ "keep_prob = tf.placeholder(tf.float32) # dropout (keep probability)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Create some wrappers for simplicity\n",
+ "def conv2d(x, W, b, strides=1):\n",
+ " # Conv2D wrapper, with bias and relu activation\n",
+ " x = tf.nn.conv2d(x, W, strides=[1, strides, strides, 1], padding='SAME')\n",
+ " x = tf.nn.bias_add(x, b)\n",
+ " return tf.nn.relu(x)\n",
+ "\n",
+ "\n",
+ "def maxpool2d(x, k=2):\n",
+ " # MaxPool2D wrapper\n",
+ " return tf.nn.max_pool(x, ksize=[1, k, k, 1], strides=[1, k, k, 1],\n",
+ " padding='SAME')\n",
+ "\n",
+ "\n",
+ "# Create model\n",
+ "def conv_net(x, weights, biases, dropout):\n",
+ " # MNIST data input is a 1-D vector of 784 features (28*28 pixels)\n",
+ " # Reshape to match picture format [Height x Width x Channel]\n",
+ " # Tensor input become 4-D: [Batch Size, Height, Width, Channel]\n",
+ " x = tf.reshape(x, shape=[-1, 28, 28, 1])\n",
+ "\n",
+ " # Convolution Layer\n",
+ " conv1 = conv2d(x, weights['wc1'], biases['bc1'])\n",
+ " # Max Pooling (down-sampling)\n",
+ " conv1 = maxpool2d(conv1, k=2)\n",
+ "\n",
+ " # Convolution Layer\n",
+ " conv2 = conv2d(conv1, weights['wc2'], biases['bc2'])\n",
+ " # Max Pooling (down-sampling)\n",
+ " conv2 = maxpool2d(conv2, k=2)\n",
+ "\n",
+ " # Fully connected layer\n",
+ " # Reshape conv2 output to fit fully connected layer input\n",
+ " fc1 = tf.reshape(conv2, [-1, weights['wd1'].get_shape().as_list()[0]])\n",
+ " fc1 = tf.add(tf.matmul(fc1, weights['wd1']), biases['bd1'])\n",
+ " fc1 = tf.nn.relu(fc1)\n",
+ " # Apply Dropout\n",
+ " fc1 = tf.nn.dropout(fc1, dropout)\n",
+ "\n",
+ " # Output, class prediction\n",
+ " out = tf.add(tf.matmul(fc1, weights['out']), biases['out'])\n",
+ " return out"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Store layers weight & bias\n",
+ "weights = {\n",
+ " # 5x5 conv, 1 input, 32 outputs\n",
+ " 'wc1': tf.Variable(tf.random_normal([5, 5, 1, 32])),\n",
+ " # 5x5 conv, 32 inputs, 64 outputs\n",
+ " 'wc2': tf.Variable(tf.random_normal([5, 5, 32, 64])),\n",
+ " # fully connected, 7*7*64 inputs, 1024 outputs\n",
+ " 'wd1': tf.Variable(tf.random_normal([7*7*64, 1024])),\n",
+ " # 1024 inputs, 10 outputs (class prediction)\n",
+ " 'out': tf.Variable(tf.random_normal([1024, num_classes]))\n",
+ "}\n",
+ "\n",
+ "biases = {\n",
+ " 'bc1': tf.Variable(tf.random_normal([32])),\n",
+ " 'bc2': tf.Variable(tf.random_normal([64])),\n",
+ " 'bd1': tf.Variable(tf.random_normal([1024])),\n",
+ " 'out': tf.Variable(tf.random_normal([num_classes]))\n",
+ "}\n",
+ "\n",
+ "# Construct model\n",
+ "logits = conv_net(X, weights, biases, keep_prob)\n",
+ "prediction = tf.nn.softmax(logits)\n",
+ "\n",
+ "# Define loss and optimizer\n",
+ "loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(\n",
+ " logits=logits, labels=Y))\n",
+ "optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
+ "train_op = optimizer.minimize(loss_op)\n",
+ "\n",
+ "\n",
+ "# Evaluate model\n",
+ "correct_pred = tf.equal(tf.argmax(prediction, 1), tf.argmax(Y, 1))\n",
+ "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1, Minibatch Loss= 63763.3047, Training Accuracy= 0.141\n",
+ "Step 10, Minibatch Loss= 26429.6680, Training Accuracy= 0.242\n",
+ "Step 20, Minibatch Loss= 12171.8584, Training Accuracy= 0.586\n",
+ "Step 30, Minibatch Loss= 6306.6318, Training Accuracy= 0.734\n",
+ "Step 40, Minibatch Loss= 5113.7583, Training Accuracy= 0.711\n",
+ "Step 50, Minibatch Loss= 4022.2131, Training Accuracy= 0.805\n",
+ "Step 60, Minibatch Loss= 3125.4949, Training Accuracy= 0.867\n",
+ "Step 70, Minibatch Loss= 2225.4875, Training Accuracy= 0.875\n",
+ "Step 80, Minibatch Loss= 1843.3540, Training Accuracy= 0.867\n",
+ "Step 90, Minibatch Loss= 1715.7744, Training Accuracy= 0.875\n",
+ "Step 100, Minibatch Loss= 2611.2708, Training Accuracy= 0.906\n",
+ "Step 110, Minibatch Loss= 4804.0913, Training Accuracy= 0.875\n",
+ "Step 120, Minibatch Loss= 1067.5258, Training Accuracy= 0.938\n",
+ "Step 130, Minibatch Loss= 2519.1514, Training Accuracy= 0.898\n",
+ "Step 140, Minibatch Loss= 2687.9292, Training Accuracy= 0.906\n",
+ "Step 150, Minibatch Loss= 1983.4077, Training Accuracy= 0.938\n",
+ "Step 160, Minibatch Loss= 2844.6553, Training Accuracy= 0.930\n",
+ "Step 170, Minibatch Loss= 3602.2524, Training Accuracy= 0.914\n",
+ "Step 180, Minibatch Loss= 175.3922, Training Accuracy= 0.961\n",
+ "Step 190, Minibatch Loss= 645.1918, Training Accuracy= 0.945\n",
+ "Step 200, Minibatch Loss= 1147.6567, Training Accuracy= 0.938\n",
+ "Step 210, Minibatch Loss= 1140.4148, Training Accuracy= 0.914\n",
+ "Step 220, Minibatch Loss= 1572.8756, Training Accuracy= 0.906\n",
+ "Step 230, Minibatch Loss= 1292.9274, Training Accuracy= 0.898\n",
+ "Step 240, Minibatch Loss= 1501.4623, Training Accuracy= 0.953\n",
+ "Step 250, Minibatch Loss= 1908.2997, Training Accuracy= 0.898\n",
+ "Step 260, Minibatch Loss= 2182.2380, Training Accuracy= 0.898\n",
+ "Step 270, Minibatch Loss= 487.5807, Training Accuracy= 0.961\n",
+ "Step 280, Minibatch Loss= 1284.1130, Training Accuracy= 0.945\n",
+ "Step 290, Minibatch Loss= 1232.4919, Training Accuracy= 0.891\n",
+ "Step 300, Minibatch Loss= 1198.8336, Training Accuracy= 0.945\n",
+ "Step 310, Minibatch Loss= 2010.5345, Training Accuracy= 0.906\n",
+ "Step 320, Minibatch Loss= 786.3917, Training Accuracy= 0.945\n",
+ "Step 330, Minibatch Loss= 1408.3556, Training Accuracy= 0.898\n",
+ "Step 340, Minibatch Loss= 1453.7538, Training Accuracy= 0.953\n",
+ "Step 350, Minibatch Loss= 999.8901, Training Accuracy= 0.906\n",
+ "Step 360, Minibatch Loss= 914.3958, Training Accuracy= 0.961\n",
+ "Step 370, Minibatch Loss= 488.0052, Training Accuracy= 0.938\n",
+ "Step 380, Minibatch Loss= 1070.8710, Training Accuracy= 0.922\n",
+ "Step 390, Minibatch Loss= 151.4658, Training Accuracy= 0.961\n",
+ "Step 400, Minibatch Loss= 555.3539, Training Accuracy= 0.953\n",
+ "Step 410, Minibatch Loss= 765.5746, Training Accuracy= 0.945\n",
+ "Step 420, Minibatch Loss= 326.9393, Training Accuracy= 0.969\n",
+ "Step 430, Minibatch Loss= 530.8968, Training Accuracy= 0.977\n",
+ "Step 440, Minibatch Loss= 463.3909, Training Accuracy= 0.977\n",
+ "Step 450, Minibatch Loss= 362.2226, Training Accuracy= 0.977\n",
+ "Step 460, Minibatch Loss= 414.0034, Training Accuracy= 0.953\n",
+ "Step 470, Minibatch Loss= 583.4587, Training Accuracy= 0.945\n",
+ "Step 480, Minibatch Loss= 566.1262, Training Accuracy= 0.969\n",
+ "Step 490, Minibatch Loss= 691.1143, Training Accuracy= 0.961\n",
+ "Step 500, Minibatch Loss= 282.8893, Training Accuracy= 0.984\n",
+ "Optimization Finished!\n",
+ "Testing Accuracy: 0.976562\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start training\n",
+ "with tf.Session() as sess:\n",
+ "\n",
+ " # Run the initializer\n",
+ " sess.run(init)\n",
+ "\n",
+ " for step in range(1, num_steps+1):\n",
+ " batch_x, batch_y = mnist.train.next_batch(batch_size)\n",
+ " # Run optimization op (backprop)\n",
+ " sess.run(train_op, feed_dict={X: batch_x, Y: batch_y, keep_prob: dropout})\n",
+ " if step % display_step == 0 or step == 1:\n",
+ " # Calculate batch loss and accuracy\n",
+ " loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,\n",
+ " Y: batch_y,\n",
+ " keep_prob: 1.0})\n",
+ " print(\"Step \" + str(step) + \", Minibatch Loss= \" + \\\n",
+ " \"{:.4f}\".format(loss) + \", Training Accuracy= \" + \\\n",
+ " \"{:.3f}\".format(acc))\n",
+ "\n",
+ " print(\"Optimization Finished!\")\n",
+ "\n",
+ " # Calculate accuracy for 256 MNIST test images\n",
+ " print(\"Testing Accuracy:\", \\\n",
+ " sess.run(accuracy, feed_dict={X: mnist.test.images[:256],\n",
+ " Y: mnist.test.labels[:256],\n",
+ " keep_prob: 1.0}))\n"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.13"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/dcgan.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/dcgan.ipynb
new file mode 100644
index 00000000..da05a1d8
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/dcgan.ipynb
@@ -0,0 +1,333 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Deep Convolutional Generative Adversarial Network Example\n",
+ "\n",
+ "Build a deep convolutional generative adversarial network (DCGAN) to generate digit images from a noise distribution with TensorFlow.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## DCGAN Overview\n",
+ "\n",
+ "
\n",
+ "\n",
+ "References:\n",
+ "- [Unsupervised representation learning with deep convolutional generative adversarial networks](https://arxiv.org/pdf/1511.06434). A Radford, L Metz, S Chintala, 2016.\n",
+ "- [Understanding the difficulty of training deep feedforward neural networks](http://proceedings.mlr.press/v9/glorot10a.html). X Glorot, Y Bengio. Aistats 9, 249-256\n",
+ "- [Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift](https://arxiv.org/abs/1502.03167). Sergey Ioffe, Christian Szegedy. 2015.\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import division, print_function, absolute_import\n",
+ "\n",
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Training Params\n",
+ "num_steps = 10000\n",
+ "batch_size = 128\n",
+ "lr_generator = 0.002\n",
+ "lr_discriminator = 0.002\n",
+ "\n",
+ "# Network Params\n",
+ "image_dim = 784 # 28*28 pixels * 1 channel\n",
+ "noise_dim = 100 # Noise data points"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Build Networks\n",
+ "# Network Inputs\n",
+ "noise_input = tf.placeholder(tf.float32, shape=[None, noise_dim])\n",
+ "real_image_input = tf.placeholder(tf.float32, shape=[None, 28, 28, 1])\n",
+ "# A boolean to indicate batch normalization if it is training or inference time\n",
+ "is_training = tf.placeholder(tf.bool)\n",
+ "\n",
+ "#LeakyReLU activation\n",
+ "def leakyrelu(x, alpha=0.2):\n",
+ " return 0.5 * (1 + alpha) * x + 0.5 * (1 - alpha) * abs(x)\n",
+ "\n",
+ "# Generator Network\n",
+ "# Input: Noise, Output: Image\n",
+ "# Note that batch normalization has different behavior at training and inference time,\n",
+ "# we then use a placeholder to indicates the layer if we are training or not.\n",
+ "def generator(x, reuse=False):\n",
+ " with tf.variable_scope('Generator', reuse=reuse):\n",
+ " # TensorFlow Layers automatically create variables and calculate their\n",
+ " # shape, based on the input.\n",
+ " x = tf.layers.dense(x, units=7 * 7 * 128)\n",
+ " x = tf.layers.batch_normalization(x, training=is_training)\n",
+ " x = tf.nn.relu(x)\n",
+ " # Reshape to a 4-D array of images: (batch, height, width, channels)\n",
+ " # New shape: (batch, 7, 7, 128)\n",
+ " x = tf.reshape(x, shape=[-1, 7, 7, 128])\n",
+ " # Deconvolution, image shape: (batch, 14, 14, 64)\n",
+ " x = tf.layers.conv2d_transpose(x, 64, 5, strides=2, padding='same')\n",
+ " x = tf.layers.batch_normalization(x, training=is_training)\n",
+ " x = tf.nn.relu(x)\n",
+ " # Deconvolution, image shape: (batch, 28, 28, 1)\n",
+ " x = tf.layers.conv2d_transpose(x, 1, 5, strides=2, padding='same')\n",
+ " # Apply tanh for better stability - clip values to [-1, 1].\n",
+ " x = tf.nn.tanh(x)\n",
+ " return x\n",
+ "\n",
+ "\n",
+ "# Discriminator Network\n",
+ "# Input: Image, Output: Prediction Real/Fake Image\n",
+ "def discriminator(x, reuse=False):\n",
+ " with tf.variable_scope('Discriminator', reuse=reuse):\n",
+ " # Typical convolutional neural network to classify images.\n",
+ " x = tf.layers.conv2d(x, 64, 5, strides=2, padding='same')\n",
+ " x = tf.layers.batch_normalization(x, training=is_training)\n",
+ " x = leakyrelu(x)\n",
+ " x = tf.layers.conv2d(x, 128, 5, strides=2, padding='same')\n",
+ " x = tf.layers.batch_normalization(x, training=is_training)\n",
+ " x = leakyrelu(x)\n",
+ " # Flatten\n",
+ " x = tf.reshape(x, shape=[-1, 7*7*128])\n",
+ " x = tf.layers.dense(x, 1024)\n",
+ " x = tf.layers.batch_normalization(x, training=is_training)\n",
+ " x = leakyrelu(x)\n",
+ " # Output 2 classes: Real and Fake images\n",
+ " x = tf.layers.dense(x, 2)\n",
+ " return x\n",
+ "\n",
+ "# Build Generator Network\n",
+ "gen_sample = generator(noise_input)\n",
+ "\n",
+ "# Build 2 Discriminator Networks (one from noise input, one from generated samples)\n",
+ "disc_real = discriminator(real_image_input)\n",
+ "disc_fake = discriminator(gen_sample, reuse=True)\n",
+ "\n",
+ "# Build the stacked generator/discriminator\n",
+ "stacked_gan = discriminator(gen_sample, reuse=True)\n",
+ "\n",
+ "# Build Loss (Labels for real images: 1, for fake images: 0)\n",
+ "# Discriminator Loss for real and fake samples\n",
+ "disc_loss_real = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(\n",
+ " logits=disc_real, labels=tf.ones([batch_size], dtype=tf.int32)))\n",
+ "disc_loss_fake = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(\n",
+ " logits=disc_fake, labels=tf.zeros([batch_size], dtype=tf.int32)))\n",
+ "# Sum both loss\n",
+ "disc_loss = disc_loss_real + disc_loss_fake\n",
+ "# Generator Loss (The generator tries to fool the discriminator, thus labels are 1)\n",
+ "gen_loss = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(\n",
+ " logits=stacked_gan, labels=tf.ones([batch_size], dtype=tf.int32)))\n",
+ "\n",
+ "# Build Optimizers\n",
+ "optimizer_gen = tf.train.AdamOptimizer(learning_rate=lr_generator, beta1=0.5, beta2=0.999)\n",
+ "optimizer_disc = tf.train.AdamOptimizer(learning_rate=lr_discriminator, beta1=0.5, beta2=0.999)\n",
+ "\n",
+ "# Training Variables for each optimizer\n",
+ "# By default in TensorFlow, all variables are updated by each optimizer, so we\n",
+ "# need to precise for each one of them the specific variables to update.\n",
+ "# Generator Network Variables\n",
+ "gen_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope='Generator')\n",
+ "# Discriminator Network Variables\n",
+ "disc_vars = tf.get_collection(tf.GraphKeys.TRAINABLE_VARIABLES, scope='Discriminator')\n",
+ "\n",
+ "# Create training operations\n",
+ "# TensorFlow UPDATE_OPS collection holds all batch norm operation to update the moving mean/stddev\n",
+ "gen_update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS, scope='Generator')\n",
+ "# `control_dependencies` ensure that the `gen_update_ops` will be run before the `minimize` op (backprop)\n",
+ "with tf.control_dependencies(gen_update_ops):\n",
+ " train_gen = optimizer_gen.minimize(gen_loss, var_list=gen_vars)\n",
+ "disc_update_ops = tf.get_collection(tf.GraphKeys.UPDATE_OPS, scope='Discriminator')\n",
+ "with tf.control_dependencies(disc_update_ops):\n",
+ " train_disc = optimizer_disc.minimize(disc_loss, var_list=disc_vars)\n",
+ " \n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1: Generator Loss: 3.590350, Discriminator Loss: 1.907586\n",
+ "Step 500: Generator Loss: 1.254698, Discriminator Loss: 1.005236\n",
+ "Step 1000: Generator Loss: 1.730409, Discriminator Loss: 0.837684\n",
+ "Step 1500: Generator Loss: 1.962198, Discriminator Loss: 0.618827\n",
+ "Step 2000: Generator Loss: 2.767945, Discriminator Loss: 0.378071\n",
+ "Step 2500: Generator Loss: 2.370605, Discriminator Loss: 0.561247\n",
+ "Step 3000: Generator Loss: 3.427798, Discriminator Loss: 0.402951\n",
+ "Step 3500: Generator Loss: 4.904454, Discriminator Loss: 0.554856\n",
+ "Step 4000: Generator Loss: 4.045284, Discriminator Loss: 0.454970\n",
+ "Step 4500: Generator Loss: 4.577699, Discriminator Loss: 0.687195\n",
+ "Step 5000: Generator Loss: 3.476081, Discriminator Loss: 0.210492\n",
+ "Step 5500: Generator Loss: 3.898139, Discriminator Loss: 0.143352\n",
+ "Step 6000: Generator Loss: 4.089877, Discriminator Loss: 1.082561\n",
+ "Step 6500: Generator Loss: 5.911457, Discriminator Loss: 0.154059\n",
+ "Step 7000: Generator Loss: 3.594872, Discriminator Loss: 0.152970\n",
+ "Step 7500: Generator Loss: 6.067883, Discriminator Loss: 0.084864\n",
+ "Step 8000: Generator Loss: 6.737456, Discriminator Loss: 0.402566\n",
+ "Step 8500: Generator Loss: 6.630128, Discriminator Loss: 0.034838\n",
+ "Step 9000: Generator Loss: 6.480587, Discriminator Loss: 0.427419\n",
+ "Step 9500: Generator Loss: 7.200409, Discriminator Loss: 0.124268\n",
+ "Step 10000: Generator Loss: 5.479313, Discriminator Loss: 0.191389\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start Training\n",
+ "# Start a new TF session\n",
+ "sess = tf.Session()\n",
+ "\n",
+ "# Run the initializer\n",
+ "sess.run(init)\n",
+ " \n",
+ "# Training\n",
+ "for i in range(1, num_steps+1):\n",
+ "\n",
+ " # Prepare Input Data\n",
+ " # Get the next batch of MNIST data (only images are needed, not labels)\n",
+ " batch_x, _ = mnist.train.next_batch(batch_size)\n",
+ " batch_x = np.reshape(batch_x, newshape=[-1, 28, 28, 1])\n",
+ " # Rescale to [-1, 1], the input range of the discriminator\n",
+ " batch_x = batch_x * 2. - 1.\n",
+ "\n",
+ " # Discriminator Training\n",
+ " # Generate noise to feed to the generator\n",
+ " z = np.random.uniform(-1., 1., size=[batch_size, noise_dim])\n",
+ " _, dl = sess.run([train_disc, disc_loss], feed_dict={real_image_input: batch_x, noise_input: z, is_training:True})\n",
+ " \n",
+ " # Generator Training\n",
+ " # Generate noise to feed to the generator\n",
+ " z = np.random.uniform(-1., 1., size=[batch_size, noise_dim])\n",
+ " _, gl = sess.run([train_gen, gen_loss], feed_dict={noise_input: z, is_training:True})\n",
+ " \n",
+ " if i % 500 == 0 or i == 1:\n",
+ " print('Step %i: Generator Loss: %f, Discriminator Loss: %f' % (i, gl, dl))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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6VWlTPKyiPmRNdO/ePcySVIRH1A+fDUjxSHkrG1cRH8pSVY2WTKL8BD2WhmoF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\nNLSZp2OoG2VZU9CVwr755psDPsnpvffeS+o4K8I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+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Testing\n",
+ "# Generate images from noise, using the generator network.\n",
+ "n = 6\n",
+ "canvas = np.empty((28 * n, 28 * n))\n",
+ "for i in range(n):\n",
+ " # Noise input.\n",
+ " z = np.random.uniform(-1., 1., size=[n, noise_dim])\n",
+ " # Generate image from noise.\n",
+ " g = sess.run(gen_sample, feed_dict={noise_input: z, is_training:False})\n",
+ " # Rescale values to the original [0, 1] (from tanh -> [-1, 1])\n",
+ " g = (g + 1.) / 2.\n",
+ " # Reverse colours for better display\n",
+ " g = -1 * (g - 1)\n",
+ " for j in range(n):\n",
+ " # Draw the generated digits\n",
+ " canvas[i * 28:(i + 1) * 28, j * 28:(j + 1) * 28] = g[j].reshape([28, 28])\n",
+ "\n",
+ "plt.figure(figsize=(n, n))\n",
+ "plt.imshow(canvas, origin=\"upper\", cmap=\"gray\")\n",
+ "plt.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/dynamic_rnn.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/dynamic_rnn.ipynb
new file mode 100644
index 00000000..d4d0f482
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/dynamic_rnn.ipynb
@@ -0,0 +1,352 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Dynamic Recurrent Neural Network.\n",
+ "\n",
+ "TensorFlow implementation of a Recurrent Neural Network (LSTM) that performs dynamic computation over sequences with variable length. This example is using a toy dataset to classify linear sequences. The generated sequences have variable length.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## RNN Overview\n",
+ "\n",
+ "
\n",
+ "\n",
+ "References:\n",
+ "- [Long Short Term Memory](http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf), Sepp Hochreiter & Jurgen Schmidhuber, Neural Computation 9(8): 1735-1780, 1997."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "import random"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# ====================\n",
+ "# TOY DATA GENERATOR\n",
+ "# ====================\n",
+ "\n",
+ "class ToySequenceData(object):\n",
+ " \"\"\" Generate sequence of data with dynamic length.\n",
+ " This class generate samples for training:\n",
+ " - Class 0: linear sequences (i.e. [0, 1, 2, 3,...])\n",
+ " - Class 1: random sequences (i.e. [1, 3, 10, 7,...])\n",
+ "\n",
+ " NOTICE:\n",
+ " We have to pad each sequence to reach 'max_seq_len' for TensorFlow\n",
+ " consistency (we cannot feed a numpy array with inconsistent\n",
+ " dimensions). The dynamic calculation will then be perform thanks to\n",
+ " 'seqlen' attribute that records every actual sequence length.\n",
+ " \"\"\"\n",
+ " def __init__(self, n_samples=1000, max_seq_len=20, min_seq_len=3,\n",
+ " max_value=1000):\n",
+ " self.data = []\n",
+ " self.labels = []\n",
+ " self.seqlen = []\n",
+ " for i in range(n_samples):\n",
+ " # Random sequence length\n",
+ " len = random.randint(min_seq_len, max_seq_len)\n",
+ " # Monitor sequence length for TensorFlow dynamic calculation\n",
+ " self.seqlen.append(len)\n",
+ " # Add a random or linear int sequence (50% prob)\n",
+ " if random.random() < .5:\n",
+ " # Generate a linear sequence\n",
+ " rand_start = random.randint(0, max_value - len)\n",
+ " s = [[float(i)/max_value] for i in\n",
+ " range(rand_start, rand_start + len)]\n",
+ " # Pad sequence for dimension consistency\n",
+ " s += [[0.] for i in range(max_seq_len - len)]\n",
+ " self.data.append(s)\n",
+ " self.labels.append([1., 0.])\n",
+ " else:\n",
+ " # Generate a random sequence\n",
+ " s = [[float(random.randint(0, max_value))/max_value]\n",
+ " for i in range(len)]\n",
+ " # Pad sequence for dimension consistency\n",
+ " s += [[0.] for i in range(max_seq_len - len)]\n",
+ " self.data.append(s)\n",
+ " self.labels.append([0., 1.])\n",
+ " self.batch_id = 0\n",
+ "\n",
+ " def next(self, batch_size):\n",
+ " \"\"\" Return a batch of data. When dataset end is reached, start over.\n",
+ " \"\"\"\n",
+ " if self.batch_id == len(self.data):\n",
+ " self.batch_id = 0\n",
+ " batch_data = (self.data[self.batch_id:min(self.batch_id +\n",
+ " batch_size, len(self.data))])\n",
+ " batch_labels = (self.labels[self.batch_id:min(self.batch_id +\n",
+ " batch_size, len(self.data))])\n",
+ " batch_seqlen = (self.seqlen[self.batch_id:min(self.batch_id +\n",
+ " batch_size, len(self.data))])\n",
+ " self.batch_id = min(self.batch_id + batch_size, len(self.data))\n",
+ " return batch_data, batch_labels, batch_seqlen"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# ==========\n",
+ "# MODEL\n",
+ "# ==========\n",
+ "\n",
+ "# Parameters\n",
+ "learning_rate = 0.01\n",
+ "training_steps = 10000\n",
+ "batch_size = 128\n",
+ "display_step = 200\n",
+ "\n",
+ "# Network Parameters\n",
+ "seq_max_len = 20 # Sequence max length\n",
+ "n_hidden = 64 # hidden layer num of features\n",
+ "n_classes = 2 # linear sequence or not\n",
+ "\n",
+ "trainset = ToySequenceData(n_samples=1000, max_seq_len=seq_max_len)\n",
+ "testset = ToySequenceData(n_samples=500, max_seq_len=seq_max_len)\n",
+ "\n",
+ "# tf Graph input\n",
+ "x = tf.placeholder(\"float\", [None, seq_max_len, 1])\n",
+ "y = tf.placeholder(\"float\", [None, n_classes])\n",
+ "# A placeholder for indicating each sequence length\n",
+ "seqlen = tf.placeholder(tf.int32, [None])\n",
+ "\n",
+ "# Define weights\n",
+ "weights = {\n",
+ " 'out': tf.Variable(tf.random_normal([n_hidden, n_classes]))\n",
+ "}\n",
+ "biases = {\n",
+ " 'out': tf.Variable(tf.random_normal([n_classes]))\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "def dynamicRNN(x, seqlen, weights, biases):\n",
+ "\n",
+ " # Prepare data shape to match `rnn` function requirements\n",
+ " # Current data input shape: (batch_size, n_steps, n_input)\n",
+ " # Required shape: 'n_steps' tensors list of shape (batch_size, n_input)\n",
+ " \n",
+ " # Unstack to get a list of 'n_steps' tensors of shape (batch_size, n_input)\n",
+ " x = tf.unstack(x, seq_max_len, 1)\n",
+ "\n",
+ " # Define a lstm cell with tensorflow\n",
+ " lstm_cell = tf.contrib.rnn.BasicLSTMCell(n_hidden)\n",
+ "\n",
+ " # Get lstm cell output, providing 'sequence_length' will perform dynamic\n",
+ " # calculation.\n",
+ " outputs, states = tf.contrib.rnn.static_rnn(lstm_cell, x, dtype=tf.float32,\n",
+ " sequence_length=seqlen)\n",
+ "\n",
+ " # When performing dynamic calculation, we must retrieve the last\n",
+ " # dynamically computed output, i.e., if a sequence length is 10, we need\n",
+ " # to retrieve the 10th output.\n",
+ " # However TensorFlow doesn't support advanced indexing yet, so we build\n",
+ " # a custom op that for each sample in batch size, get its length and\n",
+ " # get the corresponding relevant output.\n",
+ "\n",
+ " # 'outputs' is a list of output at every timestep, we pack them in a Tensor\n",
+ " # and change back dimension to [batch_size, n_step, n_input]\n",
+ " outputs = tf.stack(outputs)\n",
+ " outputs = tf.transpose(outputs, [1, 0, 2])\n",
+ "\n",
+ " # Hack to build the indexing and retrieve the right output.\n",
+ " batch_size = tf.shape(outputs)[0]\n",
+ " # Start indices for each sample\n",
+ " index = tf.range(0, batch_size) * seq_max_len + (seqlen - 1)\n",
+ " # Indexing\n",
+ " outputs = tf.gather(tf.reshape(outputs, [-1, n_hidden]), index)\n",
+ "\n",
+ " # Linear activation, using outputs computed above\n",
+ " return tf.matmul(outputs, weights['out']) + biases['out']"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stderr",
+ "output_type": "stream",
+ "text": [
+ "/Users/aymeric.damien/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/gradients_impl.py:93: UserWarning: Converting sparse IndexedSlices to a dense Tensor of unknown shape. This may consume a large amount of memory.\n",
+ " \"Converting sparse IndexedSlices to a dense Tensor of unknown shape. \"\n"
+ ]
+ }
+ ],
+ "source": [
+ "pred = dynamicRNN(x, seqlen, weights, biases)\n",
+ "\n",
+ "# Define loss and optimizer\n",
+ "cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=pred, labels=y))\n",
+ "optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate).minimize(cost)\n",
+ "\n",
+ "# Evaluate model\n",
+ "correct_pred = tf.equal(tf.argmax(pred,1), tf.argmax(y,1))\n",
+ "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1, Minibatch Loss= 0.864517, Training Accuracy= 0.42188\n",
+ "Step 200, Minibatch Loss= 0.686012, Training Accuracy= 0.43269\n",
+ "Step 400, Minibatch Loss= 0.682970, Training Accuracy= 0.48077\n",
+ "Step 600, Minibatch Loss= 0.679640, Training Accuracy= 0.50962\n",
+ "Step 800, Minibatch Loss= 0.675208, Training Accuracy= 0.53846\n",
+ "Step 1000, Minibatch Loss= 0.668636, Training Accuracy= 0.56731\n",
+ "Step 1200, Minibatch Loss= 0.657525, Training Accuracy= 0.62500\n",
+ "Step 1400, Minibatch Loss= 0.635423, Training Accuracy= 0.67308\n",
+ "Step 1600, Minibatch Loss= 0.580433, Training Accuracy= 0.75962\n",
+ "Step 1800, Minibatch Loss= 0.475599, Training Accuracy= 0.81731\n",
+ "Step 2000, Minibatch Loss= 0.434865, Training Accuracy= 0.83654\n",
+ "Step 2200, Minibatch Loss= 0.423690, Training Accuracy= 0.85577\n",
+ "Step 2400, Minibatch Loss= 0.417472, Training Accuracy= 0.85577\n",
+ "Step 2600, Minibatch Loss= 0.412906, Training Accuracy= 0.85577\n",
+ "Step 2800, Minibatch Loss= 0.409193, Training Accuracy= 0.85577\n",
+ "Step 3000, Minibatch Loss= 0.406035, Training Accuracy= 0.86538\n",
+ "Step 3200, Minibatch Loss= 0.403287, Training Accuracy= 0.87500\n",
+ "Step 3400, Minibatch Loss= 0.400862, Training Accuracy= 0.87500\n",
+ "Step 3600, Minibatch Loss= 0.398704, Training Accuracy= 0.86538\n",
+ "Step 3800, Minibatch Loss= 0.396768, Training Accuracy= 0.86538\n",
+ "Step 4000, Minibatch Loss= 0.395017, Training Accuracy= 0.86538\n",
+ "Step 4200, Minibatch Loss= 0.393422, Training Accuracy= 0.86538\n",
+ "Step 4400, Minibatch Loss= 0.391957, Training Accuracy= 0.85577\n",
+ "Step 4600, Minibatch Loss= 0.390600, Training Accuracy= 0.85577\n",
+ "Step 4800, Minibatch Loss= 0.389334, Training Accuracy= 0.86538\n",
+ "Step 5000, Minibatch Loss= 0.388143, Training Accuracy= 0.86538\n",
+ "Step 5200, Minibatch Loss= 0.387015, Training Accuracy= 0.86538\n",
+ "Step 5400, Minibatch Loss= 0.385940, Training Accuracy= 0.86538\n",
+ "Step 5600, Minibatch Loss= 0.384907, Training Accuracy= 0.86538\n",
+ "Step 5800, Minibatch Loss= 0.383904, Training Accuracy= 0.85577\n",
+ "Step 6000, Minibatch Loss= 0.382921, Training Accuracy= 0.86538\n",
+ "Step 6200, Minibatch Loss= 0.381941, Training Accuracy= 0.86538\n",
+ "Step 6400, Minibatch Loss= 0.380947, Training Accuracy= 0.86538\n",
+ "Step 6600, Minibatch Loss= 0.379912, Training Accuracy= 0.86538\n",
+ "Step 6800, Minibatch Loss= 0.378796, Training Accuracy= 0.86538\n",
+ "Step 7000, Minibatch Loss= 0.377540, Training Accuracy= 0.86538\n",
+ "Step 7200, Minibatch Loss= 0.376041, Training Accuracy= 0.86538\n",
+ "Step 7400, Minibatch Loss= 0.374130, Training Accuracy= 0.85577\n",
+ "Step 7600, Minibatch Loss= 0.371514, Training Accuracy= 0.85577\n",
+ "Step 7800, Minibatch Loss= 0.367723, Training Accuracy= 0.85577\n",
+ "Step 8000, Minibatch Loss= 0.362049, Training Accuracy= 0.85577\n",
+ "Step 8200, Minibatch Loss= 0.353558, Training Accuracy= 0.85577\n",
+ "Step 8400, Minibatch Loss= 0.341072, Training Accuracy= 0.86538\n",
+ "Step 8600, Minibatch Loss= 0.323062, Training Accuracy= 0.87500\n",
+ "Step 8800, Minibatch Loss= 0.299278, Training Accuracy= 0.89423\n",
+ "Step 9000, Minibatch Loss= 0.273857, Training Accuracy= 0.90385\n",
+ "Step 9200, Minibatch Loss= 0.248392, Training Accuracy= 0.91346\n",
+ "Step 9400, Minibatch Loss= 0.221348, Training Accuracy= 0.92308\n",
+ "Step 9600, Minibatch Loss= 0.191947, Training Accuracy= 0.92308\n",
+ "Step 9800, Minibatch Loss= 0.159308, Training Accuracy= 0.93269\n",
+ "Step 10000, Minibatch Loss= 0.136938, Training Accuracy= 0.96154\n",
+ "Optimization Finished!\n",
+ "Testing Accuracy: 0.952\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start training\n",
+ "with tf.Session() as sess:\n",
+ "\n",
+ " # Run the initializer\n",
+ " sess.run(init)\n",
+ "\n",
+ " for step in range(1, training_steps+1):\n",
+ " batch_x, batch_y, batch_seqlen = trainset.next(batch_size)\n",
+ " # Run optimization op (backprop)\n",
+ " sess.run(optimizer, feed_dict={x: batch_x, y: batch_y,\n",
+ " seqlen: batch_seqlen})\n",
+ " if step % display_step == 0 or step == 1:\n",
+ " # Calculate batch accuracy & loss\n",
+ " acc, loss = sess.run([accuracy, cost], feed_dict={x: batch_x, y: batch_y,\n",
+ " seqlen: batch_seqlen})\n",
+ " print(\"Step \" + str(step) + \", Minibatch Loss= \" + \\\n",
+ " \"{:.6f}\".format(loss) + \", Training Accuracy= \" + \\\n",
+ " \"{:.5f}\".format(acc))\n",
+ "\n",
+ " print(\"Optimization Finished!\")\n",
+ "\n",
+ " # Calculate accuracy\n",
+ " test_data = testset.data\n",
+ " test_label = testset.labels\n",
+ " test_seqlen = testset.seqlen\n",
+ " print(\"Testing Accuracy:\", \\\n",
+ " sess.run(accuracy, feed_dict={x: test_data, y: test_label,\n",
+ " seqlen: test_seqlen}))"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/gan.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/gan.ipynb
new file mode 100644
index 00000000..d7d32878
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/gan.ipynb
@@ -0,0 +1,323 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Generative Adversarial Network Example\n",
+ "\n",
+ "Build a generative adversarial network (GAN) to generate digit images from a noise distribution with TensorFlow.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## GAN Overview\n",
+ "\n",
+ "
\n",
+ "\n",
+ "References:\n",
+ "- [Generative adversarial nets](https://arxiv.org/pdf/1406.2661.pdf). I Goodfellow, J Pouget-Abadie, M Mirza, B Xu, D Warde-Farley, S Ozair, Y. Bengio. Advances in neural information processing systems, 2672-2680.\n",
+ "- [Understanding the difficulty of training deep feedforward neural networks](http://proceedings.mlr.press/v9/glorot10a.html). X Glorot, Y Bengio. Aistats 9, 249-256\n",
+ "\n",
+ "Other tutorials:\n",
+ "- [Generative Adversarial Networks Explained](http://kvfrans.com/generative-adversial-networks-explained/). Kevin Frans.\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import division, print_function, absolute_import\n",
+ "\n",
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Training Params\n",
+ "num_steps = 70000\n",
+ "batch_size = 128\n",
+ "learning_rate = 0.0002\n",
+ "\n",
+ "# Network Params\n",
+ "image_dim = 784 # 28*28 pixels\n",
+ "gen_hidden_dim = 256\n",
+ "disc_hidden_dim = 256\n",
+ "noise_dim = 100 # Noise data points\n",
+ "\n",
+ "# A custom initialization (see Xavier Glorot init)\n",
+ "def glorot_init(shape):\n",
+ " return tf.random_normal(shape=shape, stddev=1. / tf.sqrt(shape[0] / 2.))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Store layers weight & bias\n",
+ "weights = {\n",
+ " 'gen_hidden1': tf.Variable(glorot_init([noise_dim, gen_hidden_dim])),\n",
+ " 'gen_out': tf.Variable(glorot_init([gen_hidden_dim, image_dim])),\n",
+ " 'disc_hidden1': tf.Variable(glorot_init([image_dim, disc_hidden_dim])),\n",
+ " 'disc_out': tf.Variable(glorot_init([disc_hidden_dim, 1])),\n",
+ "}\n",
+ "biases = {\n",
+ " 'gen_hidden1': tf.Variable(tf.zeros([gen_hidden_dim])),\n",
+ " 'gen_out': tf.Variable(tf.zeros([image_dim])),\n",
+ " 'disc_hidden1': tf.Variable(tf.zeros([disc_hidden_dim])),\n",
+ " 'disc_out': tf.Variable(tf.zeros([1])),\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Generator\n",
+ "def generator(x):\n",
+ " hidden_layer = tf.matmul(x, weights['gen_hidden1'])\n",
+ " hidden_layer = tf.add(hidden_layer, biases['gen_hidden1'])\n",
+ " hidden_layer = tf.nn.relu(hidden_layer)\n",
+ " out_layer = tf.matmul(hidden_layer, weights['gen_out'])\n",
+ " out_layer = tf.add(out_layer, biases['gen_out'])\n",
+ " out_layer = tf.nn.sigmoid(out_layer)\n",
+ " return out_layer\n",
+ "\n",
+ "\n",
+ "# Discriminator\n",
+ "def discriminator(x):\n",
+ " hidden_layer = tf.matmul(x, weights['disc_hidden1'])\n",
+ " hidden_layer = tf.add(hidden_layer, biases['disc_hidden1'])\n",
+ " hidden_layer = tf.nn.relu(hidden_layer)\n",
+ " out_layer = tf.matmul(hidden_layer, weights['disc_out'])\n",
+ " out_layer = tf.add(out_layer, biases['disc_out'])\n",
+ " out_layer = tf.nn.sigmoid(out_layer)\n",
+ " return out_layer\n",
+ "\n",
+ "# Build Networks\n",
+ "# Network Inputs\n",
+ "gen_input = tf.placeholder(tf.float32, shape=[None, noise_dim], name='input_noise')\n",
+ "disc_input = tf.placeholder(tf.float32, shape=[None, image_dim], name='disc_input')\n",
+ "\n",
+ "# Build Generator Network\n",
+ "gen_sample = generator(gen_input)\n",
+ "\n",
+ "# Build 2 Discriminator Networks (one from noise input, one from generated samples)\n",
+ "disc_real = discriminator(disc_input)\n",
+ "disc_fake = discriminator(gen_sample)\n",
+ "\n",
+ "# Build Loss\n",
+ "gen_loss = -tf.reduce_mean(tf.log(disc_fake))\n",
+ "disc_loss = -tf.reduce_mean(tf.log(disc_real) + tf.log(1. - disc_fake))\n",
+ "\n",
+ "# Build Optimizers\n",
+ "optimizer_gen = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
+ "optimizer_disc = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
+ "\n",
+ "# Training Variables for each optimizer\n",
+ "# By default in TensorFlow, all variables are updated by each optimizer, so we\n",
+ "# need to precise for each one of them the specific variables to update.\n",
+ "# Generator Network Variables\n",
+ "gen_vars = [weights['gen_hidden1'], weights['gen_out'],\n",
+ " biases['gen_hidden1'], biases['gen_out']]\n",
+ "# Discriminator Network Variables\n",
+ "disc_vars = [weights['disc_hidden1'], weights['disc_out'],\n",
+ " biases['disc_hidden1'], biases['disc_out']]\n",
+ "\n",
+ "# Create training operations\n",
+ "train_gen = optimizer_gen.minimize(gen_loss, var_list=gen_vars)\n",
+ "train_disc = optimizer_disc.minimize(disc_loss, var_list=disc_vars)\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1: Generator Loss: 0.774581, Discriminator Loss: 1.300602\n",
+ "Step 2000: Generator Loss: 4.521158, Discriminator Loss: 0.030166\n",
+ "Step 4000: Generator Loss: 3.685439, Discriminator Loss: 0.125958\n",
+ "Step 6000: Generator Loss: 4.412449, Discriminator Loss: 0.097088\n",
+ "Step 8000: Generator Loss: 3.996747, Discriminator Loss: 0.150800\n",
+ "Step 10000: Generator Loss: 3.850827, Discriminator Loss: 0.225699\n",
+ "Step 12000: Generator Loss: 2.950704, Discriminator Loss: 0.279967\n",
+ "Step 14000: Generator Loss: 3.741951, Discriminator Loss: 0.241062\n",
+ "Step 16000: Generator Loss: 3.117743, Discriminator Loss: 0.432293\n",
+ "Step 18000: Generator Loss: 3.647199, Discriminator Loss: 0.278121\n",
+ "Step 20000: Generator Loss: 3.186711, Discriminator Loss: 0.313830\n",
+ "Step 22000: Generator Loss: 3.737114, Discriminator Loss: 0.201730\n",
+ "Step 24000: Generator Loss: 3.042442, Discriminator Loss: 0.454414\n",
+ "Step 26000: Generator Loss: 3.340376, Discriminator Loss: 0.249428\n",
+ "Step 28000: Generator Loss: 3.423218, Discriminator Loss: 0.369653\n",
+ "Step 30000: Generator Loss: 3.219242, Discriminator Loss: 0.463535\n",
+ "Step 32000: Generator Loss: 3.313017, Discriminator Loss: 0.276070\n",
+ "Step 34000: Generator Loss: 3.413397, Discriminator Loss: 0.367721\n",
+ "Step 36000: Generator Loss: 3.240625, Discriminator Loss: 0.446160\n",
+ "Step 38000: Generator Loss: 3.175355, Discriminator Loss: 0.377628\n",
+ "Step 40000: Generator Loss: 3.154558, Discriminator Loss: 0.478812\n",
+ "Step 42000: Generator Loss: 3.210753, Discriminator Loss: 0.497502\n",
+ "Step 44000: Generator Loss: 2.883431, Discriminator Loss: 0.395812\n",
+ "Step 46000: Generator Loss: 2.584176, Discriminator Loss: 0.420783\n",
+ "Step 48000: Generator Loss: 2.581381, Discriminator Loss: 0.469289\n",
+ "Step 50000: Generator Loss: 2.752729, Discriminator Loss: 0.373544\n",
+ "Step 52000: Generator Loss: 2.649749, Discriminator Loss: 0.463755\n",
+ "Step 54000: Generator Loss: 2.468188, Discriminator Loss: 0.556129\n",
+ "Step 56000: Generator Loss: 2.653330, Discriminator Loss: 0.377572\n",
+ "Step 58000: Generator Loss: 2.697943, Discriminator Loss: 0.424133\n",
+ "Step 60000: Generator Loss: 2.835973, Discriminator Loss: 0.413252\n",
+ "Step 62000: Generator Loss: 2.751346, Discriminator Loss: 0.403332\n",
+ "Step 64000: Generator Loss: 3.212001, Discriminator Loss: 0.534427\n",
+ "Step 66000: Generator Loss: 2.878227, Discriminator Loss: 0.431244\n",
+ "Step 68000: Generator Loss: 3.104266, Discriminator Loss: 0.426825\n",
+ "Step 70000: Generator Loss: 2.871485, Discriminator Loss: 0.348638\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start Training\n",
+ "# Start a new TF session\n",
+ "sess = tf.Session()\n",
+ "\n",
+ "# Run the initializer\n",
+ "sess.run(init)\n",
+ "\n",
+ "# Training\n",
+ "for i in range(1, num_steps+1):\n",
+ " # Prepare Data\n",
+ " # Get the next batch of MNIST data (only images are needed, not labels)\n",
+ " batch_x, _ = mnist.train.next_batch(batch_size)\n",
+ " # Generate noise to feed to the generator\n",
+ " z = np.random.uniform(-1., 1., size=[batch_size, noise_dim])\n",
+ "\n",
+ " # Train\n",
+ " feed_dict = {disc_input: batch_x, gen_input: z}\n",
+ " _, _, gl, dl = sess.run([train_gen, train_disc, gen_loss, disc_loss],\n",
+ " feed_dict=feed_dict)\n",
+ " if i % 2000 == 0 or i == 1:\n",
+ " print('Step %i: Generator Loss: %f, Discriminator Loss: %f' % (i, gl, dl))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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Ew8UXX5y1MaULpXdL/UgVSSnELTa5OKZMmVLk802aNMnwSMqPkpekYNWuMJtF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\ndxzHqTg+kDuO41QcH8gdx3Eqzv8DPY8Zg0BX8cEAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Testing\n",
+ "# Generate images from noise, using the generator network.\n",
+ "n = 6\n",
+ "canvas = np.empty((28 * n, 28 * n))\n",
+ "for i in range(n):\n",
+ " # Noise input.\n",
+ " z = np.random.uniform(-1., 1., size=[n, noise_dim])\n",
+ " # Generate image from noise.\n",
+ " g = sess.run(gen_sample, feed_dict={gen_input: z})\n",
+ " # Reverse colours for better display\n",
+ " g = -1 * (g - 1)\n",
+ " for j in range(n):\n",
+ " # Draw the generated digits\n",
+ " canvas[i * 28:(i + 1) * 28, j * 28:(j + 1) * 28] = g[j].reshape([28, 28])\n",
+ "\n",
+ "plt.figure(figsize=(n, n))\n",
+ "plt.imshow(canvas, origin=\"upper\", cmap=\"gray\")\n",
+ "plt.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network.ipynb
new file mode 100644
index 00000000..ebd13026
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network.ipynb
@@ -0,0 +1,390 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Neural Network Example\n",
+ "\n",
+ "Build a 2-hidden layers fully connected neural network (a.k.a multilayer perceptron) with TensorFlow.\n",
+ "\n",
+ "This example is using some of TensorFlow higher-level wrappers (tf.estimators, tf.layers, tf.metrics, ...), you can check 'neural_network_raw' example for a raw, and more detailed TensorFlow implementation.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Neural Network Overview\n",
+ "\n",
+ "
\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=False)\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "import matplotlib.pyplot as plt\n",
+ "import numpy as np"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.1\n",
+ "num_steps = 1000\n",
+ "batch_size = 128\n",
+ "display_step = 100\n",
+ "\n",
+ "# Network Parameters\n",
+ "n_hidden_1 = 256 # 1st layer number of neurons\n",
+ "n_hidden_2 = 256 # 2nd layer number of neurons\n",
+ "num_input = 784 # MNIST data input (img shape: 28*28)\n",
+ "num_classes = 10 # MNIST total classes (0-9 digits)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Define the input function for training\n",
+ "input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+ " x={'images': mnist.train.images}, y=mnist.train.labels,\n",
+ " batch_size=batch_size, num_epochs=None, shuffle=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Define the neural network\n",
+ "def neural_net(x_dict):\n",
+ " # TF Estimator input is a dict, in case of multiple inputs\n",
+ " x = x_dict['images']\n",
+ " # Hidden fully connected layer with 256 neurons\n",
+ " layer_1 = tf.layers.dense(x, n_hidden_1)\n",
+ " # Hidden fully connected layer with 256 neurons\n",
+ " layer_2 = tf.layers.dense(layer_1, n_hidden_2)\n",
+ " # Output fully connected layer with a neuron for each class\n",
+ " out_layer = tf.layers.dense(layer_2, num_classes)\n",
+ " return out_layer"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Define the model function (following TF Estimator Template)\n",
+ "def model_fn(features, labels, mode):\n",
+ " \n",
+ " # Build the neural network\n",
+ " logits = neural_net(features)\n",
+ " \n",
+ " # Predictions\n",
+ " pred_classes = tf.argmax(logits, axis=1)\n",
+ " pred_probas = tf.nn.softmax(logits)\n",
+ " \n",
+ " # If prediction mode, early return\n",
+ " if mode == tf.estimator.ModeKeys.PREDICT:\n",
+ " return tf.estimator.EstimatorSpec(mode, predictions=pred_classes) \n",
+ " \n",
+ " # Define loss and optimizer\n",
+ " loss_op = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(\n",
+ " logits=logits, labels=tf.cast(labels, dtype=tf.int32)))\n",
+ " optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)\n",
+ " train_op = optimizer.minimize(loss_op, global_step=tf.train.get_global_step())\n",
+ " \n",
+ " # Evaluate the accuracy of the model\n",
+ " acc_op = tf.metrics.accuracy(labels=labels, predictions=pred_classes)\n",
+ " \n",
+ " # TF Estimators requires to return a EstimatorSpec, that specify\n",
+ " # the different ops for training, evaluating, ...\n",
+ " estim_specs = tf.estimator.EstimatorSpec(\n",
+ " mode=mode,\n",
+ " predictions=pred_classes,\n",
+ " loss=loss_op,\n",
+ " train_op=train_op,\n",
+ " eval_metric_ops={'accuracy': acc_op})\n",
+ "\n",
+ " return estim_specs"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Using default config.\n",
+ "WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmpu7vjLA\n",
+ "INFO:tensorflow:Using config: {'_save_checkpoints_secs': 600, '_session_config': None, '_keep_checkpoint_max': 5, '_tf_random_seed': 1, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': 100, '_save_checkpoints_steps': None, '_model_dir': '/tmp/tmpu7vjLA', '_save_summary_steps': 100}\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Build the Estimator\n",
+ "model = tf.estimator.Estimator(model_fn)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Create CheckpointSaverHook.\n",
+ "INFO:tensorflow:Saving checkpoints for 1 into /tmp/tmpu7vjLA/model.ckpt.\n",
+ "INFO:tensorflow:loss = 2.44919, step = 1\n",
+ "INFO:tensorflow:global_step/sec: 602.544\n",
+ "INFO:tensorflow:loss = 0.344767, step = 101 (0.167 sec)\n",
+ "INFO:tensorflow:global_step/sec: 618.839\n",
+ "INFO:tensorflow:loss = 0.277633, step = 201 (0.162 sec)\n",
+ "INFO:tensorflow:global_step/sec: 626.418\n",
+ "INFO:tensorflow:loss = 0.407796, step = 301 (0.160 sec)\n",
+ "INFO:tensorflow:global_step/sec: 624.765\n",
+ "INFO:tensorflow:loss = 0.376889, step = 401 (0.160 sec)\n",
+ "INFO:tensorflow:global_step/sec: 624.091\n",
+ "INFO:tensorflow:loss = 0.319697, step = 501 (0.160 sec)\n",
+ "INFO:tensorflow:global_step/sec: 616.907\n",
+ "INFO:tensorflow:loss = 0.39049, step = 601 (0.162 sec)\n",
+ "INFO:tensorflow:global_step/sec: 623.371\n",
+ "INFO:tensorflow:loss = 0.336831, step = 701 (0.161 sec)\n",
+ "INFO:tensorflow:global_step/sec: 617.429\n",
+ "INFO:tensorflow:loss = 0.312776, step = 801 (0.162 sec)\n",
+ "INFO:tensorflow:global_step/sec: 620.825\n",
+ "INFO:tensorflow:loss = 0.312817, step = 901 (0.161 sec)\n",
+ "INFO:tensorflow:Saving checkpoints for 1000 into /tmp/tmpu7vjLA/model.ckpt.\n",
+ "INFO:tensorflow:Loss for final step: 0.24931.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Train the Model\n",
+ "model.train(input_fn, steps=num_steps)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Starting evaluation at 2017-08-21-13:57:02\n",
+ "INFO:tensorflow:Restoring parameters from /tmp/tmpu7vjLA/model.ckpt-1000\n",
+ "INFO:tensorflow:Finished evaluation at 2017-08-21-13:57:02\n",
+ "INFO:tensorflow:Saving dict for global step 1000: accuracy = 0.9189, global_step = 1000, loss = 0.286567\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "{'accuracy': 0.91890001, 'global_step': 1000, 'loss': 0.28656715}"
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Evaluate the Model\n",
+ "# Define the input function for evaluating\n",
+ "input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+ " x={'images': mnist.test.images}, y=mnist.test.labels,\n",
+ " batch_size=batch_size, shuffle=False)\n",
+ "# Use the Estimator 'evaluate' method\n",
+ "model.evaluate(input_fn)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Restoring parameters from /tmp/tmpu7vjLA/model.ckpt-1000\n"
+ ]
+ },
+ {
+ "data": {
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+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Model prediction: 7\n"
+ ]
+ },
+ {
+ "data": {
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+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Model prediction: 2\n"
+ ]
+ },
+ {
+ "data": {
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+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Model prediction: 1\n"
+ ]
+ },
+ {
+ "data": {
+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAP8AAAD8CAYAAAC4nHJkAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nZZUAAAAASUVORK5CYII=\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Model prediction: 0\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Predict single images\n",
+ "n_images = 4\n",
+ "# Get images from test set\n",
+ "test_images = mnist.test.images[:n_images]\n",
+ "# Prepare the input data\n",
+ "input_fn = tf.estimator.inputs.numpy_input_fn(\n",
+ " x={'images': test_images}, shuffle=False)\n",
+ "# Use the model to predict the images class\n",
+ "preds = list(model.predict(input_fn))\n",
+ "\n",
+ "# Display\n",
+ "for i in range(n_images):\n",
+ " plt.imshow(np.reshape(test_images[i], [28, 28]), cmap='gray')\n",
+ " plt.show()\n",
+ " print(\"Model prediction:\", preds[i])"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network_eager_api.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network_eager_api.ipynb
new file mode 100644
index 00000000..dc421361
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network_eager_api.ipynb
@@ -0,0 +1,287 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Neural Network with Eager API\n",
+ "\n",
+ "Build a 2-hidden layers fully connected neural network (a.k.a multilayer perceptron) with TensorFlow's Eager API.\n",
+ "\n",
+ "This example is using some of TensorFlow higher-level wrappers (tf.estimators, tf.layers, tf.metrics, ...), you can check 'neural_network_raw' example for a raw, and more detailed TensorFlow implementation.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Neural Network Overview\n",
+ "\n",
+ "
\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Set Eager API\n",
+ "tf.enable_eager_execution()\n",
+ "tfe = tf.contrib.eager"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=False)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.001\n",
+ "num_steps = 1000\n",
+ "batch_size = 128\n",
+ "display_step = 100\n",
+ "\n",
+ "# Network Parameters\n",
+ "n_hidden_1 = 256 # 1st layer number of neurons\n",
+ "n_hidden_2 = 256 # 2nd layer number of neurons\n",
+ "num_input = 784 # MNIST data input (img shape: 28*28)\n",
+ "num_classes = 10 # MNIST total classes (0-9 digits)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Using TF Dataset to split data into batches\n",
+ "dataset = tf.data.Dataset.from_tensor_slices(\n",
+ " (mnist.train.images, mnist.train.labels))\n",
+ "dataset = dataset.repeat().batch(batch_size).prefetch(batch_size)\n",
+ "dataset_iter = tfe.Iterator(dataset)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Define the neural network. To use eager API and tf.layers API together,\n",
+ "# we must instantiate a tfe.Network class as follow:\n",
+ "class NeuralNet(tfe.Network):\n",
+ " def __init__(self):\n",
+ " # Define each layer\n",
+ " super(NeuralNet, self).__init__()\n",
+ " # Hidden fully connected layer with 256 neurons\n",
+ " self.layer1 = self.track_layer(\n",
+ " tf.layers.Dense(n_hidden_1, activation=tf.nn.relu))\n",
+ " # Hidden fully connected layer with 256 neurons\n",
+ " self.layer2 = self.track_layer(\n",
+ " tf.layers.Dense(n_hidden_2, activation=tf.nn.relu))\n",
+ " # Output fully connected layer with a neuron for each class\n",
+ " self.out_layer = self.track_layer(tf.layers.Dense(num_classes))\n",
+ "\n",
+ " def call(self, x):\n",
+ " x = self.layer1(x)\n",
+ " x = self.layer2(x)\n",
+ " return self.out_layer(x)\n",
+ "\n",
+ "\n",
+ "neural_net = NeuralNet()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Cross-Entropy loss function\n",
+ "def loss_fn(inference_fn, inputs, labels):\n",
+ " # Using sparse_softmax cross entropy\n",
+ " return tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(\n",
+ " logits=inference_fn(inputs), labels=labels))\n",
+ "\n",
+ "\n",
+ "# Calculate accuracy\n",
+ "def accuracy_fn(inference_fn, inputs, labels):\n",
+ " prediction = tf.nn.softmax(inference_fn(inputs))\n",
+ " correct_pred = tf.equal(tf.argmax(prediction, 1), labels)\n",
+ " return tf.reduce_mean(tf.cast(correct_pred, tf.float32))\n",
+ "\n",
+ "\n",
+ "# SGD Optimizer\n",
+ "optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
+ "\n",
+ "# Compute gradients\n",
+ "grad = tfe.implicit_gradients(loss_fn)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Initial loss= 2.340397596\n",
+ "Step: 0001 loss= 2.340397596 accuracy= 0.0703\n",
+ "Step: 0100 loss= 0.586046159 accuracy= 0.8305\n",
+ "Step: 0200 loss= 0.253318846 accuracy= 0.9282\n",
+ "Step: 0300 loss= 0.214748293 accuracy= 0.9377\n",
+ "Step: 0400 loss= 0.180644721 accuracy= 0.9466\n",
+ "Step: 0500 loss= 0.137285724 accuracy= 0.9591\n",
+ "Step: 0600 loss= 0.119845696 accuracy= 0.9636\n",
+ "Step: 0700 loss= 0.113618039 accuracy= 0.9665\n",
+ "Step: 0800 loss= 0.109642141 accuracy= 0.9676\n",
+ "Step: 0900 loss= 0.085067607 accuracy= 0.9746\n",
+ "Step: 1000 loss= 0.079819344 accuracy= 0.9754\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Training\n",
+ "average_loss = 0.\n",
+ "average_acc = 0.\n",
+ "for step in range(num_steps):\n",
+ "\n",
+ " # Iterate through the dataset\n",
+ " d = dataset_iter.next()\n",
+ " \n",
+ " # Images\n",
+ " x_batch = d[0]\n",
+ " # Labels\n",
+ " y_batch = tf.cast(d[1], dtype=tf.int64)\n",
+ "\n",
+ " # Compute the batch loss\n",
+ " batch_loss = loss_fn(neural_net, x_batch, y_batch)\n",
+ " average_loss += batch_loss\n",
+ " # Compute the batch accuracy\n",
+ " batch_accuracy = accuracy_fn(neural_net, x_batch, y_batch)\n",
+ " average_acc += batch_accuracy\n",
+ "\n",
+ " if step == 0:\n",
+ " # Display the initial cost, before optimizing\n",
+ " print(\"Initial loss= {:.9f}\".format(average_loss))\n",
+ "\n",
+ " # Update the variables following gradients info\n",
+ " optimizer.apply_gradients(grad(neural_net, x_batch, y_batch))\n",
+ "\n",
+ " # Display info\n",
+ " if (step + 1) % display_step == 0 or step == 0:\n",
+ " if step > 0:\n",
+ " average_loss /= display_step\n",
+ " average_acc /= display_step\n",
+ " print(\"Step:\", '%04d' % (step + 1), \" loss=\",\n",
+ " \"{:.9f}\".format(average_loss), \" accuracy=\",\n",
+ " \"{:.4f}\".format(average_acc))\n",
+ " average_loss = 0.\n",
+ " average_acc = 0."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Testset Accuracy: 0.9719\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Evaluate model on the test image set\n",
+ "testX = mnist.test.images\n",
+ "testY = mnist.test.labels\n",
+ "\n",
+ "test_acc = accuracy_fn(neural_net, testX, testY)\n",
+ "print(\"Testset Accuracy: {:.4f}\".format(test_acc))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.14"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network_raw.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network_raw.ipynb
new file mode 100644
index 00000000..57f259eb
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/neural_network_raw.ipynb
@@ -0,0 +1,224 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Neural Network Example\n",
+ "\n",
+ "Build a 2-hidden layers fully connected neural network (a.k.a multilayer perceptron) with TensorFlow.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Neural Network Overview\n",
+ "\n",
+ "
\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)\n",
+ "\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.1\n",
+ "num_steps = 500\n",
+ "batch_size = 128\n",
+ "display_step = 100\n",
+ "\n",
+ "# Network Parameters\n",
+ "n_hidden_1 = 256 # 1st layer number of neurons\n",
+ "n_hidden_2 = 256 # 2nd layer number of neurons\n",
+ "num_input = 784 # MNIST data input (img shape: 28*28)\n",
+ "num_classes = 10 # MNIST total classes (0-9 digits)\n",
+ "\n",
+ "# tf Graph input\n",
+ "X = tf.placeholder(\"float\", [None, num_input])\n",
+ "Y = tf.placeholder(\"float\", [None, num_classes])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Store layers weight & bias\n",
+ "weights = {\n",
+ " 'h1': tf.Variable(tf.random_normal([num_input, n_hidden_1])),\n",
+ " 'h2': tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2])),\n",
+ " 'out': tf.Variable(tf.random_normal([n_hidden_2, num_classes]))\n",
+ "}\n",
+ "biases = {\n",
+ " 'b1': tf.Variable(tf.random_normal([n_hidden_1])),\n",
+ " 'b2': tf.Variable(tf.random_normal([n_hidden_2])),\n",
+ " 'out': tf.Variable(tf.random_normal([num_classes]))\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Create model\n",
+ "def neural_net(x):\n",
+ " # Hidden fully connected layer with 256 neurons\n",
+ " layer_1 = tf.add(tf.matmul(x, weights['h1']), biases['b1'])\n",
+ " # Hidden fully connected layer with 256 neurons\n",
+ " layer_2 = tf.add(tf.matmul(layer_1, weights['h2']), biases['b2'])\n",
+ " # Output fully connected layer with a neuron for each class\n",
+ " out_layer = tf.matmul(layer_2, weights['out']) + biases['out']\n",
+ " return out_layer"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Construct model\n",
+ "logits = neural_net(X)\n",
+ "\n",
+ "# Define loss and optimizer\n",
+ "loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(\n",
+ " logits=logits, labels=Y))\n",
+ "optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
+ "train_op = optimizer.minimize(loss_op)\n",
+ "\n",
+ "# Evaluate model (with test logits, for dropout to be disabled)\n",
+ "correct_pred = tf.equal(tf.argmax(logits, 1), tf.argmax(Y, 1))\n",
+ "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1, Minibatch Loss= 13208.1406, Training Accuracy= 0.266\n",
+ "Step 100, Minibatch Loss= 462.8610, Training Accuracy= 0.867\n",
+ "Step 200, Minibatch Loss= 232.8298, Training Accuracy= 0.844\n",
+ "Step 300, Minibatch Loss= 85.2141, Training Accuracy= 0.891\n",
+ "Step 400, Minibatch Loss= 38.0552, Training Accuracy= 0.883\n",
+ "Step 500, Minibatch Loss= 55.3689, Training Accuracy= 0.867\n",
+ "Optimization Finished!\n",
+ "Testing Accuracy: 0.8729\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start training\n",
+ "with tf.Session() as sess:\n",
+ "\n",
+ " # Run the initializer\n",
+ " sess.run(init)\n",
+ "\n",
+ " for step in range(1, num_steps+1):\n",
+ " batch_x, batch_y = mnist.train.next_batch(batch_size)\n",
+ " # Run optimization op (backprop)\n",
+ " sess.run(train_op, feed_dict={X: batch_x, Y: batch_y})\n",
+ " if step % display_step == 0 or step == 1:\n",
+ " # Calculate batch loss and accuracy\n",
+ " loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,\n",
+ " Y: batch_y})\n",
+ " print(\"Step \" + str(step) + \", Minibatch Loss= \" + \\\n",
+ " \"{:.4f}\".format(loss) + \", Training Accuracy= \" + \\\n",
+ " \"{:.3f}\".format(acc))\n",
+ "\n",
+ " print(\"Optimization Finished!\")\n",
+ "\n",
+ " # Calculate accuracy for MNIST test images\n",
+ " print(\"Testing Accuracy:\", \\\n",
+ " sess.run(accuracy, feed_dict={X: mnist.test.images,\n",
+ " Y: mnist.test.labels}))"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.13"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/recurrent_network.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/recurrent_network.ipynb
new file mode 100644
index 00000000..1165ac59
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/recurrent_network.ipynb
@@ -0,0 +1,292 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Recurrent Neural Network Example\n",
+ "\n",
+ "Build a recurrent neural network (LSTM) with TensorFlow.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## RNN Overview\n",
+ "\n",
+ "
\n",
+ "\n",
+ "References:\n",
+ "- [Long Short Term Memory](http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf), Sepp Hochreiter & Jurgen Schmidhuber, Neural Computation 9(8): 1735-1780, 1997.\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "To classify images using a recurrent neural network, we consider every image row as a sequence of pixels. Because MNIST image shape is 28*28px, we will then handle 28 sequences of 28 timesteps for every sample.\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "from tensorflow.contrib import rnn\n",
+ "\n",
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Training Parameters\n",
+ "learning_rate = 0.001\n",
+ "training_steps = 10000\n",
+ "batch_size = 128\n",
+ "display_step = 200\n",
+ "\n",
+ "# Network Parameters\n",
+ "num_input = 28 # MNIST data input (img shape: 28*28)\n",
+ "timesteps = 28 # timesteps\n",
+ "num_hidden = 128 # hidden layer num of features\n",
+ "num_classes = 10 # MNIST total classes (0-9 digits)\n",
+ "\n",
+ "# tf Graph input\n",
+ "X = tf.placeholder(\"float\", [None, timesteps, num_input])\n",
+ "Y = tf.placeholder(\"float\", [None, num_classes])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Define weights\n",
+ "weights = {\n",
+ " 'out': tf.Variable(tf.random_normal([num_hidden, num_classes]))\n",
+ "}\n",
+ "biases = {\n",
+ " 'out': tf.Variable(tf.random_normal([num_classes]))\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "def RNN(x, weights, biases):\n",
+ "\n",
+ " # Prepare data shape to match `rnn` function requirements\n",
+ " # Current data input shape: (batch_size, timesteps, n_input)\n",
+ " # Required shape: 'timesteps' tensors list of shape (batch_size, n_input)\n",
+ "\n",
+ " # Unstack to get a list of 'timesteps' tensors of shape (batch_size, n_input)\n",
+ " x = tf.unstack(x, timesteps, 1)\n",
+ "\n",
+ " # Define a lstm cell with tensorflow\n",
+ " lstm_cell = rnn.BasicLSTMCell(num_hidden, forget_bias=1.0)\n",
+ "\n",
+ " # Get lstm cell output\n",
+ " outputs, states = rnn.static_rnn(lstm_cell, x, dtype=tf.float32)\n",
+ "\n",
+ " # Linear activation, using rnn inner loop last output\n",
+ " return tf.matmul(outputs[-1], weights['out']) + biases['out']"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "logits = RNN(X, weights, biases)\n",
+ "prediction = tf.nn.softmax(logits)\n",
+ "\n",
+ "# Define loss and optimizer\n",
+ "loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(\n",
+ " logits=logits, labels=Y))\n",
+ "optimizer = tf.train.GradientDescentOptimizer(learning_rate=learning_rate)\n",
+ "train_op = optimizer.minimize(loss_op)\n",
+ "\n",
+ "# Evaluate model (with test logits, for dropout to be disabled)\n",
+ "correct_pred = tf.equal(tf.argmax(prediction, 1), tf.argmax(Y, 1))\n",
+ "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1, Minibatch Loss= 2.6268, Training Accuracy= 0.102\n",
+ "Step 200, Minibatch Loss= 2.0722, Training Accuracy= 0.328\n",
+ "Step 400, Minibatch Loss= 1.9181, Training Accuracy= 0.336\n",
+ "Step 600, Minibatch Loss= 1.8858, Training Accuracy= 0.336\n",
+ "Step 800, Minibatch Loss= 1.7022, Training Accuracy= 0.422\n",
+ "Step 1000, Minibatch Loss= 1.6365, Training Accuracy= 0.477\n",
+ "Step 1200, Minibatch Loss= 1.6691, Training Accuracy= 0.516\n",
+ "Step 1400, Minibatch Loss= 1.4626, Training Accuracy= 0.547\n",
+ "Step 1600, Minibatch Loss= 1.4707, Training Accuracy= 0.539\n",
+ "Step 1800, Minibatch Loss= 1.4087, Training Accuracy= 0.570\n",
+ "Step 2000, Minibatch Loss= 1.3033, Training Accuracy= 0.570\n",
+ "Step 2200, Minibatch Loss= 1.3773, Training Accuracy= 0.508\n",
+ "Step 2400, Minibatch Loss= 1.3092, Training Accuracy= 0.570\n",
+ "Step 2600, Minibatch Loss= 1.2272, Training Accuracy= 0.609\n",
+ "Step 2800, Minibatch Loss= 1.1827, Training Accuracy= 0.633\n",
+ "Step 3000, Minibatch Loss= 1.0453, Training Accuracy= 0.641\n",
+ "Step 3200, Minibatch Loss= 1.0400, Training Accuracy= 0.648\n",
+ "Step 3400, Minibatch Loss= 1.1145, Training Accuracy= 0.656\n",
+ "Step 3600, Minibatch Loss= 0.9884, Training Accuracy= 0.688\n",
+ "Step 3800, Minibatch Loss= 1.0395, Training Accuracy= 0.703\n",
+ "Step 4000, Minibatch Loss= 1.0096, Training Accuracy= 0.664\n",
+ "Step 4200, Minibatch Loss= 0.8806, Training Accuracy= 0.758\n",
+ "Step 4400, Minibatch Loss= 0.9090, Training Accuracy= 0.766\n",
+ "Step 4600, Minibatch Loss= 1.0060, Training Accuracy= 0.703\n",
+ "Step 4800, Minibatch Loss= 0.8954, Training Accuracy= 0.703\n",
+ "Step 5000, Minibatch Loss= 0.8163, Training Accuracy= 0.750\n",
+ "Step 5200, Minibatch Loss= 0.7620, Training Accuracy= 0.773\n",
+ "Step 5400, Minibatch Loss= 0.7388, Training Accuracy= 0.758\n",
+ "Step 5600, Minibatch Loss= 0.7604, Training Accuracy= 0.695\n",
+ "Step 5800, Minibatch Loss= 0.7459, Training Accuracy= 0.734\n",
+ "Step 6000, Minibatch Loss= 0.7448, Training Accuracy= 0.734\n",
+ "Step 6200, Minibatch Loss= 0.7208, Training Accuracy= 0.773\n",
+ "Step 6400, Minibatch Loss= 0.6557, Training Accuracy= 0.773\n",
+ "Step 6600, Minibatch Loss= 0.8616, Training Accuracy= 0.758\n",
+ "Step 6800, Minibatch Loss= 0.6089, Training Accuracy= 0.773\n",
+ "Step 7000, Minibatch Loss= 0.5020, Training Accuracy= 0.844\n",
+ "Step 7200, Minibatch Loss= 0.5980, Training Accuracy= 0.812\n",
+ "Step 7400, Minibatch Loss= 0.6786, Training Accuracy= 0.766\n",
+ "Step 7600, Minibatch Loss= 0.4891, Training Accuracy= 0.859\n",
+ "Step 7800, Minibatch Loss= 0.7042, Training Accuracy= 0.797\n",
+ "Step 8000, Minibatch Loss= 0.4200, Training Accuracy= 0.859\n",
+ "Step 8200, Minibatch Loss= 0.6442, Training Accuracy= 0.742\n",
+ "Step 8400, Minibatch Loss= 0.5569, Training Accuracy= 0.828\n",
+ "Step 8600, Minibatch Loss= 0.5838, Training Accuracy= 0.836\n",
+ "Step 8800, Minibatch Loss= 0.5579, Training Accuracy= 0.812\n",
+ "Step 9000, Minibatch Loss= 0.4337, Training Accuracy= 0.867\n",
+ "Step 9200, Minibatch Loss= 0.4366, Training Accuracy= 0.844\n",
+ "Step 9400, Minibatch Loss= 0.5051, Training Accuracy= 0.844\n",
+ "Step 9600, Minibatch Loss= 0.5244, Training Accuracy= 0.805\n",
+ "Step 9800, Minibatch Loss= 0.4932, Training Accuracy= 0.805\n",
+ "Step 10000, Minibatch Loss= 0.4833, Training Accuracy= 0.852\n",
+ "Optimization Finished!\n",
+ "Testing Accuracy: 0.882812\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start training\n",
+ "with tf.Session() as sess:\n",
+ "\n",
+ " # Run the initializer\n",
+ " sess.run(init)\n",
+ "\n",
+ " for step in range(1, training_steps+1):\n",
+ " batch_x, batch_y = mnist.train.next_batch(batch_size)\n",
+ " # Reshape data to get 28 seq of 28 elements\n",
+ " batch_x = batch_x.reshape((batch_size, timesteps, num_input))\n",
+ " # Run optimization op (backprop)\n",
+ " sess.run(train_op, feed_dict={X: batch_x, Y: batch_y})\n",
+ " if step % display_step == 0 or step == 1:\n",
+ " # Calculate batch loss and accuracy\n",
+ " loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,\n",
+ " Y: batch_y})\n",
+ " print(\"Step \" + str(step) + \", Minibatch Loss= \" + \\\n",
+ " \"{:.4f}\".format(loss) + \", Training Accuracy= \" + \\\n",
+ " \"{:.3f}\".format(acc))\n",
+ "\n",
+ " print(\"Optimization Finished!\")\n",
+ "\n",
+ " # Calculate accuracy for 128 mnist test images\n",
+ " test_len = 128\n",
+ " test_data = mnist.test.images[:test_len].reshape((-1, timesteps, num_input))\n",
+ " test_label = mnist.test.labels[:test_len]\n",
+ " print(\"Testing Accuracy:\", \\\n",
+ " sess.run(accuracy, feed_dict={X: test_data, Y: test_label}))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/3_NeuralNetworks/variational_autoencoder.ipynb b/tensorflow_v1/notebooks/3_NeuralNetworks/variational_autoencoder.ipynb
new file mode 100644
index 00000000..1e4d58bb
--- /dev/null
+++ b/tensorflow_v1/notebooks/3_NeuralNetworks/variational_autoencoder.ipynb
@@ -0,0 +1,316 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Variational Auto-Encoder Example\n",
+ "\n",
+ "Build a variational auto-encoder (VAE) to generate digit images from a noise distribution with TensorFlow.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## VAE Overview\n",
+ "\n",
+ "
\n",
+ "\n",
+ "References:\n",
+ "- [Auto-Encoding Variational Bayes The International Conference on Learning Representations](https://arxiv.org/abs/1312.6114) (ICLR), Banff, 2014. D.P. Kingma, M. Welling\n",
+ "- [Understanding the difficulty of training deep feedforward neural networks](www.cs.cmu.edu/~bhiksha/courses/deeplearning/Fall.../AISTATS2010_Glorot.pdf). X Glorot, Y Bengio. Aistats 9, 249-256\n",
+ "\n",
+ "Other tutorials:\n",
+ "- [Variational Auto Encoder Explained](http://kvfrans.com/variational-autoencoders-explained/). Kevin Frans.\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flattened and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import division, print_function, absolute_import\n",
+ "\n",
+ "import numpy as np\n",
+ "import matplotlib.pyplot as plt\n",
+ "from scipy.stats import norm\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Successfully downloaded train-images-idx3-ubyte.gz 9912422 bytes.\n",
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Successfully downloaded train-labels-idx1-ubyte.gz 28881 bytes.\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Successfully downloaded t10k-images-idx3-ubyte.gz 1648877 bytes.\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Successfully downloaded t10k-labels-idx1-ubyte.gz 4542 bytes.\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.001\n",
+ "num_steps = 30000\n",
+ "batch_size = 64\n",
+ "\n",
+ "# Network Parameters\n",
+ "image_dim = 784 # MNIST images are 28x28 pixels\n",
+ "hidden_dim = 512\n",
+ "latent_dim = 2\n",
+ "\n",
+ "# A custom initialization (see Xavier Glorot init)\n",
+ "def glorot_init(shape):\n",
+ " return tf.random_normal(shape=shape, stddev=1. / tf.sqrt(shape[0] / 2.))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Variables\n",
+ "weights = {\n",
+ " 'encoder_h1': tf.Variable(glorot_init([image_dim, hidden_dim])),\n",
+ " 'z_mean': tf.Variable(glorot_init([hidden_dim, latent_dim])),\n",
+ " 'z_std': tf.Variable(glorot_init([hidden_dim, latent_dim])),\n",
+ " 'decoder_h1': tf.Variable(glorot_init([latent_dim, hidden_dim])),\n",
+ " 'decoder_out': tf.Variable(glorot_init([hidden_dim, image_dim]))\n",
+ "}\n",
+ "biases = {\n",
+ " 'encoder_b1': tf.Variable(glorot_init([hidden_dim])),\n",
+ " 'z_mean': tf.Variable(glorot_init([latent_dim])),\n",
+ " 'z_std': tf.Variable(glorot_init([latent_dim])),\n",
+ " 'decoder_b1': tf.Variable(glorot_init([hidden_dim])),\n",
+ " 'decoder_out': tf.Variable(glorot_init([image_dim]))\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Building the encoder\n",
+ "input_image = tf.placeholder(tf.float32, shape=[None, image_dim])\n",
+ "encoder = tf.matmul(input_image, weights['encoder_h1']) + biases['encoder_b1']\n",
+ "encoder = tf.nn.tanh(encoder)\n",
+ "z_mean = tf.matmul(encoder, weights['z_mean']) + biases['z_mean']\n",
+ "z_std = tf.matmul(encoder, weights['z_std']) + biases['z_std']\n",
+ "\n",
+ "# Sampler: Normal (gaussian) random distribution\n",
+ "eps = tf.random_normal(tf.shape(z_std), dtype=tf.float32, mean=0., stddev=1.0,\n",
+ " name='epsilon')\n",
+ "z = z_mean + tf.exp(z_std / 2) * eps\n",
+ "\n",
+ "# Building the decoder (with scope to re-use these layers later)\n",
+ "decoder = tf.matmul(z, weights['decoder_h1']) + biases['decoder_b1']\n",
+ "decoder = tf.nn.tanh(decoder)\n",
+ "decoder = tf.matmul(decoder, weights['decoder_out']) + biases['decoder_out']\n",
+ "decoder = tf.nn.sigmoid(decoder)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Define VAE Loss\n",
+ "def vae_loss(x_reconstructed, x_true):\n",
+ " # Reconstruction loss\n",
+ " encode_decode_loss = x_true * tf.log(1e-10 + x_reconstructed) \\\n",
+ " + (1 - x_true) * tf.log(1e-10 + 1 - x_reconstructed)\n",
+ " encode_decode_loss = -tf.reduce_sum(encode_decode_loss, 1)\n",
+ " # KL Divergence loss\n",
+ " kl_div_loss = 1 + z_std - tf.square(z_mean) - tf.exp(z_std)\n",
+ " kl_div_loss = -0.5 * tf.reduce_sum(kl_div_loss, 1)\n",
+ " return tf.reduce_mean(encode_decode_loss + kl_div_loss)\n",
+ "\n",
+ "loss_op = vae_loss(decoder, input_image)\n",
+ "optimizer = tf.train.RMSPropOptimizer(learning_rate=learning_rate)\n",
+ "train_op = optimizer.minimize(loss_op)\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1, Loss: 645.076538\n",
+ "Step 1000, Loss: 173.018188\n",
+ "Step 2000, Loss: 165.299225\n",
+ "Step 3000, Loss: 172.933685\n",
+ "Step 4000, Loss: 161.475052\n",
+ "Step 5000, Loss: 179.529831\n",
+ "Step 6000, Loss: 166.430023\n",
+ "Step 7000, Loss: 167.152176\n",
+ "Step 8000, Loss: 159.920242\n",
+ "Step 9000, Loss: 160.172363\n",
+ "Step 10000, Loss: 150.077652\n",
+ "Step 11000, Loss: 162.774567\n",
+ "Step 12000, Loss: 156.187820\n",
+ "Step 13000, Loss: 148.331573\n",
+ "Step 14000, Loss: 153.757202\n",
+ "Step 15000, Loss: 158.050598\n",
+ "Step 16000, Loss: 163.068939\n",
+ "Step 17000, Loss: 152.765152\n",
+ "Step 18000, Loss: 151.136353\n",
+ "Step 19000, Loss: 157.889664\n",
+ "Step 20000, Loss: 149.112473\n",
+ "Step 21000, Loss: 151.694885\n",
+ "Step 22000, Loss: 153.153229\n",
+ "Step 23000, Loss: 152.662323\n",
+ "Step 24000, Loss: 150.556198\n",
+ "Step 25000, Loss: 142.779984\n",
+ "Step 26000, Loss: 148.985382\n",
+ "Step 27000, Loss: 150.923401\n",
+ "Step 28000, Loss: 161.761551\n",
+ "Step 29000, Loss: 144.045578\n",
+ "Step 30000, Loss: 151.272964\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start Training\n",
+ "# Start a new TF session\n",
+ "sess = tf.Session()\n",
+ "\n",
+ "# Run the initializer\n",
+ "sess.run(init)\n",
+ "\n",
+ "# Training\n",
+ "for i in range(1, num_steps+1):\n",
+ " # Prepare Data\n",
+ " # Get the next batch of MNIST data (only images are needed, not labels)\n",
+ " batch_x, _ = mnist.train.next_batch(batch_size)\n",
+ "\n",
+ " # Train\n",
+ " feed_dict = {input_image: batch_x}\n",
+ " _, l = sess.run([train_op, loss_op], feed_dict=feed_dict)\n",
+ " if i % 1000 == 0 or i == 1:\n",
+ " print('Step %i, Loss: %f' % (i, l))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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R6/XU19eza9cuqqqquHv37oae72pDTavV8vTTT/P4449z+PBhCgsLSSaTTE5Oyjv5pZde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WBggFWIqHKSyWSYYrXYjSwWi/Hcc8/h8ccfh9FoxKVLl3D+/Pn7CICIa5h6h8UGFyqV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19XXek4PqLvsPWUtLC7q6ujA4OMgXJRnparUKn88Hj8eDfD7P5BiNDjOB6+t0OoyPj0Or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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "# Testing\n",
+ "# Generator takes noise as input\n",
+ "noise_input = tf.placeholder(tf.float32, shape=[None, latent_dim])\n",
+ "# Rebuild the decoder to create image from noise\n",
+ "decoder = tf.matmul(noise_input, weights['decoder_h1']) + biases['decoder_b1']\n",
+ "decoder = tf.nn.tanh(decoder)\n",
+ "decoder = tf.matmul(decoder, weights['decoder_out']) + biases['decoder_out']\n",
+ "decoder = tf.nn.sigmoid(decoder)\n",
+ "\n",
+ "# Building a manifold of generated digits\n",
+ "n = 20\n",
+ "x_axis = np.linspace(-3, 3, n)\n",
+ "y_axis = np.linspace(-3, 3, n)\n",
+ "\n",
+ "canvas = np.empty((28 * n, 28 * n))\n",
+ "for i, yi in enumerate(x_axis):\n",
+ " for j, xi in enumerate(y_axis):\n",
+ " z_mu = np.array([[xi, yi]] * batch_size)\n",
+ " x_mean = sess.run(decoder, feed_dict={noise_input: z_mu})\n",
+ " canvas[(n - i - 1) * 28:(n - i) * 28, j * 28:(j + 1) * 28] = \\\n",
+ " x_mean[0].reshape(28, 28)\n",
+ "\n",
+ "plt.figure(figsize=(8, 10))\n",
+ "Xi, Yi = np.meshgrid(x_axis, y_axis)\n",
+ "plt.imshow(canvas, origin=\"upper\", cmap=\"gray\")\n",
+ "plt.show()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v1/notebooks/4_Utils/save_restore_model.ipynb b/tensorflow_v1/notebooks/4_Utils/save_restore_model.ipynb
new file mode 100644
index 00000000..62a381df
--- /dev/null
+++ b/tensorflow_v1/notebooks/4_Utils/save_restore_model.ipynb
@@ -0,0 +1,252 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Save & Restore a Model\n",
+ "\n",
+ "Save and Restore a model using TensorFlow.\n",
+ "This example is using the MNIST database of handwritten digits\n",
+ "(http://yann.lecun.com/exdb/mnist/).\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting MNIST_data/train-images-idx3-ubyte.gz\n",
+ "Extracting MNIST_data/train-labels-idx1-ubyte.gz\n",
+ "Extracting MNIST_data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting MNIST_data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "# Import MINST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"MNIST_data/\", one_hot=True)\n",
+ "\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.001\n",
+ "batch_size = 100\n",
+ "display_step = 1\n",
+ "model_path = \"/tmp/model.ckpt\"\n",
+ "\n",
+ "# Network Parameters\n",
+ "n_hidden_1 = 256 # 1st layer number of features\n",
+ "n_hidden_2 = 256 # 2nd layer number of features\n",
+ "n_input = 784 # MNIST data input (img shape: 28*28)\n",
+ "n_classes = 10 # MNIST total classes (0-9 digits)\n",
+ "\n",
+ "# tf Graph input\n",
+ "x = tf.placeholder(\"float\", [None, n_input])\n",
+ "y = tf.placeholder(\"float\", [None, n_classes])\n",
+ "\n",
+ "\n",
+ "# Create model\n",
+ "def multilayer_perceptron(x, weights, biases):\n",
+ " # Hidden layer with RELU activation\n",
+ " layer_1 = tf.add(tf.matmul(x, weights['h1']), biases['b1'])\n",
+ " layer_1 = tf.nn.relu(layer_1)\n",
+ " # Hidden layer with RELU activation\n",
+ " layer_2 = tf.add(tf.matmul(layer_1, weights['h2']), biases['b2'])\n",
+ " layer_2 = tf.nn.relu(layer_2)\n",
+ " # Output layer with linear activation\n",
+ " out_layer = tf.matmul(layer_2, weights['out']) + biases['out']\n",
+ " return out_layer\n",
+ "\n",
+ "# Store layers weight & bias\n",
+ "weights = {\n",
+ " 'h1': tf.Variable(tf.random_normal([n_input, n_hidden_1])),\n",
+ " 'h2': tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2])),\n",
+ " 'out': tf.Variable(tf.random_normal([n_hidden_2, n_classes]))\n",
+ "}\n",
+ "biases = {\n",
+ " 'b1': tf.Variable(tf.random_normal([n_hidden_1])),\n",
+ " 'b2': tf.Variable(tf.random_normal([n_hidden_2])),\n",
+ " 'out': tf.Variable(tf.random_normal([n_classes]))\n",
+ "}\n",
+ "\n",
+ "# Construct model\n",
+ "pred = multilayer_perceptron(x, weights, biases)\n",
+ "\n",
+ "# Define loss and optimizer\n",
+ "cost = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=pred, labels=y))\n",
+ "optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate).minimize(cost)\n",
+ "\n",
+ "# Initializing the variables\n",
+ "init = tf.global_variables_initializer()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# 'Saver' op to save and restore all the variables\n",
+ "saver = tf.train.Saver()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Starting 1st session...\n",
+ "Epoch: 0001 cost= 187.778896380\n",
+ "Epoch: 0002 cost= 42.367902536\n",
+ "Epoch: 0003 cost= 26.488964058\n",
+ "First Optimization Finished!\n",
+ "Accuracy: 0.9075\n",
+ "Model saved in file: /tmp/model.ckpt\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Running first session\n",
+ "print(\"Starting 1st session...\")\n",
+ "with tf.Session() as sess:\n",
+ " # Initialize variables\n",
+ " sess.run(init)\n",
+ "\n",
+ " # Training cycle\n",
+ " for epoch in range(3):\n",
+ " avg_cost = 0.\n",
+ " total_batch = int(mnist.train.num_examples/batch_size)\n",
+ " # Loop over all batches\n",
+ " for i in range(total_batch):\n",
+ " batch_x, batch_y = mnist.train.next_batch(batch_size)\n",
+ " # Run optimization op (backprop) and cost op (to get loss value)\n",
+ " _, c = sess.run([optimizer, cost], feed_dict={x: batch_x,\n",
+ " y: batch_y})\n",
+ " # Compute average loss\n",
+ " avg_cost += c / total_batch\n",
+ " # Display logs per epoch step\n",
+ " if epoch % display_step == 0:\n",
+ " print \"Epoch:\", '%04d' % (epoch+1), \"cost=\", \\\n",
+ " \"{:.9f}\".format(avg_cost)\n",
+ " print(\"First Optimization Finished!\")\n",
+ "\n",
+ " # Test model\n",
+ " correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))\n",
+ " # Calculate accuracy\n",
+ " accuracy = tf.reduce_mean(tf.cast(correct_prediction, \"float\"))\n",
+ " print(\"Accuracy:\", accuracy.eval({x: mnist.test.images, y: mnist.test.labels}))\n",
+ "\n",
+ " # Save model weights to disk\n",
+ " save_path = saver.save(sess, model_path)\n",
+ " print(\"Model saved in file: %s\" % save_path)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Starting 2nd session...\n",
+ "Model restored from file: /tmp/model.ckpt\n",
+ "Epoch: 0001 cost= 18.292712951\n",
+ "Epoch: 0002 cost= 13.404136196\n",
+ "Epoch: 0003 cost= 9.855191723\n",
+ "Epoch: 0004 cost= 7.276933088\n",
+ "Epoch: 0005 cost= 5.564581285\n",
+ "Epoch: 0006 cost= 4.165259939\n",
+ "Epoch: 0007 cost= 3.139393926\n",
+ "Second Optimization Finished!\n",
+ "Accuracy: 0.9385\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Running a new session\n",
+ "print(\"Starting 2nd session...\")\n",
+ "with tf.Session() as sess:\n",
+ " # Initialize variables\n",
+ " sess.run(init)\n",
+ "\n",
+ " # Restore model weights from previously saved model\n",
+ " load_path = saver.restore(sess, model_path)\n",
+ " print(\"Model restored from file: %s\" % save_path)\n",
+ "\n",
+ " # Resume training\n",
+ " for epoch in range(7):\n",
+ " avg_cost = 0.\n",
+ " total_batch = int(mnist.train.num_examples / batch_size)\n",
+ " # Loop over all batches\n",
+ " for i in range(total_batch):\n",
+ " batch_x, batch_y = mnist.train.next_batch(batch_size)\n",
+ " # Run optimization op (backprop) and cost op (to get loss value)\n",
+ " _, c = sess.run([optimizer, cost], feed_dict={x: batch_x,\n",
+ " y: batch_y})\n",
+ " # Compute average loss\n",
+ " avg_cost += c / total_batch\n",
+ " # Display logs per epoch step\n",
+ " if epoch % display_step == 0:\n",
+ " print(\"Epoch:\", '%04d' % (epoch + 1), \"cost=\", \\\n",
+ " \"{:.9f}\".format(avg_cost))\n",
+ " print(\"Second Optimization Finished!\")\n",
+ "\n",
+ " # Test model\n",
+ " correct_prediction = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))\n",
+ " # Calculate accuracy\n",
+ " accuracy = tf.reduce_mean(tf.cast(correct_prediction, \"float\"))\n",
+ " print(\"Accuracy:\", accuracy.eval(\n",
+ " {x: mnist.test.images, y: mnist.test.labels}))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/4_Utils/tensorboard_advanced.ipynb b/tensorflow_v1/notebooks/4_Utils/tensorboard_advanced.ipynb
new file mode 100644
index 00000000..fa869b5b
--- /dev/null
+++ b/tensorflow_v1/notebooks/4_Utils/tensorboard_advanced.ipynb
@@ -0,0 +1,307 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Tensorboard Advanced\n",
+ "\n",
+ "Advanced visualization using Tensorboard (weights, gradient, ...). This example is using the MNIST database of handwritten digits\n",
+ "(http://yann.lecun.com/exdb/mnist/).\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "\n",
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.01\n",
+ "training_epochs = 25\n",
+ "batch_size = 100\n",
+ "display_step = 1\n",
+ "logs_path = '/tmp/tensorflow_logs/example/'\n",
+ "\n",
+ "# Network Parameters\n",
+ "n_hidden_1 = 256 # 1st layer number of features\n",
+ "n_hidden_2 = 256 # 2nd layer number of features\n",
+ "n_input = 784 # MNIST data input (img shape: 28*28)\n",
+ "n_classes = 10 # MNIST total classes (0-9 digits)\n",
+ "\n",
+ "# tf Graph Input\n",
+ "# mnist data image of shape 28*28=784\n",
+ "x = tf.placeholder(tf.float32, [None, 784], name='InputData')\n",
+ "# 0-9 digits recognition => 10 classes\n",
+ "y = tf.placeholder(tf.float32, [None, 10], name='LabelData')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Create model\n",
+ "def multilayer_perceptron(x, weights, biases):\n",
+ " # Hidden layer with RELU activation\n",
+ " layer_1 = tf.add(tf.matmul(x, weights['w1']), biases['b1'])\n",
+ " layer_1 = tf.nn.relu(layer_1)\n",
+ " # Create a summary to visualize the first layer ReLU activation\n",
+ " tf.summary.histogram(\"relu1\", layer_1)\n",
+ " # Hidden layer with RELU activation\n",
+ " layer_2 = tf.add(tf.matmul(layer_1, weights['w2']), biases['b2'])\n",
+ " layer_2 = tf.nn.relu(layer_2)\n",
+ " # Create another summary to visualize the second layer ReLU activation\n",
+ " tf.summary.histogram(\"relu2\", layer_2)\n",
+ " # Output layer\n",
+ " out_layer = tf.add(tf.matmul(layer_2, weights['w3']), biases['b3'])\n",
+ " return out_layer\n",
+ "\n",
+ "# Store layers weight & bias\n",
+ "weights = {\n",
+ " 'w1': tf.Variable(tf.random_normal([n_input, n_hidden_1]), name='W1'),\n",
+ " 'w2': tf.Variable(tf.random_normal([n_hidden_1, n_hidden_2]), name='W2'),\n",
+ " 'w3': tf.Variable(tf.random_normal([n_hidden_2, n_classes]), name='W3')\n",
+ "}\n",
+ "biases = {\n",
+ " 'b1': tf.Variable(tf.random_normal([n_hidden_1]), name='b1'),\n",
+ " 'b2': tf.Variable(tf.random_normal([n_hidden_2]), name='b2'),\n",
+ " 'b3': tf.Variable(tf.random_normal([n_classes]), name='b3')\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Encapsulating all ops into scopes, making Tensorboard's Graph\n",
+ "# Visualization more convenient\n",
+ "with tf.name_scope('Model'):\n",
+ " # Build model\n",
+ " pred = multilayer_perceptron(x, weights, biases)\n",
+ "\n",
+ "with tf.name_scope('Loss'):\n",
+ " # Softmax Cross entropy (cost function)\n",
+ " loss = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=pred, labels=y))\n",
+ "\n",
+ "with tf.name_scope('SGD'):\n",
+ " # Gradient Descent\n",
+ " optimizer = tf.train.GradientDescentOptimizer(learning_rate)\n",
+ " # Op to calculate every variable gradient\n",
+ " grads = tf.gradients(loss, tf.trainable_variables())\n",
+ " grads = list(zip(grads, tf.trainable_variables()))\n",
+ " # Op to update all variables according to their gradient\n",
+ " apply_grads = optimizer.apply_gradients(grads_and_vars=grads)\n",
+ "\n",
+ "with tf.name_scope('Accuracy'):\n",
+ " # Accuracy\n",
+ " acc = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))\n",
+ " acc = tf.reduce_mean(tf.cast(acc, tf.float32))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()\n",
+ "\n",
+ "# Create a summary to monitor cost tensor\n",
+ "tf.summary.scalar(\"loss\", loss)\n",
+ "# Create a summary to monitor accuracy tensor\n",
+ "tf.summary.scalar(\"accuracy\", acc)\n",
+ "# Create summaries to visualize weights\n",
+ "for var in tf.trainable_variables():\n",
+ " tf.summary.histogram(var.name, var)\n",
+ "# Summarize all gradients\n",
+ "for grad, var in grads:\n",
+ " tf.summary.histogram(var.name + '/gradient', grad)\n",
+ "# Merge all summaries into a single op\n",
+ "merged_summary_op = tf.summary.merge_all()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Epoch: 0001 cost= 59.570364205\n",
+ "Epoch: 0002 cost= 13.585465186\n",
+ "Epoch: 0003 cost= 8.379069252\n",
+ "Epoch: 0004 cost= 6.005265894\n",
+ "Epoch: 0005 cost= 4.498054792\n",
+ "Epoch: 0006 cost= 3.503682522\n",
+ "Epoch: 0007 cost= 2.822272765\n",
+ "Epoch: 0008 cost= 2.306899852\n",
+ "Epoch: 0009 cost= 1.912765543\n",
+ "Epoch: 0010 cost= 1.597006118\n",
+ "Epoch: 0011 cost= 1.330172869\n",
+ "Epoch: 0012 cost= 1.142490618\n",
+ "Epoch: 0013 cost= 0.939443911\n",
+ "Epoch: 0014 cost= 0.820920588\n",
+ "Epoch: 0015 cost= 0.702543302\n",
+ "Epoch: 0016 cost= 0.604815631\n",
+ "Epoch: 0017 cost= 0.505682561\n",
+ "Epoch: 0018 cost= 0.439700446\n",
+ "Epoch: 0019 cost= 0.378268929\n",
+ "Epoch: 0020 cost= 0.299557848\n",
+ "Epoch: 0021 cost= 0.269859066\n",
+ "Epoch: 0022 cost= 0.230899029\n",
+ "Epoch: 0023 cost= 0.183722090\n",
+ "Epoch: 0024 cost= 0.164173368\n",
+ "Epoch: 0025 cost= 0.142141250\n",
+ "Optimization Finished!\n",
+ "Accuracy: 0.9336\n",
+ "Run the command line:\n",
+ "--> tensorboard --logdir=/tmp/tensorflow_logs \n",
+ "Then open http://0.0.0.0:6006/ into your web browser\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start training\n",
+ "with tf.Session() as sess:\n",
+ "\n",
+ " # Run the initializer\n",
+ " sess.run(init)\n",
+ "\n",
+ " # op to write logs to Tensorboard\n",
+ " summary_writer = tf.summary.FileWriter(logs_path,\n",
+ " graph=tf.get_default_graph())\n",
+ "\n",
+ " # Training cycle\n",
+ " for epoch in range(training_epochs):\n",
+ " avg_cost = 0.\n",
+ " total_batch = int(mnist.train.num_examples/batch_size)\n",
+ " # Loop over all batches\n",
+ " for i in range(total_batch):\n",
+ " batch_xs, batch_ys = mnist.train.next_batch(batch_size)\n",
+ " # Run optimization op (backprop), cost op (to get loss value)\n",
+ " # and summary nodes\n",
+ " _, c, summary = sess.run([apply_grads, loss, merged_summary_op],\n",
+ " feed_dict={x: batch_xs, y: batch_ys})\n",
+ " # Write logs at every iteration\n",
+ " summary_writer.add_summary(summary, epoch * total_batch + i)\n",
+ " # Compute average loss\n",
+ " avg_cost += c / total_batch\n",
+ " # Display logs per epoch step\n",
+ " if (epoch+1) % display_step == 0:\n",
+ " print(\"Epoch:\", '%04d' % (epoch+1), \"cost=\", \"{:.9f}\".format(avg_cost))\n",
+ "\n",
+ " print(\"Optimization Finished!\")\n",
+ "\n",
+ " # Test model\n",
+ " # Calculate accuracy\n",
+ " print(\"Accuracy:\", acc.eval({x: mnist.test.images, y: mnist.test.labels}))\n",
+ "\n",
+ " print(\"Run the command line:\\n\" \\\n",
+ " \"--> tensorboard --logdir=/tmp/tensorflow_logs \" \\\n",
+ " \"\\nThen open http://0.0.0.0:6006/ into your web browser\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Loss and Accuracy Visualization\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Computation Graph Visualization\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Weights and Gradients Visualization\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Activations Visualization\n",
+ "
"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/4_Utils/tensorboard_basic.ipynb b/tensorflow_v1/notebooks/4_Utils/tensorboard_basic.ipynb
new file mode 100644
index 00000000..d9a7f992
--- /dev/null
+++ b/tensorflow_v1/notebooks/4_Utils/tensorboard_basic.ipynb
@@ -0,0 +1,217 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Tensorboard Basics\n",
+ "\n",
+ "Graph and Loss visualization using Tensorboard. This example is using the MNIST database of handwritten digits (http://yann.lecun.com/exdb/mnist/).\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "\n",
+ "# Import MINST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.01\n",
+ "training_epochs = 25\n",
+ "batch_size = 100\n",
+ "display_epoch = 1\n",
+ "logs_path = '/tmp/tensorflow_logs/example/'\n",
+ "\n",
+ "# tf Graph Input\n",
+ "# mnist data image of shape 28*28=784\n",
+ "x = tf.placeholder(tf.float32, [None, 784], name='InputData')\n",
+ "# 0-9 digits recognition => 10 classes\n",
+ "y = tf.placeholder(tf.float32, [None, 10], name='LabelData')\n",
+ "\n",
+ "# Set model weights\n",
+ "W = tf.Variable(tf.zeros([784, 10]), name='Weights')\n",
+ "b = tf.Variable(tf.zeros([10]), name='Bias')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Construct model and encapsulating all ops into scopes, making\n",
+ "# Tensorboard's Graph visualization more convenient\n",
+ "with tf.name_scope('Model'):\n",
+ " # Model\n",
+ " pred = tf.nn.softmax(tf.matmul(x, W) + b) # Softmax\n",
+ "with tf.name_scope('Loss'):\n",
+ " # Minimize error using cross entropy\n",
+ " cost = tf.reduce_mean(-tf.reduce_sum(y * tf.log(pred), reduction_indices=1))\n",
+ "with tf.name_scope('SGD'):\n",
+ " # Gradient Descent\n",
+ " optimizer = tf.train.GradientDescentOptimizer(learning_rate).minimize(cost)\n",
+ "with tf.name_scope('Accuracy'):\n",
+ " # Accuracy\n",
+ " acc = tf.equal(tf.argmax(pred, 1), tf.argmax(y, 1))\n",
+ " acc = tf.reduce_mean(tf.cast(acc, tf.float32))\n",
+ "\n",
+ "# Initializing the variables\n",
+ "init = tf.global_variables_initializer()\n",
+ "\n",
+ "# Create a summary to monitor cost tensor\n",
+ "tf.summary.scalar(\"loss\", cost)\n",
+ "# Create a summary to monitor accuracy tensor\n",
+ "tf.summary.scalar(\"accuracy\", acc)\n",
+ "# Merge all summaries into a single op\n",
+ "merged_summary_op = tf.summary.merge_all()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Epoch: 0001 cost= 1.182138961\n",
+ "Epoch: 0002 cost= 0.664609327\n",
+ "Epoch: 0003 cost= 0.552565036\n",
+ "Epoch: 0004 cost= 0.498541865\n",
+ "Epoch: 0005 cost= 0.465393374\n",
+ "Epoch: 0006 cost= 0.442491178\n",
+ "Epoch: 0007 cost= 0.425474149\n",
+ "Epoch: 0008 cost= 0.412152022\n",
+ "Epoch: 0009 cost= 0.401320939\n",
+ "Epoch: 0010 cost= 0.392305281\n",
+ "Epoch: 0011 cost= 0.384732356\n",
+ "Epoch: 0012 cost= 0.378109478\n",
+ "Epoch: 0013 cost= 0.372409370\n",
+ "Epoch: 0014 cost= 0.367236996\n",
+ "Epoch: 0015 cost= 0.362727492\n",
+ "Epoch: 0016 cost= 0.358627345\n",
+ "Epoch: 0017 cost= 0.354815522\n",
+ "Epoch: 0018 cost= 0.351413656\n",
+ "Epoch: 0019 cost= 0.348314827\n",
+ "Epoch: 0020 cost= 0.345429416\n",
+ "Epoch: 0021 cost= 0.342749324\n",
+ "Epoch: 0022 cost= 0.340224642\n",
+ "Epoch: 0023 cost= 0.337897302\n",
+ "Epoch: 0024 cost= 0.335720168\n",
+ "Epoch: 0025 cost= 0.333691911\n",
+ "Optimization Finished!\n",
+ "Accuracy: 0.9143\n",
+ "Run the command line:\n",
+ "--> tensorboard --logdir=/tmp/tensorflow_logs \n",
+ "Then open http://0.0.0.0:6006/ into your web browser\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Start Training\n",
+ "with tf.Session() as sess:\n",
+ " sess.run(init)\n",
+ "\n",
+ " # op to write logs to Tensorboard\n",
+ " summary_writer = tf.summary.FileWriter(logs_path, graph=tf.get_default_graph())\n",
+ "\n",
+ " # Training cycle\n",
+ " for epoch in range(training_epochs):\n",
+ " avg_cost = 0.\n",
+ " total_batch = int(mnist.train.num_examples / batch_size)\n",
+ " # Loop over all batches\n",
+ " for i in range(total_batch):\n",
+ " batch_xs, batch_ys = mnist.train.next_batch(batch_size)\n",
+ " # Run optimization op (backprop), cost op (to get loss value)\n",
+ " # and summary nodes\n",
+ " _, c, summary = sess.run([optimizer, cost, merged_summary_op],\n",
+ " feed_dict={x: batch_xs, y: batch_ys})\n",
+ " # Write logs at every iteration\n",
+ " summary_writer.add_summary(summary, epoch * total_batch + i)\n",
+ " # Compute average loss\n",
+ " avg_cost += c / total_batch\n",
+ " # Display logs per epoch step\n",
+ " if (epoch+1) % display_epoch == 0:\n",
+ " print(\"Epoch:\", '%04d' % (epoch+1), \"cost=\", \"{:.9f}\".format(avg_cost))\n",
+ "\n",
+ " print(\"Optimization Finished!\")\n",
+ "\n",
+ " # Test model\n",
+ " # Calculate accuracy\n",
+ " print(\"Accuracy:\", acc.eval({x: mnist.test.images, y: mnist.test.labels}))\n",
+ "\n",
+ " print(\"Run the command line:\\n\" \\\n",
+ " \"--> tensorboard --logdir=/tmp/tensorflow_logs \" \\\n",
+ " \"\\nThen open http://0.0.0.0:6006/ into your web browser\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Loss and Accuracy Visualization\n",
+ "\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Graph Visualization\n",
+ "\n",
+ "
"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 1
+}
diff --git a/tensorflow_v1/notebooks/5_DataManagement/build_an_image_dataset.ipynb b/tensorflow_v1/notebooks/5_DataManagement/build_an_image_dataset.ipynb
new file mode 100644
index 00000000..bd19bc04
--- /dev/null
+++ b/tensorflow_v1/notebooks/5_DataManagement/build_an_image_dataset.ipynb
@@ -0,0 +1,291 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": false
+ },
+ "source": [
+ "# Build an Image Dataset in TensorFlow.\n",
+ "\n",
+ "For this example, you need to make your own set of images (JPEG).\n",
+ "We will show 2 different ways to build that dataset:\n",
+ "\n",
+ "- From a root folder, that will have a sub-folder containing images for each class\n",
+ "\n",
+ "```\n",
+ " ROOT_FOLDER\n",
+ " |-------- SUBFOLDER (CLASS 0)\n",
+ " | |\n",
+ " | | ----- image1.jpg\n",
+ " | | ----- image2.jpg\n",
+ " | | ----- etc...\n",
+ " | \n",
+ " |-------- SUBFOLDER (CLASS 1)\n",
+ " | |\n",
+ " | | ----- image1.jpg\n",
+ " | | ----- image2.jpg\n",
+ " | | ----- etc...\n",
+ "\n",
+ "```\n",
+ "\n",
+ "- From a plain text file, that will list all images with their class ID:\n",
+ "\n",
+ "```\n",
+ " /path/to/image/1.jpg CLASS_ID\n",
+ " /path/to/image/2.jpg CLASS_ID\n",
+ " /path/to/image/3.jpg CLASS_ID\n",
+ " /path/to/image/4.jpg CLASS_ID\n",
+ " etc...\n",
+ "```\n",
+ "\n",
+ "Below, there are some parameters that you need to change (Marked 'CHANGE HERE'), \n",
+ "such as the dataset path.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "import os\n",
+ "\n",
+ "# Dataset Parameters - CHANGE HERE\n",
+ "MODE = 'folder' # or 'file', if you choose a plain text file (see above).\n",
+ "DATASET_PATH = '/path/to/dataset/' # the dataset file or root folder path.\n",
+ "\n",
+ "# Image Parameters\n",
+ "N_CLASSES = 2 # CHANGE HERE, total number of classes\n",
+ "IMG_HEIGHT = 64 # CHANGE HERE, the image height to be resized to\n",
+ "IMG_WIDTH = 64 # CHANGE HERE, the image width to be resized to\n",
+ "CHANNELS = 3 # The 3 color channels, change to 1 if grayscale"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Reading the dataset\n",
+ "# 2 modes: 'file' or 'folder'\n",
+ "def read_images(dataset_path, mode, batch_size):\n",
+ " imagepaths, labels = list(), list()\n",
+ " if mode == 'file':\n",
+ " # Read dataset file\n",
+ " with open(dataset_path) as f:\n",
+ " data = f.read().splitlines()\n",
+ " for d in data:\n",
+ " imagepaths.append(d.split(' ')[0])\n",
+ " labels.append(int(d.split(' ')[1]))\n",
+ " elif mode == 'folder':\n",
+ " # An ID will be affected to each sub-folders by alphabetical order\n",
+ " label = 0\n",
+ " # List the directory\n",
+ " try: # Python 2\n",
+ " classes = sorted(os.walk(dataset_path).next()[1])\n",
+ " except Exception: # Python 3\n",
+ " classes = sorted(os.walk(dataset_path).__next__()[1])\n",
+ " # List each sub-directory (the classes)\n",
+ " for c in classes:\n",
+ " c_dir = os.path.join(dataset_path, c)\n",
+ " try: # Python 2\n",
+ " walk = os.walk(c_dir).next()\n",
+ " except Exception: # Python 3\n",
+ " walk = os.walk(c_dir).__next__()\n",
+ " # Add each image to the training set\n",
+ " for sample in walk[2]:\n",
+ " # Only keeps jpeg images\n",
+ " if sample.endswith('.jpg') or sample.endswith('.jpeg'):\n",
+ " imagepaths.append(os.path.join(c_dir, sample))\n",
+ " labels.append(label)\n",
+ " label += 1\n",
+ " else:\n",
+ " raise Exception(\"Unknown mode.\")\n",
+ "\n",
+ " # Convert to Tensor\n",
+ " imagepaths = tf.convert_to_tensor(imagepaths, dtype=tf.string)\n",
+ " labels = tf.convert_to_tensor(labels, dtype=tf.int32)\n",
+ " # Build a TF Queue, shuffle data\n",
+ " image, label = tf.train.slice_input_producer([imagepaths, labels],\n",
+ " shuffle=True)\n",
+ "\n",
+ " # Read images from disk\n",
+ " image = tf.read_file(image)\n",
+ " image = tf.image.decode_jpeg(image, channels=CHANNELS)\n",
+ "\n",
+ " # Resize images to a common size\n",
+ " image = tf.image.resize_images(image, [IMG_HEIGHT, IMG_WIDTH])\n",
+ "\n",
+ " # Normalize\n",
+ " image = image * 1.0/127.5 - 1.0\n",
+ "\n",
+ " # Create batches\n",
+ " X, Y = tf.train.batch([image, label], batch_size=batch_size,\n",
+ " capacity=batch_size * 8,\n",
+ " num_threads=4)\n",
+ "\n",
+ " return X, Y"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# -----------------------------------------------\n",
+ "# THIS IS A CLASSIC CNN (see examples, section 3)\n",
+ "# -----------------------------------------------\n",
+ "# Note that a few elements have changed (usage of queues).\n",
+ "\n",
+ "# Parameters\n",
+ "learning_rate = 0.001\n",
+ "num_steps = 10000\n",
+ "batch_size = 128\n",
+ "display_step = 100\n",
+ "\n",
+ "# Network Parameters\n",
+ "dropout = 0.75 # Dropout, probability to keep units\n",
+ "\n",
+ "# Build the data input\n",
+ "X, Y = read_images(DATASET_PATH, MODE, batch_size)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Create model\n",
+ "def conv_net(x, n_classes, dropout, reuse, is_training):\n",
+ " # Define a scope for reusing the variables\n",
+ " with tf.variable_scope('ConvNet', reuse=reuse):\n",
+ "\n",
+ " # Convolution Layer with 32 filters and a kernel size of 5\n",
+ " conv1 = tf.layers.conv2d(x, 32, 5, activation=tf.nn.relu)\n",
+ " # Max Pooling (down-sampling) with strides of 2 and kernel size of 2\n",
+ " conv1 = tf.layers.max_pooling2d(conv1, 2, 2)\n",
+ "\n",
+ " # Convolution Layer with 32 filters and a kernel size of 5\n",
+ " conv2 = tf.layers.conv2d(conv1, 64, 3, activation=tf.nn.relu)\n",
+ " # Max Pooling (down-sampling) with strides of 2 and kernel size of 2\n",
+ " conv2 = tf.layers.max_pooling2d(conv2, 2, 2)\n",
+ "\n",
+ " # Flatten the data to a 1-D vector for the fully connected layer\n",
+ " fc1 = tf.contrib.layers.flatten(conv2)\n",
+ "\n",
+ " # Fully connected layer (in contrib folder for now)\n",
+ " fc1 = tf.layers.dense(fc1, 1024)\n",
+ " # Apply Dropout (if is_training is False, dropout is not applied)\n",
+ " fc1 = tf.layers.dropout(fc1, rate=dropout, training=is_training)\n",
+ "\n",
+ " # Output layer, class prediction\n",
+ " out = tf.layers.dense(fc1, n_classes)\n",
+ " # Because 'softmax_cross_entropy_with_logits' already apply softmax,\n",
+ " # we only apply softmax to testing network\n",
+ " out = tf.nn.softmax(out) if not is_training else out\n",
+ "\n",
+ " return out"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Because Dropout have different behavior at training and prediction time, we\n",
+ "# need to create 2 distinct computation graphs that share the same weights.\n",
+ "\n",
+ "# Create a graph for training\n",
+ "logits_train = conv_net(X, N_CLASSES, dropout, reuse=False, is_training=True)\n",
+ "# Create another graph for testing that reuse the same weights\n",
+ "logits_test = conv_net(X, N_CLASSES, dropout, reuse=True, is_training=False)\n",
+ "\n",
+ "# Define loss and optimizer (with train logits, for dropout to take effect)\n",
+ "loss_op = tf.reduce_mean(tf.nn.sparse_softmax_cross_entropy_with_logits(\n",
+ " logits=logits_train, labels=Y))\n",
+ "optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
+ "train_op = optimizer.minimize(loss_op)\n",
+ "\n",
+ "# Evaluate model (with test logits, for dropout to be disabled)\n",
+ "correct_pred = tf.equal(tf.argmax(logits_test, 1), tf.cast(Y, tf.int64))\n",
+ "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))\n",
+ "\n",
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()\n",
+ "\n",
+ "# Saver object\n",
+ "saver = tf.train.Saver()\n",
+ "\n",
+ "# Start training\n",
+ "with tf.Session() as sess:\n",
+ "\n",
+ " # Run the initializer\n",
+ " sess.run(init)\n",
+ "\n",
+ " # Start the data queue\n",
+ " tf.train.start_queue_runners()\n",
+ "\n",
+ " # Training cycle\n",
+ " for step in range(1, num_steps+1):\n",
+ "\n",
+ " if step % display_step == 0:\n",
+ " # Run optimization and calculate batch loss and accuracy\n",
+ " _, loss, acc = sess.run([train_op, loss_op, accuracy])\n",
+ " print(\"Step \" + str(step) + \", Minibatch Loss= \" + \\\n",
+ " \"{:.4f}\".format(loss) + \", Training Accuracy= \" + \\\n",
+ " \"{:.3f}\".format(acc))\n",
+ " else:\n",
+ " # Only run the optimization op (backprop)\n",
+ " sess.run(train_op)\n",
+ "\n",
+ " print(\"Optimization Finished!\")\n",
+ "\n",
+ " # Save your model\n",
+ " saver.save(sess, 'my_tf_model')"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v1/notebooks/5_DataManagement/image_transformation.ipynb b/tensorflow_v1/notebooks/5_DataManagement/image_transformation.ipynb
new file mode 100644
index 00000000..56cc9c2e
--- /dev/null
+++ b/tensorflow_v1/notebooks/5_DataManagement/image_transformation.ipynb
@@ -0,0 +1,418 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Image Transformation (i.e. Image Augmentation)\n",
+ "\n",
+ "Learn how to apply various image augmentation techniques with TensorFlow. The transformations are meant to be applied for each image sample when training only, and each transformation will be performed with random parameters.\n",
+ "\n",
+ "**Transformations:**\n",
+ "- Random flip left-right\n",
+ "- Random contrast, brightness, saturation and hue\n",
+ "- Random distortion and crop\n",
+ "\n",
+ "For more information about loading data, see: [load_data.ipynb](load_data.ipynb)\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "from IPython.display import Image as IImage, display\n",
+ "import numpy as np\n",
+ "import PIL\n",
+ "from PIL import Image\n",
+ "import random\n",
+ "import requests\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download an image.\n",
+ "d = requests.get(\"https://www.paristoolkit.com/Images/xeffel_view.jpg.pagespeed.ic.8XcZNqpzSj.jpg\")\n",
+ "with open(\"image.jpeg\", \"wb\") as f:\n",
+ " f.write(d.content)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load image to numpy array.\n",
+ "img = PIL.Image.open('image.jpeg')\n",
+ "img.load()\n",
+ "img_array = np.array(img)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image.\n",
+ "PIL.Image.fromarray(img_array)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create TensorFlow session.\n",
+ "session = tf.Session()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly flip an image.\n",
+ "def random_flip_left_right(image):\n",
+ " return tf.image.random_flip_left_right(image)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display randomly flipped image.\n",
+ "PIL.Image.fromarray(random_flip_left_right(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image contrast.\n",
+ "def random_contrast(image, minval=0.6, maxval=1.4):\n",
+ " r = tf.random.uniform([], minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_contrast(image, contrast_factor=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different contrast.\n",
+ "PIL.Image.fromarray(random_contrast(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image brightness\n",
+ "def random_brightness(image, minval=0., maxval=.2):\n",
+ " r = tf.random.uniform([], minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_brightness(image, delta=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different brightness.\n",
+ "PIL.Image.fromarray(random_brightness(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image saturation\n",
+ "def random_saturation(image, minval=0.4, maxval=2.):\n",
+ " r = tf.random.uniform((), minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_saturation(image, saturation_factor=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different staturation.\n",
+ "PIL.Image.fromarray(random_saturation(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image hue.\n",
+ "def random_hue(image, minval=-0.04, maxval=0.08):\n",
+ " r = tf.random.uniform((), minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_hue(image, delta=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different hue.\n",
+ "PIL.Image.fromarray(random_hue(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Distort an image by cropping it with a different aspect ratio.\n",
+ "def distorted_random_crop(image,\n",
+ " min_object_covered=0.1,\n",
+ " aspect_ratio_range=(3./4., 4./3.),\n",
+ " area_range=(0.06, 1.0),\n",
+ " max_attempts=100,\n",
+ " scope=None):\n",
+ "\n",
+ " cropbox = tf.constant([0.0, 0.0, 1.0, 1.0], dtype=tf.float32, shape=[1, 1, 4])\n",
+ " sample_distorted_bounding_box = tf.image.sample_distorted_bounding_box(\n",
+ " tf.shape(image),\n",
+ " bounding_boxes=cropbox,\n",
+ " min_object_covered=min_object_covered,\n",
+ " aspect_ratio_range=aspect_ratio_range,\n",
+ " area_range=area_range,\n",
+ " max_attempts=max_attempts,\n",
+ " use_image_if_no_bounding_boxes=True)\n",
+ " bbox_begin, bbox_size, distort_bbox = sample_distorted_bounding_box\n",
+ "\n",
+ " # Crop the image to the specified bounding box.\n",
+ " cropped_image = tf.slice(image, bbox_begin, bbox_size)\n",
+ " return cropped_image"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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9jzv+S3kJTp5dX0N83mHsvikVisj27NlTw0Fjd2e9Xq2Eg1hRbrfVaLRba4/uBQoliabr5Va3E5QKF1Zno7CbyxUuXnyjUJ5rNDrxsFMMhIgxfQmSnPgWT/Dr4BuhBz0t/0t2es2LqAfB54RREg0QqFTMEYpJEgUYJ0YDdHuDBw8eIMqD+zd3d3fffO27i/NT/UHY73SnapXKzMoQgmGYTE3VgG0h8JUGIqcHyWhwwkxnwUuDZ60HHX89fCP0oBdaBp3g14czytwqv/fg+sLUQr8z8Ck3VZkxhivFkjGdzd29G7duvvPd39jeuQc2TuJo+dTK/cd3iPsb64N8Lf9wc7MX2nJ++u5u58yZKhWmSAkiA/PYHENUkJEjeoITfAFOZNBTwLN2hRxbbxplcj2hDQ0Ge00iT0Hey1XLVTuAfqcF0DNs4zh8771fvv7qtTOnVlZXr969e/vh+mdzUz/a2NqdlYDjhhlEucqUpdK9R3sL184hCqIgpanpCApEsuIjJ/hiPGs96AWnj57Y8F9PfH5ZI6L2ZHtnM+f5wlQu1xcXlvf39zVxPl8Ewsb+bmKi3/6dH924/ukv33u33x/milOJgZyvaiWVDPbn56avXH3t+q3HAID05LL+GvikT/Bc8KX4Qc8630TpjO3leP2esvabeYxZvB7J6DuWOZ2jx8nkZRzXXzAqwDP+oftgMvgsCskYSwiFfJCEEQJ7ObWxseU3BquvfbsvPGj2va6Kw06umitREyLbbw/f/t73i7XSJzfvRYku52YG7Z2cgnKxfPvWvaXZ4H/xn/3LIcz+t3/5cb+6CjmuB9V+O7A68XxL0VDYC5U6fj+1oyF89DiZ9Xcy19vx+pEd362eNf7x6ltlzieTv5PBU6MMXlIG3yeLT5S138zzc0ye1BM4scVeCozXerpo3GKmDFlGhEoRikvsEgQREbA8u3ymNwjzlcKZC2cgwZ3dpLqwcn5hud1pXLx4fnFhaXN3bXd3v15ZmK6VP/lkzcZxp9Mu16Z1Sd/Z2LVKk6cXpqoEAug8QYSgAAERAfHpVXk7wTcIJ7bYS4AnklFlBCQ48qU0epq0Bx6hp0lr8hQC2tVLr3eHsQkH9YKO2ztbaw8bnc52J1o5Nf/GG6/lcqVuJ7x/by2Ok2q1MjtXCYfd5eXlK69/K9L5n31898F2o1qtVotaS0xi3NIRBEFFROpkKZ3gH4RnVNP++eBFm+fTisFPhr1F0s66IpJVA1cTCpJC9D0E0ZqQULTC8sxS8PCBTXpRey8ZdHKe9nKFXpy8/saVXu/e/fvNem1+fq5nDCcmevW1K4Gv5xcq7W5nuzXoYb7AamaqVilpT4wPBoUFkcElsKJCSl6wuNjLvh6eNV6Q+Zw8vF4COEPHvYjQvZQiQjnypdBqYk+R9lTOV/mc9n2tCftxvLC0XCoUd7c2w167PlWtVupCChF7vV6z2SyVShcvXqzVaiIyNzf3xhuvz05XP/rwPWPMpVdeYdT9fpdMlCejURQKSEpSdPt93ufpBC8lfi096AWP+X2dMBllH18OysjtRBAiQmKFFgm0QmstS9Ju7E/Xp7rc3H7YTIZxTldhINp0Hz7Y3N7aieLh/Qc3RbBSqPuadnealWptdcVbnq4khaBYCNrtkBSbqBtQLUfWiUAGAmASOXEGvXTIvK+/2ml8rXzSL5qsfHr8aTtOQXW1e9yWOjOOEyGiQhBrrDWWxMRhNOxzp6lylLCw9r2cr71AE5Ty/s52c21to1SZvvvw0f5+8+zKlSuXVrud3geffmyH6sKp2bV2c/3eDb+0Wq+Uw+FGTrFGUQQABMBptqrYF02tPq6t8azXyYu2Pl8QfK1k0NceaV7WSAzpz5F0UlghYBFkZrbGIMdxHIYhmWh/bzfst1H5nvYAFdsQMRkO4vX1zbeWT1drpZ3dzWHYr1Rq1uD2zt7tj27Pz85I2Ntc68ydrjfE7u/cVz+4pDGdg6Q+8q/2RJzgawT9ZTgdWX2Cjl+v53iQ7MZUx0Lm8weP5llgJm8oq+9VBp/omHVkPCwwG2FLBIpYITAbtgkTKlJaK8/ztNbjMoYBhCLIIiJoWKywCDKA0bOKDCdhLDrkfA60iXZ6O9u7D96bXzlfruT2Y7uyUHt0865vZHqxPhTv7larcHPt0uLiUtkrLK5s9Dc+efe9f/KHf1i//K04iqgr2Gr1y8NCvvz2t7/7//2bB1fe9mGvnYdXk5wK1cD3Cn3b8LB49HnIQKY+qLN4NxlcBM7gyxxTMmZd9+PqrU9L/836ntTR43Dm/XK8ukKAGTIhkweU8TUdPc4T5+HFUp6/4SAlpJAISLFS5HkY5FQ+H+Q9ymkMFHjISgzaGEwkSWitZWZ7GMYYa22SJMYY99l9AABdEM/H3e3GmeWr1fLK3Ozp3f1t5YWep4IgGAwGhXzx4oXLg0H48cef9vv99u6tYrH0aGM4MLS0XJ6dlqtXr21uaaESYw7JF2QESyhKwLMnOvUJ/iF4odfNM48dZsnvzPzjZ50XZhEZyCKJ0uh5qLWviNAMRyYYiFh2EBbRIiwizMIs7PQgkYQThAStsQiGSaEkSaKUCqZLhXKh0x529gZhEDIE1al6saK67Wa5VJydnS+WKyxmOIjCQWTjZLbEjf1Oc6j70eCVi/XlS6t9UA83ZflsXaAoFLMFAKMBlAHFOjl5on0hnl9e4QsRg8/CCy2DvmlgMSwWwIoAoBD5fqA9RQXxYLTCmNlasFaYJQIlgsAMAAQiAsxAiGLFWKNBWBiAmNkYEwSBHyz2esmrVy4Z7gqqR/cfn7twNZc3vXZjerp+9do1Tlq//OB9LFdfe+2Nux++X4b6riFVKXlRsVQqIct2Y3uIMeglxgJpQBEEIQSyQuIlx86NeCHiMr8SLwiP5oXFr8mDe6Fl0MuiBz0tl6y1VoQRhFmsFafugKK8r8exMBFxJhgzs/FEkJitFWABtkRoRcC6zl+AiITkvMaFQoHw3Ccf/WQ6T6vna3cfbTxcfzRTvYqizq0GG/tSKJUba1trG7tLF6fOrJyJd/fWb/XP/fb51tqjqp7fb/XurN+vnXt9Zsk4n5RSytXdJqKTvs9fBs86TneiB53g14UwAigRAGKTQEJGKUWgXCn9NA4lgojWWiJCi+OYPaIrFZRuKSKkyLqUMWAng/LlubmFx/u7m/Pz9tad69XpJe0V8/n899++cufxYHNzM+qF80unCP1BN1yeX+CeVIr+3JTf2+8+XutNr7zW7ofzM8rjSGPoKURQFhCIGERlOpIzka0HvVia0ElM/ZnixIJ/gYDoIXqEPogSViaBJOE4sok17hWbZPL9CVf0GCLi+mq4Yd2fvu9v7W8tLS2QxXs314CLlcpco9Na37gX+MrzdLc3sACz80t+Lh/HppgvvfbdJU91VDzsN4d7PZk9+9rjjZZO/ED3FQ19xQQgokSphNioFytR4xsIPCae9X6/5PYnMugFAoImVESa0AdAZrIGrZXYJONXlMTjl5M4yecwlkGTUEqJF1XqxXptrrkXvXbtB2GM3W6Lgvjho/tJkpTLZd/LsYVCvlitVhFx9Vr59Jna3vp2OV8Hr7DZbIUh2a7vUagxJrQoJKAEyCIYfSKDTvAPgf4y4vBp1YU5Po6t3h8LGeVTsvs0ZcyHM2wH5Ix+Wxn1WYh76QdCpVI2ECrFCImVKDLDhCODiWgDCIASu/lMXB0EQIit0b4PvheFCYPJYSLD/ebug5mpJdFqPYq7LJ/c/PDKW98v6QVq3vvs9l6/ub6/v3/jxo1Tp06JSIkuTE1N7T3SM2e6V89WPKzPFSmKf7p4bVFXl/Pbf3/hynIYdNb5fq70Sn+vWS2oQRRolXVCjzb5LcRHfq+z+ClZyOJqZiDzutsMnk5GTYCs3T5r19ix63ll1Lf6Ak0l4+uMxwxm8Ae/nB/qxB/0AkEp5ZbXE6psYsVYtlbYAjOzAAhKdvE5IhLHXBzll1lrO52OlyvvdDvddnuqVlK5fLex041bc9TvdtX29vbMzMyVK1eazSYiFgqF6enp2/c/Cen1QQ+13t/afFCqreQrtfWNW/Nx1O0NvaCIWsVhZG3CjMr3wB6v1+MJTgAnMuiFApLG8VMOiQUtg4CEiWULsYXYWmuRgVmIxaoMdx4RWcOTfxpj9vf3k3BYnZ7L53y0w9lK3WC839rRdZXP5/v9/tmzZ4vF4u7u7pUrVxYXF3d2dmSwW+3aZjMs10wYtRoPvKCba0Inl8ttNrtQryFgHMe+zqAp/8rjfcFCaS/afF4W/JrnjZ6Fj+plx7P24X0BnAByDh3naU6SZBjLMLFhwsaiZUcOYrCZhqrj4I9VKieDer3eVDl/7uyZ6elpmwwrAXG/0Vh74IFpNpu7u7sffPBBu92+evXq0tLS3/7t3/7Zn/1ZozVstpuffPbJ7k6rWp0eDBq9XuPyxStDCLZa/aFlay0BFwt5RIzjow2rEzx1/Jo+4KeOX/NwTvSgFwiGGcZ6kJMgzADAgswoApaRmQEwLeaa7TYZrwxEdFxqz/OU8CeffLL5+L432J4u4Nrubq+5S3JKax2G4Y0bN2ZnZ99444319fV333333Llz/Z4exM3rt98b9q9evXhxYbE4u7qwtHTp4YP9XkwlDFBZESYCm5FR+MXIXL7PKeSdNZ+TCPwX49cUQ4d80id8h+eLkf002aZZAICBAJQLbwESiP3iq+7YQ+NwmLUxIs7MzKycWmo/3JtaWE62Ovt7uyVfT58/AwC1Ws3zvDfffPPs2bP3798fDAY//OEPlVJx3xQrOWPj+/ceV3Pld354ZfXKuduPdjpWS66s80UdhNFQ4jBEZM/3gU9CYy8ivhoV/h+Mk9j8EXhGOuevxFj0PLHTRMgysSCgQkQirUCp7PlYa8ehTGeIKaUWFxfv3n+IXrBw6ixo3e/3A08vLi7WZ2b39vZqtdrrr7/e6/V+8pOfbG5unj17dm1tbWP7gVa1cnm+Nl2Yni3kczUxutvdNirvF+tCHqHWHrFJ/mEn53md55dlPll4Web5JXFii71IQCWHg2KuerQwMCIgKXD/xYiHq0wfBjMjkqvrg4jMTERTU1N3P3l/9vJKqVLL5csqCdbW1qIkfP3q7zfajbfeemtvb++P/uiPRGQ4HJZKpSAItrZue6par66cWvFf/9aFbkva1x8pz+jcrM7lozhh5iAI0AoiJEkSnNS1P8HxoUt+yKBYlGVgpZ6g2LqbgZ9SvsnTsvW+TE+0L7XfjD5WmTyIDGQ+grKow1m8kpRwMjFdBADQE9NMzTVXw5CPHqiIBJYSj9iXMOoWAq8b1IPZGZrb3l67N5/fufTa8nvv28dbxY3b62989/q/+sN/81//2//Ln/zJnwYF7Wtvb6v7ib37L/7lj/vDwWef/bvZfPuV07/1aKslpdnK/Lfv3vv02qVitReVknDBj68PHvrlVUhAJMo+Q8frC5bZoyPjeLP4WZn93Y4ePZt3k/GLzOyszHpVGds/JRfIcVWhrPlkjv9s+FB6qpyPEx6EJrIxq9J4xBPf0MsMBgQQjW6ViU2SKIlDwqBWmt1Y3/C85OrF1+Yq4a1P/hQ4X8rnpqv1Sxcu5/KiVNDYjbvd/t/9/Xtvv/3tH/3w2ns/++yTjz/tmP6bv3Gx09jZ2926fHlFTCuX12pAOSqJZRDRqEFO+EEnODZ0Pa+GBB7LUGzzcHADRwy3L8l3/JV4WeRaplzPDOO8WMclCJwG5hWKEWOTYa/fo6uXXkm6W/c+e2BN5+yZqbmp6bBx18PC9trW3ubudGWqWA+ModXVs8rzH6zdPDU3OzM1tbC4cvPG1lwtVy8Ftza2FqbLdmAiflSt5PSwlKNKZEWjJfTtiQwCgOOvn6flyDm2PvJsN/+y0B4Y0hLkVEkHrd6BBjQWQE9xZy+a2+y488na/rhHdVyK/PEHEgAEIEQmUJIk4bDdbUWnV6Z3O4nv69Da9bX7S3MwM1tlmzy4fc9Xvg3Ug/v3wwRPr9bnFpfnls/UyiWTsPJL5y5dLVWEJITErq4uJQMDQadeM/6uSKwth6giw1bljmcjP6318LzGebFW8/PDr2uLAYtCQA1aedA7GHGS6X+iB6XfZ/3gRTsuEkEAERRNklgTD3vtXty+FQ6k2y7kFCGtrX3W3t/xpWm5dufuQy8olGqFO49v94Zxp9ddDoJrr1z4+z/5b3v21dv3h439frnfB+ko/0wUD/Z2WvlqOxr0FVWBjVIqn8uZWNkXTB98XjjRg44FbUgDixXgxCB6cKIHHX/748rop6UHZdmAjAygAAgBUZCTOOq3u4NIJ8OZfFFRjsgfRuHG1v0c98rvLO3145+/9+H3f+OHc4sL9/7+F9Xa4sJspdfeuXXr9uzFswMsFGdqvmysr+35tdmwRUhBGHmPHvVU3hcVeX6gvYDZvuwy6EQPei7QfUMEwJbHRflPfNIvCzLjL6NLpxBRQKxJhgOQ7unF1Tx5Udit1xYqlblkcC9q9fJehfLRo+2dc41Gbar+xreuzc0sJVFz4+EtoZxfmq4XF9AoGQz2W7fDzsOaWn7r298xa/jw/nD6zTz5YQQq6UWJTXK54/XVeNFssZcdz0sP+nVtsV5kfUIExZ8b6EAVOhFHAPDi5RZkApkBSNDF8JnZ2ETiIYi/s9VSkTmzsuwXgm7L7Edxv8vb+82V1fMP1x4Hheg/+9f/8sHdjf/b//X/XKmAbSPqnFKVtQcbU4E9feasrl488+3XPAWbA9re2J9+SwUFS5iXCH2K7EnG2AmODx0PDXnkK9AoxVxgrDWGE7bMAEiCiKiQn068I+sezupfloXj8oOyx8+qq3L0+MfloRwXWU+TzPlThm0oxbzneZ7X67TrldzavfYQi6tnz68sTt81PfaXN9Tszq3HmCjWEWszVQw37v1ifn7+7de+3dpeX3+0kc/Poidecr80CEPeb7SGj1rh2RL/4FrJK/Z/eTv4zNYuXpspRA3bVv1cEnjUHMQ1FTyV85CJjOM9Lp6a/pXBY0LJqqdzNLLKsFBGQiCTEICIRXH7YhABYBxRjidLaAJA4PvjUnYwQbNOMvqRZdXPenrG56Hzo3OBV/CVVqAA95MJctyJfvsyg5njOHYkaWauVquFQmF/d29xbr4bDVcWF/NAvR2eq11mwk6rvXr2wg9+47fyZf3ZnQeMhddfe7PRWps9M8eBDkhfuLCyeX8IUcScEymR6ZVyvlLIQH5QQFRi4qJWL5w++JJD5GhuJ7ui40CKEAQBiQQAWMY9BcccYwAAMFYOy6D09QVFzL5K6FygfK01AiC7BGtI7a+vbkE9a3n3DZSnrvSHImLmJElmZmaKxcLt99//jR+9MzdTTcLu2uOHPsTLM9MLp+e3H95dPXPx1LlXHmw+vL/ZW5ydXVw+k89DO9z2S75CGJh4bqZa4lzM5d1dsFGrXpnzPBOzeEGeLEkUF3KBSV6O8/y81tvT8rEKKEFBIYtCiApRgFHUOEaBhxUrY63L7JHR9NwMs8ouPPv75dD4pACttcM4GvTDsaSEw1lLWTlyTwvP+IC/cUBEl3PjmvAkSVKpVHzfR1S9dqsWUGdnM4qGiyunOoNhGEe/+zu/s7yyut3oN3pcnTutc5UosrPT0w8frJONVdQeNB7PTJXrC0vrXfOww9GgXa3kc762SaSU8pVWwsp+45Lmn/19wUe+GIgBgQiEGNAKiiADjpWdcTXxdKKkgTQqj7RP2kfluW+e68k7gI4Ni4ixCSeGxdUSHQuGr0g8PGsx9E0Tc0TkUue11oQ2jmOl8gBy6vz5JBpsr93rtbrJcLC712hubseXZy6/+fpP/v7e2v371qN8Ph8Owu3tEKZpZXq+YJIk6Xm2b7neSmS7b+JixYsHU77yEyEbKYoV5JkoNhaz6km/YHhZ1kNWxwmFAgAoAsgojAACjAKHjOEJnSszb+659SM7NL4OGUTAWLIyqlADaTjsJDr/ksLJIM/zRAQJXbONwNfzZ06H+7fv3PykWJkFyzev366oYY78xBiQZHFmShV0q93DfH6uXtbU/+6bb5xdnBOIHzfu3n90b3p+tZCfancavuezGC1hxcvnIVI2QhVEiXjPq/XBC4ase/u4tliW7FDAAKwIURgVkAAhAoCHMt7L5Hto7RMGh7vTUR8dQ/iKb3wdGWQgy2CdPAWA9CQijOr1vWjPjafXf/LpjP+iwdliWus4HPqBYuYwDKv5KhTz4U7U7e2XS5Xzq+cZvfb6+/391i/ff9fYYdWz+3vrrf1Gubg09Dmx7dlz86WpQqVQLdzdsHutgKRgo1ann5+Z6g+HJe4tVCqNIW8OhugVRAUAX5A6/wLhaa3nrHEyadLZ/3Hk15TRuINsgoiEoBQpBE85CSM5pSe7OY0LYGAik34Pp2mIQJIh46z9Ste/ThitgLVgGHx0ltjBf59oQy8jcNSONY5j9gIRMcZore+vP+Z2a2qqurmx7tdK337re7x/e6pYfrR2p5D3o2Hr3vX3Y2P7hfDx44fkJ5U67nVKnl+bmqmfk4oNk+7O45XyXFwud8JYMKwXvWIiksToFcEvgHk5ZNDLgmxZmSggAvAJPUXaUx4pRMlrHEsfZmZO/0QiRCSisQxy4qltMtkCz+iIjoS2YAFBaVCg2CKM8h0RABAUAKDYrPLpGXyNTH7BMfGsn1fH3f7YfZ0ytn9aOnkWopjKpTxDxApzYhZtx+w0294w7pS/PXd2/f2b52Zmt5TdCxub7Y1K+dTdXzz01cyplfNebnHz0QOvs3f6zPx/+p//kz/+s5+9q4M3Xl+8v2ZarUE1p3f7O0FOR/FleXgjKe1sd+viF/Pl+narP1+VXsbalWfcSvN56elZPCBBxol4zvidsvrQIcPIw+0khdu+pIeISIhKoSLQ6Dp3QzIwRKQVKR15hFoBkijAAHJPGGLpStMj0QOcWLEM1loRKNueFWQhwzqxZFixKCsoGX694/L4snHYH/SUBj3BCwStdZL0w7hvLVgrw+EwGvS84XBqunZ37ebM3OzC6TNb9xsPb35aK5R6fbMwf+Y//Lu/VT8ovPLKlSQZsvX+xR/+688+fa/T6UxNTRlj4sgUSmWFxiYJAvQbGwv1Cmjz3qf356+dziFP1SohxCcZVA7ZNlqWzUXwuSgbABgRJSAoiAoFjALNgCioNBK5NEUhBAJCAHSUSSdu0h26f9JeCUQg4iMYBqWJGXKSYwbDCAYEkAGYDYn6iq+jPvxMPt65y3qaPy2f3An+wRARIiqXi5gMer1eNOiVjUFpbXV2c9NlyJenquFnn90Iyh5h0GpEIF6r1Zqa8S9cPHfpwpu//MVHVsI4HA56HcswOz9/4/ZD3w6IYGtj4+x3zq9MLXa3/YePPl2+RjBssZ5pQ1yEZ8yTfsGQrX8dKkM63uwL+hWPt5yUQYkBC0AEACxICklAEJEoJyhMwAgEYAEBAVGUOppjzMaO3CrEgCgiQiKCEjCDse47yyLMwmAA/oEN4/5heCH0oKdlKz1rvCzzNMZ4CpRS+Xw+7DaMMbVabXl5eW3tYbE8tdbqVXtRfapc8qLNtXvF6u922tH5c1dKpVKn2/rxj3/3z/74Fw8ePDa2X5uyxpjd3d2Y8xubO9p0z5xauXTm/PTpWSv6estAsOhrlQe7H5tgpoSdjJyery334oueqZMCKLXFMmxq551xXjyYKJvDFhBBC7KQVqiNEBGBICIyoogVsYIKRAsiklHmYI8Tp4WIJP1OBAAZGVgAQQhEAAhAEBHQAgIggxwtg57Ref5SMihbD3o6/pETPF0QETNHSaS8qN9u53K5paWpWq3W3G0HhdpushkUqzubD+pzU/3GPcLB/v5+r5MsrUz/9m9/76c//akxsLKyst/Y2Nm6USkV91vtAWi/UNy+c184/s3f+wMsVO9u7283ehfPrra6rUJh2u6jHLPp+9cAv9LmekIPytre+Vkm/zeVQaBIMAFRjABgGRTBuAw0ARAyEWgDnkIi6qf3o4wjYO4fpQkAhJFBjICxlplFMEnIChq2iYWExTAIABNmlP9+VtAvglx4Wj7gLDytY3zWvuqnBd/3xerEEhHFcVwul4MguHnz5tmVV1o7j66snl5cWP7Jz9+9ePbU0moz7Hf8QObm67/3e7/7/od/s7e3r6m6MD9npd1tCQBXa9Mzc5cfbuy1iwVk22zselzuDzqer3LFwnZrbXphVRq5uN/xIf9MjysLL74eBF9ikpOrwn1m1IJIAgLCLARiWAhSSjSJIIki9FgSBoXiXOSjHaWpYQCQ95xEQyvALMZiwsAsJraCxAJGIBFhQEb86otAvRC22DcNz/qeca0N8/m853lRFFUqlWIx/+6t22fPvIJxZ3FhtttsYX6utPB6kEQ5VapP5975zm/97Gc/a7Z3ojAJuRPWSiun63k6R4iFciU/NTuMzLVrr63MVbTCe4+arcHu8twcijEaOCgUi1Na9TEr1vuC8cueNT4vd1K9JiOudOR6EBEkDwAEWFCEhYEBGAWEAAWNIDIoZBbUAkRgrIajZFnoAwAIijAwUGKFGRiEExRARmQQA8TOLQ2SJRSepy12gpcLURTlfBaQ4XDY6XQWC4WVleX6g4e7exs5GfCwcf3G3ZVz36ktXN56eHu6svQ//Z/95//Nf/3/AvHr0wVr5cb1z4ztv/29izvW5vP5wXDY3Ngw1k7PzCVxb3tjM/EXCGT19EKzF1I53+pHJkEKvlpm28uD8a2b2ctowk80mbBpUJGAYEoCYBlX8tIolkVQCIiB0bmJjFUwEZJ3OQ8iYq1BVIwggABoBVxSBIp2VT8siAFxrRAY8SsWChonxdBx+Z1ZtUQzev5m1eXJwhfHMo/a79HPmS+IRxxrnCwcd572Gad3YkHpxBtiqLlzpiCl0swvHm+dv/Bmzqx7fv761gbWT128dKnXXO82rudL0wnO1Wo5rXW/352Zrs/N1gi87TWzeu5qeWauvbk2o4Ifv3lmOFB31rdmFzyp4K37pjzbm6uS3UJ/er9THKx5xakka0ZZz/+jr0t2v60MPk6WX1Ky1tvR42SuK4zdaIhKAaLztwgZiOCwzeVu/tiKItIImkQRaBBkC8jWLx/mELJbaZw1TxNxeoDpAQFqAEBJBMG1ozOgDEMUAwBMdL3EiXdI3Hme7FqHAAjW9WsTAEANIwEngBl1teSY0ulL+hxOGmN+DcFswuEgSZIgCIgoDAdK4fT0dBzHnsJywctJOGys9xpbcRT2o3hjc61aKyHCK69cqZRrP/jBD69de5Utriwuzk/XyvnczHR9tl4Tjn0NxUD3u/tzU1MEFPV71YqqV5WYyIfc8z7uZwVBRaRJeUopRAJCEXHVj4Vw/D5+aaWIgBQ4wqEAiCtVyjyZ1P6VuWIlA1/N3n8lnonala03vRwx2mftr3nmPlR2edUg1kTDge9Zz9MEuL/X4FyU9PZ7SYONNxwM4mjYHSZ37twFMK12Y3BjuLmxW61OnVo52+0Oi7kg53lKbDnvdVQU9hs5jxVE7d21pVMXtHiDfvv0dCXIhzaMg1weMaOY6zH16+yzkzVQ1tdPZx2i8w07Eg46v4oAsFIHPSBGWwIAaAQkd3SjeoZAjKl+/XkRkB27yJrP04rJPB0+YBa+5Dx/LT0IM/DrjHmCXx8KpVTI53zd7/X2d3fjaCjA21ub+UIuDofRoBUkfehscmcnp5GCwvrGY6XUpUsXGo1GEAStZmdmZu67b7+zu7mxv7vd77XCXnt7+3GnuVfM63Z7t6CND7C9trW9uRGGDd+P84q0eel16qz1jIjIwszCFoURwdPoB0prUgqVQiJwL/enIiYQl5khIkbEiCQTJtik0+dX7Pdp3F/H1YO+4vv6RA96huM8r/GtjbUONKnQJvv7uyI5n2bjMKxo7MWxp3StUun1+939Xd8PEyMb61tJLJcuXRkOh0ks9fpMEKh8wb93Z3PlzIIxptPprK8/7nRa0/OV7bUdb2q53drb2trLY393r1FfiWvV6V5kJTMvPOPrl0QP8hhEBMQiikLwFWmttaKE0SWgM49lCgCApKqHMDMDuZtdRGBEoZLD7bOyztvzykPIXJ/HHP5LrvOTuNjXEGxsaEIOuBD4JolajeF0vV4OcnuPN8Nua2G6OD270OludFp7U1MBIxHm263Bzvb+wsLSo0ePzp9fbTS3792/reMwStjzC6G1YZR0hv3ecBAl4dbduysXysunFqq5qd3Gg+JG2y8taomSr2nafI6c1xsVilboeeB7oJQ4GWQtj4nODolV1uk7iMzCqchTMMpxxQk3NgDwMW2i4yJbZh1v+2eEX0sGHX+uT+fYnjUn8Gldg+fl9tOKJDE2tkrEU7pUUMVSnntWooGIeMVKUJ0RanheUK1W8/mg2Rh4nva9/UuXLly8eJHZ3Lp1c3tn88LySsIYWQkT8fKFvVYbHj4olQNrcHZ+am7lNET9jx48KO1xrqoZWwCFY83zRdODsuZTUECKNCqlRSvQxERMCIaQmS0wIzOzE0BEFKJvBI0lYRYQAGQgAAKOYWTpTH54aunoGci8L465/TOq6fHS2/An+DyCIMjlcsw8HA6Uovn5+Xql2ul0PA0iMoyl1Y+b/UEYG2buttrCXhLD1tb23t7eG2+89ulnH926/Qmi7Q+T3jBu9wfDKNK5XLPVuf/okc4H33rz26dXzxiwjWa33QbPn8rli71w/3kf97NCzqOiplLOq+SCck7lfQqINSSBgkCBT+Ih+yTjl/bIV1qrFISaSD9RZ/5Z+H2y8BX7d44LTRO5tsLHFEnZgvTorzP0gqy+XVnIPntZ+tGLVb/mqelrGfVrCslwL/HrtZl+40G+HFTmV0ql2amFiKZf617/4JVr70jt7O6tZulUksuHvuf1B80wHvz493507uLqX/zkr4Pi1PypN0CUKflL9dKm5bXN/qXzl77zm/CXf/uLj/72w//835Qv5lbuPNI/eWiGF7+liu25cCMXXaB8JkEo43iPjqOh8idPyPi0EMukEjHexgAfeV8pVJM+4PH/EilIH7+CwCjgGEMDqRCKQlYQKUjyvpTyfi5Q09QAIBASARFkS8wsAgmEhOgjoKcmZ6Vt1xJaBGMhQZ1YawVYEPLj6cnkWjWsRMTlc41q1AsAaTr6+nIGgSpTe8lYVpRBm8vaPqtWr8lQZdSXW84n/qCvIXLFQsnkiGBvb29qaipM4rUbN+Zmao1W3zXYuP3owdnTZ/KhmqHGsNc3Vr7/Gz86dfrS9nZza7szO7uwsFy6fv3G9uaGJmWMWVhYsSYu5nOWDZLy9cJmO048zqv+9NT5TnfXzgXKbz8tW0zsYb8JpMLFOjaiAOJB718REJSxO+bwOAYRCcc2WbqNRdfeXACA0urphABFCDWhIuOR9ZBznuS19RGUzgEAiutWAgigQIkIYfo4nEgQFUQEUlowsQgIYpERxCIySgY30iMCAKuALbDLxGBiBHk6rUWfObI5pV8Kh2TQU1PPjme2f+VFtL/uaHe6NlBIqt/tfOvS5b12/9H69XOnFlsApUopSaL19c0Ll6/EW7ueKGvNq99649z5y4w5IvG8KEr00sr8hSt457Pm1HS9a9QAgmJB5zRdvXxppWgY5h53USQpqt6ZmdrO2t4AlBd0EvN0ZBDLKI8cx5sJIhKqzydDAaLgiAp42N2LNtZKa60AwBjDzCCASMyCkkasGZGICBUSVaDvKe1r9DQFCrUSX4NW4PK2EBFZiIQRUImI+CjjQ5j4AIg+syiLaARAWMbqVoYioVBEUFAUGJE0I+ylEUGZ/T++pGx6IfSgZ2+aPh/T91kfV5bPVdALPA85UijlSm1tvwMAw0EH2MRxvL2x6SkMh8PNx49VZXj61DuvvGY2N3cTo6bq80Slnd1mudaanp2qvHZNax0b++6H7/6rP/hRTsmb33rd7+82B8O4WOm29kuaKn6079vWoFPUxbY93vFm5UaMq4CkB5jmEIjSh/KhxtATeRKTRlk5pzxPu/4iUWTj2DIzCgL6AiIgQoCgQAkREqEG0CRaK89DpUkhCkrCzEyIogg1KiLRxMgWAfWh6Y/lkYi4SjzMLBbBQxBki8IZNguyFQRgsCDIgCwMgkLZPoSnU08iC9m+/KOhjq10HMKJHvQ1hA4KABANu4qw2enEDJcuXQETNxqNIg+E1eKZV7e3tza31k8VqufPnvvgbmP90Xq5NEMgWuHplZW8H/Q63aunl5Mw+uzGrc9u3vxXP/7+8sLMWsfef/iosjCsn/r+3t72SqUaRru1amwGjXxhqn3MeWatN61x0hN04A+SZJJiN+FdFREBBBFxfYwJCRFrPgcB+D6KQOxRHBMzIGKCJCLGsmExbFmYwQJDBJCAxDFrId+6cUGENIaK0FMUaA4U+iRKo0L8vD8ulYNgCEAJorAGMMAKEAFshv/O7R1co0IGEUZBFgP0cqS/YGYe35fCiR70FHBcrsBxxzkuhlFM1lI0LBfynW4/X6jUSrnmg4+Fje8pjTBVrT1c3+Ak9j0VhgMwplbKzy3U49iYBGfmytaafq/voT89XVd+cPHiReHkyvkzn/zZL5rtjppSs7YrYYgzU51BfyrXLxC1hY5/HbPOW8raG9OJ3ZlRHE0KIHJWFCIhC0iaaSxASASEgFUv8TX6GpRSEijmANKLQpY5tjZMJDY2NDZOLDOEosRyZBmNIhREl+GFRc9qwpxmFFSIHgESoCtFOD4SJy4dj8haYAEBjWgRfUIUYULI6B+vCEWELRpiEVYAAkyCz6tx7bFjLBky6B+iB53g+eL41z4j/uj5gVZe4Ic5P4wSf2q60dhr7G4vzc/BoMnMnU57qlprB0EQeI8e3Ntdf2yTsLn7gEF63dbu9j0vKJTLVY1cq9VOnz4TNPo5reamqoGnZ+Zmfc8Lm/dLuYHNL4RWT3e3L54tfdgdAFSexmlIfdLOnTzZZyKHdkRKRiIiItfM2jXnHMe/iEgphYg1v6u1eIo9zxt3tkEEYiOARihhjIwaJhwnNmFu2iBJbBIbaw0AAiMggWBiCBQaAsNpcy5kBmQrPhwoaxOPEDYIRCIE5ClCJKXACpIcHTck8qwIK9DCiRVmscwiGHMWX/nZ2mLHBWWsw6zpP4ETGfQ1BJEGEMtJv99NhCr54u7j+4VcfmamtHFrszfsDjY3T587txEEpXyh1Wo1dnan5qqN/Y0wGTRa7bXHO0tL5+rlSqmQ63Q6hvnBgwf42opYUyqV+s18Pl8eNO9Xy0XxgaEWt+3pqcrH3Q7AwlOZv3U9/IiIFBEQpZKo7AdjZ5ATNNqxcMRMxuDdfxFRBRURKhKNrAiJXL8tJhgiaSBPyIuBEsbYgGGrY28YxeEQ40RESFA7/0xi0vpeACBiRZjFIsrYtnoiAwuBCUCQiEgLCiKBUpLpZVZai4hhYAalrGFgFhaB8Kmczq8AvxbJUh+urXO0fD0+byXD/58hFzN9WsdEVluzp9cXKatvd9b5eTq8p8zhM35QzAmHZrjffnzjk6WV+u7jcHG2Noi9D/7u380sz9WnqxcuTEX97v5mY+af/Mho2dleEw3V6bOfvvfBcIieXz+zsvDq+eWf/t3fgLY86BXAu/7YPmxc98PHFRokG2trZrp6+Y1kY0fv/+RO6/HDN19ZqeTv7oZMxOgLKgBQKBqNElF46F6FcZ2dWClAInLNswBT4gsp1oSBBzmfS77N+zrwRBEqjsZhr0nfc2SSySxQJ4CIqKwVomvwxzjRB9mjvBNGIqFizokrjCqGvErARhlr7aSHW8OB72mkl2kA1JZGB+X0oPQY41F/EVfyWSMDGAAoSHLk/Jn7iGhJLEtsYBhjZCQxVPbYCloGI2KEGIgFGdHPiK9lFYLO0o88RS4PDiw7qhQJIImQf3h6KRR6iKiRFAEi0KiGOGF66zEQAwqjFRaRCA9kLk30WczbiACJQKEQfNUl007wVSCOYw2EiEmS9Pv9XKne7XYbu7taa2tkOAxB6NGjR45LDYDNXuh1BuS1CwqjJDp7dvWtt7//F3/6J5dXawiq2dy/cOH83t7WvC40mq1yfmqg2euqqL3p6XyxWp+Zqz54tFGcmg70QiJsIWERItLEGkWJjB9zqccW0vecBkVIJApJoTiSDgD7FCgET0GgIdCQ88RToFAUybhgO+IBK4fcvTSCS2FHFIWCCAhMSOnzAJ98oE7en3mNzMikrIWxz5uIEOyRssPAk7U43Dtn9AR16RzjcWD0ECGlBAUAUYkV9JRYIlAYCtCIU4SSEqUU4NPKmThw9hMBiCJSgEiSI5g4w8CcvhJ0WbtECglc4TVGAcsKABhIEMAREQBEUI10EURHoEj9dIFnEVG5b4W/ETLo6dnJx8s/elo47uhKqZwf9IwJwzBJ/JLW4TAMw3BudjZBjGKMY97f311cmlVKxXHcHMbbn13/5/90dWVp9pUr50+fOXvv4aNE+cM+xwm3O8033z79p3/ylzPz5/f2Wl2FteV6f21trtL8/nfeUkptPb7303d/8S/+yY8rJJGRyBoB1kp7mjQIifEOCLaHKM45JURAIKSsRiJX7UvA1x4haAIPWZH10BIykmga03/GLwRH9p80hdIbXEhoUmocSB9kxNSF416Oh1RSyIwixKPi8O65rSf038m1NHRU60NKEIhIVgKYSWhykPFQCMTIgmABWJA1skVExJgFGQRIkFEUpOocHjM2n/X9KIqXHqki0EhIUlAJEU3IIHGvARpEVK6XGQICiwgJmIh45JuUA6EMNOIWpMFKIIUKEQPPyR9GJJBfr7fPF/zimNs/JWS68L5Zsf/BYOAXdKPRAIBKpZLL5Xb228wcRQn6hWKhtr2112w2i5Q0mnvx0HqFmgDFUfSD737H87x/9z/+6VajU6rNdPvJIIyGYRhF4fbexit8VtD77LM7r0y9ubo8/+qlU0UVdUw+onxlatZHW8tTlJhhYgW074PviQYQC9o7VKpi/KGoI2c1aQRCg6Paqz4KACi0CKLQEjKhALDn45F6kE/oEoFGF1pciwlrD6ktkMbwYeS/kNEgqXgqkZ2UZc6LjQiK1NFcAe30LxyJofSmVhnkwvBgHR6iOAmAQhRkBGQUi2QVAAMRAItCcDerBQYAQsy2/f/hSC1KEFdMX5AmTnH6IgAlggCUsi0JXNVmtCTEaNx2aVAPhUbiBQHcr1CEEB1/HRAUAn5DfNLfND0oCIJisSgi58+fv3r1nCnWkkFck7i5sbEws7Kyeu3Gzbuer7qt3Sga5rW3tr4eECjth3F878GDvf3m3PyyVyiVK14cm4Tl0dpjQTUIhzOzcx/98p72c76N6kWtwQae2tzdO7tyOorNTBWGGoYaBcD3wfdQAxAjp2rQE32vpKQtIiskItCEhAIAyIISorhHpygQJEuAgOJrBZ8ziBDRwyd9w+4ONzIhgNL73vk/AD6njACARwf+lElJp0ay6wmzC4lG8gsntaGs5TbOxxy5kNJx2LKgAIBGsEgKrQYCAq1IiNCKOOEkgigwtlm/NDL1o3Q26XEhgAVBkQGqyXDk2BbTgkKgkBAF0E2ZCMDD2HGlGYgRkVkIlQhCyilFQBAg53ZjZg4FUZMShYq+GTLomwZrbbfb3draWsp7zWaz1xkqpVQQzM7MTU/Pl4r1JOG5uVkpw+zszLDT1Ijf/e7b195446c/+dvhcPit73wHyd/db5YrhdiYQrEi6J89dzlKZHZ2pjpVnZuurd26vrOzc2HmlPbzUa9dPLfQiaMp3wYEeU2C6HmgSTSIAklwrAcdmEsAkEMkBRqBCAiZAAGZKM3zcrXjSSFiej8E6qAv++QHOrjHUh/qSFQomLgDRcRV2LCHSogdjKMm/D6T4yvCCVMLxnKHEJ6QTe5Pm/HUMIyjjeFgjgCGGQGZhAU9ZCbFCgAwQGUYABlYBFCJWGbBbBmXFZTJhkz8ZixcLQOLEKXXa2yL+YgkRIgKVOpuAwXARSUAVoDYnWNAyyySynoRSDufATupDmwVEYFoVBrVN8IWe/Y7eLH0oFwuZyOrlFpcXHy8fqsN3tULVzrtvSAIELydnYZJOE4GZ5dma7Vac2fzjasXvvfO27fvP2oNbb0+3+6H1y6fbuxsxpbyxanZmcXp+pKna2G0W6tXTq0uYtRbXV0NitX19c393sPLq4vnzp27f/fmAiZaQ6CVRSCyHooGSwj+QRLDISPCuQWcHqQQCBiAEMALUqEj5FJAnSxgbQjRdag5UFMAgDGZ1Hdcm9nxzkZ0RxEQGDGq3X+4H42YQ0B4KP394Py7yYxaMB8cBePYvksT4RFFRGfkWPjaiUgRAcYDMYRKIaIQWCREsEIiqIA85SlmRGTDlCa7IWSQrQEgKx8t0x808lu5Axz7gwI0k5rmSA1iTysiUQSeYz8gKBQA1EKMAEBODLEFCygiIZJIKr8mL33e8xSS0qQJPfXlZNAJXi7EcYxG6vX6+fOn7tz7uBuHuVzuQaNRD0zg5yLrT0/PfvTxjStnL9XqlZmZuT/4/dP/45/9SQJeuT67trXX3t+ulwvlYi5OhrV6ZRBppfNJPETS5XJxeWU+7DZmF86UKvVcoba9e2N+5RQz+5VpJYZIEYiQAFgFopA1AqlUJ4fD4XlEfyyAFCASoTAg5HxPEBCRMfV/pLEhe3R8CgjH+gwAgIijAuGEb3hSiBzwrw+PM8FjPCxrCAEAR26jMTUU7Wi0w37pLM6eQqfHuaRcdMEucbVEaDRppTxGYQUKtCgDkApoAuWElwhlyLjjuj1lnO8CqBRphR4pJCnyEEf+eBERFAtWUNBjIvIUKQV6FCIgFM8iAAmiIAmD0Wxd3zJytVOcDDuoop3zfSJSSEqhJtBH9lf7dfGcWObZWkoWX+noeUrG9vJFj6Cjhs/k9Rzv/GTZ/1nXy/NnksZ7haDVK76+Gc+9cX755i9/FtpBB2ufbGwWawuF+TPB49bC6bc/+OTD//J/8nv/+//df9XY3bh27drW1v1uu+1rff2T99955x0YtpZm54e9fQhV3I08v7syc2qjoFZe+d2Nh3d3t9fe+t7qJ/dy3WF8Ku4sSxOb/crypS6VYwCykQk75OtY+VGSOmkR0yAMgLuVLQiLAIIiAlSgyUMEoMSZV3rsk3E2UR4mLAbh0QcCH1xd50MXCJU6ECUiopQzqdCVfz6w6UbEMjtqIvjEhZ5MsZjUKVzbLjzsDAJASI6ui+QTA4CgCE36lYAlJFJCCEIM1njWGDbC3LOCwsiseJLj1koQAFhABC0IC4ogA5AKxktifNQAYDSAkHUhO0FBl5oGnvJFRKFoYI0QIGoUIkTwFYEm0Ip9AkWgEFAwIIvIiEh0eAF7Bg4LdIc46R15HoQFwI5/cqIHfQ2BwsbGiPLw/r3l5UVNkPO9Tjeaqa2sbW2WS1Ulg5xOdjceLU0XzDA5derUuXPnkiTRWi8uLsZxvLCwsL6+/k9/5535hbnrt9bLZVIe9wfdYqmwsrLYajWHw2Ghnt/bbxpj8sVSs90J9xvLZxcTE0bog/YBAFGBeNakfgpEFEnfIb2Z06U88tECMzsx5bYcRVRGf074hp/KiTrCvBp9P/mBD1MKJsXQ5+dzoG19Dk74PuE8EudCGQloZ3A53UQTiwi7Xs90MHJZKRERIJc7woAsICKJnZzGwTuAFWAEYEQStCIMoAAIFAIrAHK1kURYUKwQiTNRFRIp9ggIFCBrgLHpeui8jaX5SHtKD8c7+rTbUS6OG+PZ5M2/cMg4rszjPZ7e8aIBgQfdjrDd3dlaPXOx/eg2sNEgi9Ozj+7flrgRtcOCHjy8+8nZmUt3b92Lomh3d3d6etrzvGKxqJQKgmBxcfHM6rLv+83mvtLNYdgKw0Eulzt1evHTv/ks7LfLxcLOzk6hWJ5fXEo6uzqXDwIVmmHIpKkqFtAq1n6UWJVGxg+5e0EAyMIEncQpMojAStBFgMZCyP3J4C7NWOOQNCZ17OvyeTmCeGC6jRnP7k+TbuDusQO9TNg8Mch4qCN36uo3PiGAAECMQSRx0nd0J5OA1mZyY8SUmpBDJQyOR2kZrLAwWoBBfGja4w/uwCyIMLJKBRYjKGYkJBSdFnqzrnqI1kAEHoGvQSvySBSJGiksYykzPlFqopbbON8YEbyM/sZWuby59KBO9KBj4LgyOnPrpyTrs+ajEQbdLoTDfLlcDPzNXnfQ6xJCe3snau/HZWwPh0WV6+7vVctvPrj7eHZ2djgcFovF4XC4t7e3u7tbLpdfffXV/caOFbO3t9fpf7q9vb0wWxoOQs+nfCGAxGs2m+2hUHlhb79p+l0MI+WD4SRKYlaxtoAWlEVrlPJ+tQ3rnJeEzkqhST1IJL3/n6h9Mb7HaEIGfZlr9HkBNPpwoKdMfmA+4EzDhNHxhPrzK+eglJoceTw+EYFroCgHMpqQPMUwIdfGUKPfWgYrLpOWRUTBQex/ckradZR2MgjQphQpAYsKxzKFYeS10UoUkqfE0xQo0Ao1MSEoUQcGrHMViQCAP8G3mORecEaxWKLJZ8aJHnSc7V8WPYjEsgnDfvvUwulmYzfn0cBE/V5rc+1+Je9VA+rsNHLFqg37ntJ3Nzdv3N8+depUt9vtdrvD4bBcLv/4xz9GxM8++2Rm5nS/P9zYuT0YDC5feHvt8Y7vm821x2KSwWBQmceFqVN3H65B1OVe88LlGdaQWGtj44uQMdoTQFJ4ND+YiBwPCNy5FXF6UGIPFvSEr1noc/lQ6VAT8R05qqjrF+DwNU2VrDHhcGzRpOKQhcB5TNyfh3zeR37+/IQP1JOROeOk7ZhemVpiAL5K9w4HRhAiIiWxM9oMMQuqkTGrgkO+//EB5pzHCtF5jqy4dkNokgPNxYqLYQEzB0pIiacoUOB54pNoZ385S3kkYsaY9ClPHntWnuYTLvUTPegYeF56UJbsy5wPGzBJv9uOw2G3050pFYaBv7PTHwLOzVenq5Veq9Jp9o1hBulFg0ajce7cuVKp9NFHHyHij370I6XUu+++O1exbKtxJMaEuZz2dOHmjQcLCwW21iMcDAbD7e3S/PndVq/skU14e6uZX5gi8o0Vrcgp917O0zJ8wpmSvhORAGJqc8G4MSlnxL8O/CbjoQQANPDkxl/gkTnyxB4IhfEsBITlQBghgKQCUcAJSgQA73M5E1+83yc0rEkjayz1xgYmAHiKxtMbK2KICCZhEUTSKNYxjwEAKBjljri5jI4LOe0vJDYlgaayPBIRFAByvE0WFAIrytOiCTwFWoGHrAkUCYEIwVgAQeq5FwAxk2Jk4pQk5ujYi/YOycoTGfQ1BNuk1+30251etw2cG/aHvlZz01Nxv93uiO9RtVzffNTMF8v5cqlYLTWbzZ/+9Kff+973yuVyLpdTSv3sZz/b3t4+/e3zcSSddji3MlsoFLqdaP3h45mZi8NhH31fa33/8frM2f7S8qlTc1MY9+/e++ji1DnK5YDR8zzEBJGDQClzIHXHzgIAAHJaOacyCNOwFFuAo3IyJI1nuREO7ncrE0kZE//xZSTRpBhywfHP/+/kZ56Qgwp50jCZfD9yX9ZO+r8O5JFr++O+4PR7Nz4BwEgMOpUFEAAJCFAACZUGYEABAgA9wRef/GAFAIRBQMgCs6AICwKTBSAWawEFXEYXKSBPoUJQJJpEExIygh1l/aaSWpyXHERALKgjDznO0IOsOZT7ciKDvoZAtq1WI4qHNolL5drO7btFis+snt55fL/R3GVjTy9fGPTjSrUKhAalVCrt7e1tbm7+/u//fpIkf/EXf7GzszM1NVUu1Xtd1Wp2X/nWarVafXyn1djvejp/796982fOnDt3ri9bCwsLZy5cinqtnb397e291RhU0UMQ5RGBRs3ko5q4bycFBKM6kEgTi9i4mvaABy908eQDfWfS5nL381hTODgPx9GGAMAxrkePdxg/0w/uJDlU4tpXEzrUgZs202B38usJVSj9zYEXfBRvQlAwykcDSZmZgCCglBIEEAJSDKCQnAxSEk7OYTwTF0lnEAuuuQcyOQVErCSu4D4gEbmdiEIgBZqAXOEBYQJx3qrDpy0lWRp+UlI72IxeYTx66LifP1E/6Gi8LH6QTGCWTzQjhvrr1ab8Eng6/c7GN567J8d1vJLOw62tnfPLZy+cu/DJnbV9XVprDWvDvnjz3/vNt//83/3363v9xXOLEHeanfBxp5qjxUHnrvDm5YuFf/8//OTunYczswtb++32fsMqbPTu3X1c+9HFqx/++c99r7hvZ/2p2nf+1f/y5z//6OzZ4LWlOIpvlebO3lvzzrzzh4kZVGFH64oNIY9ohsPY0znIATi/AyKKMx2QRJn4QCQRApBjQsVJLEjCLuqMIsKOf2y8yXt+bJtoFY3PA9FBhLhI7EYeGztOqWDlpWdPAEXGzhgzwetxws9JNB0nACDoKuUAY9rAo88JpKn5Kt0pKADwOGQQw8AgLoUKFCEiWBRxabFWUvvRWUfF9IKOSNfokiCAU0r4YXJAoMd6hIEJiWPJQkqDoFH/NAIAX2t27T0sxiLGebKFGyOeklvYBESIRBiLJQZBYkYG9lBZIEAm1JPSbfzeMgcCZRI6jQOiiAi7Mw0ikKCd/PmJHvQSY1IRgFFM130IguD8+Qvzc4sPNvZ8f758evHhrY9fe+2qR4nKlXLl2VMXLpe94dTU1FSl+LNHt9/63m9+/4ff/z/91/9dfWrp6uvfanWGeR14np+Y2PcKp1bO3r3z8MKFS6V8rVKpXbpwuVSqlEulaG+j0+pWl+qDfq+/v3P29AUfQw3ie4qNU3LQimVXGYudGBJEdH8qOYgEjf3B7pY+qAQBAKk6ABZkXADIPUmdUCHRMnoUj+ouIiImcCjnYELvsOD4Nu5bTmeQ1ffdkRE5DZ2Dq/cFAII+IDirZjQYA4BmEsI0cQGIQawRAfRBj45FA/JIIqMxAAdPehy7csZHmmIkfyd4QAenDhCI0l5rcLidqBVhESNgBQ2zYUysMIjI6CymwyMziEhMqA9+ToBACCRkENzcnEAfq3XWTookGHm1QBQIp/0aXbqtC2w+IcJOZNBLjCcE0Pj5f//OnZXlU+QHH33ycT7I5fPoganWpzylPF9X5k51ra/Ks5cvTC8vLXjvvnf+2vlX3vj+ex/vru2QKnmLZ0/XQo5CBkkI/atXX1tcOH3v0cbC3Klysba+vnnp0pX2XkMLFgplESUWuq395Vpldqoct/Y0GO3rCMgTJOWxgBWT1qUATOtAMAIKOSK0O5aJRz0RCQJbRyPi8aJHobG1AgKIwCKIGIMe64CIQiRKARGSHPSAH58zSO8TSwDCaB0NEEhEbEbOpwWnNwFYYMeqFuCRG8jFkqwFtsJsRYDQT3PcCC0IM1tmZg4UgtNvgIk8UmmoC+J48oKO55lGDD9n6agR5/MJFxihCMhYZEOq5qARZKDEcsIcGzQsMbO4kkXpbkeShUWEByAaQTN6gj6JdrnyqSNJRq56GOs1Vg70mklw+jWmYU9OCRBWDnEINH45m/kEzxFZtvCk+1NEaIRmY+fCpYsEcP2jT958860kifr9PpNGsflitTq7qKAyhGBzt3l+Zcrj8Ee/84OPPn784GH30rUftXobvcRevHQ17AF33q9W68X6/Mb6biFfjSKb8+3m5ub33/mdn320llN49vRqkFO7e+0H9zcvr66WAt2wMYjVCi2SIoUEsSJjXIkrJ4AcDc894VMnNCJOdk91DBgngABo5HpAyzh6DstIWiEAGFbMaIwwC4AoBVojESK7xAIiOhQpU8ROqFkmYWRG5+zOynePrIaR7mNH2ghj6kW2VtiStdZadnoEkRLnQAanvgEziCCZ2M2CCEixUsrJSn+UDDIpUOCgVvzBk2akIqW+eRclG9MmNTvfNqb5WQwuKyQUtMKx5cRAzGwsGkYGsWPnGgAgOjHujkEheEqMZaswjYuJRHYyzjUKZh48BZ/0xFlgF3Rz2lCqEAknPI734Yke9PVE3tP5fJ4ZtB8k0bDXbSax3d1rXDoz0+l02t3huW99R0H0ySd//f1Xl9945dLf/PyDn/7tz/7Zf/Jfru1s7zY7AvHZU+fFQqEYnD23+osPb773yZ2LV14j5dnELC7OctQLO3uFoFYsFi2xKhRBN8qFYpJEbIwxBq01og0qALDgkcQggJT2RkYQsIAkxh7cbzgZs0cRZzrxgStBROyBIeCC5QjWRaaUtWJtWv9QAVlApZzkwfGNOj4/Gt0jnQyjsWhYWJRIZumLvvN3OAEkIAgWBEaxZ2ZIBRkr96hXzl8jVsQCMBKQqzmbAAA7U1QpVK6MJImlgxojYxmEiPoQH+og1i525AcUQHQtIQUxrVvo5CBbGmWrUyhgGBIriYGYIbHC4lrEHhJ5nB4FJsKM5Bw5wGhJXEXtQTLZ0+0gLUOhHc9/8mqOsuVRUq9QaqYl9pBs/VJ6UNZz+ATPF5PXZWQXsIgokkKhtL69o7SnCcNuzyCcv/zK5vZmQfH+7vbKsEM2jHvdqUoReGrr/qNvv35xaSHXHUKnq+qVsuaoXAiWp2YvXFz97//9n8ZxvL+/PzUzvd9oXn3lQt4zF07PGeP3hoPuwFRPL8Z+4d7G1lK+Fic2MRyHSWQ9IGCUyEc2CkmAARGQBF0RLAZvvCoRDz4AaGBBEnGVa5y6gQBoeJTreTgaxalBhCmDRUiEmJHSooOIiJNhCWSwAJbBMsaWEotWgAWzetGERsDxjEWsC3IDWJHEwMjwIUldQgQAHoAAo3MCk3gIgECI5GkYu6IVCKEQMkI8SpvDlHqTftByEPuHkaKR3rCpMiSIACP1RCA1vpyhJKNTlyAkVgxjbCRhsOKKbIBOCaJjVRpEEFApJD16YuBIEaXPrbfxh8/3mHKuIh65fdyDZHyuzKjOtHz52PyJvfZ8kfUMkMOc4LGbsFTIad+PEp6dX/R8FQ675em5H/7mj/79f/ffkI85Tf39LTT9cg6jfufBvfsrtZmZlflk+ODq5bqmmXKumIdkthycv3DaD1SxmL96dUkHpdhEQaAN933M14pqa6+XAO+HNhwYzpeDSq7R7OYQYoZhGBsOLEICxmBQThAAkVILAtNnMCONRYl7T/2jCCJohd1t7+IpAkI8KnYh43Pi/EFsAEDSvvPIhEAgBGZMtIZxQryICFtlBS1jzBhbihktoxXgjPhpwmkcikWssB1xKdPYs9DIKiFxYowSR6fWpBWxJlEEiBKQAhwbU4wo6OoO2nHR/0PX2lUBG2scI5ICwCg+dVCtTQQAQpaRxMCR99fZR2xEDEtiIRFgIEAFiCyH9uh0GwAo+K5/BmpiBaKRURAAPK0nRQ+MXct44EQffwAAVqmP3EUg04kJW5nQ6U5ssZcaIzt87FNM9aB8zr937x6Lunz56s33/nZjbe3VheU4Nki63W4EHpZzSlnPT3Szsd/rd3iY/OWf/tEf/Kf/eHv3djQYNte3kv2N3nTuH/3Ov17f3l1cmgtKC/ly/YOPPrh8aTWOBzP1mb1WOxy2KzNzSdS/8eCxsvLO1Uv37z708mRRR7FNmIUktLF4+VwMYxsEERAJSQCIvZQPLaN8+pFew4IgDJKmj4HTL+xIEBxShcYcRUJAQEo/CAqL+3RAq3OKl2G0AomlmCG2GFlKxHWkydD3EQHQGWJW0KaEHkwTw3GkAQkBggj4EgohafKUUkSaGMEiiCZxSlhaYlDYyVSG/PhqTt7G4oiarjgYpg2s3VkcSVMcFTlkEQlH+W6QFn1Oo/1KgWUylg2zBSWAiCRAaW2xsUtu5DwLNCCCItBAhKwEURCQg4mc2/Rfp+qocQbbAQAA0jrcKb1xFCNzlvV4DYOWjP6zh5HFZ8nIB3lKetMk32wS1n6ZOf9qZM0zS+94Wuche/yj4ergfB6hUMnP89AkwEbZIK+KAvsPHyZd6+f03NzsrY8+inu982eWMer99Z/+UYm7O9t3Zur1lZngww9v1HzpSOX9B9Hy5Zm3Tv32wzs9tpg3er+znjt1/szVK3/6Vz9FVWu2kv7e/fmF5sK0GuxteN1y+MbFuXJt229dv/EJJfmLVIUK3Xj004K6HD76yQ9W3/yok7tv8oyFYdxW5O8nkbsVfYIAxVeSVo/GAiCTCCCjGNcShoA7vpcubh4vdwsAMSeICpAAkAXZkrUsInmVOmiJSIFy0XlEtKPi8pzeZ84tDiaKraBhGzNErGKhWIgBxAYALJi2rQFyHiL2k7G8Qw0Hdf9ie3TfVOa0/mniCDfkuZUcogEAlRbOZgRRgIDsqxDGUTA4YAIGWsPhiKdbUe0kjYI7V/fYCLVjfxMKQModB4TYoAUEJKXJudYZEESSlG0wsbqEwfKAB84WU0jayTxBGHMIAFLFB9Mykj3OPSlAndpp/LFImlTZuhMcRTjpL/ZSAxHZGkAeFTZGADBRfP2z9y9cezMKC/Nz9a3+5qN790+fv7Td7FSge/Xq1b29vQ8++MDzvIsXzyFip9MpiRkMhhvrO7Oz85999tn582evXLn6H/79n/zWD672hwNjkzOnVqK4t7e3d+3CK9OVmeuf3osGsr6zk0jU6zUjHCzMXt3e51tr718sDTphmCvmpR0PQiPK5nPaxgkyWRADTATIyMDKOacBAVxlYlKjsoLWHNRvhokCHWOHyIhGhETInDZ+Fxfsco36OK3+ceRps4LshI7zujp6pwC46LwLPCMAg6CrP330+bcZzxjFiIjCyAJEyALCgoghJyiQVmJOE+Wc6+fA0TNp7IRp7i4gupqS6f8aO1brnP47TvWw+LlsfkQ0MjqXqZJEY9F+5PyNJQZU4BgSiAQkDIDRIR7QQUA2Ap78cvyOcEhGj01xgn9IbD5rm6O/f9b+o+c3/nG/P+74x4MisNZqJE9RGIcKfBTuD3pJ3N3feeTl0Fc87O3PzVSvXT2fW9958PHP1cr07OzsnY3m3t7e916/ODMzY63dWN9fXJxfXsGHDx+snl383R//6O9/9u7jRzuDN1Y7PbEJKqSdnZ1ms50rlhLQH3zw3pVLb/i5aqlc6Azv3n14i2tLW0l5frqKKvng1mO9PAVQEPKBMBwMgT2LoAVYgFkSAg8BgD0jSEIgSKhQCAhdN8IEYCJ188BfoVxwH0ZOImc9gHHdrgSQkdK4vyCCztJDQbFj6TgSNgs6z86oFyvzmIUIX6C2SoZezMjjnzppmF4vZtdEkEHUSPYgQOR8tHKYEi0wmQMxOgUAADwRVzqMcExxwBHRITXq3Fwc93pUWNtkpAMkiUJExWgICFClRArojsphjp8K7s/4QB4dvAOgkgOOqHtkpP8eDkCe6EEvMQgFrEX00sAzsljb63SrFb/T3Tubu9BpbMfJ8M1Xr4Jwc3+/UCjs7e1NT0/Pzs72er04jpVS5XL54f1biLi8MjMzW/uDP/iDP/njv2js99kioqqWC3Ey3F5ft1E4Nzvf7cdbm3f7+xvvzPzOrd1hYwgYTIG3V6kX6lOvr8xSa+P2x7evn8mH/qxW4iUCySBR6CtARlEoBlARhCgEpChRiM714Er2KUFEVKni8eQ9hmkZZki90jyWEDT2KLGVsY9+FGAa/Xz8H0gCAgxIogQ9BECLgoIWABiBRNIwmXWVTzNiAhm+gpFiMprFSB3TSo0cPAQo5Pqmogydd+hze0nwUB7VeAM9qkX7xLueKFMJE6NZTu0vERYkFoGUwH00QieDCIhIofNvKwQORY+nMakHJQdX6uDJAQC+HIrlj/HEz7/RelDW2npaetDxxz8aX+A/QmACRmCFQgBJEvV7nf1W8/S5q1ESrm2s55TWXvDw0Xqr3Ts3P9/Zut9ut/PTK6dPnw6C4N69e71ej4hu376ttPnf/G//1//23/7bra3dfs/Mzs56nqcpF/X2G63m+Svn5pdXNrZ69x/v+tzoJb3IaoapXD43N9s5tVJVtTwa6MT5gdQ9VSv6+dbAAHpF7ceOYMggiAScGjwAmgBRNIFiJMUaSCEgif+5538KxknX2yjQhqP6RONfHaxvOaqc0EHdP0ECJkCPWAQtGACwacd0YVdzB8Bm5VRmXhec2ORgMux5CtMmYYLERArFApiUZwyTfhMAAB0cHmRkpvGh+s0wKV4/NyURsU52oAigc6u7P7PWbcRELuUszSpOuVUJHIqpj/dlJgsCTQ5JI5ompE8N91TgCfVSTuJiLzesUUqBEbHsadIEwyjs97v1mYXf/PHv37zzEFShPj29sd3Za4fzS+cLfvuztTWt9UJpNoqibrdrrb1582ZZBjMzU++8871//z/8cRLLcBhaK632vtb+/u7+zeufktavvH7ZWomtlOrzD2+8t72/c+bSqz1euH/jXc1QhH40WAM93R6YQm0ZTFKgxMMESeUBQE1knk/cJCxCgIYBlaC4sJQgo4Unn/MpDI1K36TNmp2n1j+I8R+6qexEnv1YEGGajYaGWQQskdUsQlbEoOMWo2WyLIbJyYUwI2aflRduJyXCRPqFsWIACFkBGmKFaQraOOkh5fWMeyWOZDEePjQPD9VXGh+44BE1zJwbXtIyIMAueJ+2JMx4FiIKAgOq0UQcp1pG9bBTG/kod9uh+cCT85E0kntohs9EBj1rPeUEDsJGK81g2bIONCLEYZSE0UxtptEOY/Euv/LmUr3U2tsbcmPlwjW7+wtjTL1er1QqzWYTADzPIyIT9//wX/zrn/7dLz799Pobb7yRC0pEg93dTbbQarUae7uvv/46CTx89Gh2+VqhFnz6fq0bJZeXC9xGtnEl8EqUzJb9hu0nMjh95qwJdzwp1CtFgzkdDUjnAMAljLt177g/rvyOSisIcvpgFjsSFun7hA2lQAiAARHRJYURouRGVsVYyrif9JNDMmiU0AueiCA4ySWCduTaiJlZkJkti2FkK9alOGU0SIn56PisRX9yPgffO32HQRCQgYEJ0EWyANLcByIcJz3IhL4z+aGgYGRmCkzI69AqkVFa72T/xVQApernSAARZPZrAUZQoxIfLrSOE0yiJ8XcJMPIfUivF00ILBi/0+gypT7pIydxgpcCIkJEVgxY8Ug5W8xycvbC1Z/+/P363NLy+dPMUaFUHzxqDEI7X6tdvXo1SRLf97/1rW+dW5nudDqvvvrqW5d/886d2x999EngF3rd4blzF/qDRn2qFMexJm9mevrtt99mD+9t7r3xzqmdfaNoRXsFFcTK61+8sDSTRNAPre61ooaxg9ULy427G4Huln0PfdQDaBjnwgTLjmXjKnKATUQ5YgrYlDrjFAc6kCWHPphRyUAERJfoAERK4fheHW8riOhE0wFPMWVMwygp/CD3Ko1M2UQEmZQ1YAAtAKOwYJzBvTC/6lH7OUMJUQAoDU0LoLi2jhO5tTiRA8FhLz1WcF+mQi0IPr9jAYDQpjc2Ho6OIWLaBwmVgCBgVnZuCnK6CgIBCrJYQASWA+LzYf0AR416xu0nnVPcTOxl1J/KmXaHZJnWGX61L4enUwcnE1n6VMb3WT62484yS//io2O9kNXT7rjzzKq/mzV/D2mYRPlqud/vQxxXK8Vf/OIX565d8RaW/NvbqrUrHdyPZb9pBv2mCu/kCqXrTe83/vn//MGdNdhv/+jt6fqsr8pv/8Wf/+znP//w3KXXmM2dnd2kkH/11bfW19eTOERtXn/n9fu725WZpYUzl0rV0s27H/zej6YKNpwJzdb9n7xy7sIwWi6U6kTe/ocPvrtcO4trfp537j16/Z1za3utBGnOiwCIRRnRllVkJTHEDIk3dhsrJyRcMrplC+DaroJrPiMACJxogygKkFCUQo3kyvIopZ12TwAo7LYB4Fp+MgYs48vqySgWPuG3QUTDxIAJCCs0ADGIRbAsnAREoIk9Ak1MyASGUFTeHshTpsQKO3pllPYIJPc2Wga+HOqh6MQOAATQQUSl1EFbQRER6RRyAIDCGqwi9pCdnxjM0f3LhIzTgAAO6yz66HUbG89K+kiwMJq883+legumGXjuSrhe2Agw6q+d6mV0yCE1huWEERCUuMeBa5uLqA73JjjRg15ieJ4XRkmSJKRAkYrj2FNYLuTjyCRWFk4t7u5vi86vbeyfWV6ZW6iv3/gsH/iLczMyNI/e/3hnp3rttQuPNm7eu/GZ5gST2Cah4njjwT1lo2KxqFTtypXLxer0X/7Nz+qzi3E4LOY9a+Ki5yul1tYe3b59s1QuD4dxvxf94Ae/+fMPPiGCQRjXajVG38ZRoZjrRgJiBUhACZAVFAbrUtwBAFIOy/iDiAgRAAsoch2x0puAXEtkJ4PIRfIREDExAMAESAoISSOJCyore6T5wHBUvEmAxbMihoGtSz0XwygMCq1KG3JJGgRIq6EduHVxlByLgnk/zUF9wgzMqUO22/i+1aLHMsh9k3YlZUBhBEZEheJ2oRAkw0Wem8hlh0kxlGFLEosFERcEBGF0VV8hOeh7cSC4AYDw6HqYOcVHyqAQQIG7lMJCDAaEPu9GOpFBLxCy/GhZerPSnoRxkiSaUCFGwx6hFAv5Ww/uz8zNLiyv/OLnNxLsX7x46dK5M/fv/OLTD/5+7tzVs0szJcBHP+/32nt57woxXDi90K0XV8+uJEl069aw222XAji9NP3WW6/Pzi392V/8dbfbuXnj07nF059++H6/vTdX920Sx3FokujB/bvNVs/ThTNnVuu1slJqZ29vtl7VCna211V5rlCo9wYxAzCgZUoEYmYraAQmuGqj+kGAAGCZkVL3iBM6Ls1bnGfUWXPgGhAjgFjLiKIQFaKvyKaeDmeajW9F5zcBEbGHfbdj9l5k0ApZgUTEutJCLCIYICOJQiAShUJo8fDN6axApQgABQjVAWM4VYiIEDHvJaPjPXQbolXjuitwSFwyIGNaq1GUJo3ohG/Gesjob5FVWx4sA4oIuwZBJO7PAerRmUn9Sm5KypGoJrx17kNRHaqrPQYAusZIjDKqimngsKCEr1n9oONG1J/X+FnbH9cHz8xAGhFFGIWHvS6xkSS01s7PL7ZaDRYzjJLv/+AHaKI//g+3tCfE/b/8D/99a7eDZlAuBQ/u3Grt7MxW83llMR4sTNUXv/9Wq9UgoqLG6enpufkZluTyhdWPP7v12d7epx9/eO7CJWEMh/Eb37rKEl+/ftMaJlJ3bl2XhM9fuxqG4eOH99Ga89eW+0rvdHuki4bBssQWEpYEwAgYYX9Uy2rsv3DvCQowaBREVEACQqRIODEGERmBABHT6siATIBExAqAIQEEBWwYEfXnIjLuA8NkflMaFAfAyLWexrRXkML0Zs9RgihO+QIQcIxGZJnoHItpPhcJkFY8TuNCREp/S3hQXSydifuT0qYaB5UJ03psIASoEJCsIlQkikARqQz/iR6dTDj8IYMvDjBK/rXMVmFa617QwFg6H8JITRt3XkpdzzmV2tR44AgHETBAkPakFktgWQDAypPczhM96AXCcfWgKLEusCUmFGsHvZYk4bDTeO3ape7m7sMHtzyCualqt71no0E57w987jW3m/uDqBPNlsJA24/f/2XYL+5srC0tLfV67cft/Vze39nZGg6Hr7xyVcTeuXVze3N9ECavvXJpa7dJpMgM1h/tzi3Ozc7Uc/lLjx49nJ+vIua6nVaxWCTgfKHk+361UJyplHa3u7nSYneoDIMVTqy4NFHrKquP1+KEXQYAIkDAloiQNcPYg5Am0B/430jECoPShwwQax0LGmTUxxUOyyBU3udvMEh7GSoE8BQ6YYeIIFQAl8+FQgeDiAATOWeKu0oyvogTImY8uIiAndAvJj5oiph57DmSUWlwRZ6r8KFdlwtE5RxSWfzsiXpMh85qxvqhtJ4tEhGnKf+ICMr5nsdsgdGLDmJwh8SQfM6adpt5imTUippEiNB1QzNPyKATPejzOK4+8rxgBbT2FAIzKTFhrytJlAx79VKuHfUVRIPu/vLy4ns/+5v5maliDjt2CGxnKjX0S8POdhJ21h4/KOfPTU/VPE2VcrnX6zy4d7dWr16+9HqxWPyrv/7L8+cuoHCrsXv79q1adTpfLDUaDZ9keqayu71JHhEws9ncuD8cJlcuXnr8+LFXqA6Hw6JK4mHHxEZ7/qBjmMGwxCxWwGDqV5jgm8DoA4KrB4SKWBCJUQjFCCgQX3lIokkpAnS1u8SKiEeWCDQRKdAoaRsKllHo/MncAlIGQBxvRiZqVOc85VI9iQiRXXl8RPFM+pBnQAZnsIAFYNTMkFapl5RjCIiGUYRY0lwQSHUmoJG0gsNrTGE4GcniETwtAEAICoUICa1CQiSVyVdSAgcCdyzjDB/tQEoEWVIxYdwHAXAsTXfGRhasO0v8OWa2ex+aceQRMSVqjzoRjDgBjORaAjAQnPikfyWOq488LVvsuNu7nijM7HnaFx4O+mwTrWh/61ElRxHY3W4j6jZ3N9oyaHQa26fPLDR3u1sPbvsYaNUql4JkOLi/duf8lbPNZnNra4MUVOtT337rTWb7H//jf/ydH/8AUMrl4hszr968fec7b3230+n8xV88ml9aUgSffvrx3OJcOOxbK3v7O1Fo79xIVGnKK5nd9Y0901lcXJybPfX+w4eJt8QirtSqJRAAIQQaMeAAYOKGAQCkNBAjLhYpjIAC4omgECISKlJAIiAkYnOKiUATKo0KkQCYBViSUWz4CVXIpwNGy+TZVa4UBwKCQUQaPee9cXdDJAPAQJZZiRjS1gqPCkZbJ0MRDGgRcHXCUjMrLTJ70A92vFtE1FqPvdeHnn8aUUChkz4prQdHEcPPQzA31ryYecx1HNijV5AFxaNaTSzI7KqjoD3gqSNMpF/IRC7IpP+udzgtbCxkSQwjOb3Wpo0iXaXHExn0dYHneczM1hY8rYGTKETgfOAlYa+ey3+8/kBBsrezhja39uheTndyC5VTKwvNtSYJTU2X61NVtsn+dssv6qtXr16/fn1vb+cf/cHvraysfPjhh5VKtV6vxnH4+huvDfrDUqmUC9Sr338nicNadSox0fr641q9LGKr1fLVS5cFvdbWxocfflioz3//269Guw9uXf+sfLFMXiExYkUYXK8bBDVSMEaOmJH8Se9AUto1B6VUK1IILEDGxEopi0Ju8UtaoU/7opC0Rl9rhQDIyFrEij06t8BDe8A5GgERSTkHk6sFz67FEwEr9ABAgAQBU2K3y/8kSTk/zoByMghNenuiEDK7qBCLCFDyhBKBiALwhAxiZmstETERiovEYcpbABDJKnsNTqwLsyuIyMKOFjTMkEFCqR5khVxdMffnWMSNTtGT9h3iobTY0BJOYHzOtRh3xhnA1ZdLLwSbyWn8evSgFwyZ1X0yeDdZyDJPszqxHdd2yzzlx1SQVDwIDedyOQx7U7m4//gm9zo3b987XfN2kKcq+Z3N3UcbHwLh1MxctTK7fmPj9OnTy6cXr1+/XplfpeBSI6rgtKxtb3qF3MrZM6fOrc4sLP8P//HPrbWRpUp5ut1OHq4/On/5SqyS9n5nYXH427/9oz/6//2xMfHKqcVyofzq5atKBaVitVgs9/iNv/vT/7FetNXppb971Gpt7nxvlWM7CCUXBIFNrAAFQS5hGxujteZRHajx0nV1/HxhQiZfiJARjGWTgGVC8hKByCBa5z1xDhRd8wyjWEwisCSiEFGhAlGqj4gKFACgEI1usDS/LO2SyiPeI3vMLrV7dFnTGoAoniCIAIugAKWkGkRgFPEEibTyXP12AoACsAVgZstgAKy1TCgCaFPfrasFRK7Y2rg8PoMIC6MIucIAzgfvrEwthCZdPAV9ND8okoEwWlekzZBlbRhEoJNhix3p20YEraMjtx8m/pHfswoO/pi4FeTJnNvR9pib/P5ED3qJobUmNkRUzBW7rf2trS0RWa5Wq7PVjz94NwA7v7hsbdJqN6IoKgR+cXZ2f39/f3+vUinV63UAELGNRqPX7k3PzL3yyiuVSuWv/uqvrl+/7vt+v9+v12b/8q//+o///K+m5v6+Uqm89cbrvV7/g/fe//Szz157/dqVV66eOrX8/vvvN3c3a9V4QXl+oZDP5/18aWh1sx+LqHKxEPnY7vqGlWEWYWFWAppZfe7B8IRikrpY4EBXsmNXKICMi2MgRkY5HUIhEogasaWFCRFdzB4RWcRFoDQRpHTIkceDUtfs5GN8PBMGAUF2RfUZGNgKsrCFtPyQiAAQO3MDCNC6/uyC4Og8ruW7xXSXrjSIiGs3ApEFAFf+2b1QBITRkiCCQgSABIUEUMAChBmxeZdrIoKJBcvI1vF9Mh952c/Or1Qx+UbIoK+T330S7rCSJKGcv7u/b61dXV39zne+s7a2tt+LPR5ANfByedUhSaJqufBw81G73Z6enq7Xz8RJdOfOrbm5ubm5uSg0zNwfhrWpacNy7bXXB4PB1tZWEBSGgyQcmrt3Hvi+f+7U2bXHWz//+bu7u/u+l6tW6sPh8NNPP/3k4xuezi0trbz65rX69HRQndls9Y3KFQow6HeFldZLApYQhROwoBFZxOO0j8WkeeI+pOUTXezpILKU1gB1HgfmA6JKP/bBGWhp/QAEZBTU4CtEItBKFCKSKBBAyQGDpJ5WZzON6sMf8KpFwNk0wuxqgPEoXcEwWmEBsCwiYiT93nlRGEWLEzjiChBqICEBQCPkJu3CTuOyHgzjvqkoggc1SawQAJFoHlU7YwGAOKP4vqsVbwRYiC042reImAz/kcrI2KCMup3Hsya+9PZfq7hYFl6WONdxwcxaa2utMWZ/f79Wq83MzGitWeUuXn3t5kd//+DhesnnMByKjZu7O6dPn75+/VMiKBTzjbXdu3fvEoExRvtep9NZ39zYa+z7uWB2drbb7danp/7qL/8mipJ33vlePzTr6+tRFPd6g7nZhRt37u+3mnvNxuLi/NzCUv7+4/v3Hq1t7hiI/uD3/lGPcp8+XPPyxZLWe1vr+fq0F3jGgu8pi6BAfFIApBGSzzFZJlej82yMSicDjEqyjn2e4417xiMBAEZRCIIoBAqAfSGNqDR6WjSx0mBRQHCU1+6qaDgRyACAE/0emDnt0iWUpOKSrIgVYQYrIELp3c5smUZFpgkECMxIlXDidSTdWI3UukPvUeoDdiaYqwOPAECuczWjwZSP4AJiNkMPsuRqNrvcCxi1JCTEozmKWdpOlsPpi5PMvvz2T9C2T/SglxjCksvlmdmY4f7+/szMTK/X+/M///PpheVyucTGRuGgSCrwvJnpaq/bJjHNZnMYDgTM9vZ2uVzM5f12u10s1BXh7OxMs9k8fWoljmPf00qp69evV+tTKyunGD2lVBiGW1tbtVpt5dSpME5u3rqtPD23sHj+wsVWe9DvDavVaqVS7nfFDIfFeqHg2YD47PLc3lYIJsqVSoya2XpamyQiSqNTnxdAT0giGDlBxwUo0qjSqAZ+mCBM1GmmUXICIhoSbYABjUZthBABODmISZELQCOqkYXkdgoiZK0wowhEwgAoaEGIgQwwMzG44h5inF3GkNZFIkXiIliumQQwkJu5GWWQH/bEg5FR+EkQYFwHHtA611bafBElbeFsMmQQu1plzruc1ipDRvSz+ERZDsiv9pH9jZBBX2M4d/twOGy326+eXd3d3d24d391ZanX2qsVvYXCwrDXYK2KxeLe/j7beGl5cWqqVi6Xo2goYM+cOQPAO+vbncZ2Ugr67T0lcafTQcRGo3F6aVlptbm5ERSL1Voxp7UJ+0i511//FgBvbe0EOT8Igkqldnb1vOcFtfrUzes32rHWXAubyW645y9ODXunBo3YstTzxIQxs6C2rvy8NU/InfQd0oDRGHioX/MkpxEAwBIToBFOA/OpDwUtWtcGUAA1g3VV2IF64LLQCFKx5tLxR515RjRfZhJBZucOEgBiFBZgRueVNiKWmRlc29KUa2TZ9ad3/eZBkJFcuC+NOh2mKULaL0RGlV3HH8CCRhhVrZW0aw+w2AxbaVSLf+RmJwRw+VpHy6DP9wVzMBlCKDPvLENmZfVrU0/oQV9XHeGrxPOy9ZRS/cEgCAI2ptvtTk9P9/v9Uqm09+jm9vpDH5JigH4xPztVzuVy2gsuXTgzNVXzPK9YzF995WKxWHzjjdeUUoFwu90mor29vfX19X6/r7UOw9DTwTCKPr15p9XeBwAO/LDX3t/b9MtzQU5HcT+2caFQYAble9Mzczrw9na3o4SCqhIexr395m68tbG2t2ZIeTO1HHpBYgB9bYSRcNxU8AmXEFFaJAhGzW0co8YedW+IiIcWAFSaLiA6zR0FUQkCMiIhWUArqVEyBATrpBwiytg/bc3BNJwV42wxDVbIKWLOCgMr4iJQFpAF2MkRAdc92fG/mZERhFEOVJIDDtSIn+RkbvrHpAACQEZNgAaAAAnApFwGp80dhbS7mSACAgs6shOLyZBBGeNk1fDPqqOUpTd9SdvtRA96ieF5XtIbFAoF5XnD4XA4HO7u7rbb7UKv22/tztVKnVanVinMTM9s7+3Wpmc2N9cBuN1uh+FgGPYHg97t2zfz+fxiOV+tVuM4Xl1drVw8NzMz0+12lVK5UjnIlV69fXd7v9FoNMr5nIfSau42+6pYKmxuPu72mq1WC8FD9Ijo3v2HftTd32v3cb0+NZsMmxvr0GVqhUUvKCbhssaqsYAmnwDjqKnL5++ElOc28tq4b0ZdPwEOC31EBDAurVwdUIoZEUVZEHIlQcD1QWUEgIgJYBQXQ0gNMUBjJqXhqDmfCAKDBSBHnwF29TpArGvLAS6mntKIWdDVD2RAl/1uGQRRBLP8MnjARiZwZYWAEDEacY/FUWwAUjd6lgxCdEE85SoSUUoFyOr/kaWnQIbedHyv9JcC/h/+w+BXbpRRsvK5IasY99OapzytgbJ8gce8lFbn43BYzAfCho0BomEY5wqldhTOlZTXeXzzp//x1s//Cky/UCiEsSnmfc/zfN9HxDiOe71ep9MZDAbD4RAAtNadTkdEpqamrLVhGGrmQqGgtTbG+L5fq9WKxSIiztZKMzMz09PTvu8TUS6XKxaLQRAoCN3ERMRa65zizAymNz8/DwBOFPZ6vW63G4ahlGeKs6vzZ17Jl6Y3N3etLk+tfnsrDHx99NrzM563WfrmE7Vcx7eoHZVGQ3Ed310NZXbDE4FyLbRGvTisqCd24f4sBhk1zJKjb2IhJSJW0LUMMi68Juh0E2GX8EEiLupPhrSjO7IAp413SESy/DhZ+kVWn1jJdA5nxMWOaRuRZMTdMoy0RJCEPUSF1kN7oge9BBBrmNmY2DFetFLiKR9tDs2n7/5i67Of9dZvyLBXzuliPl8u6ySJjTH9fn84QhzH1to4jj3Py+Vy1WoVEZ2b2fO8aBgqyzEng8HA2k6j03XyiGzocmKTJAGAXC6Xz+e11tO1ovf/Z+/PgyTLzvtQ7DvL3XPPrH2vrq7eu2d69gEwA4DAAARJESQlPYkS9aQn0fpD7/3x7Bdhy6L9wqGQLTOCzwrJtmRZjwpb4pNIUCIhLiA5WGfD7Ev39FpVXV37lnvm3c85n/+4WdnVPXVBlNHDmQH6i4yszFs373LuOb/z+9ajabZtZ7PZXC6XyWSS7cNlh+mWaZpWJq/ruqZpAMA59+KOkas0AwyDbm6M7Xa7fmfB0CsIufvSPv3c13ts1bxnBQZKFE3SLZJRSnolQXrEBQkAUiBU3VkPaz9oEiB9jGkpte4VKCBAUSZhibRHl1Si42BvTQ2UQCgSIJgk5CfBUDQxhx/ZB5Vc5+Hb00wFaTwo7Tj3S3QKFCmjihPUCPmh7EEfN5PRD6Ki90M+bp58QkhvQQaFjAHFkAk/jroWBFuLl5avvl021HA5z0GhjAFUrVYLwzAhPlEUAQCllDGm6xwAKQVN0xljSilNY7Ztm3Y28fEj0yiluq7Hcex3OlkrQymVUiIFQohA2vHCOO5W6zU46LHaTzvIOTyTyei6nsCcZVm6rjuOMzVSZFz3grBSqQyNThjlYlPTO0RVg8PvN9UckfKA+1eCdydwJ7mdSUwOIYoCJhnnMll0mgLBZI0NTFz2nMj+vRz8oKUAAuOH89zEMyWBIFUKiVCQhFsLZEnlIyVRIFCiEk4kkxDHXpFpkKhYsrJpSr3n9Hj6o8UcpvGdNFt1uqQqdYduNSgmCz1yoIyqBzzoELlvdvq0Z3zEw+ucCtAIQUIYqDj0Wl59L/A7OUOZcWsoZw5mdZOIVn232+0qpfaanSTxGhHZAdF17vu+YRiMMSmlaZqapjHG/I7PqcaZpgAppbphcF0DSlQUMk3T9F4hnkSzi1FknHyihSXn2L8p0g1Uy20nqKfrehiGcRxblmWCYeo0YxmmbXUFFqZOP/LFXypMnvgBDZeyPc1fs++z37czA+zX+OitXoiMAAVKCNJ9cCGYFAZEAooSAkAMfk8N/J5RnKUUjuapS/5IRCKhBzGKISqiCEbIUIECUIQwBRJRoZJJuCQqBQQJkb01eJLI6qMp7WmYkqbDpm0/Kgalq3op7QaCAFAEAkjwh/OLPeBBH60oGVMCCKBpWtTtNLc32jurfrvu0i51qzaT7UZ1q9VwOy0hhBBCUUb2a4MeXKfctHQgKpfPIGKn0zFMjXMriiJd123b1jTN87w4jgkhuq4zxmSsa5pGCInjWAhBCDE557qum4ZSikqZwFCfhnBNByEY6x3QjOMoiizL8rrMVUGnFWAXpZljrBTpJckcOJxGQFrFdS3FTKf2o4HwQEUx2M+xACCUUAWJt4giIYwQAEUJACAlQJAmZlj9wPruB4Wm1RGnh683TxAVIENAul/Dnyb+9SQdlgiCjCqpQBGCCDH0csUkAQm95F4AiNJ4UIqk5jOm2NdSUllTj5MmaTGTqXMGqqSaPxJE+WC9+cPk48aDRBz3Mh05Dz13a3WpvbEoveZWeyMKwiDwup2W2+5oOtM0TQil7+dhJypYIoQQ2zZ1nVMKQshMxs5mHSkl51Qo4EyJ2AOMbEszTUMI0Qk8jTKdE0opI0xxQilFRCEosju1uA7OpZxqQghCGGOMUp4s8BVFQs8bUvD6TjAxe+7Zr/7y8Nx5xSw/doEebg/C1D6dAlrJr/YLaJH9/OwYWa/KIkkyygmhSIEYvXUg9gsVUuilkvJeHWg4oIgdcMd9QFIwgigkQAkBBUh7ufUEAAyBiiAiUKISZ5mkiEgYUQoQFQhUEkERUICIJErzTx11Dk4x/JCPaLZVat/ARhOz3QP52IvGSLxfDavbbq4tL3XXr2vCDTvbYRxLJFIB6Ca3LI1rEjyNYx+AEuLCOWeMUSoZY41GI5vNXrx4ERHfeeedMAwdyy6VipZleZ7neR4hhJpazjaklIgYxzEqxRnhnAkhlJRMs5ILIwfqBwMAJVq/DEVyUk3TOOdgMkCHGfbM+cdG5h8ldlm4fk7X2+Lw+03VEVLGvOrzpoOrrQOESChyQpAhVYiUAUVCCBiQLGjfS5KnFGjPm54YjQH200GSg/IUKEiLo9F61cr6GbEJsaCUKIKAFKkikoIE5EgVIGMKEYVSTKFUIGhSDA0hOjxPPU3S1ndJXW8m5frpEfmXSp1rU2IgkyK9vQamDzDoEyCGYRChYqUQ0XXd3Z0td3vDgcDSosDzJWGa6VBKhEJQCrhu2z0tjHOeIFGCC91uEwAajfrIyPCzzz6zu7v7rW99c3t7O29b4yOfOjl/bH19/ZVXru3t7Y2Pj8/NzZ06fbbRaGxtbSULIpqmCQBBEPRrLyRWp54CqJSp60lUipRSZ5xwojPOGKOGtrtTNfLDI2NnCB0MfGYQnYfuwfVXD0pq3EqK4IHcsYMikSblORARCWMIiiABgogUCFBFCGW9uCNCKB7MXcAD602TFF0mjSAli5QCJIv8EQBQhAIABwWEKgBFkalEIQQKhDCJiISAIkCoIgqUwkMDMv88Obw9CUk1XB39FPdDSLKoEyighFBOfwjl72MWHpSqsNLU2KrDJS0MiNyvZ5M2llKuP63OURj6nHNdZ3EcTp0895cn/4+vv/76i9/4xpS4ZRYaUdhlSItW0TIjxiJKKDKLEBKGYcZ2wjCkQGrVWhRF0nCYZKaWc5trU4PG9/74jTMzcxB1/tLP/dWdnZ3tzR2341VKA1cuX50Ym7z40COPP3lie7v6W//+ypXLV/wgRkoeffTi+YcubN1ev379ZoJxnt+aPTY+NT1ere10WnEsRLmQbTTb+aJTrdYz2VwURUGIA7Y/Nq0NT5dphsnNbS2jfIty6Rx6vwfq+N0lcUpPTLSpRPDAO00KIwLIhLPsa3JcswEOGbCCHa7rmWl1CFP6j5lSlCuN34kwJXaRaoefIOU4caqSdvhmSI0tSMXWIx0+lQeRg8/rgV/skyCI2AsCBEjc3o899phhGJf+3f/VypLSQEHDLMZAGdF1nRAugRNChPBqtXoYhrZtx7EIgtBysu1G2+LR8eNnlVI3blybPXbqF07/wvra1u3bt8+ePVutVqempp577rmLFy++/PLL589P/PEf/3G5XD527Nit27c//elP21nn9ddfHykNnjt35t13Ly0s3CiV85VK5Utf+ul8IfMv/tn/50+f/5OpqanxyYnpmYnz589/7Xe/rmsmNZxjszPnLjxsZe1mt5PLZyj4UqZoYh++pNW+SBtNUYoyk6aLkRQMTcOgP2fV0x93eYBBHyNJmzcIpYkvHHq2UhgeHjYMY+NPx2K5qplKQwxVxC3OGfW6sunWkoSvKIoopZlc1rQtJKBiYRiaRmUuY9cbVSnl9NTE4EjhG3/wvFIq8r1WvWYb+ld/7mf/5E/+ZGlxsVIpu+3WwtL6s8/81M/+7M9dev/ye2+/kyvmEMTm1sa5c2eyWadULiKS//l//rd//+//3ZHh8Wee+ex3v/vNcxdOB0HX7XoXzj986dLVydnhY3MT42OTJGu3mx0zV/GDkBINU8b8ffMJpEiQYtrWUoaDkCk15FMuM02NSqPXae3w4yr3PN8fs5zVo93Lh+3jP+qBUm2x+5IQona7wxizbbtYGt6r72iG1KgWRUIidv14b68TQ5RYoynXOecKqFAgkaCILMM0GTF1I2OZZ06diOP4ypUrx+amNjc3LVsLwu6xuSmFUSz8KPbiMGo2Gmu3l7M/kz0+d+yb33z+6tX3P/XppwjBa9euSKF++qd/2jD13/7t39rcWvmbf/OXpcRctvDLv/zLhOOt27fOnLpYKGQI6PMPnSo5ZHe3NjUSFA0exF6sqG5qKiXX4cOWOIV30JTcTnFEW6/CNP/dh6vjfELlY2fq+UmWD0am9D3EfQ+XpmmJCdZxrKHhMaoZfqTanWCv3ml1vEig4WSlxCCIGNM0zdB1M45lFAnOdcPQvK6LShQK+WKhYOr6yy9879VXXq6UixfOn3Vs85nPfGp3Z+t/+a1/N3ds5vjcrKnzTMb+ha/+/N7O1r/5N/96dGToU08/2aw3DFMLAo9rTNf1TqejlGKMr6ysFUu52yu3vvSlLxHgUuDw8GgUBzOz0zOzE9zM3l5eVe16xULXbSuqiTi9rHZ6O9yndmaHviSSQ1+KskNfacdBONpLUX7o637d78dN7nmsD3jQofJxi1IEAEg85X2hFLLFShCpruubWs6yBuysruKIa0Q3jCiKTMsKggAIieJYIZqGwaiShnQcPetYSsSVcrlUzE9MVbrtxiOPPGIYRhRF//7F7y4vLw8NlJ564tEoCr783BcvX7r+x9/4k3qj86lnPjM1MTk1OR7HwfyJuePHj73y/Zdbrda5cxd29waWb60+99xz719956233nO78djo7ObmNmO869aCKPBCpRTx61v5fAWBEd0IOl1upNhcP2TdJM3PBSm2ZJqyPb37pPmn0hK00pJQP5Q89Y+b/Nhi7Y8iH3aM4tEPQwghQggpJeccAOI49v14c3u7240GB0emxk4ypfv+3sb6LRGJUmVAKTUyMrKzsyOEQCGASgXE4swpFwsZVswXFMrZ2enxiWnDJnEce5730EMPvfTSS3/v7/03Kysruq4/9tgjpmE8/uhjr7/2TrFYnJ2dW1+9HYTdxx57xMmY589fePGF77/xxjtxJLrd7rlzp+r15uBQ/tTp+WtXb4YhGR4b17gpMDAt0m439+p+Llvo7m0PzBy37YoPFIn2A3TPQ7ffrzpNLAUj0p4XpuhWafUPMM1HnoZaqVBzNHvZR1XH6keUBxj0CRBETMJ8kgIaSqkoihCx1Wlbmezk1NxQcXJrY293r6MUTB+b3d1esyyrVCq5rpt408IwZIzZGobdsNvtOBmr2+2ur6+bhhPstSuVwfcvXfZdr1QoRlH0+KOP1Wq1drM1MpJfW1v9a3/tr/3t/9pptNyu5waBRziZOz7TbHQa9Y5lZS3TDqMgDMNz588yrr785efeeuNfNBtCqB3TNCemB02LBADVWmO2UvY6VU6EZRstT9mmLaT7kbQnSeEXSjt8ONAUP1eaMilSeVAKz0o5zk+IrZr8k+/eWavoqDn7R839P2rsWbocrcZSOqVNjSA90v5Hvd80322aRJqJQaBBwDQegBYGYrTkXPr+97/9v/z6+XNnqtUqKGmbxvr6um0ZMzMztfWFpFRQUhXI9/0wDAFAuHE+q1t6/D/8r/8+qmCvVqXM0E2nWdsslUpxLNstjxImBLRbXSHEs89Mb663qrseYZxwhVShYnEEBg+TMkMJICYmqlarVRgYy+Vy6+vr7Xa7VqsNDQ2Njo4ahnF5Zc1rmSTCYs6fmJp19bnLXSMaytPWUTOTjiZH5Qv3j//+oJySD1HwaO1JjljIKk0nTYtrS9v/HnnAgz4BggIo3CmorOta5IXbm+uckUajUdvbNTTd0LhtGaamh76brAEthAiCIAlWTJQ4zjnjnFIZRRFnxDCsdsdvdoJyobS718pkMpbtNJvNSmVwZGx4YWFJCMWYlsnlkTAgMeUEgYUBqtgII1WrR0oFcRwn+RndbrfliSeeeMIwDELI8PCwEGJ5eXlsbCxr2QU7I30/9tug4kKW5hVstDwTsh9puz6Qj4X8RGBQ+vx2f7an+1CPtj1NUAGhyBiLEIFAxtS71c3VpRsjQ4OWoVuGbhoGJUhBxVGws7Vpa0m9mp4vqZfMRWlpsBj7nUKpODY63mzv1Rst087OTx2LvcDQm4SQUqkwNQX1etX33dljE8VywXNbEkkYxUEYaowRxoAS3STJYsQapXbGsSxL07QoimqN6urqulKQzxfr9TrnPJt1trZ2JOGa1UEZdd3OzvZ62c7mtLGu74Qfslf2o+NBH5UOdVSfzH2zV/4oP7/LL3bkykVHjms44gnSz3yk7Z9MU90d4aA4AUqpimPG0NBhr7FX376dKyhBMZuxbVMXUSjjiFMipWx0u0op0zRN00yc+kopwzBq9Xrg1k+duMh17c033n7r7fd26y2uOzrRfv7nf55z+sJLr5imPjo2mMk4mXxWEd7s+hQyA4OjRFO6yQC1OCKUNBID+b5EbtANgsA07Xy+WK1WG41WoVBKyFEmk6PIQrJrFY2MMex13U5jJTdYkObw2kcUH/Tj5Qv++MoP2c4PeNB92P5h8yDOCDtYt1Bga3eTha7XCeJA0zkTFN1OWwQeN01OlOE4Qoik9I8QwvO8KIo45xtra5ypbCFfbTQvX7nKDdPQ4++/8Y7JDMZ1TWdXrlzudJujo8MnT87PHZ/V+Lmv/5c/urW8Z9kZxmWhXCiVh3LZcrlIk3KLSTlXwzAM27KzpW6zQwg5ceLE5uamEIIxpmlaPp8PWl4z1JhuW3re9wIVuw7x3WAP2PDRGuKI8oAH/Tl7f0x40H25iAfyoYpGkjWPVVKQrNuub68tZ3XQOZNREEvGUIKMDJ1bOgWgmmEk1cgSD1qr1Ur8YvlSIeg2bMdpdzo3FhYnp47Pzp3UrdK7b74+MjJSq++5rj9//NT582ebzeYrL731mU8/sVNrrm9sW042iLvyZiwkYdQ0NR0AEpQxzV5ds0wmk7PibDb7D/7BP/C98LXXXsvlcpZlSXn7zPHjmjEYBCSiNFMYyGQ1nQgSrxE+8pG05wMe9LGSnwhd7MPefvT7PZpyyAgqAKkU0w0gtLa3u7GylDEYIzECMgKMgmVogpEk439jY8P3fUKI4zgJQPTqeGjUd8FxnEwmE8dy5fZqJPRyZejMhVPAVRBFp86cOXv2/NbW1uuvv53JZAwno4Ap4EA0QjXTMgE1AnrsCUJIHGMUoZSSUrQsblna1taa5/nNZmtpaWlra3tzc+vq1auc8+pnPrXdIN97/d1Ydh6/cPzk3LHT58+dvXhqaflIzfBA7rMcFYuPyh8f6GI/PkJQIUpE5JwLia1Wo7a3M+UA49zUNUPnDEin22rW626nI2UsKE8qtBJCdF3H3urpKvRDxhhhNAxjxnVK6e7urueLRy6eQYShoSHfC99778qV969aljM0OB4EkYgVECYVRqEgnEoVx6G0dMYYU4QohZQrpYQEijTO5XKXLl2qVqsAEEXRzMyM67rXrl27sXBTz5zNZqemjmW+8IUna5vVa9euVSY4wPGPumkfyEcvnB1ck+iIPCU1GiHlOPcvGiRtHaW0YgopR0mNbzpa3ASm1RtO+0FqSanDjxNRAxgPfbdCWNDdbN66PJi3gUZBjI6G0ne3as3dts9NJ1d0hNeUUKasHsYNO2vGIWk0/cHBchh3SZe2vNWZqcH11drwwGlJgpbbePvSG2PD2t/51b995fr1f/Wvfmt70ytmx9xO1e00GO0K6EagpKRoZtq+6xjctnk2V1JKdvd2KKW6bRFCKSUbO5u5XI5bJ7/36it/9+/97L/+N/+x2jAmjk1eKE2M53H8M784uCfGTTRN5Zra8nY4t1W+WFl63yvG2RHmt5QIwRlwQ2Eql9DD6wf+kPEmB1v00K3p3fxo/DR9nr8/Dr+0uojp/fyIzpe0w6QqOGnHT6kTkNb+dx//Qc7qJ0AS55NGWbLI8NWrV1fWVltd98qNpcVbKwI51e1AUkE01O1saahQKBiGkclkNE1zXTcIAkIYZ5rv++Pj4/l83vO7cRyGYeg4zjOfeXagMnrj+q211a1yecA09U63CUTqRi8iifQKRGuccwCqlGp3u61OVzcd3XQiKYLAD4LAMKww8DSNbWxseYF64lOfbrr+TsvrhshyFROCuawssLDmRm3M5seO7VZrhmHoFDCOkhDwpLj1R93YD+QvWn7MclaPJke1Z6XJh52nk9TtIIyAFDvbm5ubWwOF8vET8wNjx1TY8duNWjfOlEdBs3da1YLFTBXtVeu5AldIwjhiXFeAru8NDY04Gde0DNftrK7enpgZPX/hPKH27uqKwMVWtzU+Pg7KWryx4HsdICFjmhSoFIpYIRWJTgdA7Jzd7XhKAQiJGOo655wLIS2daDmzVm9vbtYvPvHY5cU/DpRdb3dPUou61elctuNGt1qqjZmp2en1pbdPCOXoEMRdqmnIDalinRvqgc34o5aj+5GPtvu99YOOdtAHcph82GNGCmlqnHFCQVx+++1CoXDyxMzI5PgAahh1v/tnf1Iemf7Lf/t/hdy6dukdroKbr7ys1pWuG5xz285UyvliMRvFnm1ls1kKAJzT0bHhqakpXTNvr26t31onfGp1c0MznMmpcUNjN2+8FYQtQogQChVJiBilIBUqVN0oNrLFwI1QBSjjQiE3MTGzsrRKZMfJmJSThcW1Jz/zpRMXzuYHxsTyEol94TZoxvR9P+gGSGmpMrK+Prizs5MfzvgiDgQQ3YZIoYopZ0fWET7hknpfPxntQNNqtTyQH14+7IeklEKUFJUM/WtXr5w5c8bJl64t3RZITSuvO/lTFx6ZO/mw4o6n9KtLW7lCycnl7WzGC8MwFk4uq1u2k82XSpWTJ0/HcRiL4OGHz1uWcfPmoqHbxUKlXKo06q2rV68qpZ5++snPfe6ZkdEhKREAstlsPl80DUvjOiKRUmpO5tTZhydnTg6NTeuWmck7Z86ccZy8EMLJ6LqWeeft97mG09PjbjcyTbNkA+e8JfTtjhR+JxdVTSadiVOr6xs2iXM8lFGoqEYJYBwxqn1U7fxAEvmLHDskLZH3gRxJ7tfDSDt+JmMCIkixunwLZXz+oQuRwK3dxu5u9ebikm1nRsYmry8u37y1NjA8XhgY2dnbA8Iy2XwUSyTUMO1YCt00ZmfmHTtrGFq5XESQW9sbQoipqRnd0CzLymTtOI7X1taiKJqbO35i/pSIFWO8UhkcGBjKZDK6bhJCAMjP/MIvPP3ZL5w8c3FgYAwBIhEhyka9zTStUMzYVnZnsxb59YGCsba4aGvoZItmJuuh3pRGIJRDPGxtjZQKrudJt5ZjgjMSS6AUGH5kRaY/Qjlqf7hf/e2o5/2Q5MfKHvQJrZ/Sl7RnYRjQdmOLw6V335qenKhUKq+2O+MzcxNj469873kKyvO86q1lCUZheHBwuHWjXjcMI58v+r5fLGYGBoZ2djYo4a7rSWwWi8XxidH3L98QQpQrQ27XlzLUDVaplJBo2Uz+1q3VwYp15swcAFDCDdMBpgmhhBAAxDTtjh+sbW5zI5PNlQhnus4ty7pw4eHrN74PFDJ2Psjk63urx6fOn5qZHBqzt7zAiiQ3hWZmQ5YxHO7t3LYHURZKzb2N0pieyVTagbQp4ZzGSqWtRfNx66uf9P72UQl54Bf7xInrQeQHhqGvLN+emp7wPG99fXNsYnJmasJ33W670+l0isXi/Py8EKLdbiNhXDeDKNqrNfwwlIi1ZqPaqG9tbdm2jYjb21tSykKhoGlaFIkzZ0+eOHlsfHz0iSee+Omf/ulyqRJF4tzZhznXAEBK6blBs9l0XRcRDcO4ubCwtrE1O3d89vhxKeX6+uqtW7dKpVIUy0ajoZTSKLv0zqsGladmJjmG13a8WqOhK89xrFDPg13u1rdx63q5XO40qkzEGdsWEgkhhq4J8ZNIhX6ShROI/vy90iStBiV+uKbutPnnqOEj6QWNj3ac+zUdYspiMRqH4bHyuy8+bzI1MDx5+ebtCw8/PJAx1q++1a7u6rnS8PiEYdGlhXfGZ+esgWIkwrxt65QM5Aqhj9tru416d2J2OD89evJEqb7cfPPNLY8YtxZuaKShZZe9HbFT7bx16XI2V1hd3VNC5DLq2sKls3PDKvTb3RZ3hvKlEdfbjvyWQnfhzctTnx/u7N5APzg7//TLr35/p83OXRhmRtnIm6Yj1m+Tq292fuWXuydPd//gP6/mI313B4dGhrm39NBYpas0beb8HobGQtXg24P5vcbu5RzMK9tptFsVxrppxtiPGe+4b0sfpI3B1KXY79f6d4fDPTniQDo6P70r/u4BD/oESOCHvtvZ2t4AQCnjnJPhlN64cW1xcXF6enp27tj62maj0Zienh4dHGSICuXIyJBSqtls5vP5XCFLOcvnip7nMcaq1WoQBLlcbmBgQNO0mzdvlivZjGPU6rsLizcGh0ePz59SqF2/ttzteohYLpenpibGJ8ZKpRJjzHX9+dNniwMDb7z9zrWbCxMTE7ZprC0vCr9dKBSEUABgGFq92VxYul2uDE5Ojk/MjnBNNuo7XIZjJafElOm7o7pmZG2gGSmNcsHSsSPcOJPJiw+3rtkD+djJj0RY0vHvw9Xbf1z18LT21Bn1ve7WxkYxmwm6nTBWukZavru9tpKvDI9PTHXiKAiiyYkxIcSlN75PidQZb7UCJSRl4HldQvnA0DhVaFnW8pXFjY2N8xPnjh07Vttxr956L5Nhmq4mJ0eDmM4fP+15/urK8upaQwqMY6EpEceh53WjKCKEoZLj08cqQxMvv/JmKZsfm5wql3Kt6ub2yiLh2u5evWjls8VM/ZZ/6b3rZ88+IonQLM0Lo421FRHJgdIIut29tYZpWz4Y4JG19e7gTLlo+oEf8IzWiiNTS6t1/+MpH9U4+ujy+++ST6RN+pN4zT+MpMW2Wybf22x0GvXTJ+c9t1NtNIcHyqVsdoti2+1WhgazqDW7ntdqqTjo7G45Fm+3GqEfDQwMCRFtbG+admZ4fCpsNUql0ipirVa7ffv2xODw2NjYc889J9p7Er1Pf+ZJiY5umpcvLzU7IuNYhmEppVqtlis2t3c3hGhzSi3dFBINyxqbnHEMM4qlYxohg921pdLIqVbjNhJWKNq3CSwurrc6wW51KzMwybi9W20uL91y8qMSjO3anr+tps6coDhwY7HGM9ZQcaITxCKAiFLzL7jdH8jdctTx9SOOxwc86GMkae1JldxYX6lXt5WcanfdyI9A5AK/K4SwMszJ5yEmu7fXv/P88xh2o2bVIoIqGUVxJpOJEYKoO1AZyuUGNcfSdd3zvGazub6+XrCcjFmZm5trbWDGtphtbe52F5dW1rZ2ALWh0QkCnFFNEUSIGUdCGY0J50arvhcE/rFjx1EqP4iYbiAqjbOJyelOe5PrGgglUNXqfrsTFEuZ5fWqZZhdj9c6sqtgeGKUD48J5BPjhahrXnnrTX1p7aFHh8qmXPc9M58nQfwX3PIfrTzgQR+L6ziSfNyu+cPGRCWj1du36nu7K0tLyM3iwKASwfb6mgI1MTWVL5Qcbj2RKdy49PaVdy6D3/agqfMx3w1QEStnc51phuWGIs8QEcMwzGQyrutubW2ZvEDt3LPPPks0+uIbb73wwivDI2cMM+/7kaIsigSlFEAhSssyhZBh6EqBfnO3XdsdGJrk3NQpTkzOLl97d3BoOFaScrvrBVxKXdcBzZ3t+skzx7Za26bmjI7mYiS5Uhl1alBbo5bGqYfKA6PaQr8dFDLhmhsSGP9QG/OB3Hf5EcfjA5v0fZAPO2as1aitr9zOOjanxLFM2zI8t9Nu1uM49AL/5uJCo9keHBw0OfNbdYh8jRMlhEa1UrFIGaGUFstlBG15eVnXddM05+bmGGObm5u2bdu2vXZ7o9Vyu61Ou92uNerDo6NDoyOZQh4VYUwLw9B1O0AEpURKpFSL2rXbC9c4IOO6mclPzM7FSM1M3nEc23K6XS8I3UKpaBjZy+9fL1YKkfQC4eUL2ZGBskWEIbwClVklu/XG6vbt/NCwmZ3a2mrptJs1Qhl81I/zL1w+7P7zYcuPePsPMOgTIBtr6zs72zMzUxfOnTk+N2twrVlvCBGdOXdW07T1rc3l5ZXLl69cuXLF63QsnY8ODcZxWCqVzp45b5omoTg2MV7Il2zbppQuLS1pmjY9PT09PT0/Px+G4WuvvbG8tFwolI7Pn+z6Xsftur67W92hlCdFiBCUruvJZ865DLrLC1dbzcb29vbtlTWu21Q3hcSHHn5k5tgcY0ygymazmmbeuL4gZBQTV6AHGEVuw91btyJ3ImOOaDxr2WHUHZ2eLlRmNraqSnVzOf6TZY5+IAD8yCVZ7pK0pLqj6fMMGAAQUABAAJPyPQQUIEcCAKBI70zJ15Qwmg9d0tZRSp8JDm/ctHU7DW5FsVIMAxnatt1tNkq5rEbYm3/2J9MTxwZnJoJs2e20RiZGVleWygPjZ7/4N0dGRhZu3PQ7rcEMjleMHT0mIC2n1IiZsit1s9gImKVnNBTN+u2xTA2QlseHSkiPzT8egMVKQy988/vHKyNrrjM4OjI55oO8HXhbnfreieKEVdSD2PaiVqFk7+0qjEDXZLFIQpDZnHH56hsxdYYGJwaLudm5h955d/Vn/zobPfvlP3j59kR2c6hI127vDY+OvP/G219+eOLVFaxmZjLzY/76m4NM+u3VqDC2sd7urtfEVKTNjzfqNFzdnB3LNHCvrRU1QA0lR8mACEBJiKSgy6Ot+yZS+idPsbOII65relRhKf02bTUydsTYPZUSr5e6RmNqqtZR6xClxev9UODyseFBvVJq2OtP5Cdipe17RClgnCilOGVKxjrXdM5XVlbabndsbCzrZK5fvx5FUTabbTabtuM4jjMxUaGUvv7669/5znfW1tYopY7jdLpd3/c5I4CSEGJnsoHvv3/lkqnrayvLcRzrut7puM1m0/O7AwNlTWPj46OtRrPT6RyfPTY9NXXhwoVCoRD4oeNkDcPQNC2TyRBCAj9KBmSlXP7c5z538aGHxsZHhoaGiuVSo9NZXl6Zm5sbHh7utLuOky2VSq1WY+Hm0ujwsEaVCD3L0OxsISKaG5Nas4uRn2EiAx6PvWJ5aGG7FRLT1DgnkqCiCIDkx9X/8ED68vHAIKIIQsJyKPa/KiCKgAJQFBU58PUju8wPWSRKwohCwTUKUlmGpnG48t57hmU+9sQTlNLazq6MxcbGRhzH41OTmUzm+edf2tnZeeSRRwzD2NzclFJ6nkcIUyLWKbQaNd8PR4ZHx8dHdUbKxWw2Y4+MjDSazcvvv+92OqAkQRFHgRRxt9u9dvV6FAnGmGXolWIujCOhZBSJyenpr/7CL33huS9mC/nVlXUVi4xlnzg2WyrmNEoQYHB0PESytbnnOJqmsWazq2vW5NQ45/zmzSVQyJXs1jc1rvJDw7Ge49kBQc1ut61DxL2qFrZGxqZ3PN4JpalcThQHmcxDCggAAYL0fgUHP5D7LT+inehj4RcjCImy1cMaBJoADQLsV1yluI895CPzi33o/i8ldM4gVIwxGce6YURuvHTj+vzcXKVSef6bfzoxNn5savrNN77vZDPFcumtt95SSp0/f97k9MalN6WUg+Vya3eTadwiMFLJ+7FQBEqDQ0NDQ5ubmyr0HdMwDGNra2d9pyGplS0N7W6ujZ8Y2Nxcd6xsu9kM/ZABqe7unBydHR0dL+RLC+sbtUYjs73dbLYNyzY5E1EMUjbru0Gng4q2Ou2RyaniyPj62k612tANTkCvVTtDQ05loLizUVtb2xguZLdrdQ2iTKHYcFvDwxXTjUKiaZbt1veMfFErjJnZcqdeHRqyW5gFSlExJABAkSgAIATTn/sR1xpI3f/D1cWOvAbUffLNfxzG+A+QjwUPIoAJ2QGiABQFlbDwPglKOBEFBaDIEYs938/r/JAloXmUUoqKESBSba+vua32U5/51PrmRrPZfOzhi1MTk3vbO9V6fWNnu1gsnj59mhCytLQkpTRNExEHBwcjIQ2NjQ0NZC1d07SuH6wu395avTUyUCpks5lMZnxyeubY8UwmY+na9Pjo2TPHcxlzamLy0YuPnZo/MT46MjRcnpoc3a3WvTCkGmdU29javrl4y3P9MBIG46amb62t6QwKuVwo5NjMsdlT565cudFs1aenJ3PZ0tra5s7ONiE4NDi6cHN5bmp0vGwaEAAlm9VGFEsSh2DlsgNTYQxBq11dXy1kc/WNWyO8ZZJYA0UJAlCFRCVVrh7QoI+r/Ig86GOBQRQVRSCgCAIFIIik91URUAQUTT6joj2E+vEUwiCpqSyV0BiPo2Dh2tVCxskXiwsLC2PDI1nbWVu+7bqu7/uE0fPnz+/u7t68edMwjMHBQUJIspYh143Q97qN3a21tXa7vbm1c3PhRuR1TE63N1ebzabrB0KIKIp2t9dV6PlumxJotRqlfMn3w93d3axj53NWJGKF6PpBo9Ve29ja3N6hnGULxXw2Z+ua22iAjFrtRhCGhYGh2dNndncajUa1UMhbZk4KqlA0mjXfkzcXbpmMnJwYMJQX+O1QhGG3rYcdiLx8ZdgpjmRNm4euRVR9exXdmk6kRgQFhQAKKCIBAEbwqJie2s73af+Pm9yv+/0Llo+FLgb7TjEKKlkhi/QVLwQkQBAoAdX/+vG45h9Cjrb2NGNEiEgz9dgPNEvrNN1rV66OjwxfvX4tiMJKpbJw4+bt5aVSoTgzOFsol959990ois6ePUtk/Mp3/lQpNTA80NheH52c2dvaWL21uLldM8yiZhhCxJOjo6ZOv/ut73UjLqQMwljzvPfeeYcCXOLVzTalJLu7crvTag/PTLb2qjcr4AwO5fNF07B10ySQQcR21zM4N7K2EtLStdj3Ll+7VRiZ5qY1PDVr6M7bb789MFiulIcjcG3bbHcbvhtForF+e+nEiRPewu2Wp0q5TNiqWhhkZDNjzbsqazAYKxdau03C9G4Y644EoDEQAIqEAulNUUdu/b/YnIOfWElrtx/SdvGx4EH7XjB171eCQBBg/3Xn64+nUEoFKsaYlDGnLI6i7c31wXJlr16bnZ3VGL+1tFSr1UZGRo4fP764tLS1tTU5OTk0NNRsNj3Po5QiommaApXneb7XzVj2yZMnJyYmdF3PZZ18Pvvyyy/7vn/u3LlTp04xRhdv3qSAtmW0m60oinwvHB8f/9KXvhQE3trt5Zljs04u22w2TdP8/E994Utf/vLY2Fi344ZhGAbBQKXEGFm+vYSUEK7ZmZxl2a+9/v1OpzM1NQ1AwzDUdV3XzVjh5vrGcDmvUxUFbinneI29uFUbzRCLg++HrUazlM14nlccGid2MeG8H6Hz4YH8RQpncCeW56OaB5BRBACgP2Sn45BS5uo+1S26X7bntDggltLOKlQGkqDVyjoGoP/6979dznKDeJbpXLl+ZXhkzC45tZ3rXs03ZsePzZ4hdj5j8iyXnc1b3b310ZGBQPq+rsWN1dkTx6QXQhQ9+ugzmx4dL40Oyc2tVrfDh/7gu1efDfRzD50Ag45tzTqGGcvsF37xZyZmZq+9+PXp6ann37709qp7dv5kbWlxYWNzdGAkXFlx53Yff+qnurs7gFqns1yPpjxryPe8Tz39uazD9pbempg7kR0tBEuX1r7/DWN+fnt3zYJMJpvfJYzwiRdffftzn3tYhFW/GXfqLsTuamuDm5UZdptS++W3r7555eZ4JRPWNoK69fOf2VovfPa9Vl5J39LirqCakWeekmZaJM3hkt4b0uKG0uoWHem0qZIaL5MSd3bU4+j3a7351P6fUm8oZbb4IeHkwboaHyPRdd5odbN5h1PSaTX2dnaHh4c550uLC0ODI4OlfO224JwDAKX09KkTL7z69mW3U1stbG9tRJ7bojFjmM1bRABQHsfdfL64V91R1uDUxLhRa6GCs2fPmvbeu+++22jtPf2FL3/qU9bq+1co+pwqilCvtf1wOcyMjIyOGhnTi7AyOHJ7cUXasLi4sLHekbFX291Qna38REfJ2LYMz7L8wG80GvlOe3KkfOvNKgyVjExxcPJYt7U5PJLxSLyyts0r5PriKhK91W4g54292s7Gqm03zeKAMzg5OT5MNX2oUtAGC16r+tL7KwPnayO5wZqnxwAa1zhITdPkA2b04yh3rzf/ideHP17Xf1Q+hQQYo5wRhtjY211ZvjUzOry1s+l226VSqbm7vrVxu7q7s4e4Xe9ar77plAZXrjcvKyG9NshQJzQWUexKiSBlKKQqlgtbG+u5qWwhN0o9HseSc24YrFbbC2P3wpPPjo2NFRiWC2Lbby7cuLm9VdOMgI/mdccRRA5Ozjz1bOHa+9eY5raa9YWdtRNDlo5+bmAEFG6u3jaz5bGxkTD0u1Fw68ZC2dao9IWSUjONyvjyytJp29HcvXypmCsbGzvtqakpypugG3axYkc+Dzu2bRbzmUx5wItELpfPZyauXnrn0h55vL43mh/3mLknjKyhaXGEhH7y++fh8uN6Xz+kPOBBH6IctW/5oZ8vZFUUAoWVpcXd7S1NibDbHRodbFV3otBTkW/ajmEYnsDbVy6PTsyYnFEZC7fldRoa+LajO6Z9a7Oey2RMRh3HaUSBbWp7extjXIWB2tvb83x3aGhwYGiQMT2O5fT01NgwBpv00tW1rY3dfHmgPMIIg3qzZmeKhbLGNMt1d5kRBG7Td/3hwbznRo5pUAxNDUqlQhDbuh9IpSDunDs5F4LSswVdcJ/bkjAlI0Gk4nqMdnlo+tQZ+9ZGzSkP0lyF1pcGRwY1i9qGDj6NUcbcaEqmj1/sttqsva2xkUhZhCABGSkF7EGNxb8ISe+3H0r81AMe9CHKUXmQUkLTWOCLOIovvfWOpemFQq5YKRCmBX67vrOJUtjZgpMvlXR9cGzKcuyg3d5YvsVEkLUty9A4p0SpXL4MiKbOdF0fLFTGxoY2l948Oe9Uq3umqQ8OlsoZfu78w6dOnrtx/f3V5nqnFWfGn2TaXr3RlIQNaTRfKGUcb2tr5+23b1BKCSFh6BeLecq8SqWyvt4yDUMGbc+1Wt2CF4o4itxOm1H1+CPnv/Pq25XB4dxodm91odb1/SBqtWsMwtrk9O5Oo1Qovnt9YXRwYmxw5uZLC14Qctk2M+BoVjsI92r1GPj4/KPu9e91G7X88KClRBzFDAnQBzzox1Me8KAPUY7atzTT8H3f4GxjdXljdfXY7PSFC2eyuUzbFbSQc5t7+Xx++sRZZha6nlsq5gvZzNuvv/bG979fcoyp8THLoH7Q8aPozLmnlpcWM5aWy+XM4Uqx6GyGnUK+cuWtTcuyJmdHo3ZzaHAMkK2vbWJ3bd2ip4aZ4WQqA0XX7dy8dnlmvDg4Obm7tX7t/csGZ9mss+l5+fyIrisv8hg33XZrdekGzVa3Gp1OIDKmFbWaed3IOtRr1+PQO/nQ07vri+9/5z+TwM1nNCFEvekuLa1cOH/C1rlm25WZk1dfslptv5TnBmDWMePYXdne0rmRyRYberHhiQGIBjTSEBgxSzMMKR8sufFxlB8RQ+8ysH9IoVOfOPnRnsj//8I0mnjl33r19YmR4VPzxw3D8DyPGo4XCd/3B0cnzj/26Yuf/uzw9PFYghfJ4sDg4PBIJpuPhWq5PnAtUyiOTUwqYJlcYXhsFJTc3ljXODE0cF2/2WwapjY4WAGA3d1qs9nknJaGjqOeBV0/cWZudLTkNnaaezvK90kYDBWzgdcOA88wTa5pzM7stNqbG1vbW1uB17FMJkTUbndzmezcsWNEM12vk7O0q5ffdhzn2Pyphhv7ilRKTiGfE6EIup7FydlTs0HgBUJNn7ggUHdM2wRFA4/4fmtn19G4BtIePlaPNLe6UeGuwUkATMCRYxQ/bpL23O/Xce6X/AVfz8cjPuiBAABAsnoXAfXO228+dP78yMjIreWl9y6/OzY1y7huO9nBoRFmWMzMxBLeeu/9nd0908kUimVkeiyBaQbXrSCMgTDf9x3HGR4ebjab129cJVSKOMxmcp1Op9msCyEo5blsoVwum5ZhZQcF8iiW+WLuxMnZT3/68UcunM+b9kAx96knn1BRFIbB/Pz86OTUyPh4oTKQyRdkLCjB0yfnn/3sZ5548sn5+flSocBNU0o5NTm6cP1KFAfD4+NmrmBki8NDxUIuu7ezu7Wxsb25OljKd9pN1wtm5s5IZEqC32nXtjfcRs1t1i3GdSJLw1OtkFW3VjPo26YWSRLHR3PMP5BPivCDkWBpkEZSAiRS66GkxU2mmBTT4oKOHKdzxLpFqYc5Ym7S0e0+h9+w9CMnn//WH36jVBy8+NjTb7z9FvKcWbBkbfGNV14YGZ4enzxHY3b51df3WtVPf/6n/I3rb776Shi2hsdKtxdvDOgFhzt5K1vdWCWhNzY58/0rq3Zh4IQW6a1FWyOjx05/uTh/Y/HKa7feGznBpo1pP8pS7te63YF2mOVDHrbiaH1oUKtu3IpHTwdxRura8KOfv/Ldr59SxCxULl+7NmoOazNBt9bsdtuWnh0dmNprLq1XtwaK5uDZz9166/nSLG/d/Nb7bz7/5Gd/7vj5p178+tceO36iOJyt85rbXnv3tc5fPXW8ZOHyle9Nnb9QzlDOVXF4dmmrjTbXN3YHbJ+vfdcYe3Jy/tTi95fOMt2Ou44MC5m8H6fU08GPZipNGy/p698djTJIFffP0mcchBAVH66TUqIffp30cPhWabmyqdQGAQhFAKAEgWKSx0cFvet6cF/0uwd2/7CBDAkhlNLE1Mi1g+dLi5VK8UfgEdNHH6Qd/mAxdC2O4zfffP306VOVSmV3dzsMgi995cuXXvqziYmJkdHJW7cWW140ND76xGOPE43+3vO/v7m5OTkxNjY80Kzu+J5n67pVKsVB27Y0gjA9OZkvF1cW3tFkaGocae3qzfevXr1KCjTfrtd3boX+XjYbbq+v5AaOV4rO+k4UeB2ND0yMDdgW396+7Ydly4CcQ2XQ3lxb3NteGRjOcNDK2dJAZbBTq954/90wIiYwv+ZiiY0MT5IW5g2jsbGZoWBxs1gaarU6Tk63c4XhStnWcGNjy2bSIWG11dWyhWq7nR3SuJ2rVRtKs7bqXWLmu7WaoeXK+dzu1poxPFsuZJrNLjeMj/oRffSCiKmxjmklBX8QphxJCACoA2uJIiKC7H9PoAcACQEAjBS96+zY+2zyZHsy2SPlgP0XQ3XoK00PRIqHvo6qT37c5IgP5siSdl6Da0s3bzQajWee+fStlVs7OzvTk5MXzpxtN+uLNxeuXLnMNH7i1ImR0VGpxMKNm6VCOQ5jgxuhFxqayYDJWPpu0G3szc/OMAp7OxsL16+sLlzLOiYqVRo0nAJUhnOzE1NFyxB+bXw48+ST5+ePTZqask2l8YioMOg2xkZKjz1yYmVteXdvo9veQ+GicqXoel57e29To1nHyA4UC3HQcpt7paxdsLJxN6oMTRYro5aVmRmduv72262dmmPawJzd6l6r06013W7MpGbv7OxODuQGqRtFca5Q2aw2m25kZxxFYHxyRjNza7uNjY2NTr3qmFqntqMJV1dhFP0ICwJ/MqXfG5P3Pr2iQA59JQneh7z205zuef3g8x42MBgBdgD/FEBSbEcBKlQy+UAACeA9nI8QkrAeSmmW0SyjDgELlYWKEzyQq5F2Uepw95lM+QFN4aJJAvTHXz5sGErj6kSKq1euDA8PGpb55hs3SqXiyNDQ2vKtRq3eajesfGlidnJodPLKtetxHNu6Nj4ymrMdpmB9dS32A9u0OKGN3arn1Z0TzpWrV5vdgFNpYvPEVy7GQty4flM3tYmJKU23lSdqjQVTJ92mEwauaO0oO8dpPFApmJypOJDCbfiRKljE0L04DKUsjQ4P+yJsrN3e2LE0mS06xsCAY4Ifuu1alyEpjuUaG3yv4z/8yCNf+4NvXb96uThQsSuV2ub7lcHpRsev1dujg/luu37u9Oxcxbyytz6cm9UZxF7LIKja1YGhAct0fFbkWl51fCXiVrtWcqsotaHKaDdK490fr351f/vPwaMlPScNPtJsJmnh5Wm6Ydr47QEiIAVAUGS/3VGG/R0OClOKHFAk+58dQERUqBQqROSajO45xwclStO39cN1tNS2SDGBp+mlR5f7c6APu1ZZWjsL111fXh6fGL128xph5PixmY211e31FZ3Sz37m08wp3Lp9a6vRYozNzEwV8tnf/vY3UAhDp4HbjiMvb+cJyFa7nrG467qNyM8XKpYmjNjPOvalK+9eu7o5NDTi+96tG8sQx1HYyOSsKxi/cnVp7Pg5RNxZujw6UDx7/kyr1Vpbvx3zbK48VhkSt4wsEuP4yQuz555qr9586fk/7kRerdsd0XXdMq8u3Vy/tXn2xDy3QMs5ux3vmcceIvzbz3/rj6fmz2bKTm05chwHib65tbdX7+ys7z3z6MnTcyM3Vldk25oeKjgkpEHNjusOOIP5ws1WkDEAdB4wveu5hvKLNGwrvws/WbrYB/tJ0jOlPBxUWIrNRMrD7UE0ZT17mgJyHFXyX4qKMCSIjCAA9M9KCFBKKKWMMUqpKd3+XRx8j8P4LgziBypqp9aRw8NtYHEKeKTRHQWfjDjXo85j9wuzdjY2by8vPfnU41EUhnFgcqext+t2uoV8dv74sT0vunLj+rETp77w+S9ywLdefX1x4Wocdrqtahx1QUS6lo+CAIU/Onpi7vwjkV6knLvVdeYpocirb73nuUPWTIWC395ug3Bzdjw6NmbY2VxucHz6uG3y09OjNmOFSnl7/b1mqzs+Ml1DjcQqr1tZbgyXBgsj09sEmxfO7q0v+n6oMWN0eGKvFrfsvYKjuXut8eGBG1Yun6tcOHP2rUvXTMZmR0e7ZqZVq1uWVclnNF3f61YXFm8/enZ2MKuv3LyG3ARUpZxjgW9iJIJuu9nEdrecH5Sa3fZjDDvlsux2G8QYSWm5j1ddzbT+c9R+co8KdufnKTXqE3PxIdtTTptmyU8r0WUCJtyHMcUIUoqUIICyNbZ/eUgpUoqMIaVoRPfaqpMPHQREZASQAiJw/Yeofa/B4f4mVIcvxBKn+b/Snk1q+u4nw4h9v7j3m2+8lrUdx7EbjUar2yllMlknU9vashz0PG9sbAqdnJNz2t3W8o2FP/gvv69UQCHeWL9FUGgMNaaQq9Hhsm5YgyMTJD/eaLcMiArMKFQGNDt/6/09ouPkWOXUyXHms9APRqacnVr41V/6W0PH59xOUza3X3/pla2657db1tOnS4S+e+Vy9dbKAAHebi68+ppRXtu9dY1JVxfY3WtuXd+o5HYcQScKBdmoukvXyiPDA2a2vd2eKg6/UX1h89Kbtn9cM63lWzdnxyc0qsWRMi3nxvLq5l7bsqyllSsxMdxuO6cTXWNKs7krFxduhvVOZWCGZfIyULduXp8ndHzykap3X5r5EyaEkH1bb29E0NRatCn8KHX9jNQzHrrdVIIQQqliFDlFTpEyIAQdTtS+oESaoBMh/WvuS/KVEKT0jmrGtQM6YRpn01L0xigFI36yVuq9f/Lu2+88+fSTjVr9+sK10eGhY8eOdWs1GccZJyulHJ+ayAyrpbX1q1ev3nzv0o0bNyYdH0G6njtcKaKKUUWOpc8dn+2GfLta79ZlJpudnZrKyJpu2ENjE577zsuvvLgymn381IkxJ9Qtr5DD5fXa+la1OD0XStzern77O98/dfbcUNnOZIuXX/nD779+S0p5Ohf522vXb+3q5XEWNIOoljN00fSvvPrewrWdCNFgUdTZDZ7/3vTksd3NveXygK0x0485aXdXbkmq3FbbmibNVmtlt2HnnaDrrm7taPZotjRoFIa2NlZWF651243C+Hxer5ycm2lv1XKV8aG5s3l2YuXV337ntRcfK0wDL3/Uj+gvVPrD+B5JXzPncAxK2/+oVQgYSALAETggo6Ax5AwIQV1FUkohBAqBSinohZNGugMAiKiU6r8DAGeUEGCM9qxEL15e7d8nS2FnB71FB/W6bkrovC9Z/1cJ/iWn58REAoqAJCAZkRSQJNXJMrCP8Xc1OjmcUOkQYc9NSBRQRESgkK7H9ix5hCBQRci+ixCICg+/gRSumxbXk9ojiCalTJCdHkh3sjhW641ieUhIAIVExnnb+O63vvntr/3byZnj1HA0wxwZGXGb1ZWbVzDsBkS3bds0zUKhkM/nG43GwsLC3t6e1t1kjAkhNE0rlUqFQsFxnFwul83oYRiOjY3Ozc1xjRKCpmlGUbC5seZ5roxDXefZjJV1LK6BErIVmPlsKfSi61duvPy977ZaOxfOz/+3/93f/9X/8df2bm9mwS6bhXJxOOI6LxRcVAhly7IajYZhGIwxxliz2YzjWJOglDIMQ4jYMDXfdznnUkotdNHmgJHtBReHxyaHK4WT46th44lPP31zcXu3HmoZY3dvpb67Njs2e2ziBEycc7ttIcRAuaQxsnDjRqPRGKyUvvjM6Ws7/rbMmcVhouLAbecLpWrLzdmWUgql4kBkLDiljFBOma8Od6WljclUu0kaHU/pJ4yn9J+U9dHSlk1L4yMsxTYiJUKvIHJSkR0ISgAQ3Dp0fz32D57oTv+kEdztlUs+VAzR3//gT5J2+6DOSKnW39LnQXD3OmiUUs4JBdIf//fe+T2tcM+1shROSFl/H0xgEIhCVEpKIIRQQhkBBIIEkkLuSsBhmhem2Lb7d4P7+/Q2pPnpQAGAQgoEKKIiPQ/dh21FSDyR0OOfd3AcKFQGBz0/AsbiKDQoRAIWFq/v7u7qtmPYedNyLJ257Vqn1ZChN3fmDGOs3W6vrSxuMgYAFOJSwbGdIU3TEJExZlkWItZqtVqt1mruRlE0ODhw+fLlIPSUEplMhhAcGiz7vm/q+sBAmQDU9xpxHHLKjNKoFK3ACyqDA3/9b/2NSinTau3cXt/4a7/w1916J8NMk5iWlemGEctkUGPUykspEZFzvr29HYZhtWoFQUBcGgSBprM4jhkjjYbPGCGU5fSi1JmUkROIXDGHjIaRQCQ7Ozvnz5//02+9wkI6OTpGRDA7O6sBC9obkwPDq+sbGBquRIk4PTffarXW17fzpSkvMv0wACk1ygLPN7kWuw0CjBEChFMgSikpRQSU6PfnCafNPWkYhOJwLEN1+Jyq0sZRGn9JuR6UyPYXA02WQkomZS0FsyyWLFhCEuKShAsRQgzaJxz9Ib+/Yf8TYkLTkuvs24OSrn5n1ge46/P+b++0m1KKM57sBwAgYrwH+ZJ3te9jg7thKC2eWNtvO0RUiNgrR49ECiAEkVBCKVBFCEFKgMQqOBTs4hR/nAJKABVCEoYgk7sGmmY/2n8wKukzBGkSRJVmq0ub9tLmpdRKBwQpI0jpPgvtPYxmp60bVqwIp4RSUihkrr739sLNq5Zllgv5QmlQonLbtb2tDdftOIbOSVQulkcG877vSynjOG63291u14g1pVS32/V9PwxD3/dbrZYQwjKpUsrzvPX19b3qjlKiWCzmcpn1tdt7e3s6044dO57P5va296rVqsa4MThgaka1WvW6biGfO35sIopd3aBbWwEhxDJtJYTjOEjI+Pj4yMjI6s5iFEWUUtM0NU2rlGxO2ejocVPkOt2WYRiMUV3n9XrdMDXbtnUKIcVut6u78TCzMRKs7AAUuh3PbXeoknMz0wODhebuTrfVKeY10trhWT3PBYs6bTc0DV4u5sMwbFbrx8bmfYU8imMRZx3H9b2sZRkaUwixhDCKKDeAcGpyJCzan+d/SEl7vvKIGAQp9TPTQnpTkTKt/6fxNUkIKEJI4j4nhFAghBCesl6rw5MOCXAHZYCQO4sv38M58ICigYj9couMMUQEcgdJknfZW6KSAPQ/JATirobgiX0L909/qD+/P7bv5UEpOG0w1lPBEBUAJUQRggCUyN4yLagSBx8AAUr4/qq89xyfpqT1x8AhMcEjqn6QQvr6UwlcM0AKvfWDkiyTtJqqaYlJR/ZrqOSSCAGiEHtsCCCXzzc73XKpHIYxocgZvvDt54mMP/vZz46PjzuO4/t+u9VwmBoqZTOW6QfVTlNQSn3fd1232+12Oh3P8yzQhBCdTkdKadt28sh0Xc9kTF3XBwcHgiDodFuEYKFQGBoaQCWiKPa7ISDPOCXPlg0SyBgK+bJSijHGNN71u/Vue3Ji9PTpk//8//ybumNIRnYbO5ZlZi1T42qknP/spx/nnO/t7bVaLcdxlpeX/+QPvz47O1uwyjdv3vS8brFYnJwa73bbURQJEZ85c4ZqWqPRAjfeoLZBdV7PBRoQnfieylj6++++Yxi6xa1WowlKCSE67eb49Izvd6JOp1IaEJ3qYFanLa+zfgsELWUrzW7XYhEEvkVCL3IJZQRYHAgzWxIIUhL14RddTO1vKeMCU7T21OUb03hWyvVwIJAEKxLKCCQAxAgx2eEYZPH9oXOHCsHdYXx3+BEAANIDZuZk12QFCthHmT4uEURM9Ju7rjzZh9zRXQghPNFTsDdF03tQYP98+/YUxD4kEULS2o7QngmKUCSgKEGkAEBM3ju+Igkf2j8sP3zU85Qxn1hxFFAERCD7YESBpjjklAIAJFQiJIxsn/0ejasflQchyt4dECDJxQIqRE50TkBEEQeQcXjz/Rtbq7cev3BmYmQ4Cr3t5q6MI05JztGJ0oLQD31vb2e72+1GUZRQngQyvAgopYkJJlmLmVIqpQyCQNM0znmipmka6/1LUV2zI6qEUKioxg1NMxRRjp7Z3d2uVRuZrJUvZBHx8rUb775/VdcN28qGTMgm9eKQEum6nVa7dumdK9lsNggCAMhYeZ1ZjpkrZMsMsNNttNvNoeHS2bOnMlk7CLx2u+04WcJZtVpdXl68VOvKQAYK21H4qc8+5Q4HxXzp1tXrcSRMx1rfWh4aruzUuoh48sSJer2+u7s9MTqWEC4edbqub2ULE7Pzyxs7ChljZKhcqiqeL5Ry5SGl6eNODiiVKMNYWSnxa0d9vmlxN6k+b3b4cdLsQVQd7sVJtT+mXCfd9zZRCvsYhBSAsTSL5R0t6aCiI1UKj9s3LAAA4gEDkFQHtt+xCt1zmDvc4kBzIiLf16cQPqB/9pvg0PkfEVPtL0oiIulhXm9aIIQUrHt/0Ds55QfvoX86Vx7+kHWUPdDpLb6hkq8iBRMFJQAgESlBRUiCRAiEpMxL8j4VMafQM8ZTSjljAKCUklIFHXeoWG63u5VyxhfR9y9dmhkauHBybmdnp7a326nthF4niqIwDIMoDsK41ay2223GWC6Xo9RgnFJEQohl0wNAo0VRFEWREAIw1HU9iqIgCJRShPBOp8M5bdbdMAwJYVIqz/M8vxtFgcZ55EYcOVdAUdmmVSgUOh134eZyBnLE1Jijm5YOgJSzjuvfur36yjt/EkWRYRiO4xBCDMMIAvADYCAoMwjVt3fqL7/ymh+4cRxLKc6dOWfZmc31ne1qI3JDS7cVEsYYIbyQy99evFnd2spmSrVOrVQoX7hw5tL1zcpAWaOs1WqJKGi36sX8ZKdZv3btRn13a3hooF6v7naiW6vrjqGfPz2fm39SEk0iDUMJhBFGdZ0DU6m60lGfYwqvSY1XTvlH2nF4ynXKNOWNHq4fIKUEFBCCkDingAIiISJFnwj3QeIeS0u/3e4xMzN253rusukcQJ+739nBw/bDD9kBtz0hhHPK+mgikMDdWHDPcftUqNcUKSCUcLDkf5QSxnoJsrlMT79jQAghfTjHu6Xvw8MwBYOkUEARBRKaNFfyNS2hyFMaIlJQKgnhJgnvQ5WSyJ82H6ZJ2t6cMoGoEBmluqZRSoUQMYAO1OTQDILGZtjY3VhbvJnhuHLt6js3bgbdFhGeDLza7o4bRprlMG7adsZ2mGVZmUwGEYUQACCEkG6TECKESLSwPhiJWPVt4YZhWJbZ7XZbrZbbFYQQQ9N0XWccYuEJ5Zrc8RqeaehZyxaxX9vZ1jVm6lYxVyTIFBUMmQaUMepYNtXMWseVhAuQIIFLqFb3EsPQ0sp6JV9UxORGoeOJm0vrjUaDa8wwDIOvOnZm5fZmp+sTwjTGlBI61956850Tx2ZkGDRrVREQy7YNrr3+xqualnfryBhr1qqNlisUpXpVKrUVstzQZG6koucrX3rumfdv3GIofvZLP9VmQ5quxwjr2zvAWByHnBAlBWPmoc/lqDp16nNP0+VT7DVpkMJS+E5av1Ip1y8oUkRApAQpICAkixKn6YaR7Nuk74IhDfo4cJeGpe3fwAfcVvdagpIfHjzm3WdRB4/AKesfAsl+3PM9/vw0SRuqB+1HSYJ+AkO2pQgBCoRSygklhCQWJRFDH316kU6IiOin+BcY9giSBJmYonttk1JnLyAaAiChiMAAAUEll35/umKqMEaVIohAKdG0hNEzKcXexvaNq/Vmo3F78abXqN2+cS1D1XvN+k7oi8DLWyxvcdvSM/lctjDAdKvRCrJGxnEcxpjneQoIIvphxKWkB83/++1WLpdt287n8wAglZPJ2JxzAKVijKIIFVJKGCeIcRR3paKxFxJJiMR8NsMtTaOaL6WIRL6SDfwwigIRxZplFfLFweERpVRmrz1oDwVBkMvliuVSHMdSykKpODA4UW12225ECM8WBriZDcPQ911Dz3Bu6ppdKJpJl/A6XZ1yapiLi4uB1y1mc6Efu+hzFxterWyJhdtLx0+dpZRmc4XS8EhHwKnT56v60KnJAR2jjh+dvPjUVqit3lqMuCOJTqmOgAog6XCMk1SWfnRJGwVp3eeoGKRSdJ9U3T+NNzFUBAkmB8R9Jz0E8vCaHiApuZsB9d4T3ZMk9uM7egmosM9oDuyPdN+snVimcd+/DrB/fEIOmr4JkQeblAfyDtMR4i7oSeADAEAhokxGLueUa8AYAQAm7vAmODAMuEETAOYUOFOco84UY8yiToKI/WCZ5N0wCCJKKfun7pmN0AO4A093rpPfFZ+tFCJKpVRJN5RSAhUARSAKiJRSKGUyjxCSLMwgFQoFSimJ4MWKEKIoRaIhoQKpRJCADhK4K/iIIKGImLauWUD0xAfBCAIoVFLGQilldTYrjjM4NLC1vlFfr6+trN5eurW1tbW1tbK1tUUIcRynVqsRQppRVCqVRnPlYnGu3W5rmqaUiuPYzJVc181n9WazSYErgXHYsSwLACgwLyaB6JkSROBzzrlpMMa48G2mPXxmMop9ISLLcgCP12otQOp5nq7rlFLHccpF++Sp467rZvOVer0+PHem3W5ns9lMJqPv7RnHZ8CwhRCMscFKxXXdSqlEAXK53NhAsd1u2xwwdCmA8NxcLpe3NGbA6OQQMtHtdoGTXLFQrVaHRsdoaYiapjUcJLohZcx0iq7rlnkoAT2Emuyihr7n83A09CAql4nUy+MzXUljyifHRjqdzlDRpt3WziZ54oknrly5cv3tt0sQt4hiElucWggUhMaRhF7WMr0g1DUdMSVaNiVuOIZD5nkAYORw8NDlvUpD8lVPybFAkrbe3J3dDiofVEuxH+FdOlT/ag0V3H2bvb+oDvqy78CHFPdadBO7sEyrT2Tohx6Hinh/CyWEwL5ri3HcB+q7TiMVBwJkXzfjB8d2ctjEzJn8MslAIwiIFJNUfQKYqJugOGH9+0/gow8xiU1eY4QzyjnX9tWx/qX37vkA4vTVh/4zS3x+SSgK7LOqxOh2kKMxxpIL1jgVCkFQgQAEk+mCAsgkkQZ7sM4AKUEGqChDSpBQBJAECCJFYHcs1kBBSUi8+ApSTfBAULHEZC+TyVhpjAAjQ5miZVnV3a2v//5/Wrm1TIG02+3l5WVC0TRN3/er1SohxLbtOI4BwPd90zSllLquJzeVgC/VeLKGahKNGoYhIkZRpGkaISSJEkyM0JxzSmmGZ7mhG3a+nB1mjHCuc67PHteBxN1uN1mhTNO0ZrOp67phGO1mJ5M5G4ah67qapum6jnii3W5jDPV63TRNznly0jiOTdOk06MAo8nZfd/3PC+TyQwMDHT8wJB6xR5PLrtWq2l5fXp6JJJ+RmddS/kghRCWxaMITaVK2YJlGUo5tRoPw1DXeblcnJgYc0rl69db1d11JTzbpKACTgUj8chAZmtr7eZVXt3eWl7gUkoVRbFfz+TKXMWcKAsYSEUUY1QD1ACCwx9YitwZ8Ygf7KUflCTW46C9ojcse96ifUbQdyul2U9pcpb+e8+TnRZzS+7gzj0urcMxS/SwteeH6Yf2pOVw8BQbNulh8V3BRACY9Cj4AOym8cF7aBxX6oOqE1VKJSOfUso5RyUJoQCJf0sRgoRQQihIYIwlVyCEEEIkMMQYYQQYY4bGNM4YY5zcCdiDDzzU/vNjfae+Uoioado95CgZb5yyZDTCPh5LKZUius6ZJDFVVKBAJSkQqRBlDBZBRVASQA6SEkxmHk45AlVIJJIYFQeQQCVg2HtmVAFhBCUCAiHpBduYEpRSigqlUkpwCjrXOOd5xywUcsWs/eynnjQ/9+zw4OCNGze+8Y1vTB2bm5ycfP311994441cLlcoFFZXV8vlcr3dsSwDUTJGlFKIMo5DpUS34wa+yygQQgAlAcUYRU6zVr4/FyXtFkURInphHIY+N99SGCklbDtjGFaxULEz0Gw2AcAwjOHh4QSPpJQmpdms02zWk5NyTg3DIAQHS/lixiwUCgl/6T/o+fnpJP7bNM0kdiyOY0rp7u72ubkJ27Y3NjaUUvn8Q0k0k1ASAAYz6DhO8tSCILAsy42JYRhRFGWyZoK5xWJR07QojuemRsbHh30/v7u7K4O2QQmVfsmQKkMHHcKKRmtzMY7jqampPI9MGsRxSCnVhK8CV+k25Xr8o60EdFcXTbHXJHE6++rJQZMK7vfYu2P2UjDiYIxefyxCus+efsCKvP+eYt+UH8COZHtKAVNdS6tZeAdnIbExY3L9vRjFgyQuGcaHHkfdDcb8YFsjqsRSTCmRiesJKAACKEoZpRyxF65FCWOMgQq5xkzTSHphGEI/L4FRouu6rjE9AaF91Oxf5T1xj305uEPi9Olv72MQ0w0hRIJoCTNKQFNnTDBCpZQcmWJxLJUSRMlEn2IAFFAjqDPQGGGUBDFHREGIkCqWKIDGIBRgDBwJpagOwtAPEANjipSAkihRCg7EZNw2GCXQbrVkLCqFwuTkZDFf2NvaMhibm5ubm5u7fPmy7/tjY2ODg4Pdbnd4eFg3LEKICCMRxUEQhGGIQsZxrDPQGKWAnDEwdF3XNE0TGk8U9gSOE0kgO3IFIbi9U9+rbnW7HcfJeG6QzeZ1AzudTqJeTU9P1+t1AGi320XbHBsb29zcBADG2ODgoBDC9/2MaVBKJyYmarVa8pjK5bKmaa7vWZZFCCmVSq7rWpYVRZFlWWOjAxsbG7quE0ISa1QykeicW5ZFGWYyGSllPp/3PM80zaYrk8CCkZEhy7KSaU8IASrG8aFisSiEmBofYoyFYRjH8dn5cW+8lM/nJ4aynucppWzb3lm7UQ+Wwlhm8wUvRsMEI5fRdDOO46Pa+2ifufSGQ+9zmo886cN4IAi+14nlXXH//Q9pNY57rnxyJ14k+Ula/Np+zO0H4ulSXPAHffkk5ZgHhafZefd9SPvHuat9D06HvYGcZpK7hweRA/U0hIooAgGGgAgSQSkEhaBxyjljjElJoigSQiESAMoJUgqaxjjnlAKijCKVPJiETyWIQWnPPJR0soPaVvLIDsZfHHyoBO4UnU3+mxzcpIRxlmTS9jU4pRgqQQB1pilCpVIhjZSiSgAFpKAYQZ2BwbjBwOSU0aTPgVAqQsJQRUpRCojYwZ7ydRCGVHooGcdYQwZEISgkkjNmUzQp6roehmEURd1ud29vL/QD13VN0/Q8r1qtbm5udrtdKaXned1ut91uV/d2ENHzvOSmdI0ZOjd0bmjctu2kWZRSQgilVBRFoe8dtOLDPiJrmsYYMU0zm83GcZQ8jqmpqdXVdVQmZ4Rzjsrc3mpZlkWIhUqr7nXarTBR9By7tLGxQSm91mkKIeY74d7eHiJWq9WRkZFcLre+tUkpDYJgYmKi2Ww6jtNoNLLZ7OTEyNLSEudc07TBwUHXdZMYonzOmpycbDQaQRDEcXzu3LlWq9XpdPL5guM4pVKp2WwiYhJ8wBijSjDGoiBkjMVxrOu6aZqMUI2RQi6j63pmbERKmYQvGIZhWmGnG2rcJYRmbZGxMKBBGEW2drhfLE0I3lGg8EAccJoNmIBK6pNSQhOra9/22u/Jd31IzWvv7X/XsQFoSo4Fp4djEEnTre7afAcZ02ImIcVudXfq+p02kQf54D4cU0ox5X7vwSZ+jwdQ3V36LJlmLZNpGmOMQQRKQRzHQigpUTMQQO2TI5W8EGVCrxKVqqcTogIAJQXea/O+gy/3KGiUUilU8oEx1p8kpZSmoRFCNE77FwlAAGgUCUZoclyhKCQeB6IIACGMEqpT4JTonFJKGAFDSokKJJEgFUodaGLtoomt8W4YoqnVtsEESQEZUEIRKOEMDRCaoju7Ndu2ma4D54RxruuRUrv1+rwQm5ubnU7Htu0wDOv1uu/79Xo98FxEpACGxhOzNKMEALxuBwCSYqZJEBBjLMmW6Ldnv3AUY0zn1PddSsT42KBlklarI2I8fep4u9lSIo7jOGNbk+NjezvbQohutzt7+pTv+92OJ5hARcbHJpuNdqPRyBXKuq4PjYxv7VQ515xsoVgeFEKYmRwihhILlcGW63uR6AZRccBe2dyNkHHN2m00iG4LITwv7HQ6bc9pdKPd3V3Oue/7Xky2t7cppUGnWS6Xs9ns3t6eUsqyrEql0ul03HaHMVapVEzTrNVqnucNDg6OjY2t3L5lGAbnfGxsrNPpJAg+Pz+fy9Ldaj0QKibG+adxziqw3Ij+Iyydd1CngPQ4INbLDweyX1gnean9OOA7WhgBREzLfSUg4UD4TH9EpPERRu+ynf+51EbrG6cPUjMCccrvUrHyQHDhwfbpY9A9Cs0P6ZnkUsr+nVAKSfBB8nlfM5JxHCaMpq/lMUooYYyBUioIgoMmpD7RkVIKggRQKZWwRyni/phJJuceS9qfKO5BQCnj/p59AFJK6RpLrLbJ9j6i6RpTgAAKCGGM6hpD0LlGhWTJAXsVbUEBgACgTKBCgpIplAwVSIYECVCpFKFwNwxBeq0DDSQF5ERRRjlljBJKkYogUkQHRoCEEmJFFNGoZnHDeeGFF6SUq6urnPNms2kYhq7rUspSqZQEGSa6bT8kWkZ+YhVOLDJRFOm6rqQwzSwc0BT6N6hTobgcGy5cfOQCIbi0tPzqq68bXP7cz3662WwuLy+3Wq2zZ8aGh4x2u/3KK69YGTV3YnZg2A6C4OrVq5Uh66J1Ym9vb2OjyhgbLufHBkuapm1vxwOFjK7rvttEBM02ZkaH3Pqe53mhRucmRkPE69evB77n2Nb42Oj6+nochRnHnh6fAIDQ9SzL6nItZzsNxi3L8pptx85TwqUgUgIajIC2vVXNZgpd12c8sCziBxDFbHevE8Xbrg8bO3tRFLU9TNTDdrtdb8eWJuq1ZiDQzFWmTkUgTRAaxbTwtVSh+xaZ/dcdKnSoJPz9Li0soQBJTyG9od4b+QRkygVhz8/VB5R9MErDPtLnQXfeASDN/tIzXyOSPgz1dL00e9Ph2+/y3wHiflKH3D/+PQYjTKs7dnfMJFfqzp2wXr37O62Z8Hzf90nP3UgAgDGmcU3XTUI8pVQYhv0r6KOjUiillAQJIKW93pCAVH/ehoSwHcDmRA6eHfaHVvKrBIai0GcUQGMEQCmppEyCCChnVCmhFCikVDFGDNA55zSJP6AMgSBiLIlEUEoZFAEVSfxhSiGl/edPQSlCcT+i+tCmPPjMKCCnhFPCOGWQaLFSIHWDOArDxaXbl9+/RoGsLt++uXBLSj+J60ssQVJKTdO63a5HlO/7fVNXYvdNoDYxzydu9eS3CVQBQOKf6jcaAEDUTRaDHx+pTE1NHJueaNV2TQ2efPykYRivv259+9vfztjizGcuWJbFaXd7p/mZZ77KGNvd3d3aXjZM/NyjT+m6/r0/e2l1dfXs/PTjD51WSv2H//AfRiu5p59++qe/8Mxrr7126dKlM8cmT0yNxnH84osvstj70nPPzU2Nrq2tbWxsnJqbOjM/c/v27cXFxVImMz09Xcnltra2SBw/cu5c0XE2Nze7mdzMzDFd1xFJs9nMZrOzs3NKwdZOszJUHhsba7fb9ZanW7lCoVCpVNbee8+yckOjpUKxuLZZLRQKZTNXKI80t7cJKxYy1uDEsTOnHpuaOL7nQqvpmpn7kDKGiDwtr72XbAT770gOZF/25c/VxfZ1FkIIQUDYj75Js6n3Ig8J6fnv9kd+mtWyd17EOzCU/IQdzhXTSp4dVFn2AeEuZfMe/ogpsSz3xExywXl//pRx0gykfwJEiohC8tBF5vkaRV2DsqNlM5ZpGjKGZqfd6XgKmWY6lNtRLPwoMkFxQplSGlIukDJJEAAUymSM98gLY9Qgms505gtEBJIs4IE0AQAGiQ8F9iOPYH/mqflgiNgS3DaJrmmE6wAoETAWhDBKeDL5ECmpUqAUZ/tmFCmlAiSUAlBCPV8SQpAwDgSpVEKKWAglHW4KIYQIE6zc54NIuI77cUwHYxoCElGkQumMMCIQkShJEAmjqBnmjRs3/uzP/sztdlQYolJZx4qCWEoJKLfWVuI4Tuw7yT0yxmQca6YZhqFpmgIIY4xwjRBiWo4QQtcM1wssyoWMB3JWo9EwHScMQ8qYZVntdrtYLNrZ8VZn08rqGgev7Zeswvz4JCi3kCns7u4++eiT7775bjFbHCgOIOLD5x7+ztZrDmPFsj45dGz92Wf3dtqTAyO5vDH6N/7Sb/zGb3A9vPDw+SiKfs77/PPPP3/s+C8KIeaO//yV//1rXAsmJkceeeQRIZsvvPDC/GjliTPHG43GP/7H/3jQ5o8//jh59qnf/u3fXlxc+Pzf+Kp88tytW7f+6I/+qGCpv/6LXwrD8D9+7Xeku/lXfulv+f5jL7zwwvvvv39yuvjo2c91uu5//r3/dHxy4tixh6rV8RdeeNky+Rc+9fT0aGFhYaHZbHzp2ecqGRrH8WuvvXbhs49HE2arXtdzRVoaKB6bWPY6SAm3u0CdQ8cAT4l9jYlKmItC1SdDQIArSg4Etd2xJ5AkTk1RBFSS7Cth6gPxxLTnOzscgzTUAKC/9E3/VwLkAVvPgX8pCdDDKtzfmIBKf7wc/ODKu/ka3T8UEYdiB5eH10cVog9y5MA7COiFJirEXlAjIgBEYBx6fHr3bfLQ8xOdiCR+3wMzap+YqCREjyISJH07ixKGYRihxVgYh1L4IdMoEMo5F3EIVClFlZQqUX+SpHZ1F3wCwL5/PcF1IAQppUmBSKLuutC7dE0gURQppSgoXctwBgRJHAtAdfBRJZ2GMQYoESiAVEgkAKqE2iRhR3SfdN85EVchI6jzRA28E1IQKIIIEogivUTZ5DFwRQEBpYyFUBKUAimlUmDZrLa3u7W5WatViRSGpvuBF3puELoJiiVwdqcvalriou4DX/LfhPv0Gy0JAup5CHVd1/VkH03TEnNJs1U3Tc1tt/b2djZWd3RqlgcGUXlvvvH28PDw2urG/PGTuztVSrhlWRo3RkZG2u12s+UahtFsNueOz1WrVSEd1w9nZ+ZGR8b3dmtDQ0OGbs3OzAV+VCwWu93uhfMP+1547uyFhZtLF84/fPXK9UyOt7u7o+NDD1086YeNYtlyXfcvffW5f/n/WLcsy7bt0dHRP/zDP8xkMpVKpVKpbO5sv/baa5Zllcvlr3zlK++//34ul3vsscc2t7bffe+dvb29/+q/+sudTocQ/tqrb83MzFy48PDKysl/+S//JVHur/43f71er4PsirD5cz/3lWa9fnN5ZSsAQBWHkWE6THPS6vKkmmKxZ8jomx16fRUBkqWw+qpZ0o0pQZQUQRGVVMMCRACiUe0uOrD/q9S8s0OBBgBQ4gcilQ5+/cFyEIkOUpU7p6MHQwHulNdQabnoKSci+36kfmhh73R4518/4Dq5jBVSQNnDxbso/T4MkST9FijBJP9bJgM3GQOmYcdx4MdxGCPjBmWaEgIJAYgpEEGBUsIoJQQZ4fcAXBQJKTFWMaWUUqCMMMaIxISM4X4MJAIiBaSoFCIFkJCEEfs+cEZN02SASimyH1eenKVv845jTABIKSV7c1zi5yIKFEGWLIwESIASkNTEYN+jRwiBxDRGKa37CpNiSOqO4gkAABoiSqlkwqUiKSUqpeIo9jyv0ai73W7ouVnbctudMPJN0+j3Bs75QXRlB4RznjAjsh9alWxMksghMYHpej+gkRBiGAYhxDIM04hnZ2dHR0eXbq51vW4ma+ey+d167Tvf+c7Q0ND8/LxhGN1u93vf+9709PRP/dTnt3eX96rrQogLF86JGDY21l/5/rJp24VC4aWXXiqXy4mHa2hoaGFhwXXdfD5/4sSJTqfz1ltvZTKZMAzPnj27sLBw7NixZrN58uRJz/M8zwvDUAjxqU99amtra2xszLbtr3zlK61Wq9vtWpY1NjY2OzubhH2Pjo4eP35c13XXdacmJy8+9PDSrRuGrjtDQ2dOnV64fssyzWJOs46Pnz4xSdEbHsgw8MdHCoyJylC5WMq2PdevRY6muSGXMWCEzDh8LKUtE8N69aV6I6s/PiUgAhxc0ZNQAkBiFRMAuV+6UPac14of4B0HP0DKUFTkDpe5i9pI3NfO9okHIXgghjZR/e5ZiuIe4LuHiRzcSOhd6HBQ1Tq8gVIkqcGTcCCgJLEVASFE3QtAPUiCu07EjTv+A1QfuNa+UEI4BcYJp4xSCkQRVFEoKGWW5cSCBMKPwhhiYBw1RmQvdV4pgowxlbAJ1luAsdfEChVKIRWRMSGE8WQEql4FAiL5fuHrexoxgT8AiKKo0YgMw8hYpmmalNA+d4P9Qd4jFEiUUgJBSKWUkkgAFFEJ2ZIKiFSogEgkSCDDKedJwEFih0qIidKJREBFlCIKD3gYqa4rBUIIRiQFwghNrPOUcse2zp46fXX+vevvX5ZSMk6yWoYecJYenPqSaOkkLjRxSHPOkzn5DqvfD3o4OGOTXpSmAgDf97OUiCicnBhrt9uNRmNwYHxpeRlILITw/bBebw4P+1euXCOErK1tVCqDr73+crGYC/xYKjE2NmIYzu3l1ddeey1byA8ODhaL5evXby4sLJw7d65UKt28uXjp0iVK6SOPPBKG4ebmq++8886xY8fOnz9/+d3l7790eWtr66GHHsrlcn/8By8sLy+PjY0ZJl1bW3vxxRfHxsYIIaVS6Z133lFKjU1OcM5ffPFFy7IGBgaOHz8eRdHi4qLOtJyTOX3i5OKNm7quU4TzZ842qjUZdZRSn/vsZ13XvXnjxsDAwIn5+d3d3WqzQUSkawRE2Kntas6EVKAZtoDuoWMmrS4Ck/fqUL3+Ru/qV/0JAwUiUQQBQQEBipB8PRg9e1CxSIszkoT2B0W/vxNC6B0cvEvUvS7//b4Ed+EO3I1HH1SLKB48752wgtRyAynYdOhZ7tnnICKjgoP78Lxj9iPc0iJLGQWdMZ0TnRONEY0mFZJULCTup6UpCSJWhEkgklM4uAIaIgEkqAC0/VJeffxGAAAlFKFAkTKFVAJjLEFog97Rh5OqF4kpJrEoSSlRxgSQEKIMnVLK6B1dvf9BKSUVCIQEgGKJSvXq+hAEAJowIAVEJEcmuF8lmWEvjVZKiYQQIgEQiVL0ACASQgCBAnLKCAdGqZIJFaeaDvmsMzJQuXH10srCDSUEpzRj223PPdg1+++JLpaQo36IZvL5oPaaRM0QQqQERAzDMHHVI2LCIxzHmJwey2achZuLjWZzfHzOdrL1xvZrr776mc985uGHH/7GN74xMzPzu7/7u7/2a7+2uLi4sHD9kUce0TTrwun5eqM2O1NYXFy8ePGxgeGB3/zN3/ylX/qlOBa/8it/a3t7e2dnZ2Rk5PHHnzh27NjLL798/vz5ra2thx++OD4+fvv2yun585cuXZqamkEkm5vbmUym0WiNjU0krC0IgpdeeunixYv5fL5er3/nO995/KknT5w4AQDf+MY3NE07ffo0Y+z111+v7uw9/fRTDz18FkG89tprI8PjMzMzmUx2Zfn29vb2zMzM7PRktVpdvPl2Npt96PwTe9Wm9NqlfKHUkn6r6WTG3CgkOk3z76iUkPc7fqV7CAsFANyvAAWEABAFhGh9Hw5QRhI/nDr483uGYhoG9eUeXYzdqanaGymkFzd0xxxDyB2cIgf8Vvec/YMABKmQAinLl6VKfCDn9q5bPiwYgdxd2QQRuWPTKIIwlAQEYcY9PCgZJxxUQlI4I5QpSpD0Yn9QqDgMRRQJIQQApYRzriMGCbukhFNASoEQSggqoAqVlH1m0bsIlAokAIhEeWJcMsYIQaR3Qp72DShKKUU5E7EQQjCClmU6jmOaZqLN4b6PHw5YsiOJSinRMyUrkWAUUFRqP+mHSkQkFBUoQhTVEEgseveYKFYAkIz5vvT7ShwHAACYVPUBygAVBQBDY5qmZR27Uir3bDoAUvYS/A6GJvQ7X4JBCcvrrVWwj6fJDknhHt/3NU3TKQeAJE6vn90ihKgUKk8/8UQhmxkdG2k0wm9+6ztDwwPTcyfKpRJj7I/+6I9Onz4tpfziF7+4urra7XafevoJy3R8X798+crk1IjCuNVu2Fax1WoNDAxsbGwkCSWLi4ue5zWbTcbY0NBQrVarVqsrKyu//Mu/vLS0dP369YytAXX/7q/+/X/4D//hE088cenSa//gv/vVmzdvfv33/+hTn/pUsVj8O3/n7/yrf/Wvkuv/R//oH12+euXVV189c+bME088MTMz861vfYsxNj4+fvHcQ07G3lzfOHP2pM41yzA31td9L1hcWhseHl5cWgNiuG6wtr576lTZ82XDC2gcDxdZKZNhKoTYFRELZMxTdDGWFnPYH71378D20wnu8I6kfpPOAYAQoISw/UqnhCAxDNwPjut7MNI0DACQ/VzZu3Wrez70R69EcsjOhNAfyIDgEPXwECUOADBFWU27fpHWnh+oAX2ocEalrgElzNBJOzqccyZowAgSAhRBKSVEBEiCSAkFUSSVBMY4RwDClNx/EoTShDFRSntRW0RKjOPE0qb6JjqlEs4iEZEyYIxyzhkjhN25jINGXI32zCWGxizTsCwriQzGA5FH/aeOiaVGoZQyligTYxASAJRCJeY3lejYiMkqtm4ESt3JUwNgiX9QoeoHjyTMN5mgUESEMEKQAO2Zi1SiizlKxJpl2rapc6abZsiIxjhwjez7WcgBI30/diG504Sc3pMQkFiIELFvqE52SLS2bDbb6XQGK+XhoYGEK1FKv/3tb+eKhV/6q7/wi1/56d/4jd948cUXs5n8xYsXH7n42Isvvuh2/Vu3Fp968hnG9N/8t//m1/4P/5tSqfDlL3/5P/zW119785Vf+ZVfOXHiRK1W+3f/398qlUoXL16cmJi4dOnS137nP509c35yYurC+YdffOHlMAx/5is/l8saiPh7v/f15577suu6Tzzx1PLyilLw7LPPJolp77///tTUVBzHjuPs7u5mMpm+JYtSWqlUdF1fWlr63NOfuXr1yrXrlwfKhccfeVTTzEb1/XazCRq58OhDly9fvnz9/ePHj3/xK88h4quvvjpx4qEcz7UaHYwFxcjvNuxshXGMUmq5GOnr/eKB4Jf+c2HQt+8k02ayHYlUJOlvBCn0PhBCBDm89E3aOJTY41N4AGgIIZgSJ63gcDtR/2wfVIgOYsEB3eJwDErTVdPWmEiTe6bq/ZtCQg7WhEUKEGkaOo6Wy6UGtpNeDDQQBEQFSighkySDIAiSGJYk0A4AoiiSUu4vXEFJYlfGfkaFEkIkDukk2EdKKSQKiZGQYRwFYRxGcSTiWKpYKqFQKOx/SF6I2F/oxjDucLcPZtj3OBQmxTr2FxpCgohyn1spBQcBCxG6YdwJok4QdcM4kBghEYQJwhDoB1/QsyP3/iShpMlttpuNZrPpup3QD3zfVyIiCAgyaavE3oSIQoik5mG/EGLfW5/cDt2XJDM++Xl/XR0A6NuPstmsZVnFYtHgWhwFq6urlUrl8aee5rrmed7Gxsb58+c///nPJzkTSqnh4eG33nrr29/+JiJ22u7jjz8+Nzd35erlhHBVq9V//s//OSFkYGDgrbfe+vrXv/7d73735MmT29vbv/M7v//bv/3bQojBwcGvfe1rX/va1959991zZ55YW6n93//5b/7xH37XsQaefvILv/Xvfu//9S//XRiGTz755Pj4+D/9p//0xo0b586de+655+r1+s7Ozhe+8IVnnnmGEPJbv/VbSqkLFy58/vOf/53f+Z0oij7/+c9blqXr+je/+U3f95944onPfP7T3bBjZPRHnrx45qHTMUQ3l288/qnHdM0ZG50mwCql4vT4mMZQY+h6baLw0BdDcuir384HByoAUCUZKoaKA3LA5DNVMvaDKAhF4MdBGIWhDIM4CEUQdLtd13V930+eZn9eTJOD3TWRnmMU4NAX9DPz918H7UJpbOXguLjn7PegxpEFel7t5JX4kskBI1p/r0OvjaM0ozjBKxASEEHKPpsgjDFKKCeSKCJikAII4X2MjwiH/VwKTaPcQC2K4lh6EiIUKlJK3VnAiBAioagQpSRKSaUEACaZKUbcOaCbEKFIGCuASLdoUkqi7/pJeFCu4CilKEgCxNI1XUvcZz0XUgJGSWGt5LBAYkKTYvZUSSUESEEkEMF17Ks5sH+/lILfZYQQmjwqRfdVQm5YYRh6YSCEQiBAOSGABDO6JEwDQmPJQoGB4EJyAMoiVxHWbKubK9uZ8iglQPRYCNlpVXO5HAAIIQkh7a7rOE6362ZzmSiK7IwTBAE3dAWQLxW73W4Ue6ZpKiUJJUIG7Y5EQIUsVkyhUkR5fmdqYnJosIIoHWuaWaGR0eM43tvaHRvTHrsw8Qs/89Tu7u4br780Ojr61JMXy+Vyu91euX1zY33lwvmTD537m1cuv58vZJ75zFMZu/Anf/jC8bmTX/35r2RyOc75+vp2pVL5J//k//LP/tn/NDQ0tHx76Wd+6asCxMvf/pbyO2G7/j/89//tv/jX/++3r152vdqjj5394nOfeemllx6+eEqqU5/7/FO/8zu/8/t/+qenLl60SwPFkfE//OaLx848fOLECV8Z//if/j+//l9+b323Y+YGFlY3urEYmBirVMrXtnZqsXx7cfmv/NJflqgfO/P4f/7d/+QK9vDjDz///POEkNmZ+Xqtvba6deP6ktsNH33o4bZbh3z2+NnzTGN2dTNnQhGgFkS2bSddPwgCxlixWHRdN2sqQkgYhpZlUUoTZRYABGFxHHuexzlP1kpKJI5RKRmGYRL9kMA35zxG6CvLsVTUMBKbgFnbSVJ2GaNJbm2pVAqCwNR1z/OkEoahMcbC0I9FSAixARjXqWa7sWp1Y+QW4aYfRiIWuVwuWTgg6YGJ10LoJiegII7CgAIahgESwjBkZuag6tcHHUlgf8s+fU4ieWJCKQ2CMGEPQkjTNIMgCGLKdQYAsYyAUcPQkGAURRbT+23SG9FSSil1eidWrj/eASCMZG9+JokhuDetxsAtywp83zAMEUZcKYFAEFApQLyHESAiUkoD6EUP9hWHHgbt+976aRMJwQlkwjgA8UACKiFB2MReYLfaDwUilNJiPkMOuNL72OwYJJnhNU2j+wV01H4OGgIkWyQFxu7kGPdBty+GpguJgAKVkkqiAuBIJMaJ867H9XrBZQoVpbQH6pQmYQLJ1/1oHQ4khqStCBDCYokMMKlkTgghKFGhVGAZOiGk022FYdhoNExdGxsbi8Mg42gA4HmepmmJYmIYxtDQkJBx8swS9EwIphDCMk0ASOpjaJpmWVY/SBpR6pw7jq0bPAxDISKCGEVoWVYulxsbG2s2m5TS4eFhz/OazW4QBMePHzdN8/XXX08CtcfHxwcHK8u3b2p61rLMZrOxubXa7XZ3d3cLeeurX/3qr//6r589e/r69Wv/u//tf28Yxv/pf/y1//pX/66u0V//n/5v337+m7c3Nq2M81f/yi8++vhjv/Uf/+MjjzwyfezYF7/85Var9Y0/+7NnnnnGjyI9k2m32/lc8ctf/sqjj1Zt215cuDU2NvbmW687jhMEXqlcfOaZZ2LhIyrP85559tOIeOXS5W9/+5uaZjzy0MNPP/1UonFXKpX33ntvc3Pz/Pnz8/PzmqZdunRJPfTQ+PioZmqNZv3W7fWd3cbYeHf+xHnNcJKW1HU9ijSllKkDI7rDWbvdztm2ZZkrKyuU0sHp6U6nE0YeADgWj+O43ewmXNX3/TAQCQBp1AaJDBSgNDgjQugaIIKuG8lDCcOAAatUSgm3lZISgrrOoyjwfTfoytHRYV3Xa/W9OHRt04xjaLVaY8PldteNIsVA07gkOlAdFEIsJAORtXVdI41GwzRNyzCiKKK9etLc0i2FUkpkQC3L9j2f3p29lCjvhm0lqv1BeAIAximlhHJCGFBKkVDCgGk0Y5pKKQRgXIulkEokOpQX+EnwmqZpBCCOokSPDsWdnNX9MagAgOt6Ym/B/RQwyhilNA5lskJMFEUG17gCiUgUICJBvAMxybGSc8QAfRp4EJ7CnmWnxx6xX4xVaj2/E0KSy5tcikHDfb7DOadco4k+UjAOBHHux8IQQnRNMca4RhknlBJEIIwqBVEUU0oJJUqpOFaAknPOGcH9COyDVYcSGGWIghCaqPwgUIJCpaTo42MSEyulAACjF8PeU/YRe3RXqBj3rzGWSoEEoJQqIQEBKCrZQ2dJUAFCtxsOlItXF27sbm+ZupbJZIYGKnEct1u1JP3FcZxut5vP58MwLBQKnW6bUiql9H0/KVgBAIZh6HovdeMgc0ZEqWIK4Dj2QKVUyOWVEhSoaZpnzhyLoujWrVtCiDNnziil3nzzzSAI5udP+r7v+/7CwsLc3BwiJuD+0svfK5ayYehJFQIRu7tbcRyfPHnSMa3f/Y///uKFk61W7dj0aOx3bi9dffTh05srN0rFrB8GJ89faLfbW5troyPlyK1du36zMjC0V60/9fRQtdZYWLz12c/9lB9E+cHMG2++PT09rZvGsbnje3u11dXV+ZMnvvPCd5588skyK1FWOueea3caFx+7ODExluQ8nz493260V27fnj8xNz8/v7W19d6VS8OjI7ppMI2vbaxPTk5OTE3Wm43VjVVu0EqlXK3tdLq1MPI2N27PzExHkVutVhuNhu/7AFAoFIrFIgBEph0Egd+mtVrttddeo5Q+9dRTuVyuG4aNRsOyrGTqrlQqtd3m5cuXpyanb9265TjOzMzM5ORkJp9pt9sqbJmcJQUPHMfJjowQJcOwy3RdCMoYK+YsIQQAo5SGYeCYzNCstdVbQRDk8tlcLoMoROzrGtnZuV1vtJhmFQdHM7bpR10iorxjom55XjuOIgZmt7Vr6QNZ295utygKQEoIMQwDJQa+r+mMc67rvJ9RiIicM6VUHIso8JJZlu1XUk86cRhHDFisYhn3ZrtYxVJKi7DQdxljhDMpQhTAOSdSAucolCKoCCKqWAlCiKZxFIQkWljfuImIiFEsKe2FR6r9DC1KKecaISSfyxFCVCy4AsT9kOE+XhwEGkJIiKw/nvGgsU31HP2wbwNHRCBEYwdrTWKfQzm6RSgm7CwJwGGcUEo1FfepYzL0ExiKMZZKSiEZMnogR1wJZIztV4TqxY4R6C0Y21fZcN9HphQIJdW+9UlJmYQvJRkb/XGtVGIcV/EBL2mSQNIb9hKAEERQQFWy8h0hBKhQXCIACESQShFAzpBRtCynkMvfuHa1trc7N3tMyrjTbsZx7LpuwnGSyjuDg4NJ7Z5khkkum3OekB3t/8fan/5YnqXngdh79t96l9gzI5fasqr3IrvVZJNqakiKECVL5ljyyCMLNoyRZWAWYPTFgAFj4D/BgAFjvhiwP1iGZ4akKA43kWou3exuNpvV1VVdW2ZW7hl73PW3nv34w7n3ZlSxm7CAuUgEIiIj4v7u757znvd93ud9Hsa07pIkiYnA5ptpmnotkyTJs2Q0GArBrHYBWJpwhNB4PK7r+o033iiK4vT09I033rh586YQuZQyzqPt7u6ORqPj4+PRaDQo04OD/aJM+r4uiuQ/+af/ZFBu/czP/KxqOkr9jRs3PvOZ19u2/uCDDygJ//J//7+rmuWkUr//R9/43/6L//zzn//8v//9f7ucHt/94N3/4r/8r1966aV33333crK4dv3Wr/3HNxDmg+H2m2++eXh4kxDy4QcftY08OzubTGbvvffB7dduff6Ln01TcXZ+8tG995quni2m5TDLskwI8ct/9xcmk1n9u4tyVI7H463tUTEuQwic86ZpdnZ23njjjd/5nd95/PjxRcFPzp7lRToeD2/eupmmy+Ojy4cfv7d37YZtp3J52bVtURTbxc72gCulphdPkySZzuchhK9/7c22bZfTo8UkKG211tfeeAPAn5+fu3Y2mUwunn3MnDx7+uTOnTsJ0vOzp3OAqIJ0Nps+f/58MpmMRqN2frsoCoxx4Hwy72IpN5vNhsPhcDjs+35ra+vx4wdvv/12nqdf/epXWqeath4Oyxv7u0ePns+nR9NZdaNbvvaZz1ME08Us8MSbUM/nnHOl8Yc//Iu9vb1f/MVffO3m7sPjKWMCI8YZo5gF75mgsc6K/YrN7ov7KAotxMCK1u0dACAEMUYAeAghdqKdc4wRirR3ktEkERyAhICY4N57oMR7ukmmhIg6DVh5vM5QVs8ccSocVtOO6224ymy0agGgyDIUwuOTZ9S7qFSB/BrBRlc416u0AlZE9bAeoYnPJegL3jNc2beCmqt5zea/Eh9RFsAI4eCR18EgBy9MIDa/EmOf0w4hj7FHaFN6hBACjv6NAWOMAwREsXMOo4Aw2uScmwQNAIJH4EPs7lEMQFbIPPJhDZ/hEIIDcCE48MpeYcRexSYDQgh5wNY778GHGPewD9i7KBvgMEKErJruh3vX7t+//87bP6CU3rp14/Li7PT01Kheah2RiBgrI9S1XC572cUB+qjT+qmIHxnSIYQkSRBCaZrajgyGRcJFCK5rKqN0AIfBX7t27ezs7Nvf/vbXvva1tm0RQjdu3Pjt3/7tr33t6xGeGAwG3/rWt7761a9OJpOIbnzjG9/4+//gV5xzJycn//yf//Plon3rrR8cPzv+B//gVzHGj588e/rs8c///M9//e/8wre//e2XX3v58tFJXoweP3r6t77yM7/0y3/v+OmHs/PrhuwmRbF3/fpbb701GAzG4/Ff/fCHaVl+6ae+PB6P33//g0dPns9mMxdQORx//PBxUtLlcm5dev/+R48eP3j48N5Hd390/fr1tKBpkv/aP/qPi2zgwHWyCTPXdTLJs7quizS5NhoSQu4/fPD42dOXXn2llzORskU9H22XW+OcEVTmyXBY7myl4BOKB+Px7fF4nKapEGI2U8WN/SRJEgZFUbz88st1XV9cXDjnPMB8Pr91Y7eqqq6hOzuj6wfjz3/2lQ8++JBinYqwt1NIKZum4ZynIvzU51/LeTgSoLVeTo4Z7Ozs7FDqjp8+2NvbE0Jw7HbHBWP4+OnxYnJ69ORJmZEvfuGNhMFffe+bbdu+8Zk7zfLS9POD3ZHqm+Mnd7HXNMmUdOPtrScPj549e3ZwcHDnzp2tnPIg5fKiXwTdqWy4EwCDNRgRSikjpFN1sDgm8tYaACAEI4QoJYLwqxVMrDIAwIOjmBJOtNYUY0yRBciyhHhlDQbkKFhBiHE2GG1dsLKLVViwFgAoIeCd0QqjZPPHN1sYIcQZ9d4HZ2ORRddbqSySk5OTy+dPsjStpudUGe8BBY/8FQ3DTSC4ug+vfhkfFPlNfL0aRBL+CWW5TQ5FIod9pQoSiUIhBAecX31qQggOASMUtbjBfcIJBAAo+BiDIoa9ef3O2ohGr4GbtXI+EBQAY8xpwJh5TkMIHoFUa9A6ljYY4j+lX7x2f5VXhlnwwQXrXLAueEAEIYe89yQmWQg8Z1gwIgSjFDujv/FHf/jsydPPfvYNJTuj+uCM1SYeO865tm2NMU3TAEDXdYBCTFKSJNmQpK21ZT7CGEc8KPa/jDHGGPAWfLBWe6u9dd5qzhnGaDAYfPTRR6+99lqUBxqPx3fv3h2NRpPJJH75zjvvjEajhw8fFkXR9/3ZyUVZDo6en3zpzS9Mp9PTk3Nj/P/w3/+bb/zxd959/96/+lf/9f/x//R/OTk9/pf/8j/7+te//n/9v/23490DkeRf/Omf2R7v/OCv3j7YH7///oPZ9GLRHzPG+r5vetlK9fToWGu9u7t7MZlgSj/86J4PwQdEGC8GbHI5SzKRleL45Pk7P/rhoppKLWfzyWirfHp6QoDsH2z/9Jf+1rXru4PxIE9yD3Ps0Ed37/77b3zj7/7dv/vlL3/57t27COOyLKv+fJQNtGuOjh/NpidlPvjMG1+4cbirjZ9Nzu/du3fnzh1vVdu2+/v71trZtO77XgiR5+n9+3ejFKQxpuuaarGYXIjpdCr73uqs7/s8z7dGpbdqOZ9QHBJOeuQHRUqQP33+tEzF59+4E1GSiBxXVfW1r7y5ScZTCgT7V29d55xf2yqSJNnd3X7y9PHxs8dNUwXbOue+/rUv3bp9YzwsHz89Jl6nKMkHYpCS7SF/aiqnks+8dvjq7b0IXNy9e5cEkostGzwG32tjTM9FCkhRlsdUhAu6WrwhYIIEI9Za6yyEwCglhK7qDC0TSpxzSiujVdxE+WiYCcIZ7jrprKSYo4CkNsH5LGWrGQa6AnqMMQCeshdarlczD06w1nYF4V8h/WIjXTM/efLw2t7+OKFUKgghzi6Au0KL+EQ5RqJjmgcI67oPIYSItxQBi0KJV3h0wa27dCs8fJ1P4RX0ghGObNNItenNJ/rQJARKEQaE3KdV7ldpGollEwIAhil+MeEZNi3/mNqsgpdbkSARQpQRhKI8kkfwSR42AocgENz5Tzzv5hPGmLbG6WCst8GvWLHOISDOevCeUaCUCsHShFGKv/Pn3/nw/Q+Gw5JR/PD+x4C87DopJUvTNS3Ac87ruo5hhXEaRZoJIVHcHmO8XC7j5UUtIWNMCME5RynNKfbeYqCM8cCc0zAoysPrBzGTeuWVVxaLxfXr1znn77777le/+tWHD5+ORqPBYDCbzV5//fX33nvv1q1bRVEwmnz2zmefPnu4XLR/9f0f/tmfffPzn3uzLEaf/eJPP3h6+uv/9g++9JWfO/53v/fbv/8nNB0Od24kwx0c4OH9xynJLy8v967tPXn2OMkzQpO2bUMIZVl67zkiw9GWcy5NU6Pd6emp9zCfL7XWRrumaTDD55OLP/vzP3v7VeaVBgAAcURJREFUR28r1WGOdw92gcBwlIUAH3703quv3iEMPX788Gd/9m/v7Ox+9y9/EIVKohJ2URRa66qqpFGn50dpQhfL6fOny8NrN/Z3tkeD4s7nfnpeTd/64fcn8wvMAGP80qu3MMa/9W/+3dOnTz/72c/e+cwbhJD5fL5cLr///e/fu/fBa6+9du3GNSrobDZbNssf/ehHRVEUxShghBkFgh8/evrw4cOf+Zmfubk1TrhACH344YcPHz48PDx84403Yivg9Ozy/fffz/P8p37qp7RsIhr14P4RZ3R3d/f4qDk5fjoa5vt7o1u3bu7t7V3fG9aLJQX8pc99FgK21iNMMMYc9CijKXGmnWutDUJCiFKgXnWUauypC7quFrNqtk+3mCDL6TKuqEi8inPd0fwyZtMxY/DeR4nL/dGAeq+6bnJy0vf9imjmfXJjQImT3aLtzXC0LXgWXXqKlM9ms6ZpYgDq+z6uw61duurzk9VAu48TUdoHaykA55xz5r1vmrZr2+3dQcng4QfvvP2dBUWYGh1CWDH3AvkEufsFRQXFFteanLDyDULeKSABAcKI+FjwhACArOFXk6l1AQmeaLSaC1vFytgmk/qF/i7GgVLkgscY2JViJFwpFUV03AkvRKRiYhXhnM3k1CY7M0ptSilMMay8zUjCX9R3fmXOg0MIjH1Cc2DzoJxF3GdV22IPbnUlsUUmMIreFpRiTvGv//qvTyYXBwcHVVUdnzy/ffs2xlgIoVdNE0cIiRtpNBo55wL4mAdt+oAAoJRazquIBFFKIyErwkPbg5RizBjJUgHON01dlNnOzk5sfsWMKQ6O/sN/+A+bpvmpn/qpoijatv1n/+yfnZ+f//2///ejW8arL71xdPTszS99JUn4X/zF9/7q+z9sKvNP/+l/Wum/ePfdd//w33/z137tH7308qOzsxPA4j//L//VH/35Xz786KNiq/y9//G3f+mXfmlyPulVoEXijMuLAed8Op02TbO/v89F2vf99s4eY4wJ3vby4vJya2snIEcYZZx+/PHH3/2Lby8WszRNOKcA/o//5I+/+ObLo+HW0emR9/b09PTf/f4fVVXz6qt3fvf3f897P51Of/03f6Nq6jt37jRdu7u7q4384ON7t28eUOQBWWP7H7337snx8Re//HPXrl3jnM/n8xBClmVSyvPz88MbN6azGUROIMaM87woxltbIYQoho0QOjw8FEKcnJwghMqyzPOcMRaNj/I8v3379ksvvRTX0ccPHyijb96+9VNf/ukIBRTF4E/++BtFUbx0+9ZoNIrkr4cPPj4/mfzsV3+6LMuLsyMtW6txcObWjevPnnx8//79O6+9fnh485133nnvRx/cufPGl7/8ZYx8WaRpwiBYCNYY23f15PLsvFtiRJ3LXUgePj1+dvrspe7G3sH48f1FCGE0Gl27dq0oipg4E8K9swQjQmic+6nq5fHx8WQyoa+9GkKYTCYffPDBbDaLypwXJ3c+8+ZtCPj4+LRp5Y1br4639pwNnCeL89OPPvro6OgIAKy1i8UCIbS1tfXLf+9X4/j6xvUgLu+Lk+cR9BwOh2madl13enp6cXFx11RbW1tONrargFJaGQhrNIkCAGAfAgB2q2YZBATIkRA+wfuM2zvjhQpIKVgbJ26sfmKtBJvIEic8nVOEEAYMEEEraeTgvXeYAcRZZAAA4xA4D+ALXkQU2VodQhQYCgiBQ4hgxAlxFnywndIEAgLonQAUAGhkIIZgAHkAyFac+shX9MiijfZ+vEQIAYJf2/xAwXXwaA29rbAnANDYSNf31vnAHWBrAiZAGMVWWaMwhGQ4ogjytNCy++/+9f+3mk92tscIvLV2Z+9AW58NRsaYjCqMMQC11nZyHkKYLyVjbDnrCSF11cREBgCSJNkab0uWnJ6eckrAeS+lwei16wfjrWHAbj6ruSieH18Q7GU1uXlt9PWvfn6wszOfLz/++PHdj+61rXI2tG03HA73Dq5/8Ytf/OEP3zk7O7t27VrTNNbaoihwV/3qr/6Cac9G2y//b/6X/+ziaKGt+Y3f+fW/96v/6NGjH54d351NPv9f/B/+19eu7Xtrm+bSyVokBBJy+PorHXKVavYPtp88eWJd+JVf+ZWqqp4+eXR8fPz6nVcZo7L33pDZcjm5mC6X8xs3dpTqd/cSLvjJ+ZPJ/GS+nDZtk5d532tjzCuvfHa2XATcF0X5P/yPv9H3Pef8W+/84bfe+cN333+XM6GlsdZ/6zvm+PjO5z730qMHD3dHW+dp7kyQRne9cdNLLujw2vDxs4cPH93b2ku6vpXOcbB/8f1veo9ZyPZ3RrJd4mA++NF7n/nMZ06PzsEpkbHp4vLo9Nne3l60fiMcOedG5SBY57Sp5os7r7x68vyorWohEmtN1/fXb9w6Pb+U2llPABHK0jRHh7fuXFweYYEsMklReJR87gs/++T++1kyZpQ3jTTal2U6Hm9rrUmyd3zxtqdHb/7M1/KtrVnXesb3b73avv/Nj569n6bpS5+7/ZWvfDUV2YNHDy7v/+jPvvNHhLCt8R7B/OTkpKrnk+NsOCy7ji0WS4zpr/69f3T4xS9/8NG9p0+OhsPh62+8Op/Pz88vBoMySenZ+fNHjz+6e+/9e4e3dnb2ptMpwfT84mIymaRpXpTzrv/o+OTZ9cOdNE2e3r87/MLPgy3+9Ntvl9vzhw8f1nUthHDOYYDxaFzm3dn939PKGBMQ0POz6WSy4ExobS8nRy+99NJoNFJKxex7OByenJxMp08GgwF2ikB9ff+Qok16s55/Q1em4DY50Sb6XC2LrqYnm+9cBYCu/nwIwQMBj8HGwd+YH4H34D+pj7v5pHNqnUYFQAFjhBFZ0zDBA0BAxgEB7MADeL3yM/KA1jYmAQBAa4tecENR9ClCCDn3AnffDGGEEMJ6KDXWd+uqC3POCdHxigIghEOUS1TKJ6JMBFHapSJrWv39v/z+e+9/VJY5gG+aKhLkMGbO2a5rAIVIoYwwM8a47/RCdQDe2BXtjXOepilCIFU7GAxCCPVy4Z0VQgyHQ+/9vbsf96ZGwLZ3rj1/fpKljAWlVLq/v9808u0fvHvv3sez2YJRwRhfLuqL80kndVmWy+VyPp9HIi/nvKqqw2FurL5989qTJ0/G4/G/+Bf/4v/93/9/Hj95/Fu/9Zv/i1/7n+/u7t64eXjj+uFsNvneW28RhLa3t5fL5XQ63d3dFULEUL5cLkWSnZ2daa3zPB8Oh1VVEUIYY1zQt37w0WQyAWQPD6+/8ZlXz89Pf/d3f3faTDjnk8t5nufWhGrZpmm6Nd6WjlJC66qrlm0kEBLMnXMIcNM0nIqYmIzGw9dff+3G9cPf+K3/bjgcKt2Px6Od3W2t5dbWyBr/wx/+cLGYTCYTbVQccHvy+Gh399o/+Uf/aZTKjaZsi8Xi6Ojo6OhICDKbXbzzzlvb29u3b99mjAHYrqvfe//tGzf333zzS3nBGYfX33h5b3+8mJ1Z5DCivV6mBQVizy6fbY13MMaz5dn2XmlCXnfzgI22qmk1EN3IRlrJgBaDwc7+Tts255Pz7b1tY9v9g61yIB48/Oj50aPRODO2+4vvffMHP3xrvpw8eVYPhsOXXrm9s7P38PHD58fPtdZaybbRnCV93zvnm7pzzswWXd/3GJGP7v1gOju+d+9+VTVb451l+7iu28lkkiRJmnLrOir0q3f2Z+dLQtDp6SkAYEyvXdunlPZ9O52dTKZnATVbW6Ptrf3xVrY9vgEAf/qdf50XLC+2Ijqpta7qydn5s60iYUx4a2RvpKmMb6zq+15lpUgLvrU7PDo6Or04StO0103AdjweOeedN2WZ37x5k5IXOkarVnr080EIUEAAARD6FG9xE3HslSHhqxopf937bfUJIhAFMtBV5eng0Cdi0PoyQHq1jmsBYyAUEYRwQCFg55EPwTuEYZWooIDUyu8xYAJoLYmNEHJxtj4A8gHjsOq3rzmHn3ppIQQTfAjBuzjIBuspoaCbTkljrYXAopdCJHwHzLQDMAGcGQzo0+PjP/2zP392fF5wAABjjPMWUJCqb5pmsVgQTBljjDEEWEkd4ywCTJhnjIVApZRKt8b2q1GMQJJEaMlkr7O0uHF4k1NS10+ny7Od7WuMMak6AFoKSBJxcHDw//jXv3l8dKqUbhs5n50nSeI9dF33lZ/56rvvvvvhhx/Go6Jt2zfeeONzn/tcic13v/vdV1/6xw8e3v9v/+//r6/97V/+yle+Mm+nX/1bX/nK3/pymqbHx8fPnz7b29vb3t49Ojoy61T85ZdfnkwmR0dHQojDw8Nl1UQ0Pe7wdA17/c7v/M69ex9FWnDTVPFFDYeDxyfPGWNae87DxcVsOp0NBgNrIRtQB8QaZ63VGhBA25gQQp6XWtvInHr48OF8ujDGjAYjQhBjmXV6uay9t4BCnud5jqbT6YMH987OjxAGzjkE9Pz5Sduq3/2D34tR8tHTx9PpdDgcvvfee6enp/mALBaLk9PnSZKcnD4fDAZPnjyZz+ecsuvXr1/Mnl/Mno/HY+fcs5OPF4sFpmg4HD94dG82WzTt9PziySuvvCaE4Cwbjund++e/+3u/KYS4fu3m9vZukhVffPPznWx6VW/vjYrh54+Ons/m8+9897sip42co05+87uPnj17lmcD+8S8+8Hbj588Qgj1svn4wUff+vM/S0T2zjvvnJ2dKWXms2XT9GlSDodDhJCU0nkDSDMevNen5w8up0/m8zmltOqa+d2H1ngpdZIkXGBMXF5wJpDzum4WTbsAgCIfIMylaqXqR2PBRWjaeddPLy5PnXNZuv382ZmDNklFhOSMgclkuVhedF33/Pj+9evXuUi4YEk2Go65tb5pmpPjc+vaLCc7u+V0ql9//XbTNJS5y4tOO22DA3BNX1GKX2Q9HgJCKzd2FAChyP1B4ZMPtOmdr+Ghzcf4ifOfSJpeVHBuMzXmrv6Xwz/eu3bVF0MeY4QDJggIeBygky/IRDjAWhIcrLVR9IOQVccdE0AIWMJWscYHcC8qyg3m8qmPCvy6FouZkYOAAULdt95hjEnwyHnngg/gAvKMCeeNti6h5PTi9Ft/+sd3P76/s7NtmzMhhEh437u+75R2ztskxYyDEJhzEsLKqCdhjDFmjA1BQwhJihiP/KBACLGuw4SXg7Sp58agre2xkerWrVvnP3zGBfXeCcG0VgbD7t522zZ//s3vFUXxyiuvDMptaz6eTCaEkJ2dnYg9tW2rlDo8PPzqV796cHBQ1/W/+8Pf/q/+q//MGDWdTtq2/YM/+P1f+0/+yX/z3/yfnfTOGtn54Pz9Bx+3XZ9lWd11ezeu37hxA2N869at9957b29vbzweX15eDkdbb775pjHme9/7XgRHpZRHR0ePHz8G8FJ1xujZfPKd7/z506dPLifnWjlnwWg/my6jYr/gWd/puuvLsuScO+v7znatkb0jhGQpstZ7CsvlItgwubgE8K+/dgcAZvPJzZs35/P5YrE4ONgblOPPffaLSqKPP/6oLEul5enp6Wg4zvMcY/zw8X1CyMsvv3x5edn3fVEUs8Wl1O3pw5NoTNT1VddXjLHo3jHeKi4/eP7x4/c456PRqKqqNE0ppda7vb29y4vp+fm5UjpJstu3bw8H4+fPnyOETs+OR+cDxtjzkydZWmCMdUsQQrdu3crzvKoWH93/qGkarTVJtfdmd298cXH29OnTwWCUpQMAAjgsqyUXQhn1B3/4+ysBGSCCpwg1Td0p6ZIkQSj0sqcKU0Exotp2Z2cnjLHBoCwH+XQ6JYRoY7QxxvakR4SCdTxNWVUvMaIYByFSQH46O/cOhsOhSJLx1kAkCGPknD+/fCL7h0fPz27e3ullRSkdDoeME+clwnb/YOvx87seySzL8rxM01zklgdIikzqgnDX9LPxTq5dk+S41w6IHo6LRDHKUV2355NTiq/MegRAEPALIwAUANCmUvvrj82m3USlTVrx1zc2ADhAG4LT1Z73Rs7lr6dU8WP8mzG98t53Ol7z6soQQiuJl8hrJgh7wBgRAsgHhICvY9zmYsIa//5UabmKZQh7772LEFikj3sIGCNOOfWeKuWs0Q4sxh5hJPWcM+qcDEDu33vv+299E0E7HOzibBDnxZ3vlDaYwHBUpGlKmOr7vu8rCCErohhr8F4Shi4uLpVS29vb1w52EUJR4j6jZdu2o3IwmwLCTghyfnqxvTPe3dseDktj1e7u7nx2maXkc5/73Nn5SdfJvldZVhweHr7++uvOmel0mmVJRMFef/313d3dw8PD0Wj0+PHjt956K0mS4bDc29v7lV/5lbOT5eWs/Tv/0dd3d3cvj08nZ5fT+eLg+o2f+erPnpydf3D/fiKyL37xi6+88gpj7NmzZ3me/9zP/dzFxcXDhw+run348KEx5ujo6Pz8POofzedzrWWWZVmeFcV2L9sf/OCttqsRQotFmyRJWQ7SNG2aJgb9um6VaxAiZUm8B8YEAHgPhGAlNWMcY+o9XDvYy5I0z9Od3a1nx4/bti3LcjgcPnt6JHhOsGgbdXY2oZTeunVrsZxPp1PO+d7u9cPD213bn56eEoKqanF2dhYHEinFTVMNh0NKBaXUe9v3mhBEKY4fk4RTSut6eXZ2ihAaj8eeBEQRS1kr2/l8ORqNnh493dvrzybHUsqmaVvZGmNmy8VoNFRKnTyd5XneyOqVV14ZDAaBhIvpJIRQXZwyhmkCNjhEcdM3ndRZVgKEquk4t8b7xbwSIt3Z2fFe58UgSVLGhPfQNJ1zppe1ELTEW4yx4E3VNISYshgj4NWyH41Gfaeqqm+bzjmXF8n+wXaWjK2dchbbi7ZpmrquGRXRLQ5QECIvyzIOymnbuFBNp2hDZ8uyDCFUFMX29jaA1F41s1o0VZIkSukkSfI8T8uk0+3Hj+/fuXOnkfVHH3+IMZZG7u9uGePyIkmzpO/kxlp6JUkNKKBImYYQICCEA4S/7iG7xnc3DCCAK1Im0TstQPjURxtlVGP/DL3Y9i9si9bSCPHvs/VzYbye3AKEAKJ3sPUeAPmAogAaAkKBIgjIIeQDJgH51dQXcXrDJ8AYI7SaUdbmhWb+1VensAse+TgP6uMVYYCAMIFA4pw9ADBGMMEB+aeP3kUI+q4aZMnF+ePxwIntsu+O8oQbF6y1hKliEAljDpGecseDcyH6ICvkGGOMc+odK0rBBUozinBkGfTOu4CI801WDF965RrBrBiw6eyMC/S5z32GkuT8Yl6Wheyr0Th7+eXbjx98kOd5mqYhuMvL853drS9+6XNnZ2dc0PPz86qqbt269corryyXy+985zsXFxf7+/tvvvbTBwcHd+99+Ojhk6//ws/v7N9a9vX3vvcX10bb9XJeL5cH168Lkc2r5fHJ2fXrN37wgx+8++67zrknT56cnJycnp5Op9Pnz5/3Us/n86hYRil9/vx5nue3bt0qiuz50dPBoByPh8+eL733h4eH3luHF1rrNBXj8dA5M5/PEQpCMAIZACilYl8/y7LYY6bYO2cpoTHJSlLetNXl5XnXNSGEBw8e7O9d63tVVU1RjJ49O3n33XfTlCHslFLD4ZAQ0nWd1noyv7iYngHxy2Y+W06898PhMIQwGm0RQtq2z7IMY+w9cC68bzuphBAB4dliaYxJsrzv+4ePnxSDgVZ+PN7uOlnXDUasWrZ9Z7a2R8tlRUkaAuq7ZduoEBYXF+dZOvbYfXj/PY/cP/gH/7PDWzff+uHb89mSpK4c5MtWUkrz4VhKraRXVYe9Gw23jXGXF1OtLQIxuVwopbd3Q9M0IYTgUdt01ilMAqU8dl0BwLsgpVzMW++IlujyvLLWCzawnLdt2zVhctFSnGPEhUiFSC4vn8teY0wxpnXdn19MA7jxeHjj5jVCgvOGUlKUaSLKaMD7/NlZhNIYY22j9/euee+9a2LfTWsFELx3k4mK5KBIyzo5ORmPx5zzy9kZpVwZFZB1YFYxKIQACKxHsPIniereqy+vos6fiEHrmLGqoeBFAhNCrOU+FYlWKj1oIzobP5LN39wg3AEhRG2ckAJCECZoI28QCLEBwCPjIIqqeoQDBAIsROvLSAlapXKBeb8JQBivuNEIIb32CfjUC7TBhwDeB+9WY7eRCYQ9eK+tQyEAY8wjU1Xz+XL23o/+VPYtIzAsM+T1wT41ujNycjExCK3GbrOEOeekbGUjU51GWr21Nno6p2mapqmUfTlICMmttfPFRcStAcCqimBmbH39cJvzhFBPmQekr19/aTpZ9n0vpVZKDQZ7ScKXy6UxajgsRcKm04uqmd64cf364Q7CMB7v7+7uZll27969u3fvRgr19vb2zu6W0v3J80dn52e7O7eShD87Wx6fPNeL5d7ewSt3XpMmfPNbf/7o2bG07vT8Qhm/WCyMMVFI5OOPP0YI7e/vd72KJ2ScgDs+PhZC7OzsfOnNz80XE2PU86OnUvZ7+zvOmbpe3r598/T0tG3rvm/jxQyH5XA4rPsFAFhr67oxRlmrjTFpmpZZ3vXd9YODwWDQdZ2SnZSdYPT69eve+75X0+l0sVi0jYRwP8uKiHn1sk5SwTmfzxZNLT/++HExzhFCnerSIh1uDeu67lRnrS1EqpVZLJZGrww1t7e3IWDGC6WNNt1kMnfOHR4eIhyqWjnoAXHnK8oyIUzbWYzx5WSJKWob03d2Pl8qpfb2aACstAO0TCDDmJ5fnn3w0QcnZ8eE0jTPpOuVgtPT+XBYOkebpgueYIy91uUg06bXBkJgxoZe9tZaTBfVsgkBrfQzIaRpKkSCSC+1ss5nOQtgZ7OZMU6ItK6XhLDBYFgUw66VXd+0TX1yckERWBMGA2p0oDThTFBKrfHj0UFVLYzGWqKoPzoaF3meJmy8WCyU7KW01spI/qgr7UOCEPIeEswQxiJNCSFV0xiLpFJFUVxOJhhjpfV0NuOc1/VlNPJ2zmtl6V8LL58INOHqxMPVka5P6hL92N+Fv1amuejbgVeRa/MPX9HWXtdfCAAwCjii0RgoIZisHbUpJy5YF4L34Lz1GEIMmASAAHgPDgIOwcepEkRjooVCQDGLQWtNtfik69pzk8eheMhcISQEBIQwEoJfiYQQUrX106dPHzy69/G9HxijXnvpVtdUXVshp43ud7eHk/kMY4ywiBovCHtMLGXeO6KkiToMjGYYY2v8UnXLajIYDBhjSimMcfR3btsWE1cOsrafj4al81DX8+Gw2NkZl2U+m1YAIKUUCbtx48b29vbe3t6X3vxC13V7e7s3b12fTM4wCTdvXf/MZ16vKvzo0aOzs7O6rg8PDymlsV0ahzmL9PXPfvbzJ0fz7373u/s3D1966SW3aF9++fayar/5p3/63b/6wY2XXn3tpVcwYdevXWua5tGjR0qpOAW6s7Njre2PT8fjcZ7n8a5FsuV8Pv/www+llDs7Wx9+9EzKFpCfTC7G42HXt5ggxmkIYTAsI4b99NmTazd246iKUr333jkD4NNUWGudDbdu3R5vDS/PTvuuoZRSRqLf9OHh4ZPHzxgTRUE//vjhzZu3t7bLk5NJktLBsJzNZstFxVm2WDQO2/39/cj5jJ4Cbdtaa3WrMMZaW2t95FXt7R1sb+/2xs6mc865s2Q2W1pzijEWvOxaJbjVqsrzIsv8+dlllhV11QtBOU8JIUp6hDjGXGunpNNOTRfznZ29s8uz3/2D3+/anhDmEaTJ0Bg1bStKeQhhOqmGg+3tvf3Z5fHz50dKGoRIURR5XkJAfd9T6jHGnFOMmFLGeRvJq4MdaJrGWL+1f5gX4vRkShna3dkh1LdtL1XrHcIEp6kwtgPwlCZKWQBcFiMAXFWV1h1CiHNeV7LrdJ71zktCTVFkALhayrPTWQhhONyy1rZta42mlHatIoRggqwFxlBZjIVgRjsjQlVVAPDo0aPd3V1CSBxXXBsyB8YopRT98Q8eblCSDlJYsxOvojbuJ/gN/aTHp0qbzcNDD1dGPV48fgLiJMKqp07WLsZ4nQuFqNqxpg/Fq1VY/PVnDyHkaDWIv/n1FdOcvZitv4pbkfWoRxR4jkeiMQZoNplMBkWuTV/k6PnRBz96/7uPn9zNbT+fzymL3ELAGAkhrh8eLBf1fL4QIq2WTdPINMmcCxjTpu7bto3bLFJXYwcaIVJViyiFlmaCcy5lxxhLCxWN2JMk8d43TUMI6ft+PEjH5VZX22ApGPyLv/DLr7706gfvv//RoychhDzPw1plMUmSGzduKNVfTs6n06n3bjgsGWPOm6Io/vbnXy6KgdH25OTMGPfhB/eLovzKV75Sc/3gwYPf/M3fvPnS7euHN49Oju/cuTMcDncGN46Oju7evRsCStOcUlrkA++9Naiua2ttlmWU0ji9nSQJzljXdZxzyvDbb/9gOruMkhrSdHGGqyzLLMuqqppOpyGEw70CE9/3zcuv3K7r+uGDx9ev37QG8jGLIcNau7+/H4fd0jTlKAkh7O7uPnv2LMuyJEmWy+VoNEpEcXJy4px77bXXBoPBvXv3zs/Pt7e3kxTF5o7WOprZxpLBKGatjWSWSIGJRVkxLs7PL6uqTkRGKW8b2XUSAIajgnPatrUP1jmtjcyyJAR3/eYNxljTdMdH532vinzImJBSMrxSZWFMBA9Srjx1lfTDUQZI5QXP8iR4oqQ/Pbm4duOmc+7s7IRzvrU1BuSjXigX6FNCgHHdDgajuCPCFUUdhFCaCsaYlHIymcQhlUh55YRiTJ3FbSOrpVTSY8Q5TwNexhxcCFaWeV5kEQPaPxgsl8uYuSul8jyPrJEkpV3XpWkaN1f84dFoNL2U8/m8rmuEUJ7nWZZF4cOsWI3XRg4tDX6F5kT4Z/VJQAA4hJV6/H9QAPobHgjIX48/MVD82J/3gBEggNh/R8FHNQ2glKyvEUFAmK5mxtgVg8hPZGrrWixeBCAI0XRxbUwZ1qa+64/xPqBoQhsCRB6T1KYcjJKEPr374PT43vPnHyxmT6VaiNit1E5KOR4Pt7e3+7579vRoOBwBQNu2zgUhRJR9CSFEvcRwhfkNq+k24JxjjLTWi0Ufk77BoKiWHQQqhCBYSKkW8yYGx9m0piQt8kHG85Tne3tbFxcXf/XWO9vXrv3lX/5l0zR37tz5whe+wBg7Ozt7//0PAygAuLy8mM1mlGLGo2q1+dLLe5jxrutny0Wely+99hJnSSv7RuJv/un3m9Yp6dq23touqubck/bybKq15ilmNGWMaW2bru57tbtzPQveOccY894bZ5VSbd81512AqBOQAPJFUVCKy7KsuktjjJRt3SiEB1yg3b2BEGKcp5RB0/BoJxvjb7WsgYmiKDBGfaerZWu09x5ZE7RuNh1bAJjNZtbai4sLJU8jCevs7CyqNUUD+yRFQoiiKDYTeQCQZdm07QghjMVvY++d1kprXcvOGIMRreu2bSdKas6TohiUZT6bzZRS5SC3Fg1H5Xg8nM/nShmMqeDpeDzGuI4K4pRSLRXGmFLurG/btm17hEiSJMZ2TWMBOR+s94gx5n1wXkci8toF0zFOxuMxpazrJGOMEOZcYIzkOY/jh8tFFWv/yLO31rayU0ptbY9jC1iINMJG8TKC9YJnndVV1Wjti2JgrZ9Oz7Z20jzPOechOGtNVVVRt9O5MBptdV13cnIipc7zEgAbo7nA3vvothDnHOu6vry8NIrHF47WQumMsaIo6mYyGo1kL51VeT6g7sr2W891xSbUJ0hB/0Gx5if9fBwn+bG1249/YByRmNV5vl5k1n8yf0ErMXG+DjToyicQHRk/pbEUZaTdi6vd8AcAwEQBRgjB+TjFYq1zPkjn81Qs6+rB/Q/vf/j9tjki0ILvG54pZUIIxug+UUqZpmkXi4XWrmmaxbxK07LIS2NclH2x1lvro7NjDKXWemOcEJRzlmbCuURr6Zyx1mKCjIa2ld6jJPEYM85TIUSWZW1VK+kE7RX242Ex2hl27cQa/+HdewHhV++8fnD9+uV0VlWVMWZnZ8e6viiKpEnGeEwpDuCyLFNKTtoG0qQ3ctJWhqLdvX2EyPHl2Tf//EOpyBc+/9NNP/vo/ofDUUITNOgy1yVFUeSFYIw660E7pU3f96enp5tBmUj1Xs0PixBC8MEa2xmjMPaE4iRlohzUde1C51xvHGaMUY4wNXWtRcKklE1Tcc5v3rzJWNI2fd85zgDAV0vp7DLGDtn7tprFULK9vZ1lWV3XGOPFYpEmZVz6EcEtimJ3d3c6nVLmvQ/WuiRJsyw3xiKEyrJMRAkAVVWF4IztrbM+4K5vB8l1nmUSy7qetk0XWzSROQHgrdPeJ0UxEIJhTLOsuJxO09QkScJ5kmdBax0PM+8BIeSst9YrZbS2BCNLPONgnbHGWRNk77e2BknK0gxPp9MN9Ku10sYzxqTEUrVFUcRBMIRQNLYEACk1AGBskiQOnRCMKUI2ctAopUIkMTZZayEAxXnwRMnOWpukyfbOSCndtIuYRI9GI+fMcjnXRsXpvOl0NhwOrXWM8fE4KYrSOa+UTlLKmGBMEELiR+dCVVXeirgY4rRjPJyEEMb4tpXGGISoc0D1FT6hXX2+SoWuUof//40af+NjnV/EcIDWsDVcYRd94uHWmPcaOlp/372IKVc/crwWUkIAV7D0tXT3p0kDxpIrz/7iGqL1vPfBg49Dtys9IgQYo7qZzeen1fyME1WmxFvsEEFAuaCEMCXd5HLmnBuNtjCiiSi8b4IH59B0MvM+IESCR96Bx/E1BghOKYOA+KCU6gNkhCAuCCFcqZ5SnOc7WmslzWy6IIQ4571TWtlMFF3fBlA9BsFp2y6N1ePt7Q75a4fXb926NZ/PHz16BABlWUqtgLhGVotmkecp52w2qxEDD/47P3jr9u3bRVFIZG23dEvStu2DBw/Op/PXX3+l7pazxcyD65VhCC+en+c8daAYTa2daQnWBmeRlKqpztdB38dDjzGGMBIJs1ZTyvMia9q5tV7r7uJC0gQ55yhJGEUQiOxXc0YHW0NCOCbQtjVjo63tUfA4SbnAKSFcKYUQNcY7F6y1CNl40pZlGbtC0WUkbpvJZKK1TpIkirclSSKEIAS1bTubVl2rKaXOIgBoaplmjBCiNIlTe2mWCiFEQpQJ3ruuk1JKxlie5wBQ1/PzCyOEUEpOJvrWrVvz+XLxeLa9vT2f112nBU9i+MjzXGvb9z0lwjmnlXIuIGCCRzVxNx4l1oClqO+VMXIwKJKEb+8Me9kZY5IkLcuyaequb6SUjBFrnFYm+mU579qm08wghIpiEF+mUibLsizL0jRP09zaGJvwmmiC4/VknHVdvVwunQuUUkCeC7K7tzWdTuO98t4aY6KWHkIoBDu5nEVhmZ3tHYTQYrHQytZ1HbWTYqmFEIoKJ1arCDh47+PcbJSBFzyfTZdpmpJcLOYNdR5tEh0T/NUtukkQfrzT2n/4w79Q4XgBbwPAGmr+a4/19z8VO9zKumMdcDawkl7Fpg30E7+0xF19US/+jv/xsQ85HMWJotHSemoMcwYAqqtn3rbWtgKMoCmhBS332rb23sc5DEqTNCWDwcAYJ4Rr6p7SJHjU99qalRuqXyscXX3ePBcIOUIBY8QYybJkMMjKQf70yXPnnFJqMplQSgeDQZQZ8r6zrseUsoS3ffvs+PFyahDzn//8Z7quWyym9+/fOz09femll9KU1/WitVOE0Mn58fb29mBYaC97jbSWs3k/Xc6j32kIfjAYWGvn1Xz/MFNuNl2c9bJN8gyhzBvMWNGpScBEcBejD0Zce2PB8oxthPojkYQxSgixQWvTZ/loMMgWSw7ArWXL5fL8eRvrI0qpls7aYAwY47uky/Mky5K+b6uqwpgymg4GAyBZXMp5nsfEp+s6Qsjhwa5S6vr165upbillLKji9URV6ajrEkKIyZkxTusmhgmEkDHSOhlFFGOpG5VSnHOX0ypJEsbIaDQghJRlCeDbNqnqKcYrmwYpZdu2Z2eXSllEGMHce+g6ybkvyxyhoFRPoQwBWQPRWia6ZTrnvEdZVlCSzufLvm8j1sk5v3ZteHJyEu9kmqY+WEppUeTOpQghjAljQmvddT1CcaIlgaC9Q957TRyjHsXY4VeevW0Ti0FqDbSNcqzWWiulpJRxU0QULwaUvu8xhng34o/FzkPXaUJcmipKqdbeWtDKGu6c7SO8hTHWyspeI1hNX8ctGZswnHNrPUIEAEeXHaqv2BZHn6NPbXj48VZlf9Pjb6i2rqZUm8/DT/jx4K4kMJ+gXK+A7Bda/oAggLEvZj7iQEb80q/5R2vcZ2WtHeDFeP3Va95ExKs1KULI9ouL45P33v3eYnZKsaMUW+NtAAYkeNK27WJRZ1myvZU556bTueCJlNp7rKSxVsNKPYoQwjCmMdPEGCFEGBNCpG23sFaLpACwSmvnFUIBYTfeGkauY8Q1nDc+YEYZExQ0lr2mmNCuny3nSVLeuLk7a/vp4hwAbJDG98q2mI2TnP7wnQd5ns6bhQ4K+H42zIVgulJb+U7btpPJc84ZwkHpPlLPF+2xnpnr129N5pPHT57duPWqNYExgcB5p9koY5QLjjGmCDvKSCLKyPcLIfR933WdMa0HXAxy66BpF4BM21bDUVmURZqxunEIoRAgopzrcT68XM63dwZbW0NC4/ScowzfvHl478GxlDIym+NKiAlXzIuj8iQARB6Q9z6SA/I8jzsQANq2bZomETmllLPUGGO0C95RSjEmRluCvdaOEFgZyRSMYOH9PE3LqEOilEQoiCTZ2SsnE9p13dbWKFqfDIcjo33btoN8UBYlQqiqF0opSrG11lhtjY6zitb4VRgKKISwXMhkf5DnqVI9oZ5S3DRdCI6yPM51hxCyLAPk4yh8hBSdcxE4jxoaxpi+q+LLFEIwJkJAfa+itB5jLP5kTA8xJpQySqEsh3meRp533ymMbdu2+wc7sQ/DOc3zPEdZjEGz6TzPc85E27bz2WI8HjPK26bb3duKwtveByGiAwXrewWBxeM2RnOtdXz2tm23tkbOOa1lUWTU+ReI7IauHLcovMBo/6fJgzZcx0/9wZ9kPxnQlTh1BTPGeB0VQ/zWpve/0gz5ZOkGyLv1k6Krr27Ti38BWK/+ToTkUQjgPHgfOfLo+cfvP3r00TvvfCdhFpPQa9u2PQrQGNy2rbVG9hoAJpOZ1to5s79/bT5fdq2UUgVPGBMIOe9gNBoDoNiCCcFiTBDChNAkSbynw2FJKIppcNe1dV2laQqA8jzZ3h5lmYhndZZlLgRMxOSiMsrDgGpltoeCMf3w7PL4/GmWZdmAXyO7e9e3MPfz2eVoa5gknHKCUKCc8IQFCDzhYlXDGyE4JpCmYrmcG6u9t5ggqbW2xnvvbJDKnF/Mtka062QIHaEIwBOCfHBFUUhT2UADTimlNnRNPzPGMMa2xbgsi4uLs7qZGWMSRZ1TWZZdu74Tm7XGeEwo5xxj3DR2azSOeAQXxBiDEZNSEszm8wmlNE78dV2HMXZOe4/6vg8hnJ6eSinzPI9fWmspFaPRKM6vbRpGlFJjXMTvYkvbey+ESNM0BOss2ohYIoTyjBR5maRTH4y1inHivJeqRYZzkY3HQyGY91BXrXM+S4vBYBShYqUsxoCAUBqdfm0IQUuLVl4UgRBGCY9FiuwlBISwR0QXJU9SXi0b78HDMsaUqqqKIg8hdF0H4ENAfmXDi7wPhLCVc5+OTTdGMPMOlDOx++GD3SSnQkCcucuyIs8gTZK8yDDG1bKzJhjjgmcRC2eMWcu854zTmIj1ndbaxrQkMhgwps6FjT1JTLI2Ddw4YROl0znnsZcnpcQYGGOUptbaJBF0g/vAGqn9sWHif5LHJtdAnxRmDD/Be9eFTciAqzHRWv/JX199wqiAK8HnxQ+sgtyn0y0cNrkSuooKIcAAOM6phOCjpj1C+OMP3z0/f97Xi9HBYLmQFxcXVvvhcNzIqZRdJNpI1R0fn3pv9/f3u05Op1Nng9YuTfLd3T0I2Fo7Ho9iHRF9vuL5770fj4dN0zhvwBFCMOesbYNUHSDbtK4oCucNJt7Yvm5kLwXhgiDa95ITEQKWWk2Xk7Pjo7YzvWwoQ5zzNOPlIHPOzeaX4/FQKZUkPK7I+XymtR4MCoIZS9l06heLBSY+TffzIqO0UNJm5eDxo+dZll2/WVxcnO3sHry2+4rqaqV6a1Dbdsb2IsFFkQ2H+b17DxFCEYlQSvWywhgzzhaLWZ7nAVwILmoJnF9cDIfDJB067wmFNBOEZLF3G0Baa6fTKYANYBlj1piTkwuMaABXlINostbLljLMBXXOjcfjiIjHEBOtRAghiUh8FMnt+0jwDSEMBoPtnb1YtaErdpiEEO8DxkSIRAihlOq6rqpqa9329rhpq6pW4/FwMEwzS3ywjKPFvCrLYdN00+mUsUT2uqqawWA0mdZt22IMaZqUg5xScN5u8hetLSFsMMiLfKCUrqoqIEcpt1YbI7O8TBJRVz1G2FhHKdVanp+fd13BBe26DqEQjeYivySaX8UIOyjKiDcbY7pOxtF2a21MxGIgCAwZ7RAnicgwbru+piQdjQYEi/OzmVZe8AKhZjO/4pwL2se+2Msvv3p2dlZVVQhBa9u2PaUUALdt9J4KANB1PcZqOBwmSRq8idSZeJ1d18V4VA5SKfvReJ8Q0jQN+n/+2T0ACMgDALZJuELLe9E+xwoCxphhIAQIBhSCC8EZ/MIfFSCgNdWQoExKmaapW7sdSSmLovBBX41Bm5AU/I/3uU+o0Fp67xkjmIC1FiAQQni0Z8aYEZRnyfTyMs9zpVRPGaW86zrGOARsjOE8kVJinn6ylFs9KAkbReeIa8YvjSAYCHaBeLMzzBcXR2+/9R3V12fHf/no0SOl9Pb2tjHu4nwCAKPRVnzjCUEIh8iqAAh1XecFi41VSmme59HDB2Nsra+qxlpbV+3l5WQwGOzu7mutt3ey2D4QCU8SHoKTUkopGSeMsSzLtNbT6ZRSurW1JYTQpp1OFk2tESIHB3ujcWZdPxxld9+rBsPUBxWNyTDiRmMIxMJ5nsXWT621TZKEs8R7v7M1cM4tFtVkMgOA0XCL80RrnQ9yQshyudxYMJZlGULIsiRWW5HlNB6Py7IkhEwmE7yG8K7aCiQpz7OyqjolbVEUy2rWNIuDa3sIy9g7z7KCEGaNBwBKKUY6ztZH/s5G143ToZQyy4q2bWfTRQhIa00ITUQRiTxxVUSAA2M8SEZ1XUcHgbgOo1hKMVjBPWHNgIsxy+jVcUgIYjxqj7oQQpKyGN2i0EoUV6GUdvISIdI2UitPSVLX3XQy19oGVOzsbiEEmIBSvXWqKDJrbd3MJxc1BL63P9q/no+3MmvQ5KJlnDAqJpPF5cWsKLL9gz1KQZteG+6coxQDBKUUII8Q6vtWiLQoCoKZMQYhnCSZ975tW4ZEDEbxLYg0wrZtCV8ZYWZZtm66RynOHgGx1pflUCt3dnZhtDPGYoycc3mRZlkG4CnFhJCubyEQQljbyLZRlFKEHSCXZclgmEc+bV3Xzrmo92aM4SJkWVZV9dHRUZrkhLCqqvb2DrI0j7LFAH4wKOjK3hjRzRa9+t6sECZHQgjIWIyBYkwAnHfeuj6e15hA1F32Ph7pwVljzEaSLmJ+hBBnVqEtXJEZ+hvAo836wBhv3M0AoDMtp5RhagMyDgXiMAsUwniQYoyFSClhzrmmUQgpQozHKy/DTaK3PvoEIEQoxRj7EPya3MWRUH0nOEsSvpxffvzg/UdPPghOPrz/QZZlg+GWVkZrtbe/5T1Mp1OMOOc0y3JAvu/bGPXLstw/GEfh57B2NYmwHMY07oE09VGaL4qfMgYIoTWSojjn0XJvwIq+7+M0UJqmq6aDtQcHu0Z7JedKOaWU1hSQ9x6kanHjKMWAuFbgrNbaegdJTkLAhBBKecT1A7gANoSglDJGZVmS52WWFl3X1fVyXi0jNyfLihCQtZ4QJoRAyOG1/1JkGCKE6rqmJFdKRXgiYplrFnLlLKqWrVImppl5XiZJkheZMcYYJ6XuuoVWNsvy8Xg8KEcRgICA0ySP9wpjbPSqzxDDQaS8R7xuQ6mNMSJSAWPGFPs1MV9I0zRJkmU12cDVYWXEokMInKcheIwxITQybpqm6rpuf38PISR7PZ8t40uLmoHlKPXeF0VBBoLRNM+74NFiUbW9V0qttYU1IYjzJM9ZWeYUL7vWhICUdEYDBBI5q2lKgscIEaXcclElKSM0dN1KZK4ocsaYNhKtTL0RpRRj5Dw466RsjbF931eyigEoZjE+eEJRmommb8qyHI1G0ZTYeYMxFglbzCZxRizESSQHWhutLOMEIBjtNNWEoBjOnPV93xPClLTOeYQQCo7x1YRaFOSM4SIu+Ij0Leb1cDi8dZNfXk6dC4wmJ8en165dCxA7ZdY5Q8FBQBgFBBjFrYI+KW6PMWaksNY6b72HEKwDFAIEDyLJNnWEDdZHjWdEMLYx0MbmRVyvUsq1UuKn1T5+Ut23UTtEV0bJEEJpnnHBGKHBmkCBpwnlBDCv2ymlLISAMPcBCLUAnjLXOenX9kbrAxDFBYLWdNJ4gMT32GpLAgSjp/PpydHd+/feOj+7DyBjXZMkYmGlsX2aiZTzrqeycwBUG6mU6romy9I83x4Mi7hbItM6bMzXvKd01S/wDjYEVu99XlCMsVJSSpmkIiKLhHR930spEUJFUQyHwxiYvPcIYcZEWZaMScZWpJW+k1nO+q4NgVAi4knuvTPGGBvAmyTFGHEhgHPKOUOYRRO7JEmil0fb1db4JEkWdSOljCa38S7FnM45k+c550QpY63X2nrv67rFUNR1H+lIkcEkBGCMjdPOtlJKpRylUghCKdXKckHSNGfMTydzox3ngjHRdRJDfN9JkvCYEMXlFC0AOE8452VZWuudc03T4nTlfxkXW8RrMcZRpSTSlOKriLslSsqtqAMIRSqTtdY5CMETQjCGtWMXN8bEHRGPk9hrp5RGPFtKiTHJ0gSQp5QmKYeFN9Z0HYk5O8KEEGK0ddbneZ5nYPRSKVktPWcpIajv7GLRWkOsQQioNaGqOuf5YJBZa5RSQnCMS0IIMoRRxjnv+spaTQihFMfFBQgQZq0NSvVKKaVojJJCiMGgsBNdFNlgUMTFJqW01jtHrAVrJQLMaOZskL0xOiBE4oSw914rm+UJAMTmvXOd1lYrhxGP9yTmp9YaKSUAxKUeb68Qolv0WtuiGDGayN5gjPN8GAJZLpdcsLionHMUPEJovS2DhiuFUlg/jPGY4CTlAB4FBx6Cx4Qyz4i1VikdhZwBIASklCnzVV0TD9i4D7XW0VI2xD++QYWuiHV86hHW3WvvfYAXfXdjASBYbMAHagPCXGlkXSCYcCpCCMY4azwGAoCDswQLCC7K0iIgEJB3zlovqKWUMgYIBYxDVLkmJCQOkrKYnB3d+/CHR88+WM6fAGoZsS/duXVxPlGqHQzzAF6qmtLy+vW905MFQkhrrVSPMUpSnmYiy7LZ7IKsH5v8K57VERqIYoYhBIxpkiTLZY0QslYD+CRJECKEAOdJ0y7izokt2zRN428tl7X3vigzLiilMUwTAHz9cOf5s/PFrEeAQgDOmUgYwkEr13cuBEsZEMIIiTaTWHfOWosQwdgrZfpOAQDnSSJSJbXRlmCaJlnw0Pd91/aE4iTJEEJtu2KjCCG0tkVG0jRBCGKo2mxy6wkAjpCH9z4Eaq1bLKq6sfv7+yGEqqoB8P7eHsb4/Px8Pu3yPC/LknOktd0cRWukoxNCoLXJmjE2LrAYgxBCm9mdWIVtlnHUOe66jgviXAjBeg+MMQBMCIMrBplSSoRDkiRRD+T8/LzrOmttWZaj0TjC3k3TpnkRmXTWWqVM8EgIVpRJK7W1K8s8TngIUNe9tbaue2t8RJqs5ZT0COlq2fS9RUEDYIIFQgEhG0+vvEgJRYSiGEatdZSyECCyKNZgljXGBLCYhK2tEWMkMnRiciAEy/N0n+wRQpyzIfjYx5GyV0rlSWa01cZUy8ZaJ6UOAaVpGjWXN2s1rl7O+WAAy2UdgsVkxVyJ5MMAq8RzU99EsN9oz5lom67vldbWGu8dFiKxrovLOA6O0dhFCmtxwfDJR3wLnXUEECAXvDJahoA4STHj3mjT91JqjEma5EmShRCshVjkbwq6cEXQf4NGoyuzrD+pHIvpj4/mzsjHe+G9R4EY7QlCgjGMkODUG4sQeIeQYxhhKfvgIUky54INSAQeUEAYxctACHniPfWMt+vrdIJjSoW1tutahj1x7Pzk3pMH71bLk66fYqRHo9x73/UNY2wwGKzeHop9cHmeh+C01kIMykFeliWl2LkV2ByfMd6NWCYw5jhPKKXBI4Rw3CrOuSwtur4xxmEM1tqu7TFBGNMsy2L4XiwWWZbFjY0Q6lqNEORFEoLVWmMSGBWC55zz4TD3jsguSKmdw5wXQhRtowH5CLuEAD5oay1jVLambVtnQ5rmlApKoW36rq15msQeirU+TVma5m3bd53Mi5UUkb1iHxxC8NBmBR2MyrjhrbUAGiFEHSWYIhQgYASRvIsAIet007TOBSUdxqFpOgDcddoZ5R1ydnWuxg0Zy9uu65zzxhjvgBAWoVCCVwDtZt2uSvh1tRWP680IGwCy1nlvMDacO845pYyxFc3eOWeMWiz6KKsUeV5t24cQhkOKMW3bvqoqKZWU3FlEeGQqSe89BMw54zyCHaC1NsbGRJ5SWvUNpdQH47032re1xcRaa4NHWtsQEGMkLwRlgQskEsYSZm1GCPMOlNKxG9W1OklpLAswAYRWFShCgQAUZToY5pE2HZNBzgliiVKq66t4W3zwAYzzCuGMskiGwiEEzmnfK60lQsjZEK23rPEICABGiJRl2bZ9CCquZB+clMY5MxjmGxeGWOTGZ4+ZR9d13gMhBCMaK7U0S+LMmvfWGEsp9sEHHxCslKTD5ujY1A7bw1HTTs/Pn0+nx13XCCpG5U5ZjmfVkZTSaJeIfDTaKosxIcxah7OdaL8dUcBIXnDOEcI2E+rhinD1TxpaDS/mZy0mEIs+Y0zOiHcOCCI0qE6aLnRtKwSj+UBKxaiglCOEAHDftdbasozzYhCC9V475/zqHFw6hOIM3mAwSEejvq/Ojp53i8da63t3704vT6zulotJkiK6v71YLDhLOOfz+bJpurIsKWFHR0fDwR7GhFKCcBBCUIq1lhHRiLVeDEMRGY3hJu4ZIQQAil2MSL3TWjvbO+S1towZgYXgSSF4PNWbpnHOJUkSSXTLRc85HtI8SbnzClYwZOeDLQepEGldyfnMOWcRQkIkWjspldZWAEMIR3YZIWF+WRljECJadRhTaxxClLMsy1hcElF2J7JsOOeCJ9GtljNR5GU0Bek7qU2HSYIJDiEEa6xT6+p+BTBrbTgXIQTOWVGOjE28A0bxtWuHSpn5fCl7BQAEY2u9lDqu1BCCUqZt+93dbcYYY5hzrqTR2gJA3/dZytDaPjTG/Ri2gnvhKRoXNsY4SRLrYuXlNsdhDFLGGMYoY8xavekocc63t7fjCRoz0DiXmyRJhGZjSI27yzkNyCrdIyBpmlrrZK+10wC4KATnPM0ItwFjAC9CQM56xonR3vuYlKE0TbKCEOq4QAEx5kIE75zzShnZ68WiiiQGTDxCgXGcJJxzihA4u7r+eKgLsZp8k1UXXR689yEgjHGWJWkqjNRJQotigIAqZQghxiqpGsFzpYz3ljjStp0QnBASgkwSvgFJnHMIO4LAGBPjTkwR4mkR0/zRaHB0dFI3leAJQigv09Foq67rvq8JjV18TAihBAcHAXvrEY5v5AZXXyVUxly2j87Pnz5++v7lxVNnZZrmZbYteHYxved9gECFSLO0FCLHiIUQrr3+i1HSJb61kduKEAovyIifHo/4sY+InHsffc1WrrVt2z56+jYAFHma5/l8OtGyb9v22v7unTe/Ppst0jQtioHR7uTk5OnTZwihN169Fl+alDKqc8ZLKnLivY/4RXRruby8fP+dd+rmR33bV0uJEevauq07wYbLmcIEY0wRYl23XMyXjCZFIZxDTVPHQQEfrNZS6y5iz5HkHglasT7fECistcvlsm16Qmhc3Lu7u0r1CGFKqfMGYypEyjmN50EctAkh0LV9CgDIXjmHVxkQI5wzJX3TdAFsmqaEOuu8D1RJcM50rSYErFPGGMZJCMxop5QBMHUlKeWU0q51su9DCEVRJiIF8EKkGOPlcqlU1IcGhMiG/AaAhUg5T4wxlHJGqDPQ6NU8N0KEUkoxC8gQwqI8LgD0nTIGiqJAwKxVhCAhBEasa5X3ynvPBCWYcZYInhBCjDFGK6X0bDbjnDMmYrxo2w5j3HUdglWOE6PMhuJcVc3mmxEW8Ct3ckwJJzgAAI6Ovw48hk0jL75NMUIZYyBgRoXWuqm7WElRSglmRVGkaRo7aGkqIn8yAGfnerPmGWMIsa7r2kYNxogLnmRcCGY17zunlKTcBXAIIwQekEPYcc4wdQhbpZxShhJGaRJCMNr1vdLaYJRSiq0J2kjKwDtwLnhv81QQypw3sXKMHQyEEMLAOCV0NX++QfdU1zImsixrm55QGAwTY/OuI+ATrWU8OSLQwzmzFrRe+Uo5i4wxnLHBMI/9+xiJkiSJmzTe5+2doRDs+PjYuQCAvffOqcEgq+v52tOBEUIoxt4HFJAH8Aitmnaw7o7Fv/5X3/7j2exoOn/mfV1kHPm+mc261oi8IoQRzKym1fzMO+Q9hoBnZjfCWnmeb21txeaIEELKF5bNV2uxn/RwzsXqEKEVMh1ZHn/11jdSIfb3d7dG44uzEyl7Z22evfLue99/9uzZcDC+efOmtf7dd3/04YcfCp4+uc82k8SRlbNarIC994vFwnvf11/g2J2fn9/74J2dg0vnYDjMCc6mkwlGNBHl5KLe3hPz+bIsBkU+7DstpU4TtLuz//Tp0+FwuL0zDiFoLatq0XUdZaQoingzNxMJMcRLqYUgWZZRwgmhxpjlssYYc05jAzViZ7H+apolYFWWZezsxO0XHekYE8Z0dV1hYhFCWVagBAdvYgDXpjO2TXPBmKiXpq7bvYO861fyEcEj2ZuqarS2HCfOIu88AGI0AcB9Z9rmkuWqKIrxeBxnHeIUe9u20copvrQI7kbuiVYhpgkxAUzTNM/zJGGMk5jRUOowpm1badMlCXdeG2OUMhAmeZ6naQ6A5/M550kc7AoBIs8FAKdp3ve1tTaEvmmatum1tsPhUAgRDUJi3r2JIBFVjTc/9m5iNhdfyCY5XR2JCIUQ4lD+hquxOQiNDnFsyq7tM8l62t5733c2EjsxxoA8Rvjg4OD09LRtW2sdZxmlkSli67oTqS9KkdPUMtF3dS9b6q33DGMGgAI4H0wAipAD8Er52WyGESuKkdG+63qtDQKipAXBfQCtXAiAMWFU+ECsNQACICglu67re1pVS2PM7VduXwV3NsjAzu4otsO6vtbKleVwNC6LImuqlW5fRCdj98Na08suBJSmmTUQQkjTZHt7O8uSp88e9X2/uaVxcXLOz8/P7ty5A8g3TVMWw6Ojk7ar3njjs1VVUUYiAz4Eh37rW+/GVCWEQOhg8/vOueFwuFhU//bf/tv56bci4ArIJolIUhqCM8Ywmm9WpA82TUX0zBV8MJ/V16/d/qVf/Puvvvy5voWutUIkLXd5nndK933PRQKYKKUA0zzdudrD3twjHyQggWlqtBvk9P69v/z2n/yb6wfDu++8necpwkAISlKqtcIYdve2z0/m3sHOzs5otDWbzS8uLrSyIQROV39wQ1qJeEpsySEEjCNK8f7BTtvW8b/Ozs68B6N910nZW4Tw4eGhtlXf98PhMM/zKF6zvb2dJMlyOY01V5IkkagSrW+2t65rrY1RAMAF4zzWyWZYEkJI8EhKLaXUyiqljTGXyy7NxM7ODqV4sZiFEIoyj32oKNeyYabFXUcpjqh2HCKLXsPGGG81xjgilzHLi6fT/v5uzPti08paW9f106dPraFFPkzT0miIEYRSEAl3IVCG05SlaYoxNTpo7awBazXnSZKkk8kEIR9AXz/cyYvk/KhezBuCed8rhND29th53cs6xpQsS6Rq5/NpliW7e9uUksiajYBrCKEsyyRJlFII+EZgLCbjMZSkqYjCPbFMK4tBVTVKKUwMY4yxFAGu69ZZVJYDBAT5Pp63GFNKOQAYbZVS2zuDSOqNFOq2bQEgy7LX3jjouk4rC0CaulssKu9DlhaUoXUpGuqqxTiOO+BiQOL4K0KQF2nf986Z/f39h/fnTd1aa50Lfa8opTGNGu0nsRpiNCmLISFiOpmfnp7mAx87ifHAjvhgkiTBk3h2RiQ+0lkZYwRnUnZ93/pgkpQPh+VoXOZ5fnl5PhgMiqK4vLyM8MIaZxgtFou9vb3ISqeUrnyZUht9kIQQJycXbaM4K7VyhKC6btu29R4QEO99CIAxvn5jdHBw0DTN8fHxcrnc2tp6/fXX0zSdz5fW2tlsVlcNpTxaoGZZhom5du2aECIuwg3Oo7VO0xSh4INhjNB7H/0ozkynaVpVXlAB4DEJwau2uZjPzo25dNbHvIbzlFDQSgdwlBIpJYAXQgghnDfOuRBQURRa+b5vtZacM4ThcnLmHblx8/NBNQBYUIZSHBBGCOEk995LUwMAZrEAtNa5GCwEZyEE54zSaqrkydHxycmJ1fPRaND3fQDPOW9qGbU+J5fLWzdvxnbp6enpYrGsqgoCZox5jDd48Aa2jHeWUkIZNgakNFmdWmuzLAkBUZr0nWzbXkpNCU+SlDEGSFTLulrWCDAljGBqjZt3i7zIIwrbdVLr2L0OQqTRSH6lG6u11pJSyjldzKvIu/HeJyLb3iqMMfP5/NnZNM71MMbSNNdaKqklyL29PYQa7yEiowghpZRzIU1ZJA1FboFSakXJISjqcsWY5dcDO7GjtAFZ4ns6Ho+Dy6z1XaucRQTzNKGEBkqxkTYt89GoZAwZY5yzAN4Hm5eYYMQYcM4AwDncd14rKaXsZUuQCwGtahlYpYER8kvTNISRtTqaNe/t7XHe13Vd101scidJyrmAwL0HKeV63CkQQjAO1nq01rQLK/IHShIekMMY0pRpbUNwCCPnteBps+jiex2BW0IYoTijaVh3+mMox+vlcXZ2ZrTDmBDCYr7DGE3TdL6YRACOMcK3E4SIlHI2mxmb5HludOj6put6zlmaZhAo55wLjRACMIwRQihlOATWtdo5FwIw5rwDjGkvG0w8Y4LzBGMspUbIRDqKMU5JCWtuSjxU4gGpZEdoKAcrd3mt7WxaLxeN0p1zwXsIARHCYlIoRHp0dBTf7phdYoxHo5H3PksLxhjGNN5YADBGOReybCylRaC9M95b72JbCTd1vxC1MYZgTonoWnV+NuGca7PSM8OIdJ2UUsXSJzIYYjcz3vPIODXGGKO2d8ZZNlKqpx+9/1dOL6P63P61n05TIVWvtcwLRim6//Gzx49/5NultVokvCxzY23XtQiFoszi4Q8rmmnSqKZaNsGXWZaNxgPK0POjxw8fPPnOt7+PUfLLv/x3f/rrv6SMwYA5RVJbHxAiGDzCbIUORhwhFtKUYadVQAEQ4gSHgCjFRZElKRuKojtupZTeBYRIlg0HZRJRHgSkaZq6bvteaq0p4Ru0bNNW22TsnHNCVw1OpWzTNF3X1TUZj3YI5hhb54KzAYHruu78/Hxvf4wQ0XrVBLHW1nVb1/Xhjb1IP9kQSVZzOiuqHgGAXnbW6rIsB4OiM521HgLlLOFccJ6EgATPr127zjl3NtRVG8BZ60MIlOKu7bu2j6VohBiCB+9CxBEjZmStD0EjRJKEE0RiNMSYIkQQIhgTSqm1EUNdJeSRazcYDNqayr6VvcOIUSoAPCHAGOlncyF8yyQmAcCGEAIYbXoRKATnlXfOhICNcdVSOWcZCYQQghHBjBBinfYhOvys9ByShGNCvdd9Z/Kcyl5HFmJZGO/AO+g7Za2FYBBCCDAEFJ3unPVadZtqK/Jx07SOLd68SIwxecF9bRG2lAhrZZLQ9dsN8eJhracVP4n/G2eduq4DAK0iwwgw4pxzjCkAogxvbW11XTebzQBQWQyjFXiWZVo5wZFz0DZKEruzk4WALy6mUq4gbWtj3q3jakFAV2NG3npfR6RmNM6LMouVR9u2IYSY8GqtrYlioT5O3saK0jln3TRNU8HTEELX9V3XtbUGAESs7J1Wa1nU1kQyR6xGIzQWV/5wOGzbVilrrbe25ZyWZUlJUlfSe9PUfd9pa0Lwa/s+gOBJ37nJZRVCAGAEp0rq2bRJ0xSwir5ywUOURoqvlzIU36nIPvPex9sSglsuW5EwzrnWli6mRw/udVVVYYx//hdxlqUnJyeT6dmrr7788isvOasoCa1xzgFSTovYKRCcsyzNm6YKIdR13fcqz3Nrfdv2Stlr11hR5HVd/8mffOPifHF+NvviF35qZ2eMghcEG+eD9RSCMsYrIJwxIrz3PniCANOVhTwAABjnwTonuIBgBEPDQcawBfCMkb6Dtu0BcPDMpwyF5Pz8uCyGsSEVE4TgUViTpshalXV9xDHGIxfBxTKKM7FQy6ZuCc66ru97GULAJFIlXd+HtuUxciVJEpGFuKWXyzraP0Tg2Xvf96rvVZaWEVCIgcn71ROZXvSdEgIVxSCEcHkxjdFkZ/vAebNYLLquSRJBCMcUsiybTqcxfQVAhFBCmLXeuZBmSdxLxhilpPc6TmMOimQT02NFE1/7BiIJa63PiH0s5kulXPCYMOI9WGuJQ4RQzgpr0GLeYOLKQToaDSIJsG0rzjAE5Zyz1iCEMA6MU9k2UXnPQXDOVbWhDNJU5HmJEOq6rmmqmBJijAGw94uYHA2HY0q5UqppOiklwUlkAMXDIl6nMa6umiRJ0jQdDrGUMvZ6EApb2+VyUSUp7TpgHAtBmloaK7OsiDW+9xZjCGCMjQcyj+BaRN82jb8hHQUf44XnnDMWOVzN9vZ2rA05F5TSqqoWi0UcMek6ba0NnjIhhMiscWdnE2excw4hwjillMZbGkLAwBCgOHIRQkDY50U2GAy08owyCAYBAQCMKEaU4CBEiL8YszC0Hi3Ic5EkCedCSeMdWAMQOKVUmSWAc7ZFa2VOSinBkKU5IcRZP58t6qoZDofeBWe9swgAaeUJCYOyhNBfnM9ns0WwadRdY0xQSqPuFsbYO7SYt/Etw0ggAO8Io1nALtbLIQTOeZaFOGSDMJFSxvwrrJk6nPPBoJhOp3FejxBCAeRsdnJxccE5//5f/m5RDJbLqq5ap+vZxcWDBw91azHiHrTWdjGv04xnWUKJ8D44byI3rG2X1jpKePCk78zx8WlRlF2rJ5fLvnODQXFwbb8ok2BlXpZKGYVcxrOuk03X5SLVDoMHDJhTvsHCnXOeaOedsYZxomXXtbV3tu7nZ8sqasd5bzlP4j7Ps3K+VFnq4q3HmIQQonR80zdRt9haG0viNYuUrZ7IW61t36uuk1rrGAWUUpzzPE8xhjzPi6IgFEeDsKhUEFXsQgiL+TKE0DadJCpNU8YYRgQjglZWriFC8gjxGAWUsgBgre9a2fdqPl/ELoYKFAC6TnqPKRWMkRACBOwdxogTLJxz1gCCoJXHGBhXkcXr14M1ET3pWggBIUy0stZ6zgUhpOs6SvG6U4NiLI7ogF8POsSV55xBKFinnWNa+wAaYSMS4lyIWZWWlOFIoQzGdHmRjLeywTC/PKW86aqlBPBc0BAwF5BmCec0SRIAH4nOMUtHwIPHdV1r5YbDIcHcGqmUsTYkeQoBa236XkUImVLGGfEeorkYgvgW0/F4OByVZSn6vgfwmECScCGSpu76vs2oEEIkSWKt1kbG2o1x0tYKrRWm4mRJLF2rqo3FjnN6c2MjakYIyfM8dnI3ZLembilV0Vg8sniccxgTj3yaCsaEEIJSbrTt+94Yt2x0CAFjFEKw1tE1hij7tu+lMSaOtS0Wy7gL4hw8QsgaKXuN1jroIgVrffBGSqWU8R4IxoxxY1eltw+BUpomWZRb7NVCa1sUg+WyVqofj7el1GVZ9l2fpAxjH49qAGCMlGVezVcz5CsEw0ZCMfKO9J3BGFMSMCYImNHBWcRSEnG3mDRFRF9r7dyLmdMNiz1N03KQU4aXy6XRThQptV4jhJggeZH23WQ2PQ4e7+wcDIrs7OTk7gd3F/NqUKYARCttnYyNt5hKZAUXIiWYObfoO8UYeIe0clpr2QdrAsEiz7Hs7Y9+9KO6av7xP/1f7e9fY4JTQIy4RARnwbuWhALHHpy1m46+YEwFzCjH2Odpclnptq0wWOuMcyFJMsYcQE8p9l4ZawNi0ZQiFixRkyG+qZsbsWniRNwEk4AJRRbaRi2Xy75XbdtjRLXuKMUiybe2RlFNLi/SJEkwot5vRu0Zxl5r7ZyNY+Ixum2oQJFuGyeWCCFcsPhJ27YISFEUAHg+XyyXy6gmM5tWNBsAivcWKWms8QGclBoAYUyizo5zLk1TjEmSJM5qvxmjCwgCBA/WuN6txM+NccZYxkRsqEdFwaIojDF1XWutCSGj0Wj/ALdNt5h3XRvpZAiToLQ2JskYFyIBhOMVOue7TjqLQsBrsp8FCJgEzvG1a/vLRaP1efBoMBgwTjjHmITou1AUhTGu6yTBLEkSRhPvjdbWeylE6pyLyV1UKXDOO+cBkPdeKW2MBQDvwFrvvRKCpamgFA+GRVHkxvTBg9YWAYnYM8ZUKRVUW5ZllqXWIddoQKEss+FwMKcq5heRdRWTQULIfFaXZZmm3DlnnOWcpanAOLXWR7x/Mpn2ncrzMlZndd0mqSAEWWut1VW9AADOmfeKMcYYYYwlScq5i+Gs7iUmaIU5OG0MZlQS3KCVmZyNuN5m4M7oF5S/eE7ECTilLWOWYBbb1t57hKyxkjJMCFHKxiFO543zxmtrjAOAohgURWw48K7r0tQvly3GJeNMa71YVCGE0Wi0v5+eJ3XXdV0rYxZpbCTriOg2GtOOiGlEOL8cuzjBF/ed1hathvVWg8GblDxu7fl8VhRlkiSy10oZ6iEIznkijLMpypfzidGOkWRULpVshQgH+yPZO4wC54IDRThoZQghaZpSCnHXleVA9hYBheABHATcd1YrGwLGiAPgpu7v3fv4m3/2RwcHBy+98kpZDn0AKhJjzPnFxd74IMsywTl4FSH02Na9rJu82AIkvDOTycXZyVHfNcGq4KGpW0AhgAdkkpQiFKSax6I3nvBxwIpR4b3PknRDWY5wbAzzVbUghEUeRGyfJyLDmCQpGo0GaZqOtwaEIKk6QpAxXSdXzKl4HBHqGQDC0LU2ziKEEHkQUTmYxKIjpuIsUM5TjLG1pigGSZL0vVTSOBsYE94bY1qOqbUaAQnBV1UTe53e+8gRx5gqZay1QqRJIopiEECSK/PlcW4QY1xk4kVf2RilVHzh2vSb1vImIg8Gg3YEeZ5Sys/dVErFhUgzhlAAlIuEcoExBuecUqbvnOxdXhAuYi6GvAdj/GLWWxPyJMcEheD63iCEuMB5kSAU4ipHCKVp7iyy1ilpZV8jYp0LhKzYRhjTNGXWWq3smkOIgkfa2njPrdOMsSRL9/e3RUJ7WXvvptNLhJ1SDoIDwN4hrQzGFIGzximlCEEIO84p42w4HAyGhWDji4uL+O5ECcHYQySYR0Ecay2hKEkSzqlzLr78iJ11rYznTeSsj0YFpbTrG0Iif03G9MoH2/c2qiAAYB8cIXRru0QIWeuapnGtCx53rdFqMRoNrPHORtgFQcAQAgQcPa82yxWt55aswUZ5hGUIwfvIoXPWWsqD8w6Qy/IUIdQ0jbEyLgPO+WKxiLexqqpIZcKISWmdB2Nb7x2lVIjEezYcFSKhSSK01n0vuzamkAHhwAUVgkWMmRDivGm7GjEfa2RKVtMR8RjGeNXU8ytRTRazyMWy2QAjfV9TRAlPk9C1s/l8etYqJRljF2eXslPe+7aZCyGWS2utpgwLwa2VbdtbaxljbavatqUkyfPBYJBhxIwJ3lXT6TRJMiF410rrbZ4VEGhd1d/8s3+/u7f/c/3PHRzeaNp+NBohwj784AN5Y3rz5s3R4WGWUNmp5fyyrUOTJH/8l+9dO3x5ONrdGu88fvLo6OgoT2SW4Js3byjVM045p84rhKBpqmfPn+xt3+haCRBtMHyc2QshcE7iVozfiX0lpZRIMUIBY4i9Z8Hz5aJp23b/+s72zphzxhgBZDnHXDDXSOfVetjaRgALkGccxabpJnWPwT7P8+VyGd+MruuIwoyRCF1zLrquj6qjZTlEiDBmCCGV1NbaJOGUcum7eJ5bK621QhAIKzadsyEiuE1XbzodK4SLMSGEt9oYG5noUXVciIRzYSzaNCki/yjC0oBcWeaEMCm1n1uRsMGg4IIpja3VxqgY6azxXavaVt98aUtw0bXWWSxlSnDStVrJDrYgz8ssy/p+XtUL1IQAwzQVfa+apqGEJUmxyskROBe81oQQCLhaNtba4XA4HAxDCLNprbWN7Lj4SJIky3LnDEBYLpcIuSRl2nRJwpxzxipGBQJLKXMuSKkJphhTniTW2qqquMDlICnLLMsThELU9IttxJjXRyZkno+C903TWavLQRortcVyxlk2n8+FEFtb22mKqqqJTAKtJReUc45wVpY5Qmi+mGqtGYuzx72zIRI1ESKUkb3x1rr5hYJHziHvoGt1CPN1ozaE9ay4956QyNcLm2PPWh+Ci36n1hgfDEKB0DjqGKxdETJHowHGWMoOYCUkkCRJXdfxTXfO5XkeW3tdX3OBCAkioVHoQkoJgRGC8kLkkKZ9ylgtpQohYEQoxZSSKDgrRC4EQwgp1cd1vnJJtD6Wt96vRNriOxi3HqU0CnIjhEJAWiv0y//478QV3HVds9TW6u2dYdRbRMAQ8MnlYnEZuKDe6wBWJARhj5ATCWOCNE0TSRYIob29vZhMHj99ZozBiGZpSSlX0sXXoLUtSnFwbeull292XTWdTstySCnXvr1xeCvLsul0VlVNWZYQ8JMnT6yyhJDBsKAUL5fLtq0RhhDC7TtDzpKm6SFQ71DX6a5VJydn1w5uWWsopQgFbSTGWAjmvR8W5QYJio6mscjHBHmHutYYHUJAVbVou2WSiFdeH924cSPLsg17JfJH7Er5MMSIHhXIEEJWr/SZ4t6O4ynWWmtI5JWs+5FGCPH6669TrhaLRTyOkiSJMr3Pnj1zahiZb7GVQNYTdhhT723EreI4SJ5nSZKITMddtKKTrPuv7aKJjfnI3o7xN4SQj8Visdjd3Y2XHQEvAJhMJofXbyJELi8nsrfWetkraz0VHAKOslsYE8aY0a5tW4o453R7eztJeNNWSinnbN/3ecF293YICW1XK2nqum8bTTAri61NN8CuB0pDCGXGIhchXkkUIVJKda2ZTqdZlhVFsVwunXOj0YgxZmyHEFrrfXpCY01NBiNGMGMscRYt5vVi0SCgWZZR5iKnOR5FaZoOh0PG2HK5jB2oqIjCGIsVmeqplPLrv/C1p08fM46dM0r3jNHzS2md3NoeUgoIQyLS5bKeTasyyRFCeZ4Ph0PvfSxvOecIQ+xJRwh2M1tjtPXBCUFEQquqOj256DrNKGc0v0oZ2dwfQn68rlakjMJ6Pm4D5xHCOSeUuxAMQgiAyi50nRofJBF8iL0RhFDUJLu4fJplWV6kRVHkeYZQ6Lqu6xtCB6PRYDq7MEYJkVIinjw+bhslQupW/mhs3WbxGOM0KY0xnFMuqPceY4h/ylOfZRmlmHPKOe9lJ2WXZVn0AtrZ2cEYf/zxx6tSM8aO8Xjc9y2lFCHw3rdNZQ2SSmFKMQkIex88QlGJAryD5eIyTdPdnWHXdfP5fDY9izv84GBHKaWUgQAiIVmWKZV0Xae1hYAX8+opfsoYAcBV1cxny4MbO++//0FZDhGQxWIxnSwxJnXdCUqjhq61IYLEeZElSSJ7Yw3SygJA39lq2WJMh4Pxcrn0Po5TkXggRBivqqpNHyQejBGvSbPcmoCQiQoPsfc0Ho/293edc3Vdb9LgFbXBQHRVjusDraeT+76PKyOW637tZBK3FqU0NuaKogCAtm2HfIUrFUURkfIQwv7+/qP7i1j8xyi2WtAI+SuqcpGxEvlcrTyLe3uzw1eyOzbEDHy5XEY2UAxnsVKLPxbDaOSjFkWBcEAQhBARxY8YbcZo8GHd/ltRctadPrdYLCjFxkYKj3fOUZaE4BhnQzawuUvTvEmVkiu2V7znm80W698NHTkON8bICGElPBRX5hos9wBhLZ8QCEGxi+ScDx4xwRljbr3tvQvGGOedtZ5zGvEmY1xdtxjjruu9hzTNAHDbtl1Xr2wkgmYc9X3rnBukZQiu79Xx+YUNVKqOMjQYZFH51LkQw+XmdXnvo6gT53wwLDfxIt60+FooZcZ6YwyhUBTFjRt8sWjaprPGbQLKpuZCP3mEIP7BT8WgEEJRkuGoKEoWwPR9J6XCxBAeBUZWQj+R7hh7UlmecZ4gWJ2USSIYY1RzhHHE4LVmxhjtVnP8HHG7lrvZAKNoPQgppbQOx1YPY3QwGNSq1lqHQCJKa63FeDWuFFaSVYYQQjllIQTBBS5Rteyt1W1rrDV9389mC9kbzrP9/W0AaLtaSuO8BeRDCD7A/rUB57wc0rws8hKvV2c3HJfOirbt+04jbEUqGOeEOmdolnFt2q6VL79y+/DwMHh0dnbea2k0evmlO1tb28+fHV9cTGazmdGBYuMDMkbFPg6gkCTJaDRo1Uz2UiuHEHStahvFGBI8C0GGgDnnjBFkQ0xfnXPgQSmDkI1xwa0VMJRSznpjjNZSKYMxDAaDnd0tCHi5qCNXMMJ+MdxQkluD+s7GWYRNg2mj1rYh9cZgtFxEYWkXD+GyLOOX1q6wvTzPo+1MCGF7e/thmMeGwib0xDfv6gK9ig7EZ4nRMPLBYiQd5WUsLqSUxijOKWPU2uAdUMKt8VpZBCR4ZLQTnKwEH4DEdA3AZ3lqDQeE3LqfCoAi1hafPT6dUhbhGKRInud5ThEKhEQ7isCo8w617dzbFyf8Jp4CQIg9Q8AQkLW2DzKCmlGjK94BIcSGkUgp8g4CxFkKxhjBGAdwXacI4cEzKVVUuvEoWOudNxHH3WS+8Y3b8DMiPBH5FmVZ2tT2fX85OQMUEpHGqiR4iikQgkNwCEOSJN4hox1CmFJmrfUelDLOuaijhLH3LvgoFQPgXbDGRTfN4TDBRHiv/XqSSWvfd9KtJzQ3j78hAMHK2uyF3cMmBkm9zCwQVqYZLYaZtTSylE5OIJ6UG4W5eCTHJoDWtuu6tumHo5JSYq3v6toYpbUkFBtthaB5XjJqkVppOcXVvrnOeAo6Z31YDZZ7jyI7HOGw4jqtBI9o3ytANh42Wus8z2nXdHGP5XkO4LM8wRgRgrIsTdPeO5RlyXJZIQTG9oyjre0yTTnCjjGSpsY5511NKR2P4my37rpOytgJQtaC1n3bWko5FzhJkijuNxqN3njjjS9+8YvDwRghDJheXFzcuHHrxo0bjIkHHz/6jd/4jbff/mEI82hPKAQrB4VzJsuSJEmkFdZoY4I1SkkHQKyB4C0XNIRIh8HOr2KiMYaTJL4BsO4vRFsLrXvvkPMmSh0TihECrfVs1sUSGoDEwy1yc+q2CyF4h7xDkS4Rmf7lYKXlFt+huKYZY9vb48ViIaXCGBOClOq7riMEKYU3VJ2IEMf8JRIOoiMoWdtba60j+R0h5H2Iz+i96/t+tM02/b4Yiay1WutokMsYxThFCBGCozmtdYFS7j04t+Ica62TxB8cHMSCS0odwOV5LkTadZ0y3rsV+hgl32I87bsOoTSEYIyKvRhCIovX9n3vg0kSDoAhrPByFPDV9GfTpowZ5dWUIf5vPJZjDIpVg1nrLgCA92jdXhAIBe9x17bONoRIo130jUEIU4qtIxivHLUQIjFYEEL29w8uLy+7TsY6l3PkXHAu7O2PZzPQWu7s7DHGTk7OqmXHWcYLPBqXacoIxQiwc94Y62wgCYv7MT4FIQwhjxDZkGVgrWkb92rbtrE9ipBXSjkLAJBlWd/Vn7oJIbzAgH5sHrTZ/1dToeWiMUYr3W9t58NRlud5UXrn3MOH53GALjIJ4yKJiQlngjGhVL8BueKbvFhUSvVlmUfD2DSF4LXqlFtrH29OFISQc5asfKVDWGlme0KIwyEC1XWz1Fru7m5Hn1vO03jYhEjIjCMtVVXt7OxQxoqiwDg4byiFcpB7jwlB88uWccQ4lIP0+uF4MBLWtQFsNW2jwi4AGC211ozS3Z2t4+MpQgQjShnxHislrTOCJz5A31uRoKLMCAldVxVFduPGrbzY2ds7CCEQwop80HX96emZMUYIEtll5aAoytQYQykG8GmSUSKCl9Nm0XUaAQWEnA2d6yMZh3NqVtw5sNaCi+zMtf2Gi+0SYl2vtVfSWuswAc45ZdgY5YPN83xQjuz/r68rW3LsOK6VtdddsDSG0+R4FppWhBT2iyPkkJePtsO/wAfrlbTpoOnwkEOKs/UGXNyl9io/JIAZUZb7oRu9AY1G3cyTmSfPSYnCjMTfnPLhMNKT+ifGDlErCJHQ+g5bvHh68OF2u0cA9Xg8WmvnecRcxDkV6nQUcNVLSumcu7m5QWB/IRZgT6d+tLILUMuZ7uica/oO8/ylSsJKELvdWmv04UJ8BAAJKj+73CAzKITgnPMeNTpyCK7WYoySUh6PB8515mcNqXPFAQDIkIoxCiH6VauU4pxprQ/H984tjIHSQnBlTA/ApNAxfEjvl/wJJ9o3lswMtWEJAUqh1ojZAkfUF2KXUgqNl8ophibOKQDlTDkbS4l4txg0pZTFlVKrXdwBBkqpdyHFDIQyyoOPF8NCwdlSrF1cjCed5t1ud393eHh4OA6L1nplVpvNSmmOXbxSaIolJYJNJcz8cNa9yTkjD+sMVT6E3XEcZRBNI5XmyITknG+328N+uWTHj2/8OTR0oYPBHwt+Udp6Wx+y95ZMx9z1yrRMCIpmAfjPxAsWX/dxHBkTjelTxM2V2DQViNhs2hiDVwKd5lLK07hMkyX+VPhfkGn9aMETn3FKCec8tVYimLVOCE6BS4mEMnFpSJ/nRZI3qoEC83EusSxp0kZIRWutjLOmMTlBLfTp857SUqpXGlK21tlSPeM1hiwFiSHimfY+yl43puN88D6SWoxpm0ZRGtBbRSoZQtSNqST84edXt3fv2rZ99uzF48dfNE0zTQvn3LnwL//8r7///b89ffqMMQih1pOqNk6LSy6RcdRn4MNwTClwDhS4UqLUjDgIw2I5+8xWAEZFAZSwCQCglVTSaJ6XOZQMwZcQUq0l57gsvu0aQngIyDqntZJ59mgUVWstJZeC+RbJh0Jpc7nGLviFUuqD6/qWMpjm0bq02Wy46KQSl8SFnRfcS7TWen/iOmDLptaKC00YhhDrVELxU8QLl2yZz+RvSqkRrNaqlGo7QwhJOXhnCSGViYvJbQiRcwFAcy5397d9t6oVKCN936/WXfAphMClwCL0fMRPi1rbqyvvbc5ZKbXdbtu2zTnlnIOvOdEYkvdZ8JKiqIVSULW6S5L/GMMjawk528jcQ97JZasGB44nE8TTqgEFqDmXeVq4YFprpUTXbcZxdM5hA7DWP7qGcS8Mja6wlry9vZ2mCY8HPgQil7dv7q6vr5Uxy+J+/PFHxmD3aC2EAMiUnqS+p3HmrCmF1AKpZAAAArUAZYxRUgBNrtM5Z5yCCGOMUpBS1FpCCFwgdIV8ojXSSyz7UKj+eWOb//NbAMCZIoTUTOeRzNMi1bzeNOtN+/z584eHh5ubG5zurddr1Id8uD94l+sKGFM5EWf9MvtcUgXJOdO6McbMsz0O4+3tfYq1E6acV74vqJacnREx8sYYlRJNYwghwjTDMJQSuq4lhEzTgn0356yUsm1bhLc8x7Rdb5SQADC4QwiOMmmM4lzWwkgVACznwRhTas3ZL/Y4L4UL0rbGzTGHeZ5nBMwpVAuB5FlKTQFV04FSrjVnNKVUzEr5kJtWOH98+24wxgCwt+/+8Mkn75qm/emnnxrTCaFefv9dTH6ah6aVlRSUqiCkhOhw9mzdTAiVQm02awAWQ7VLyNlro8rJr+5yyk/z6RiTtQ4VBjabDRqT67a1S1xmf38/3N0+OL9UEmP0SqlltnZxWH3gSItSerVbI4I9z3cio0xpsdlsMLoRQnBAjqfKOY9a4tiJwP70er3OxVprEUdgAxsX38e9XZYFpx5t2xpj0Eel1g/9P9RRQpV3axeMO5fLFQPW7mpz7hEgOKJCsBBCiizFwBirldjFd+1KScOZ7Dq53qxSzDlXRoWUehofUgoxU84ktmCx/4VjsmmalmUqpZSS0BeYkOqcczYJKUmlwfuaSUm+FFrLh0LsEhpOwaicNADpR2IJOOO7AH4A6PueUjrPM2eScVy+WVDjVUrJuSwZgNBaSMqZ8dM4yXurZEcpdy5Y6ylFca8aY6aUS6lTSifOJGPW+hhjX/t5Cko2ObnDsH/+/GnXdVLK0Q8h+lyCc8s4jlpRQhilVHJBTtU0mhRwQihACsFhEiJnxVV2luUHSgnJCMEYlaUUuyy/qFIvRf3/E4Z+0ZE54aMaSKUAHAjLhcRQarU5kTaJGCPKm+Scj8cj8vIB6Jn+UwEY0hq8t9YnpURKkRBCKsVBQtu2knwYYV3+POwx4/GWik/ThOgSFXIwoeZchOApJedSKWS14TguPBwOwzBwxthnn32Gv/Pv333tvaskco6LiEvwmTGV6pt2db3pNzmreZ4Ph2NO1VtaEmfSSA5KKMFErECJ5rQhNRhj8KC7GDgTQihKqxC0VKC0TNNAWdle9YyJZZ6+++7bJ0+evH//DlcrS0kvXjzTWhOylFJCcPM8pxRi8n3fG6OtnWPM6/V2s+2aph0O8zS9nRcfk8QBjRAnLX28w2GYEHwCwHa7vb6+RmWfcRxJpVrrvi928ZVkrWXK/AKq8VLBJLnZbBgjtQLnEjkXyDM2xpSzTg3GYkJw59v2/Rr31K+vrw+Hw8m3R6mU836/L6WgVQ7Slx89ejTuh8uO32632+1233//vXOOEIrmTYgE8QQAwPF4xMONUwkAkFKWUnojMMNjmEOlDkrpMKFw1ElSE39eCDFN9wDgXVgW15hVCOk4HmKMMVejKTbITwGuxBjjPM0xBnym+/1+miZjdCnl4WFar3tCSsqVAaRKSq5SqFLGX8QgfJ/jCV6d9qEIAKlwbnhjh0trvd1utdbzPNcCQggCBQM3IYUzobU+7Ed8uUJwSqPuUrHWr1ePSim4VXOZ0GMZTk5Ldh5fQdxcbcwqRUIp7/u2aXTbGi6IVLBSq2HYo24tMhgpkQToiaB+LoTJuUOcUyW11pPVVQUOKGI7DEPbNYxVH3xKqWvlhQN9iSP44uLtP+1V/2kkIh81hiiLMZRahOANZzJlO0+L93Y/TRce2TRNaJHAOe/ada21lCqEMLqljDDGSiGSihjj4bCnjGw3u7Zt1+tN3639cYGzbhQ2gwi5dAmgaZqm1SklNPiOMd7e3K9WXa11HMe+7/pu7YPNOVsbMMHgQJn/09//7u9++9tHV7v1ev1f//3Dl19++c0339z/PG6utlDKqlNCCFqSSHJ5cIQQSVUvusLKqlm9dze3w03XNaDE7A96pUzLrN9zwYRglArOdK2VspJziMnfvipKCRoJVAO02n3qOklCWZbl22+/TakYY4xp1uv1fr/33lMmuv66bc27m/cp+6urzTDFYbpT4urd21e5wPWnj6JdHoa74zGQqoyiqdi//OIvuEyvXr2Njnz26eevf74lXtdQd/3qarcSkkL2bg4h+PUVSckrRbqWKqEP+znFTBOfxmga+OTxphJ/f39nWvbJJ4+1ao6DddYDgLUTJmFKS2NkimUYJkppv2K1OoCT+2glfpyWh30Qgj2+7hcL03S8uXt5tf2UUupdHA6WVFEy3PpxmhZG/G5jCKkxpuRmzR8LIDYGwU1wDmeCpaT9fu9L6rqO0zWjzC0suEypYoxlEJzz41wQ5QohCFM1ckIIYVyKUFjJOTem67urt2/eppRevHhBQKUI05gIEbXwEApUXbLw+5KYlTKfbdGSX1xwXnGuFCeEQAZNWyiQFkII3a1XtdZaQYKCTBgUJTljYU754iGJVyp+CIU0TQOn4e5JNUFKSUp+/Gi3Xq+/+uqrRqsfXv7PkydPxuHwD//4uzdv3tzf3y/zYLS01j57+vRwOBjVeW9HPwGhDJjk0hgdffqbv/5N13Vff/UfL1/+cPv+7tmzF3ZK3qd0RSjIGBbO9DKHWuzV1eNlWe5vH5pW/9UXn6/6ruYiOFWSvf75FaOP3r8/5Jydi5J3iup5HpVShMgzdiMpnRrtnFNCxCUknXu0gRCilBr27sz5SsPD4bKJekFAlzcAQO2XyzARv46XNw4rhBCbzabWiiwqZzOllPEKzBEATkkpouRKFnYcHaUhpdR1nfOFMsZBHoYHrbX3Sohuu706Ho/HwQJwA8p7IrM5vrPj+9dt2z7ebOd5ljoKCSkRzuXhcASaXzz/vG3br7/+T0KI8xOBAJAJgNL817/51d8a8/r1a2ttSsE0Uik5TQGA+8JyYuPRt83WOfe/VMoLm/3SkB0AAAAASUVORK5CYII=\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display cropped image.\n",
+ "PIL.Image.fromarray(distorted_random_crop(img_array).eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Apply all transformations to an image.\n",
+ "# That is a common image augmentation technique for image datasets, such as ImageNet.\n",
+ "def transform_image(image):\n",
+ " image = distorted_random_crop(image)\n",
+ " image = random_flip_left_right(image)\n",
+ " image = random_contrast(image)\n",
+ " image = random_brightness(image)\n",
+ " image = random_hue(image)\n",
+ " image = random_saturation(image)\n",
+ " return image"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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A+dU7dqU1cAoBzMeQSbnr6eIp3d8XRd5z+7Xu78whMeMMYgEkWKlSzhJrLQCQ1eS6dOPGlcXF+V+++wuv5Pmhr0yq0tGVS5f+8J/8oyzL+v1WpVwETgEdO9NYn2U21WecPTSBFmAlZ9IqYTNpUqFSJAlvvn2z2iy/86u/39y8t7w+v7I211ioHbS6H7z/AUkoBIGUGlAAZ+TOpvozyLPnM5zxymMlaFCKhPB8p0jAzDErLtddRHYlXLpyCZmvX724sbbmeObP/oe/OBi616+/sbRQubWbAQogX6d25mt7mplUn3H2YAmotdau6xaLRc8LEFFbPRiNOkedVBnHcSyA64f1er1UKkk/fPNbb/kh+r6uNQIwI/BCoFmyyzPQrAz8jOnBnJ9TQloggzJjVuRYr4COIyxB3DMPHjxqt7vtVrdSKN27c29ra2f70WFQmtvZ2e73u55n6mVXeh6wAfk1bIfTntdzvg6nyuek+nka+oyXFpGBQ9KFhHujpCsc5RdlGFKxWL93b3PUGf3o+z+6fvX1u7cfvvfeJ6NBHCvzeOux1VkcjVjFYegCZoBnLW/xBTNT4GecPVgBCsdD5tFg1LFW+770Q5lESalQ8f2wUV24f/ux43iO8A4PO1mS/fP/+E8ajdLO5oMoHcZJBMIHmj3bzyCfcZHmye/c9NgpBf60/cbzBmRz/M84rc6W8zTk6X65/tgpv/e51/3OOX5eAFne1+bGHUx5v6aVKLoMdqRsT5Lr27KNvBF3ykWxulpcXV43nP7013/NiKsX5qUcIvbWoLxxJfzVrxZ/9dfJ9d8tvf6aeu+XA6mlnrr23otaHaat//91mK18M84e1iKiteC7fhgEYC2ATVWaZdnC0srR0dHm5naWZFEU1evNy5cvW9/96V++++DTBxcuhnPzODgagbZanFJfkJcFOduJz5ie5/zQsGFGZuOHfhAUDHfBWJVmnucNh8MwLF+4dMF3/Ual8J1vf3sUd95/508P9tgXlUuXZHUpdSAAXYbSEEbn5eH+Jsb51cIMplXUz8txZpxVpCSdavLJdV2wlpkNmyTKbn9yO45V+6AP0G9Wr41GKRtkr1CX1apfLJSSRt2EbhmMBS+G0cyx/oSvGAM/Y8bTPOellhARrVFprKy1jIiAQog4Tl0ZJtEwy3SzWR8MBh9//GG1XCwUvAfbR2lv1FgKViV5ngBS58p5dIakes7r064Mp3WcGS83LKzVgDZOR1lmyyUJFok8a+Hhw8fb2/tvf//3hBDv/fJvS56plotRv2spRm/1qGXuPmqjG4IogZ11XH6G8xknnKfAz5aMb4jTqriai7UWgLN4lKbkOI5S5Ap3YWHhcL8XeEGlVGm1DpIk8/2ilDLrdr/z48uBuPLe3z0cuEMOFPgxRClA+LzHeUp8EzLwfE71GS85zGwAADDTWkoZ6AyFEDrLbt68Kbzap599GifJ+vo6IxpjdHs4t1JJenJnJ7u8WinUPJC9EPzoRZ/GmUKC8xVqs9sp83sp55h0Sn5jk+eXnlLaTDucvGulTikwC6etk5+zUucOJ+f6mLw4gpwD5cYd5HztlPEC6CkRa62oWt1wyo/KTYq38eH9gVNRb337d/7mvffe/+jT5eXlxtxcacFzZTL33bf/9f/lY9ftVecXXRUW2tFCWe4P3dy+7nmPc5J3PXNOLO84+pSk8bTmZ5UzIN/ATKrPOIOwMcgIQMWyT5J6g561ulwOXT/c2tqqlqu/93u/Z4zxfbu+euHi5bmPPvjTUiUAyUyjQhkbtoBiBKymL4XyMvN8pvpL0Pd7xgvEsAULpH3f95zCoNNCY6ULUT+Khu3Dw85oYAaD0dpGIwyLgRPM1+tBSaYsGHF+BVOX2CgwpRd9GmeLmVSfcQZxABLgnrUy8EOyrsUojuM0Ntv7DyW5uzuPXMetV+ff+fmv4tG6zrJhp98XSblattSVoojCADv5O4qXlS9T+J/TVD8v/swZZxLtAQxAjLpDUy9ZP3AIXHK068p+t9s66L397bcdx9nf3x0Mkrk573B/txVlmUDfl/utXUnLRd8FjmfJbU8zU6lnnD3QRUQgHgx6o1FqUuH6slgKmLHfjbJMN5uLQPJg78AoluT3evvzzeYbN96oFxZ3Hx5Fw8SVLvCrVzH2S3PQn9NUn+W9z/gHoElbBQIYjRAOcmA1eAXhOYHrhm9+69sPHjx6/HDrytXrg0HsCK8/bBeCoOg1TVpoP86yGISD4Mxscs8wk+ozzh4MgCkQ+6EshKUgCHRmjTGe5/3xn/xx67B179690WjU6/fX11f7/f7ifB0RD7c7UTsLnErBa0igV2+j/luQX63JeI6fUEypI/GUC21ufvspReSe1rqfex3y8sNzTCR510fmPLV5bvhpy/k7edGHU/arz7X8TBkNZkdgyIULrr0HtlOpqWS/w7FxSiqkIltx4UojipIsMWsrG9feCK39/b/4i0/v3WuVFy+/8VqpWb13aePKuw/M1Iqkn7c6THmc07oOuc9PXrxDzmGMhJlUn3EGcbwAgIAzIVAZ1e9HRDIIAsdxDg4OAKBQKlXr1cX5ph8Wr127ptgsLFa/8723Ah+DwFtdXewMD4D8F30eZ4uXzNk2MwcAwLm/DCqJQaeu0I25iuvDKB0h03AYHR4e7u96g8Fg1O7GcXxl/brOkiRJ/BBKRdFoBgfDoTIjv+hXyxZ4NP3jfc4v3Jfykk31c860hbeeN8+9LkBeqBWDyQx3UYFWnLBoFAo6i4Ig2N1+NDfXoJ4KPG9lZeXjT2+tXcajTi8syu3NT41Chc291l6ttgA0BKg85/E/b07z+r9cUz03Su8VS3k7/9cBwdisq1IcoSO9ggiAVUsI0ev17ty7//v/+IfCEfduP4jjvc3NwoNHm1dXVoxqF4J56boPH2+lphj6TjRtGuv5v25fwss11c87uYv4i5LqL+gLLEvSDqdGo+MEIGSqModoNBr5vi+ErFRKURwfHBzUq1it1/v9e/u0++b1awNz4bOtx0NfY+C5qM9/Zttp3oCZWW7GmcNxA8fDwDFslFIitUIprlQqVmsL9MMf/vDuvXuffvrp5cuXO50OEQkOMOVaqRKGYb8dpbHw3SKnr14IzZcym+ozzhwqi1CnxaI/36w35+uIzmAQa61X19e/973v7e/vP3jwoNPpaK0vXbp0eHg4iuzli9fbO63Hd28HQY1EYTRIfXdmgX+GZxX4vImfV087T/3P7QudN4ocf2ZevfEp3ZC5e7DnXU1l2jz/3PFPuSLn1QvI/d6c4+eOJ6c8ozydNmkOZbJZ7o1e69y790//2dFqsdXbzXq9noPe3FyxUJAXrs33+/2jo53vfe+N1cXaf/Uvg/f+zv6Pf7dfvjp3vXJ1qSjTkjISAXPOK7fses4/THsfT+s5yavvkHe/vpSZVJ9x5iAgw8rx0HVldzg8OhpYoFKlorXut7tKGSHE+vr6/MJSlmRvvPba4uLywf7+j3/03YVmdWv7weWNxsK8E7jDF30eZ4tX2yyXK+1zOC+W2GnP64x9b6qitN+dq4eF+boxO/1IB0a4Wrdb/Tv3DpXWj24/jOP4jSvfD8Mwy2wvNTdu3nzQ06HU9dUq2XazVHljw9/cO6XxvxTPycsl1RGn+5lxJkEMQQ/1sGtUPBjFmfUzCNmY4TBpt9qucD3PE0KUSrU4Tn/5y/fuPdr1w7Dd2gI7tDrb3Hm4slAoB4MXfR5ni1dbqr+00VEv6rxO53ullCpO0lHPt06mXTcsOEkWq1GhUIiG0WGne+XmtYWFpWHLfPzhB9X65bubu9WUqmV40Nouaam58Hjnoft1GuCdsRCmU+XlkuozXgpUmgJljjMqhhCEZeFWYyUYGSztHbTiOK5V5qyGxw8f9jpHvht6jnN4tF8oiKWVpfrihccH8MntHa/UeNHncbZ4uaZ6Xpp8bvr81B84J7yg85p2A5Xzg4iF0A0loGDFPEiMBVpbW4uiqFgs37jxGhHdv38/07ZYrksp5xfrg/ZhsSje+ta3M/Y+udOTwVpfT9/FKXej9zI8Jy/XVJ/xUsB26BIVy0GtVgmCIIl0GutKqRIEwZtvvD4/P3/3/sPBKJ6bmxNCFIvF3d39xlytUintbO20epmiwlYrSfXMr/4M8pmO81Nvb6b0B+bxvCvM5llEpz3faf38Ms9fPWWf+by4g/NCnrsdn710eOwxduIE3vzk4NZS2vmdxXm3vjmUB+9/6P5v/puflMPV//e/+fvDkR0NNJr4+rV1xEHRL89//8rHv9q6fbtfabyxvrgquewXBiAcAAnWAQCQ9ljeCjA5/vM8y1VePfks5wPT9nXPq/+fV0dAfR3F4RU3y804mzgupSgco1Sr3c6yLAxDKSUi7h8eFYvF2I0b85XFYLHbf7i09HqpsvE//Ju/GsVhY24FheMX3XohKzfcydwmfmHex7PEbKrPOHOgHiCbar3s2n5nMECV1auSpN3fP9rZOdzZ2vGaaFLdGrU2lpq1WqPRoGo5LBUujAalR9tdz9iN5eLqKoElEAAMQAyIwACIuSrVy85sr34anCfrzItgyuvj0SDtd3xfun4xSbTW2lprtd7c7nUHQ8fhUafz2ccf9jqHjh/8+r27R/vbly4sG1aH3b70yXHSaqgXizEIeuZrXu1IiplUn3HmqBbp8OAwGdZ8V6OVbuADWEk6TtWDB5v1xlI2OCqX3YuXN/Z2D/vxKGqXOkO334fDflYpzzObg4ODKxcuAgjksRDn2dI7k+qnwcsajWfxi3+mZcrrUw0Up4Mk6afKhOVqsdxk5jRNnaC0s7X36P7dK+ur/9FPfh8NP3iwmWk6PBptbe3VGgVfJgxDp1B6sD24twlCIOPY9Pe00j5T4GfMOBuwGfmudVAoYxzygkJBCBEE0pFFIWWq06WlRqVS2Ny6H8ex55Uqcxud3shkveXV8MKFea9Ue7yLP/84ISB8ekF5tY1zs6k+48whISuUgrDop3HaG42MUb4v5+bm9g8OLNHv//iHmU0++eSDSrlcqTX8MGQOhsOkdbR/49qli1fXbt+9/3g/UmINXwLF6vSQIJ/26Z3SpaG8FeQ554c/d6b0q+ceZsrrkJf/n5vnn+fvnTKOYNoMrTyxmXe6lgDtZB/NBAwAFtDsZtVuL+z30rd/uLG27Dy690CiWLlRu7xm/pd/8gc77dLf/On7gwG8dW3p5sVOQWzv9gLG5dXV17tRt7O5W3cWUj+eLw7/5Kb3P71vEygDG9AZOAKMAVRAOXXUp25vn3c9p7y/efnqeeEUef3e89CzOvAzzgL4+bUvdMO5xoLm1HDcH3U67QOTiof3Dm7cuNFcmN/Zeiylq3Xmu1IDhX5Yr5pLlxYPWv0PP3y0vR1L4S8t1RC7wmGA3yg4oV7RZ35mgT/PTJ1HnZePnddl5ZSOn4f5Ike3xSQCARAEHOvDQZoKR4RhUQ2stZClWa1WiTFdWrqxt7fz5s3ywtLcwsUlNdi/f/8o5ppD5YFW6yvltRW+f59d3yaanwmPewm0+q9ldKDn4weeOZpnfBXw2d9x/ELBDxxhNi4uMPWHw4NaqZAMtc3cVr/f6g6OjrYLAbqUNRqFo95Ihv7qsmth5Ep/oXHNcr1zOCIcNers+lY4DMQgGSYS/tV9DmdS/VQ4radnyr1xrpTO+0DeOHO+d1op/TWug0Wgz4kpRIqloFLJi4htoh1EA1oC9PvJ9vYOCj48fNjpdK5vvFGrl4fDLImGjVrh2rWFo4E7jLTXKAlhCoEjfRCuhewpZ5uls2cAmp5p74tFAKB/kL90xoxTAwEm2vVB54E2vaPDQ6ndsl/NMlsthoHH+0edew8erS4vBp5xhLI2ay4sPNref//9Rzs7baV6vc4nSfSIVe/+/b3HD/pOwE7AIC0g05Md+yvajPn5SPUphceMb4rnvZp/jeOPc1Hw6Y9b6kYZWYIyewWvpB2I04EUUWatMemtOx/ffPPyyspCo3Jxe/NxO7s/V/vO7u5hseiGxX6mswArSoW37nTcygoRAAM6PMmuswSKX01d9hW1Rs44M/zG6oAYhNwbHAaOYxLyvNJic77f7/q+9ZyABfb7HWPU97//3YcP731469N4lLKpqBRKBbEwR1L2FhYqFzeufPzxPgBMjPDPHv8bOa8zx7Pr20nf8rEy/1vXAX3yjuPMY8sADOOiAIwADJaAEQDAfo18+CnvyrR9xafVMnLr3k+7YuZ9cc5x8q6bzvEP55JznKnjIHLG/yQv/fiD412ll9cfnsAYQAgKrk0yIdj1qdtpNZKkcfFm19peJx7GQifDRsm7tNoXqYl76fWbb5ETfnx7Kx7IElaTVrvoQ6VQ2Hq4dfmy+7/+Vz/Z2qn9n/4fdx+r5ZtFLkMROg4XtBMa3U+tkeALoFPS4fPuu5yy8f3UFWanfN4kw288vCd3CJ69zb+1x8LxL5NBM2gEsgA4mfwvhzlkxm/hN27x2I1nvnjJEAhGEBoAIJKAxMwM1vrFpcNRGpT9C2tLHOPBgS5X55uL81HWX7+w2mjMddr7R+1eqdCYb4YPd/YFqv5wSE5loOSH9zq72wKFWK4VhWBy7SSLVQkcO/BfVUWWgPDJD9BTP88GD3/VH5rM6snCxpPJP5n2p5Q+MeOM8jmvKk9+CL7wRwToOOSG4Lvgeei65DkIYCuNq52BIpss1YXH7cHRbqc3erCbLa7Xr1+/6suwe5Q9urOfZbpYLC6sFYwZzc/PL61db2feX/1i8+7jXrFYnG+IQqA8MuPhWAJjaOJdfiXJU0k/J67zCiE9q6jg8f8MT3QMHOuMY9PLtGGH03Nu7uJZG+gpOdXcp6S6feoRMl8sSR0X0QHHoSBApYTnoECWDrKcd5wdgbGwXUnDwBMg/FZXX7m2evhg/96tfsFr1KsRK85sdu21S64rG3PF7aPR1l7S6nkSRaVUaiyKomNKnkFrmdAYAkCwABmB8/wfxen4Jp4H+ezX5O3l8mK/LcBTO3wmRCBC4RAzggWbgR3v2cdLRu6ecKbbvxQ8Uyju5JlBIb74/vq+BQBJ5DjCldbz0FqQAgexajTnA++g3z4km1Sbdd8LNXQRcRTHg96gUCyvr6+TtsxZvV6/fv1qNOz81S9+bbzS0sblnQc2yaIA/XpRew57khNL4CAIBAASfNYm+jfDs1Ldnmz4n3F+5EFEzMxj8xsgESIKInAcAgCrwZLVGbBhpvHbnjO55ShnS8k3BsLxND9JLBM5UlQgo0AprRcYm4B0kNmA1EnUrZQrjj9ot/usVKaL6LJOor2dfuugneikc9ixGqphmQ0d7feC75UubsgLy8U+OdZzhJPJ0JIYlfxSJbSICAIBCciC5lfVAP85qT6xxiEAIiEzjrHmi0t+SknMzMiIwIwCBRERUeiC1mClNQZJsraWLTCyOXOK64vijAUeTDuc3PdbPEEgMo5nu5ujzZHMkIUkAGOYDLMAnbGK2fYzS1axNY5rHQDXEVApOIebvf3dQ9ev7HV22+1+Vr3YbC539qNP7t+FLr1xo3b/oH9r96HvLtcKBWsPSkXrOey6EFsCy2ODOZE1X6uT6XPkG0n4/NxenQAmNe4RSSABwZdMdSEEI7NhACAHkAVJIiCS7AjWmQAwzEyaDBucmd9eGUgCWCQiksCMjvfFzyYKdsEiI4BlNsxWK5WqlKXq9zpSDmuONOgYIxhS19XxSO3vH167sViqh51hK1VxEJSEh0eHnZ1PHjfr1cCJR519a8ujgRnEO47YcHBciGYcXf9KK3dSAFhLAJYZSoVISuk5nuNIFGi1VUYZZRJjAQARGZEFshCTGe2SzqwxBrQlIE+CECgQrDII4BKgACvBOMzMxnDKxmpiZGtJawRxvGWYun91Hnn9sc9glNhUx8mxnublLauc9+flsYsp4x1iH8iAtSBACOtKYDZEWhESoSNISklSisk0g0YlNQqZ2TAqxYrZKLQAe4fVasFKyNpd0U/80BchtWF0FOtPw9KaH7q6ZC+u+Tu3NwvMri13IvnR3YEx+z96u3ljVcbewvbw8OHHn/5u8I+G/vVomIUJFAaD7iBxF8Nv33z9v/1/7lz+HWfl4bD/8ytQJygkYHzl9SAOpjvfvCXCnXLXn00bB5FD3n3/Ui1M+tJmVoMmIcXFdV+MQQQAC2AUGWarQ6VUnOgs0doCI0vpkiTjMLJho4HAlQAsmFkza2vHyhszMCIbsJYYmYiByCAj47hW74xziQSwCAKEYyWRFzBJQnZ8NARIcrwJnzyOyGytZSZtrVGomRksM2pmtqy1JtLKAAAqA8YYAHDr7HtwtNu70rxIqVN0oX348fWK77rkuu4wSgKnVlupvvewe+vOlo1j8jZ9vvnxzwcrc7iwEXqaS5XLH7/Tgno4ij2jLIy968hgACL5au4jZbNusyxzXdf33W9dA0QkIiEAAKwla4GZMldEbewPYDi0oxEbhURsGTKHE8UoDBMKgQTWKNbWWjvZs518DSIijMU4IrIGQANM/A044F4G8q7SCzIxoTQAFtmQz45Ar4BSOpLIcxNkJCJEYLbWWp7MczH+HYitYsNsDDAysNZaC2GsBWCymjVoAlFohp4OyKbd3STpZVK7hUqpukhx1C8Ugkat4YdFY3QyUFmUSaWrxfatzdHjHcEm+d0/KPu15fd/TR/8mi98uzzqB4lSgABCgwUYgZDCvJItnuT6EupMOJ4slcSVixkACYeRhXAQGQEEI+91TRrifCR7A4z6MIo4HaG1eiBQBiZlNgwC0QJrbbU2ihFgLNaREek49s5FgRIUM01M/V+jLe6MFw8Kw2yQLAEID6SUXiBcSfMVCQDICACGgQ1Yy9ZyeyCIgJmtBiIGsGzAAgKwUYZpYu5hZmON67qZbiYddfP6hhOOlBV7j/euXbnESmvdr9fLaxuXIzV479efxVi8dPFa+/GtOdX4YITaD7kQhGEIDO1+e4BqNJiLhz6PWz4wkAGrmVgaf0oJc160gC8dp9xY9iQ5fiACD5sFkC4gk3SRDQIAMzPzKNChiypE15OpD9EQkoLV1ooUkgRiRsXIlrSmFAwyq+OaPuMSwHS8z/cCBosC7bGnHV8WS8kLehby4h1yAlFP62pba8aPhrXMho0RxjBIKLqSEceDsgxsaSzM+7E0iGgtMlvDbJEIBU6mNwAwIjCNj+kHfudwtXX3vfV52rhWuvPgcOdgb6F+MWoH177nLN5m1w3bvdb2dqc4X768tFxS3fb7emVhbTPbXZhvbD2MNre3wb965YcGOwIR6bhzHhFZZvwGnL5nEnlhTXiOdF1wCXzXRZxYy5DZsLHaWrCuIGuZgX2XKSThYFBAY6TqGFeS53AUycwQG3QQU8Sxvx2OVwpGRADiZ8ruI+O5WSxnfA6DAGgtANgsAkcYIiJ7sr7j2E7DKCb/RyQARmSedFU+PhAyngRWIiMws+/72tZ9f28waLGxm7sP3OKc0YFg7/vfuvjuu0lrpxXKrFxdUKkT99LV+aZuc70u18nJBtEHH0WZvapK2aXr1P1MlcpZ4CBoAag1EjgAwfSbxjyzbk5o0AvjS+NKZKOExQA8hwFgpKS1wJYtW20sjLMPmLQmsGCtRYeFMY4AdEEyFmN0HCGJSOJoREYhSeMIkbIY79V4vGwzA/PYSodPt8qb3PIzdr1m/FbGlnxkC1oxZALAMiubsUZAexwGa8GyYQuWGaxFYy0jm4wtGmvH5d6EMU9iWpAZwDqOc3DUWl9sOqbz6NP9pBNIqPfiwVGvJf2LjiP6/YTKUCrNdSNIU+PVgst/ILreqNRLd1rJ4z1eWL9y/95HiwuV5lJcqAZhwQEG0AIchNBqYeGVFOxUCI3nGdcxpVBrA0kKcczDkU1jTlJS2mHj6AhShYhCIIILwjHkZujEnoeuJF9Kl6SUBBKEQJJARECTavt8jLUWLDAyf65s4NRVjWa8aKwEK8CKcddhlaJOwCjWVmfHP6lRyqjUqNQolRpjjP4NgBmsZWZkPnlQSJKsZMVGUCnWWlvZSvNbwz7EySBoqp29La11sRxKcq0GzwmKxSIill63l16v9PaPXFuOVbDdHgyOcPTYqVTTQkG50oImQAJCEGCDV9RCJHVKscFUwigBtMZ12ArrHtt8mS0iVqxjrVUpM5KnUbFjjFGKU8dJU8vGsAFjNLNhpiBw+olGAEBGRCEEHAe/D5Mn/kCSgIzgAABozwJasBYAAcdhPAzWQOZNdzanlYc8Lc878DY3dSBnlfzNegxjMOf1PH9vTkCrW4iOvx+lJCklCmFQjCJIFSfKDCM7GGGUjfPsEZLx957cneOvE4aFk7LMWIMwDumi08N0Z5nmUi0+7GhSnMa3V958a6HRTKOtD98fCDwoFHr37z9cWlqQxF6wrstl86gZXOj+8AcFdVS+cYES8cHBqLn9eP6N6odXq/PJzeFnD3Q3WoduJBwy1s31XKic58fNaRDPUz5vefcljzwhmGeLETkPCgMASEa2ZlKIQgjDzERsLQDAWDYDgHGtzkAEzIoNostWKSDJkILKcKTMMIM4hiQiTWAYgQiZjy0uE0MIIrKl8SufH4omwOOKgkhgEYhn5vkzC8mJLYYQn7ZypYq1tiZlnQGABQugEdwvOxLA2NGOIAARrbKjZBSEhaPhENLB+nJo0UuSdv9ogMV42Betg3a9Xr106UJ/2EdG3/fLxerjg9s1fr2ziyR73eEO87zNSsP00cGRavZSoACJQFsAzdaBQIJ6FZ8tSWgZeeIaOc75ITo2riAyo+MyEBNbIxA0GAR0QFvILAwz6Ed2mNg4klEGCgWy8By2lq0Fa8dhdoACEYGZrAY41urhZNobmKxg4zJjiGBgVgzrzMJGwImzH9EqZAOaeBRZqyHJINE2y9CCBSJgzr2V+GxqM5G2etjvgk2CsA7ScSGtL5QHmVJZO3BEEHhxHAfBShAEnU7nwqUL8/PNdrudlg65ZY8Os+aFmMXg4L5sDb3EG24deKX9kTYlNghWgZFfs4RknhbwoqxMX2vPKydms3GIqrAw0bsRxdhPhpOQF7LGgBAWJIAlci1mmFnIEhtFNok5NSazwhhiAZ5AFAgGyAIzIwIQCgSliAgYmRCsRmYGBkYGhceOtycmOwCEU4ojfGl5cY/gpPAIswEgYxQzWjsYsQWbppxp1NmkAhlYyF+1n9byUCAYY1QSNVertaWl3lGGeDRfJu71Dls7xXCpP+x3Op1bt24tLS1dvHyxUZt79/13Dw4OvvedOmT923fvstcMvIriXqLDtUtXjvZbj/bjzLeGASyT9BgVGPVqShGJ4ol7U0iLjAhIDhAgME564+qxg2TyBCHy2LSeRKDHZhXEk66XVoMj0TAhsAVg4Mn+2x57WRgYgCRbPfmT5Ngfh2MLzYndzr6qdXzPOIqfPDNjOYHMADAYobXICDoDaxlOZPaXzKynHW9sgRnQ8aW9c+veoLe93jzKIuy3OybtFJxFAKlM+ujRg1qtduPGtYODg48//HRtY2XYcv1L/Z3up+rXl65fWZ9fD+acptYbP293/Q45NZfZAFmSwGC/ju5+5iz2X0uqC+fJ1CIW44w2ZCIifGqiaUXGsNaoNWmwVnMGVsdWoPEcREEYS0aOQZMFxwFhAeQ4aALssY0PLHzO/D7eI8jCZBVgA4btOHYKCKzKk1oz/9yL5LjAzJPVf3xb4wSPpzUDAoD5beLTgCWmcVUyslYJxGq1urQyt9npusV5FMNer1MriKXmEgCUSiUp5bVrN1bXl7d3t5Moefvtt6WkODaFiqdB7zzeWyiHb/7uRb+68td/3t7tykUdljBAL4UuW5UJ1xp0vomCSGcPyWZSDAwFew6Py8iMywoQTWapyoROWTGz4syAYVYpKGYwiSttpYSK3ZFAHBkLRmtGIYUAZiAgAGsMW2sBrFV4XNifYZzqCAAARV+iQLBg2GhtrZ5MdZVj+JwxIW8iPfcn+WSrhc+8iAQWJumKyAAS1LjjQt5hLNBxfVEkZYxk0ZxvPni0a2ylXGvo7HEcx7VGZa7Z9ArF3qBTKpWu37w67EcfffJBvdp87Y0b77//Pujs4uB1B+puXZbnfIdLWV8acThIPGXLmZWgDSCB1YhfS3XP3Si9KJHzdaIh5dOFsse5LgAkxCRZ5cQaby2YDK1lk3Fq0BirFApMHUkSPBeFtais1hpSYdAIxHGIFFgLCEYDWA1smJ5NoxyXpvEKk7AqY5g0aW1h7J8b/UMux4znxqS0Az6ZAzzZmAMgiHHLIB7XDkXMc/EBgAWk42qTCNYKByulyqNbn+lwwfFKjg49zzk42Nc6e/31H5pR78a117rt7k//+qdWQzxKC6VAktvjTRMXHb1w/dvOa2+td7f4oLsblo0RNZB+lmhrLZArBCMDsH5F9+qlEABAeIyIziR19fNCwRkCkhWuiWJQMegErEWwmCmX0ZNSag0cK5kqx1ppqLrSzwxpLa2mKBVJBllG2pIywgEmaSVAwWPfJ1eSlHB12QKA1pQqUAqVkePJvrGaqZRTZeIE0lRoTakSOoNMj509/GRZHT9zzzntfXqm3FPl+efz/L3T9kvPk05eXp5/znEmw+HfECP87BsAPGCgvE6vmBAjqZAg1GBGriMHR+WjUbWVHJHe+p3vtgvV+b//S3twJ6jPHXzrT+7/kz/8Z//d//Xf/exnPy9WpUuyszu6nWz90T//wa8/SDr8Z996M766/N27jwab27VW5+a9g3u/94+DjTirmbR7Qf397o5Sy5AACAVpznnlXYc86S1zrmde+/O8RU9M+ZxM25Nv4ldnJJpEJuc9Cb4/jp8BnwEAEhd0BoxYqwrpWsMmGYFA7bpYKjnMOLeIxgilRKZoGEEcmzSyiYbMNQKZJHiCXUl+AK4kRPQ9g4ipslKidiG1wAaZQQutkULfKYYiyyjN7KBnUqmyfggAiMDwGy17Z5wfiKyVwFaABkAgsmwyCxlYN8Ta1v3DQlWvz1/xh1mU/dz2/XLoVovljZWNYh2YHdeqYT/5xS8++84Pbvzgx6v3/O1b79/bT+NyeX13pz0YtqReCEqDsCqcLsEoHAdogxGvZkqlHM/w4ySEL542jmulxzKDjMBx2fURLKQpbFwCZtaJTksmSqxWiEJIkAurYAwqhWkGgxH3epykNkvsKHVIWsGMAiSx54ELBgUGgWFE30dtITXgZ8gCEVFbYRBBC2McbWAUQ0HqJLPd/rPjw0npQj61ajPnZPnIPd/zMX478cYAgAA2gg3YWGuqVS4V3VbvYCcajjaWK+vrlX53ExL/aPso7XUalYpfcrMYSxsrjM5B/+HGUq1WqdRqWtJRs+rVas7tz1orCwU71IW1vYvX3HcehxgVWDKQgdSZvsvQy4AEeCLP86ppFgpWa3AEOi57Fk0C2oIFrho2CrS1SWqTZHwk4Tg0V2VjMUogiaDkczWAJBaKIYkcC9YoY0nTJLrGkrTCB2QhBAqFqMF4DFowoi99sFYpBquUwUBy6ghj3NubT+XJHM/z0+S0tnIvaiOQdzmmDeDNG/+01+e3LMEEyKAEUQw0UFnWnK/ogRaBIMd0Bts1BxpzJQDd2tnySSaSth5v9/tYDsvF8nxYXq6WQ9CQZGFt8WJlnvvDLPBMY3m+f2CKteH6FeN7zAMJYQpSQWZBTnkCp/V4ndZxpr7+AJ8rWoY5yrCD6DhgXHYNGsPaHyvwTNZaAGNYJZRpMEoAgSAohJnRIBEdYiL0XUh8UsrpEzCzMqz12A/HzNYgWsuM1mZCGVDMVgEjEyPA2MM3LksLUgIGwMeF0ybJcjy5gMx4ejP+fEjF3CUgd499ts4LHWaBgAyZAKvZKDBDq4atLAnssFERokS9zv1s2J5vDqRfevRoF2UwV/Pvbj+OU2VtVK67199c++jXf9qHKx98lHQO42WM497IdZcY405vkEZDo2JXFsFqAOF5mCavok0OxlP9JKn88zlnJ2+ShIwSQAmWEsCwlJaZQVsAyjIhQ3QzUgKN4XEOEyMbRmYESaBJOGwQs17GzKniTANY0gBmbKvvZwTEBg1ykoyNGgYBYjBoGBFdKSQQMhtj0BjEybABnprnp8iZK247rXkvbwmYVjvIeX1qbeWLnysrLTCBIWBEA8QK9NDqTIm0XgiKBZcKTqrS1s6O14vK5bnNXfXhu7duvv52fa6xufNxo9pcWSsY1dl+9MhdXj4Y+gwlgMN2t5tltWRAru/0juSdDyNGh4rKOg6AC645P0t5Dl/rPspxcNp42ti8WxhJJkBkQWBJuxb0OPaZkRUxIxtkI4xhNpwZFoq1JW0otUJbTiwkI86s6kegLSjDKsPxPDcsGFErspoAIAPUic2s1ZqITCfRJMEVwnPIc5AACezJrJ4kwH+JK2fGeYGBAAQaMInhUdlbdkGmyahebyzW61FrK8sioQoKs1uPOqW5fnWpfPP1y6Ez7/r9bvexUl6qqxQ02AhLSXf4eHN3V8L8a2+8Fh/hnUGK5BcW0sGI0lSB1ABTVow9LT3gheoTcizL+elQx9/EAjOCALJsLQGayYeUtBbAgLWoM2DLqWatOHOJWRiQjEJbGyszypRKbGw8CzbVkGlINGgFWjNIFiiZ0SBbbZME0gzGFavbGsiC6xsXMPCE7yCBsL+xpPFJ5tzzvVbniLOmlXwx6DAbAI3j1EZjGFCzStXI2e8MGmVzcX1eVt1OSctERW27uz+o1le39vYikf3JH//k0d3DP//z/3F+FeQANLqJKu7vHTbWzNzcioX16mtXfAdGm7Tb6obfoqCGg8QHAPDznW0vNXLQJyLCGJEx8DPEse8NpQsoGBmFxyZVz6wCFgQKADHSBgAUIGeggRNDVglENhHZjMACZ0ZkECh0UWhHhKuZMagVpiMcDinNbBbZLIPIl8aCtWwAFKMVqDNAy6NegMK4kQ1dSxk4BfR8QJfLRVcZo1JWaKyGcT9ZBvp6Ac5fxGlprlMu43lqlchz1OZljOUtetOao6Z7e+71ydlQcOaDdYQvDAxLJa97OAARxHr16uXqIz/aNvP9+7Xh3l4zENWySh1z5Up6+4OPC17ju6/dUMnBwc6hzWqDLq/Q/YsiO8TuhwfJ//Rvsz/4jv1X/yKInfi/+3+5P/u49MM3qjcqPeoJYAUhgVSgnnMeVV7T02k5rY0kEgBIg8YYRouIGAAws7UoBPBxnzWTYhzDOPTtRPgjsrXAKKwF1qAMKsNKsbHWGPZdsMiaQUs0BlEDO4INGGa2oDVqKwBBa9QaWLA2PC4nypMqNQjAbFCCFsCOY3xXhKEsFMh1QfDnbArnQ4LNyMGabBIqB5YBi77v93qduVpjkKbzzWYfyEdeWtkwjMP+cGFp7Y03vkuO/PCjnXjkX718PbEHiyv1HguvJi5fXYjaKZss6nsjDAOKKgVHStCaBPgAAqwC9aqa5aJovN1lRCy447ox1hBwRuyAEBYQ4/TpCEhmw4YNMqeZVMisUBlQlnRGSqG1YFADGJaoYpExK0Rt0DicxMJaMooVozJkLbDHnIJibTNiZKvR8HiXgEBQDC0y+r4oeCIIyffJJQAC5nFq5JfFAjwfnvey8gouWxbYApBhBtbgVIPA37zz2Xd/9ObCYjGKo3Zrp1RUslytLNaj7tbS3Hq5fGm7vfvRp1HFqS0sLJcJ2rZ9seIsAnT6KvaKtYrbaoX39yAIBvONuuOYWDE6HiCBVtJ19Zkzu+ZxmuOUmZrEmyFCkgAAEwEKFMKSHhei4VFfnETS8aSSLFrLidUWwBoyRpjxfxkBINOamVMDKmWjWGWUZIDMkUZjwBhSGcYKlWVtWVtQBgHZakJkIAIgIrAaKoFhRtcFzyUHUaWshUFlGOUTwU74VP2d530LZ9aAU2VSbsgiOQIZWBfCouMgK5HGg/X18G7rUHHamFvsD++nSv3wB9/7m786fLyT7HYZ3UXNhTQ2SyvVX3z62e99R5E3dDEuNObAqX722Hy6Zdcrw9rcUhCkBBmyACU8ZFeYwSsXA48AIMfTGwAA+Ggyt0FIiwLHv5OEbm9yacZ1JgwDG7SAGQEAZBpNitqC1swaLYFxwDDojOPUqJS1NalCZM6MZLZak9WcZGA0jJv72HGJAsZxV1dmAgBEIGnGYXwGIMksW7CowWo2gpkn9YSPz+Qbu2Tn+fhnDQIwgEIIAWQBFJEHwI3VVbBJ0tuyOuIsabX7UdzOotr6d6/qP9ve3t5WDvqun3SyVqtdaeBypdGUiS4kc1Uz5NLRiB91dEsVVzEJfFHw2HNUGChgDyUmmT0/1/lUpfpgdCyukfvj2cNIEoXHyJPZHkcAk426HW+lrUYAQT4Zg1kGKgOVWmWMStEwax+0RpVynNpMgVGcGjQKpbSIqLVlSxZskoHVYNiCDzYbV/xHNoDI44YTiZ5UxRFaoEBrwWq0VhzXq5rUqpyJ2nMLARgACeOyJay11uCK0vySLD7e2b/nUo2s3bz/+MJa4guplJFSX1gtQyi7/UiF3tJcwfPi73372krNZ0fe2e3du70t3eVisYwHPcMOoikWs6Wa1yxkj5wMrKvUK/q8yFFsTrxUg6FEBCCQElCOyzwDM3oKDTNYHpeGH3doQkQkYQybzEYJpKnNIki1BbaDoWM1pApSBSYDpUgZZIOhD+O0RsXWGLTWGmQGtgnAscPcKrJ2IuQ9gzBOE7IoEBWj1pL5SQjEpPrdk7XvrK3W0z5V047/nD+1CGCBhNA6tZaArDIpilLqeQlkwnYrQWF9dTXLZMm/pXuDT+5+ojGpV4tDsyO577hzzLYfDdcLjXA+LAQ2uJswD0oB+0oN/Ri8cpQkgYhuXCi8+8h+dD9N2Ad2AbMXfeZfkdN6nhEAZJaNK0YxAAxiQQTIKBwGGjd1QgAQDhjNlq01zMwkgJCIyCSWkZXiTHOmITOgmJlhEKFRzBbTFFKFWhMzshKO0OMWIBYws4DjdpwMx/Oc2aA1DGCMQQCwKBWyUePcWtQarAZNELqnHB0344WAiGyZGYEVgAPMWhkhxOPDPS4PrjSLR5sH7aPwyuU3hX68Ui1s7m4WCw7QoLt3SymTRen+ofArev4CHsYgQ7daL19YLyRdXYS9H16ofwaFuKckZUtzsl4EwYo5AB9eUb/6o7aEY4dub/jF/sZSyQLbcQogkQAkRwpEbPcmntTjnpuT2LVe+4kNjwAcwQAM0vaz35RCCIDD7DcckQgAMNbfj20ollwgFySILDl+mwE6LjIPwBa/2K+bl8ZzeplwL+o402a2Tfv+abWG6cxdrMgreSCzdIQVzwQw8gt9phQeh9///ZU5fJhdr/30Y9OGPqSHpdrig0921aC63Fwd9Zp7BzsSuitrjf/Ff/3jP/uzDz6Q7vDSa+++s9VuJfNV+aDfTlD87MGFC/bB/NvtrWEJS4HwSlkUNzw+ygsV+3o1aqbgxQgoQgsAMjle4SxAknzxVCEJ1vKk4KRhIiayRKRSgKfd7McVIC3h+HXAyX/Hf46jX2fMmCBAa210DAhWU5qmFiJy07mN0sOD+43rNb+47Dm97v69C81w1DOVwtJf/PRdesu/cuUCc5ol8sc//sNbH386GozK1TIbk8bGcQpEBrQmBxx7GFaLBz3Te3cHaKni8cAvRKTO3kbvm0COegKOC/SO+l/8plRPeuuNEYgoxuLUntR1R+STJk3HU3rcwe8k4gVt3kzPLf4xnXTKq62RK5vOd7r3ywBPqsQHiEkURVLHhbIu1wb7vc6DXrjih81G2r390GlItk5nPyMtB4NBwzrrl1aWGjc+ff8OuJkxqUpHSQaVWuPWrV3SiXRh5+DwxvW15bC5tSd7D+/d/B4WvQGbaoIaXrGq4+N5IQdDOrFmR0nuamf1SSYZkgQAQkbPAThOfT0uJ48AoNQTBR4ATsoImmkL8Zw5TkvBft6ck3EaAAekJCeQaZwaY2qlUnN+/vBo13fKnz2KQWS1ucJSP4uSLa/8/X47W1u6GARBlAx++Dvf/+s/+3h7c99gvHzNGGM6nU5qvL29dloYrawsfGd1lUq1aCR+8Z6Rzty3HVHzjUkNNAMcfHEANb+0zlQGADlIn1R3T5KcGmbHUndiflcIk3qvTy7Z0xLYHE/dcU2xE3cY87Qx29OR2zo75/i5WsCsiNU3BRvWrLQ1OBy6vrswVwlLpe7BMBClbtpiWTrs7JTny6q35ReTXq+XdHVj5dL3v//W+x98YBTMzS30k4Pe0cNSKdjcHvb7gkTQbm8Lof7Jt383tsVPht2t/ejyxeVBPCiUKrqPcOFFn/M3znheyNSceKaR88rZPVVU9lh6g/28w+LJZ+1x+Nr4yCfl3FXelMsZ4rQK/HPntKxgeZzWCvO8rXWnBDoghNCIBKSMqgYFx3MePHg0F16yave1C4v16vwvfv3JazcX682BUSOvwKFb/uEPf/DZJ7/udHqMxbm5uhgOUmYiWyxUl1YvPHjc1daX0o5GnXY/TPXICYQb+p1k34hlYBeyEcCUbT9P7YRfzNeOkWMJPHGtU45Z7lgYP12+gpF1zubbajpZPo7V+7FJL2eP7c6k6Nnk+T6bzECSPOGRi3ErK5QKQeDt3b41d+1SSY4urdYOBoNBVO9GV2syC1RQX/RurH/3k48+6GftNNEqHZWr4cbNsh6uCsRCWCiYWhTrqxtXL18suD588os+NToby3UBJnFhaHyvhAykc7W5l9lcRyAtSGvpy37GFjcCwEnwKrNh0DAuCXPyc/KBE4396XkOAJa++GfGK4oGNmwtxH0NduT7/sLCQrlc7o8Og0LSKPU2H9zyC1cyc6G9VyqL+X/5n//Tdz9+Z3N3F4WjDN97cG/v4HGpJpiNF3hxmh4eHGptq9UqG9Xda/VbnoN85XLDD1gUvFY/yyJwc+TZS4806W8vnj5R1Z9WpyeRMM/yJAUlp0ZdXuGh7IvHkKfA55aQyzmVvH2JMTl3fdoadXlVGylH68nJS6e8/tg55B0nl2nHmXd9TosS0EimFkvl0RJyuVH9i0+PasUblzcOqkXvnUeHfbm4sbEB6qBYfeCvuHy0Wm96jhCjUdSslwfzJbDy0ft64+IlGdb9+v53q06zsDQ6ErfvtprLkov4d7803/1OfO0KejtYavYGb3hbGOReZZFXD/+LP5F3nLwiKXlXM8/GlHecPBuTCBQAgCZjhDuuIIOIBtlRcHpJ9DNmTA9xGhmoGildAtI6kS5U/IpS256HdSmjUTpKD1LT0TqLDbfa+5VGEPWzK1cutNujb7/1NqIY9oery82lRilJukFQTvrqUbfn+1ApCGu7c5UKMtosqjalDyT2MogqAC9nhzBlhBAIQFIiWGABaNgw2HGxmRc9vBdJbo+L57xHzf/eF3Oc/C94voeHcXM+DZK01onVRoIUjO1WvxJkvuxK7otMyiSxTjKMaHf/gXDMKO3df5ge7LWLYWVpbmXQS4u+67tSoKqXZVTKHotepcJBoFR2sFBdk5nUZji/Wowxc99REOdet1xHUN7785TCvMPkOaByojZzL3+e9ZyFUSgYmcAwCGSDDMQEcly97+WHEb/w50WP65WHuVSSRDIexf1Ox6iUpG23WmHBNSoFGMwV4kbQKjntUgE1+IdH+wLFxYtrg17P99xBb1Qu17/1+pu9o91eZz+KulYPj7r7adKtVkSSdear2ic42jxqHx0K2as0VNElSH77uM44mAcjjsu2kJVkgcDz0A/J8VA4r7ZUz9miwm9WqjxdzotUf97HZ1KuK1ImC7rX6wQV15RqOs0KHiqlZCDrjYKHcTbsWJ2lKR/stdIRr61djNM0S7hcrPohuaE83D+aX28aY0aj0UFrL00GlWbhoN8O3PnuoNtqd4rF+KjTm6uoerOCdwBzat3lh8DnWOzzwjhybFXTPm95x8nDBwBkIiuIpQu+S0IIx8EkA7CzvfqMF0hm49RAyRZ92YNs2E2EXy6G3qDfkjSol4NisdluHSRJNwQns5RFfjdNAqfbqM3t7u+uri93h+2tncfzVa0UOk5hpEyW6MNBHCaJ4XRre9MPw8XV5txyZWt7Z6SHjtP0S6Be0g6/JY/HpVx8lx0H3QA8D4SAVIN9Rab6tLHxp+VfzbOg5h1/2vLWz3uczx2BJDRkFgAcIYpFF0uebRkPY81sRCGBahr3hHCKxVJQcAZHiXQEcm/j4trGxjqDefT4YbffKgXzcYoJk4nZkn/UG8LOTrnh6gQblyvF+mIg4ge3dvp9a0n69aEaTVcHPu8653XWyHve8pTFXNvBlK9XAhCCXAluwK4PvmulY4kgToQxeZGqM2Y8fwS5nuNZsFmSSEn1er1aLI5GIz8ERB7EfNhRO60kjo21NukPdSZVAkdHR91u98ZrVx5s3d5p3RWe6fZ1b6B6oziOFQiv0xlt7e2B7169fHNhZSkj2zqI9jYhHVWEEyjZe9Hn/bwoBlgrQqMJcw1slLEYUMHjoq+LARRDkM9sIPL8tDmbjOfdxdDxvlja6Gy6b86zlNqcZdnJ6W1mTitWPy++4Dkn+VKODmf1dJ6IabUAyrnDS2G62XFKtULF7GQ1B4MFx9RKdTWUV5P01vXam1vdlV8d9K/O67CYulImup/EyY//4DsrF5Z/9u6vra2gudY7EiSdjQVv54Bv3Y4vrW+sX4G//tuP3fT2f/q/wvVw/p2/lv/Hv9aD8vUfXB2+ER78+3+74tS+eDx5ESbofrFzjs0kQ24cM3YSBiLGqSKI8FStBGTOwJ5UcHr6ODIEq8EYPskomxxHEBzPMiktHV/5dkSI4BJIgtDXlQqXS06xDK9vDNmg1WQtWIMqRjZsDSibOfxqm+VmvFik7zsBSQndo+5SqZIodbD5cGGpFMdxuVBwHGf3YGd1cWl5QTRqPZXGSvEbb36nWt7Yfdzf3R9Vq431S+H92w+7nQPBr2utG40FZFUMXcMGgJzR2u2WHgiebyShs7r9sFO96paWomTc5uUrk7sBPBaNNHnDZA5nmn/zg8xAEhiYifHZNdSkTATOk0ivcQdFHCeCjr9kHFQuEIig5oFL4Hgchrbo2VKJw4LxhLDWBQQiRMHIAB5AhsxMPjB+rhPrtPnep8S0lt5Ts2DnFSPJPfwsVv806Q8jnRVJQzwaLV6+cHAUtzoPLl9qZhmUy6G2WavVWlm/4Hsd1ydms37p2vz8hTh2R72SirOulWsbjaUNHA37lVqpPPL6mRuEInTpypX1q5dMb7/+4REg65XlCNzSwWF3cVXU10c7t09pqiMDAMnJA4OM434K4lk9clzTARCNOC6EyJP9/1jPCkRKJIVDAGCUGTc5IKA0Izqu+GItEhFLlARr9cwRIgjQ97HkC9eH0AeBwFYCABCiYSEYGMgDZvYcftVDaKbleTuf8hTs582035uv8H8xec6tLJNhEdCwIzkslEZ7QwDQdijAKKM6rZbnYJqmh4P90WKyvPzmhWtmf6sTDakQNJIobHf7YblYny9fXrsshBMlyWefffLaP/9upcCv3bjWLHV22sn2XlEl3WaA/ny20zb9bFgNg90p72NeYLUYa/z8bKI7s/QRAMAeT3J38i8kCY5nPjkANNkZLxSFlMILgS3EIzDKGGZEBHAm5V4IrCZLLARKCa4LDoKU5LqADiCCMqAAdJeEww6iK1FKkC4LsAToeQCfC4x9UVElef7G03r/tOQd3syE+qlix55gHDkOdvvDKIOl5QvSqvagF2KiYrGwcHn3sBVnBxKKF5ZX69XewdZBsVh1iQMPa7WFwHOifvT2d+d1Et258+ju/Yc+fWt5udp9aDe3d71awvytx7ePatdLTqmzUVec9kNVmXacefPCc/HpvqZPsryO65ezYLAABOP9uXCZmcEBa2HcGXGcfbAyb10X/AKAhTgipciCRcZaisygFGjDSWaNYcUIALGGGNgxdphR6AMQgAVrIfS1I9HzMPShgBh67DjgiHGluFfD2XZa5Ja+OK3jP9ej55s/p105TysJJk4VGSr4aSnweoNYimKz6Rp9F9H4PqEBp1Da3D30WEmXEp0INo2aVyqV09SQi+V6AazujeKC51RqFRbO+oV1IH3z6vI7H3486I3qi6JaGbk2S3S5F8evX4idmHa3Pm8V+wp88Rovjs23x/a4ycz3nAxxrHWPxRIREeK4DwKfJCkR0bia02pDOw46niMlWECrXTiWZ1kGibajmJPEDpXJEqs19BJiYxOwJhbUI2TUGqyFxQXjOVgwSICeg4xAEqSw4/rLX22vPqvKMuMpplX485ZIS07gQSFwAnKSRIPrd7vd0BwtL9c9t58M7TAaVgolmbi+L/d3HyX9fUekzDvCYeENWntbQL7vF0PXlkqlhcVlbeNQQrVZ9BxBtZpgWQq31y4nidPo74m3l9pvXw0//iwBKJ7CVYDjksaIgCgEkpwsmtWSHYt5ABjPcyGEEChh3JVoMtkFIkkigrVFLQRLaaUrCWg8DYlAMBuDmaVEw3AoRolNEptZe//QValRqbFGa32cnGohjsg4KAk8Od7hg4NWShunDsyk+owXCE5MVDpVoyghUQ5G7e25hlethlnncBSPWkmrubgaHTi1QjAYDNSgU64Xo+gwsckoHu5stavVlWa5GATOKB5pa3d2dlg0mU0YhsPEIy6Ewfbl14NPd6DTKqkj88ZPCuXaCKB5KuO3pBERgYQkSUgSpAsEUKs4Vk/0eSFQuuB64LogAaxGrcW4EJsUIF2QEpplIkIilsQkmQDHW/TQTRmFyaQmiuqQZBQllGmAEPpdEQ0wjllnZAMACxYgVSQMKDMu9GhRWHYsSB47iaXIszk8fUo5YT75+eTTvZ/cL3wZ8jydmOMAnVb7oJyqOHnI07IR5BxHP+emI895+PnHz3ke6g3gAdv+MGrdXb1U7mE6f7kUJrJz+Ffl5XpjpXitVBnsj371Xt+I70aWe739BADkyq/evZVkUJTli2vN77wx/8EHvzSeKvlZ3ZV//3OoLNy/uLSXFBKCg7/4qLIzuM6qfbPy3qC9/8u7l64t+YUg1UBx7Izz0F0JvmsdZM85Ucj56U34YCAcxolJTAIKHpe38D12XQ59KJZtvUCFQBRLLBCLYTZxqk/86zjWxhOtTx5RRBQoUCAB1ecFMqJARIvIAGb8Nmk9RnYcZtaBtRwyMlsLWkuoWqOMYTNWEMY7f0881XlJICKiEkqjk/6GAj9jxjdJGhsXCBG11nEaG6c8jKK015lflCblNM3qIe7t7knXtdYC4H4nLdi4UBjWCtg1amNt+fLVt/7mZz978/WaBHcwOFy/sNoftvxq0BkMKlQZMbsu+c4hoO+E5bBSfPToUPrVgtdIjWVfKyVQYOCx77IE8I5Lzp3UPh7/t+CBQJAuE5DrMI2bBSKHvuNK8B0IQyiGUAzY90ESFwp8XHIVECc+XUSUQJ+LPhICENkR49j1sUn/yXLzdPlGRAQGRiDiSgGtRfBI2+PKrogCkaQ9Uf4nqW7j7kxjqf4c7+SMKXnenoXnzbTDF0IUCmAPdZZkOnOEL1SUmiyr1WoJQNzHpMCDXmdppSYlpbHeaimz/+An/2h5eaV2/fpqc37l4eO9duQkXZumHCX9a5eW/uZvfjm/vnq0PxgxilrZJvuL5cGNK6+RpGF7+/57H//zf/aD+QbHKY8SrbUVjnAlBS64Ujveibo4nswTZaTiMwqQANK1jsCxNU4CeEJICY4LvgTPM4FjXd8KyZ4z+ex4AjNP/nRdAgtPC/ZxC2IiGk/OST/EScwcoBh76pmQTxQNAGxWwBhkprFIH1vykdF3nxhMn9asuw7AV5zqp5XsedaSLp97354cZuX0xiRREkp/2O8DQLFYTD2v0x6G1iaJzrTviNLhfqfX73uk+8Ou51nFJWQySv3u91+TUv77P/v55s5QOLXugo6SLEoypdPu8NDwSqbl5t3N+s3rF9cal9YXrMwe73jtyPMKtaJvF2uUKjPIjFEghAgKHBAQgXSfxKUiTzqIIeJCU0kiAHIlOI4VgsdbOcoEAPi+FciutK5jhcOI7BYQgIkAeTLbx7p84Iz97Se1WCez1zAc9zudqBKTeS0tHG8icDIWBoCG+6TPIkxeB0SQchKC/PTuAwDQIUSeSfUzxIsKoTk1pvTCOY5Tb8LoIa+sr168uHpkSmakaiWl0sOwNF8sXL57a8sNKVYDnaVs5O7uYdEHZmcUq8PDnW67X63OWwqDgkxjkxre3t83lpIsqZbr90dbNfQ8J1tdFO2+DTyx1+q+cWUxyfTFZRimMByituA44Lvou+wKPOlUchzAPr4jvNS0iOwIOw5fdRwGANIAOiMLQCA8dgWTawUjCvYCguMCEuMQVwAgguBZWwAed0NKY3zylZPe48zMsQE4WXqeEmOFwpP+C4g4XlCYwZVPJvnJWsDMQATw1aLl8qX6V7ulM2Z8Edbagx3R77XWm7Lf7x+MUiKSwq2W667fcLCcZbbRqFVKUG9Wk6zvS3jzzdfXL1379UfvpnF68dprSjmtdr9c9pUxjlNQ2pmfuxBHUG9W/UJpYa7U33vQbrcrtcWFzEMz8NzGfi9baphhBFFIhlFKcAT7kgOPEziR6icV0BEASh6SBE8AEQjJEgAFE4DNDCIKwYhILhzr4RS6k67hT++c4SS6DuDYEGAnc1IIfGoyM7O1FhDRPqVlIJyY91yaxNVO/okmXyTlRNEez/xjPz+GPvxDpfq0S8DzXjLOzV437zp8s6M4daa9/H7gmBEDiUZjrtV6dDiUl5Yv4Kjruq7N5OGwl8YMMrlypVYulVr7rW+/sf6tb71+79HuXstWKvVWN7txZTGLWqmgerFcCuYKYk4VStZ0SvXC/GqzKKLSyrKFUuugtbO7+9qVudXV1f2Dh4tLOvQgzkRmEcgGDvuOlQSFybj4cw+kJ5AEEJAkEASutABIFtwCTeS2M2laSBIQWarjtDZGRCSePJnsGHxGeqMxTMRSApy4HifNTpmZ6XgHMfmQHfdQAxZisog8ez0RUYixYEdEtHZyTEnwVaX6jBnPgzQ2aDgIy+urC7/6+M5olHqe193uL85rz/FYOZVSbbvzwHU3StViFtd///cX//KvfzZMJLn13k43i9rNql8uu9ompVqpcCA59XSSkC8KpWBhqQGm5xeWPa/Ebsmlh/X6orVWUdV1DLEgYg8YwEgC37UOgaInMepP/G3IAA5oGkfICIMWSEoLBL4rx8VYLQEjAsGxncyeSF0iIJpszfTEIj8RzmxxbG972iw/1imOl4MnBjxkRHmsHeDkF56YFZ7RQeDEsHeiRCT/YGdbnhQ9Len63DcOL0gLmNovPaUWMO31yW2CMG1uQl4+fM7xnVA0YAsLgwfJ1U/u1a9vzLcff8AyvrtbUnhosQm4tL91Nem+/sFHt/6b/+0P//f/u/9bFB1eu3y5dbg9zIalktje/uytN970eLBUq/VLlEZiqFTJHV2/spAdkS3+oN/aGg4PLlxZfu+uqwbq7dXRtfk+iHho1zd7fmTBQyNhxEIMjJOmkz0wMwIgHWfp+K51yVoCRsEC0AUpJQDIUJ9spMdmvImlXcKJyW3cjNyOlwzjMMDYb/7UZUDX5ZOrNJbJ46nqjjsvjTcCCAhAyACQHseDID9zZZ2n2p8+vbcfx63MpPqMFwZZMKg8hw/2toJi03XBZdlP1Up5YeegFVaL6CS1uh4NdgMv4NQsLSyuraxqraUQxjYzpeYazYODgx/9yRuNuZoyBxgguDZKoiAIFpebt3f6SZYUgsrR0cAY4xSDdn9okl5tqWnTLE4diwIcACCdSG3BWAQAEgAAbNEcu7JOFlVmZgRkMIaJYByGhpNt9FN/yifz/FSY+OiPD0jH5SVPjj/+uvHS9HTbtaePIL+KBD5re+CzNp7nzpTne47MpSoZ+b7p9Y9W19fN6LHwje/wQrV2ePC4WOiDzpbm4273XtFd3763mams3e5UaxUpHd+RZSkc12kGzeX1ecdxBqOea/uKB0YnTuDNrcz9zS/vMw9KBT9ptx1RqNXnAdqaPTcQKksNU8ZFkQCAQHSGifVdAADzlMV74t0KnprqDMyTKHZG5om+DRaQxuZ2YK1hbHg78YRbO35l6lySp9MHTmrU6GPpPVEETvT/YzMeAQA9idJDNDCT6i8lUycFT/0PUx4/5zi+BNUdoZeGfqHkOYPWKLEReWBGbcf0AsJYpYsLbjbslsvX9x7u1eq1NEmDMEjjtNPtdjqdQlC4cu1yb3Rkdky33VXmXrvfXi0H6Sj1AgxKDqey1xskGaRZo93pOxxVQ3UxBNvTqVaaldBgAVzCLKKnQ1DyYGYLTEzWsjETp5plJAl2bCdn/JxefbLy/sae/Lfwm/N8MgBLAMDIk8pl9liJMDyJrSUS1trjmJxj49wZlurTWvLPPaeUTXpehDpZkJRpPawVF0fDTlgkabNYDYb9nXpVzhdpL+oFTlE6cdGVj/daD+8fLSwtjoajaBSlaVoICr/zox8g4r1790rBUhQl7WE3SZOw+PrO47Zfzjr7+4g6TWMjlp1w4d6j/VCOjsTg5ver2oIyJkkNITMblGwt0fgG8CQK9eQxE8cGdQAYR6EDWURI1VivZkZAjUSTaBnrfP4OTMxpJz0Nx8643ygy9yXwU8vEZF5YtPxE0QAAhSdBO0x0HJaL4DkWZlL9peRFSfWpl2YLknQWDU2QRv1ovuGjcpJBbC3OLxYbtUI6KkT9OM1sarifJN1+f2VtNfTD23fuION3v/8dgeKTTz+5esWmYphFAJQVCkKC//DuzuK6z2A8F3q9ZBC3w1ra6kbNAhmy+4/7EVQYHKVYeSgQNFm/TGFBnwjSpwNXiAgskDMOU51UAbUWMm3HlkgcO7cAxy2ZOBur9yfGs4nq7olJ0uvxJGf8agU5eWKfOxbsZmJ4Z4vWMo9jb5knwh6ALRAz4mRX78qvHgP/vKXoeRFDM04Vm0EaDaUZJsFQoKvStBxSQ1YSOxiN2O9RMSx3tgeOV0Av9Mthv99//90P3vr2m4Wg4PquQPHBhx+0jo7efG1N9bnXTZsXa77vD7tqcLQ3v7yeqdiTDpHc2jlYcOJ6ffHCajmU8Z3bd4orqyr2mEGg4waarHWL4PpPcvB4EqkGAGCJCCbz+GT+AIDVYDUQjaPc4dj/hZb45LNP+dHBoiUCALR24isfR7x8laX56f7lJ3Hyn/vXyciZESfWhPHxrWNxVltuxgtEoOkM+wU/RVZBodTrbZU8tbq+GPdMP+pgy6w219ORqoRFIFDIoR92u93WYetHP/qh1voXv3in3W1Xy2VflruKht3oWnW5WCzufjZoH0WCvc3N7csbS2trK7tHR41Goza3oc3g8Kino66sAJG0hp0AiaT0rCyAFHzi06bjwuSImGZE8thE95RpTYMFADaICISMk4qxLMYT0o5XgacKRTMbM1ks+JkWDF9JjX9qu44AOA6zsZpOdPvsKZH5ua0BM8tvMu46d/XKGcPUysQrph2cF5vFpO4SARFYC1bDuEBStbb7eNSuhytrK2vvfnTQ7oa39tPV7Zi9xk9+5/VPf/WXt+8nSwtNEY4OWtnfvlMsps0jtVleOnzzR2/+h3/32eOHu5VKY/twGPd6NsBIbN3bLL35nYu/ePQRpsGvPq7bUomW/uWf/+LOa+vuH/+RPkoftQcr7/xChu4fsEyurrb3WoUsdosBoEnjSKIzcUATATGQYAAQkkuOwme08UmhmE5qjSVmNgxKISNrjYwsY/mkzty4qpxEBqzNZXwcGS+E5eOMtHqRAYAIgQDsuC4FMLPiiYOe7OTZHt9wq5840MWkFD0BgK81jJOpxhE7AADAjH2rrT73CRYzzgHjeQ5P3MJwHAqKwO7K2lqlMlcud12/Xgubg86d6zcvIetMhwZrYfXC6nJSrZbnasGHv3x881vfubz21v/9v/0PvjO3snG93U6sdoVw2CgCf6G5/Oj+7srShoelIChtrG4EYaFUCpQ6GPVGQakEWQRxu1JbK3iZJ9jzBacoXSCBiTDGCOEwWADBTGwBhWBrgeHYYQ5wnKd2POclgD42hB8L2HHVF55E1AMjGEYAThJ5IpmFACAc55UrTz+dGMOWxwo5kWWFbMECCGRznI6jckqqjC3zFoAVAoB+IvtmBadmfDNMhNHx7wRSAhHsb27WawsW3Dt37niO53ngO0YHFZeIhMdysTWQq7a2uFpZXGwWvM/mL63OL771H/7nzie3ae2ybDSW2LFuj9EoNs7a2tVKcan14LAaLnpOaX/3cO3KxYODvmOw4BS0JpFBOuxuNIu1hULgdAPPlDzBAXoS2ZHEAFJrQBTMFpBAkDWMKFgpwZ8z143/FEQAxo7tZJaZrQFmZkPjoLfjj8DYEDccCGuPU1wQEFkIEAI8h0kyHheQHX8IAIwBRisJTIqpYWZrNSFypr54qmeJPLnM+viyawBE+VVDaJ43pzWGV0x/P3vkW+CfGOctkAQpgSQMovaFC+vGwt37d69fvWlYxXGsWEiyXlB0S02ICkcjZ2uvf/N6pRKmP/jdb//i7/Y/+2C0svadw/YhhWZl5dJQguHPysXy6mJjd7MjqRjHhqxptVo//sn3H93fL3h4ZX2ZiA4OhnuPWzcuLIuSkKSEMI6H7oAEChYAmmJjEZGQaRzJB4gOg4UTcfr5fFIrGHk8z60mZma2RqNK8Tjn/HjnTwgAiSY2aK02BgCYCKVERHQDi4xCABA/7Uv3PGs1ZMwqI6NQ60koTppTJ6LXG6fRAwBkxzqUpXFw7kyqz3hxlALhSt9aAHKZU531VWpbrT5ibTAaHXXSxsJrLLIH934t/mD+jZsbf/eLWx/9+sNvvfmfbB4e9QYjGajlmhIC/KI7v7y8+c7DD9/fXFy+Yq3kgllYqvkUoe7Ww1IQBLGysQky3a8Ugr7JkI0xho1JrEgUEUGcSikUAKAlRCQFwmHIQDhsUjyZgSfZZgCADluLzGw0WmDWaCwicWomqeiTfJlxVhqiMUJry0zj/i3IJCUgUmGAx7XlgJ4y0ZnMKoXMFGeYpqgUZxkxc54Rq9UDALBj+5wFCzCuWKWUga8YQnNaPO+QmHMUEPpK8cx9IbAWtAay4HvsecFOq40kHYGjUawAFpYv7R62mgU7GhwF1RHpFGFUrweOV+nu7H3ve+urF1zlghxQpVAo+NlC0V1YqWxcXP43/+5nSqlOp1dpVPrDwdWba9Wqee1GPerL9jDp9Izy5zra/+xhK6yXyqFxE9uPdH8oSQOk3GdgprHxigDQYUxJSIYEAmQ4SWUfO+EYAMBHqy0xgzHHqjsjG0xTZAYL+LmcM6PYGADAsfkdkaQlRBglE9/bsRIwIU5BWUhTyBIcxZjElFmwFp/KanmGwQBgvEVnMJOQfDDMyQisfbnMcmdhM/Iqk7vU2skW/eTPsQl5LvCE48QxV6tN1yfmkRfW33r7O598+P8tSii4iLpFTtxooMOj/e3tm3NV57XGiHZ+sF6++1m1IIL5sl5bdNcuzpFLYehfujJvOFBGBQVBblIpeYvz9GgUJ2B3Onbg6phD5XpHRyPfhUhDZ6h6Q9dmoIQZkEMWAUA4E3u4EMyI5Fr5xPEGMJm3DACOYiZj9TgyFY1BQLYZKYPIwDiR+TD5ECZjxf2k8KMDmQUhIVWTLNWnUtkZmfuRSA3qDKIUhxFFCWgGrSGvYW+STG6BtqAtmuM4/DT+ByexzpjxVbAWxt2DJ842O3G2BSVnc3PbMF1cv9jee+/ocH/p8nwaGzZiOOyFBWyURDGQjZIc9rujeASx/vTTn37/j3+81X6MmLZ2jqruYdH1GnM/3tvrLC7Wk6xBbvnWnVsrG8ss4mo1KATKwrBQqCUH8Wf39h3mH72+sflgN9GEmYwSG0WWmGOjBtIrmXFIKZAcjxZJAiRUqJlnnW0TBd6iHXvB2BIDM4NVBMc5qsae1IgDGCe7CINjizzCOFgeJViATNPTVoCTWNc4RW0hjijKYJTAMIZET67eF0MAAAoALGQatAVrwR6XUHymtLmcMt9YT5sXfcYKV52WFpB33bJTquv+oqr3THt8mVPPv6+hWQbbhURDIqFYh0WCaH9fdYyn/GqttvvgTiiiSxfmhYxu3/rpenPEo82V9XJjzbn92YODLt/aLP77n2Zvv15dHX7vzjuRUVgxQlPXKawWFy/87Tt3om7xcF93k+2Ftf7lqyT1YTgMk2R9qaSP6oNf3b+3GHvfXiweAB2JD9Towop478ffuvqv/9L9+VbdEgxHjqjhpmVJ6PkculByOPTBESgdNgcuEEgAcq0jDNG41BwfaHkSssrMAJMmTVoCAFlNYFFrNCmqlBm5UYVJMRkiIhKEUgIQsJzE342bwsBxvQlGZRgMk0KIjUgsjsa90xOAsb1tfOOOfwmfet5cAPdYk4oSgJlUn/ENQAQ2eyLVx3CqdvY+qy/eMOwvzJd11Gq3t5vzG73eaOCN3rx8sdvt3rp1y3Xk+voqIo5Go15Hx6P0YL9drzQePLy/vLZyYePiX/2Hn/3RH106PIwVq9XVBQtRt929snqpUqne+Xhb9fnRTtuKbIh9mSTsXLzzPncffnZ1Le4n2g19cnX3CEXBBBWh9gkkQAQ0Np1pdH3rqidl2VzDBOQFTMSJRnUckDop5PYkUp1O/iYCiyhd1hlqPclFMYYFWKsoy5AIyP3CSHjMNJiMLIBRk8yWcRMoCzRWJ6w87s0IQJAr7ccK/z/ILHfe98bPvaPr7PgAAOBKyDJwCXwJwyFIALKQ6IgoypI9r4DSt3rUXZgrXXltDR+1R4cfIVZrtdrmUb/b7nreerVeNcbsbfUac42FRdzZ21m92PzhD77z3nufbD9qJ8lyFDEaJEuH3c5wNBReOBjK3a1PLyxdA1uEwGezeef2IyHmPr5XuH6jGGn981/vHQ4rUvogHUYcHAFkoDU4ErRFJSF2wVcEAP64gKRgkaHnsFBEAiWNO/PiiQv9SX13B8EgIthjRx0iSpeTVDypWiNOakahn9fTTgllQBlQCscxeWSeROnbcRA+TX6HfC1s/PpMqs947hABZDBuaXaMTfrRWtPpRN2F4ppKjzSmr1+/iGCH3W7B93u9TrlardVq8SjOMi2JCoVC5+iRQJxbqc4tlH74u7/7tz99p9+K2SAbUS76o0Ey7B6QSeulRq+j9rY2q+XD65Xv772bbkbglCsYdstlfyO+enGNetGje3/7IFhIPSEQRRwLjgyykABagkugABwX+gQSwHHYESgEOC64EoUDrkQgcCdS9PMTVYb2qRb0bO0kE25isiAABrAnmW8s4FnL+zHakkFmA8Jj16IvAdmiQTOOe7XAzMqgpUnT5S+xisI/sOXDeee8SMUX5aSc9vhfsrcnAEkwjs6WBEZnmR62h/1a/aKGbL910AwFgLu1ddDpxOvXG8NoezgcprywuLjoec7m5nYURS7Q/YePRUH/l//Vf/bf/+v/vt3qDPumVqtJKcuhu6e6vc5gaWOl2ly4fz+6fadz463eURJ1+2J/p1Jbceero8vXi07Z4wwe7/hH++WLfqkROJspg8FKUUQJAIHOwBJIemKKch0gya4EmaEbWMeiSkF4jPyFijeoAaJ4ci3G3WBIovy8Q/xzZeE/n74uCQQC+EAaHWEdRO1bYzDNDABkFthgptlasAa1BZXXFHwm1Wd8Q2iQPoAGq8EPwZWgoyxJoqDWeO07P7xzZzeOA7deffxwtH+UheGq7w937u8LIUSplulsOIy0tg8fP7xQT2qN8ps33/rpn/99mnKUZNrycNRDdI46vc3NewDS9zeU4TRlko1HDz67dLG9cPFKP2sODj5xy7BSj1Wy3+1UWx2j7bwEXQ5tMdCYuSUC8J8M+ellyzCDxgxAeGwskmElwWQwLv/4tE1+DKc4Ls1J0o6T28b91X33RMV/dk7SOKIGj7s5TjJbXQAA9AxbC0qTDa1RZJhjtqDBGExT0ApShcYAMw/0F0/1sXn4q0n1KS3zU/OiQl9OS6rPQne+FLLWd0lr0Am4RSAJaZZBmjl+7XAvGwzl8tL1+fkw6nfB9mqNy573sTKmXC7LsNjv9wFg3HgcKP7JH/7Ru7/6+O7d+zeuXXNEIApJt3toNQwGg1Gnc+XaNSLY2dkLCpeb886H75baP9JLN/2DIQz7aq4sF8raR+dREMOn8fL8ildoLy77FyDoDtyCVqQdgIkjcLL71WAAyCBJcMQ4imaSfUpyYv8e+7IYnyhBKiYwRMKyQQvsuiAEAkGlMHlQJokzx72iBmrsyT8R7JM6VgEy0CR31RhUjCgYAOLUKoPMNo0oTVGloDJgZpvmXH8NMJPqM74BmJnkpL66L0ECREaBq+cWLv7il595pbnG2lKUZUTlXr9npS3dLF2+eFFrbRzn+vXra2uV0Wh05cqVP/rHb28+eHzn9l2H/NEg3VhZT2yv3gyVUj7IarX6+uuvx4h3HmytX1oYDAz35q32g4YqLcTXae5br6kwyyzG7PZkmKy9Nl+Gw7nlaNmV5SGEKah9AABrQfMktnQ87U0KghERhLDSAjlWCAZAFse5buPZftLOZTKrCNGOE1pIAhG5robjYhVPtHWCOB3/f5IGdxJN45/48nkSrjcOsyPSAJymwrUgLWoELdkYHFLOhkIBfM4CP23sXF6/8Tx/e25/8tz+6ueEKbWDqa9PDjbHuTJ1Wfcp68znOXXyxi+Y+kMoL0P7ACCCpTn4+MHHjfWLbZ4TfDSPnaUmdga8s2WM7V+4tBnq4P/zKzl/8T/dvLv//cvD/+gnVfSdzH39T//yg48+urW+esUI8+FmZ5m9q5df6xwcMKcYmLU3r36ydSS8Oa+0USiH1rn1L/7rSiPMLqPB+nsLr69H0dwRl62QR492/uPvlr792v5By+5v735/feVuMoyI3rqcWUtZRnEks4yGEcQJ6gyy0knJCjKIbIVKgQAoYwBwXQsAAlkQA4Akm4YkBAtGR7DjoUQct2MhV5KdROlIskKyACRh/cKTILmne8t49vNbg3HxSBOhUqgFJxIzCZEGTZBZVjFJCa4LvoAgYCmt5xnpsOtao15UL9IZrxJegMZwEsH4QYwGAASl0Esjk6Zcn2+2+90oS3b2WrW5hVqtcdDaK3jO8mL1wnKz29/r91sLC3OIqrV1vyi1h0rqpOCo3uH2zsPPHI6FEBsXN25evxnHfcdho9JSWQKqwHWEoMP9vc3NR73+Ub/bOjw8Wl5eJgtSwjDSpVKpHBbRZkHJA5DMwloyRhjGVKHRaMwkkhyeKgIzyRiDSUcXpcTYeWYQhUBGIYmISEqS7ridGo018ySCJLNJApmFTJNWUrHQxkUUk6AaIcYfFAKFQGWEMiLTNP5JDaYGEwtJImMl4liohHQGVkOWgc3AleASuASOYCLrCCb7pE3NTIGfMTXTWualC4icROhKkARprMBAoeDderRda9RrjYVH2w8HqbO+vnHl4tJe6+Phww8X5y5dXavVBG7fjlXaLXoXpYYbV5qDUbCytmCMevQoTZJBowZLi5XXX79aLM7//d//ajQaDZN7hdLS44ef2awbBA6zMphayHZ3trrtCI2/uLhcr4dS0lGvM18v+j70eodoa2Gx2OkYC6AtZhklGSTWZhYzDfiURByfOx0nipJACZBlJDwWjJoYGZkNGGTBJkXw2IJFCwDQT61wWAIKxsBDrckVYBgkA/OTpWQMMyd2HIrDMF5ZJuE6PBihVphZSA1nCaaGrWGjsexZdNiVQBI8h93AjNNuJnfhaaX91Bow5b0+0yEA4BSvz5Tm0lNznk1phhy7lOVxMrVJR1JqCRmzaczNjeIeo0mN/p3vfMun7NNfPVosMBTjz97/y/7BsBYk5bp7uP8o6bdXl70oMoGX1KvljZWbg1GPiKolrFar5WrVkr52ZfnTW4+2N7sP795eWtkAQrBqffUSOurerUeMFgXt7d13kFdXLyZZtrOzLdAsrcxvtuXWbmK0n2jQGUQZJAYSC6kGba1/XAeOESci3QIApMhgwCVARDdFA5OAc20NMjKBYETDrrSUAAiWBIpJEngIsUXPA44ZEQPxuUZOk1/GPZ0nrjg+SZ7BOAGr2Y5jEAEkEBAIF8oFLQRLh8kdb/hZCiCy4yYWM6k+Y2pye/XlvH84BD8EkmAzAGuNGkjIQPVef31DHXZae4/9MiwGRaM6ESWVghMUONFHR3ux6quLC2m5bB/e/YRMEHf2mwtzcTw8Oux5gTPstuI0LfsXGc3ezsN+96A/1Devb+wd9JmFoLjfbhfr9Wa9HJY39nd3682ijr00HhQKgSPYylAIZ74ZzFXD+7sj6Td6B5BpyDQkKUQZxClqDYZR/EaBp8lUV+BKq4GEY4GBAZ1JbhwKh9lM6spbTYjGahDek203M7Ox492B1pOMN3hqeWVmw3I8ydmCHf82Mc4xChIAvo8+oB6X7rMwXzMwrifrHNe6mijvCPbZirHPu63iTKiPOa3rc17y87UF1wVXgrbgCh6mkUMZQVSteEet2A0zsN3Fxeb9e+8uNCrVGhInDpj1uZI753jeUZa1Dw+3fV6t1EquJCcMR+lof3uzXC1euHA1CIJfvfvOytKGQI5Hnc3NR6Ff9byg3e0nBX6jWRwMDkGSlBbRtDvbw6G+enFj72BPQ1GnKbJGHFmr/RC6Q9AGMg1RAtpCaicNzu1ThfEAnig1RoMxQghGReb/z95//liSZXeC4DlXmXxauHYPLVNWVmVlsopsNsluDJvg9Mw2ZnrFYPfDigF2Puwfs5gPg8ECi0bv9mJ7e8AW6Canm0NVSZbKShGZkZEhPMK1+9PK5FX7wZ57RFbFK1ZURTAzyfjhIcLdnrnZtWv33KPP4ZZymxtwiKWKAbWEEUaAUCAGCKGIVhDDBDBA5oIghTHdorYqLa73UyWfkXNtT2tCP1kcOghpUeuCUkBriJg3Zq6KueleGdRoLYIxKC0YyQz+zZameInni2fdMp5XK4iFFv4Ff8BOk6hdHxxCh1kCRjFG8uSoVSUQ6Wk+QTVJZ7OYj6nT37rSHJ9Ew51dhwlOp4FHdRYd7extXF6bTCbdYZcw8EqVy9evodV/+Zd/+fZvvIHUBiXvlfqlew/2bl6/GUXRD3/443q5RRhsb9+vtusqTxXAaDZIJ+bkSIW6nFmdj7rCzJbbzWZ9+cMf9UfjhjGQG1AKNANjHldfffLhn2jMNI9itzgv7WgRLbOusCYnhM1LazECYIgxUPIsY8AYUo4ckZCiGYtNsict8I9leI/BWUm7J8Nv0QEAQAuMaUSkOI+rDQigBQM2t0Ra0JYoY5gFZSgw+1KAf4kXDjcEpcCk4DZBELA2Y8yELpM2KYfO3tFhUJNJdiLA6XcOVs/PvFIY8GZ29NBD2agEQcWzNon6yWGFXjh34eHDh4PJ4Dvf+fZyu3337l0vKFVKQSaTK9cuJVHmur7n0StXXjUmL/tlaWWvd1xpeEh1qeRfIufynGHS/fzuXY2Nd755qekcHu5vT+LAoJumoBRoAItWGgR2mo0H8+3NqPk2VzRlo2K+HRZmCG2QIChFZCaZsFoTk6Mip6VbiXE8y4Awhp6HjAAgEE2R6FzNO6H/FKm7zAD8dLQsoUCpBQNIrSDWoqFoAYALgykDAKUII5AazGXRMhJojlojY09u0c9qblmwUYiXksLPxaIwgmfui75gnhfN/zPnny8UD57xOjHkKYRVIFN74Zzsyx1to/vb+zfPcSNMu+5G0TAe3PU4+o26y2pHH3ZXlpery82HDx7a8Wo6urm9+0EazkbHPU2d0tJKeXlVhO0/+uMfodVRhL5bnfTMo93dpY3zk5kyg1mlkr799jf+5I/+Slu5tNbyRXj1/Hkwwl8OPSc4jq5Q/peOpzlv/dsfTpN8cPUVo0WqhBChyHOjNAYezXJIMsvnfVQBAE67us1ZvU+ACWAOFL0Z0xzyBJQCShkkgCkSBmw23y8AyPp5rdESphIgHC2lSDgwAqUwQcQi+s4oQvW85IUgCABYFMMhhhTlcZgp6eLIfFRFH0ZrURk2z2Y1ABqottZYo5BmlumXXP0lXjzcEGIFjEGthvEs7g16aG21WRJB+PDB7Yqv69X2YKBm8UTleeDxUlgbjcfjyahU8SqVEgAg6vF0HM/icrl+4cIFLwg+eP/9hw8fcs6TJCl5tU8//cmf/Nn7fvVW6IevXr88m6X3Pvv87vb25asXN7bOt9vtO3fvjAa9UiBbDeYI1/EcBf5gTLsD6QlSDt1Gjp/d59qQoowE48AAXGKooT/9PF/c6eap4/MIVjQKtDtv26gMmmJ3MEAITGakkLc5RYogGFhESi1liIiFEw4RtQFCinIXBLm1gJRaZBaKzBmLQIGcdmF9sm1jEZqlAJQBo0BbKyUaY4pad79Sd5eviVXoJeb4cu0yaQysBaPeyCizurp69ZUb3ZOTw65KwoRyQZjL6ZRBXi27g+Oj2WxWrVbL5RVl8v39nXq9Xq/Xs0QbY6ZR5gWVTNqt85fTNO12+4S58UzFseoNDjnnG0trvePex5/cHvbHgonQL6d5+uDBg7u3HzEiGo2l81cvBqXKJK7udJJJLnwP0jR2LKG0AgBoKQENCjgBMMDpaQH705IvcPpr0akGmQWDujCVWwDAsxx1wkDNk1mAEBj0KZzKBaL4gVoC6DLOKRIGnmMpInUss0CoDagt2kIWt6Vzu7o1Zl5XtujdpgtvHJhcAgAoAkqBUZBJVGAQ5ie8EK7+t6s45d8czHMqUPVVg1HgupDnkGYQDcelUqlarXJK48xZXr/UP761u9tp1GyeZZTIdDJYW1l58PABIeAFTq833NvbYwK01ISwKInybnc4HDMmqtXaLI6DUuX9H3ygcvXGK68NJrrT6WgpZ7O0Xm5+fu/gpD/tD8ctt1GptIR/vP/o+PBwoEj+6+++O86cezsnlnquy6JJx3MqjgsyhSAElVJGwBeQ5igYpGc87Qk6P4NFa4y1BCyekvrcwQVF1vrZyb3ZKdkbIKRQBxAAAkocilRA6oLrGweBUgsSyz4AACpAakEiASDMgAWTPdbtbVGtTwIgybQ1BqzF3IC2VuVgALQlmQKtya9WheaX/9OXeApeNNf9spxzxkBYB6Mgj2EyGVWr1TiNf/CDH3mVVsn3u8ooknJLiMtq9TDJZizSs9kkz1PCVL/fDwLPC3iUTBmUOcdarTaZTFbWlqSUjkMZIY+2t71SZWlpOawyzkiSZZ1er1wqtdvLaaq2d3epQ6v15srK1qCXJlEWhmEQBJRa1FnFc0uBKfumtVH/0/cBc1OuEcXm25PK5y5rgKfQ+RcI/rRHKsC8BAWc9Xcx8zMnEcAZP3+iiC7hmFPLDWoAiSitZQwJMalAAEANFgmiJdIiUsLMqXOuqD9NtLbaAlqIU2MtGmJNTgxgZqxRRKPNMjTmZQjNS/yNoMjMiWdqMptdvLI6HA57vYO31lpajlp11gybFsdMUs/zRqMRomy3m5VaKQgCrTPkemVtk7Cl4VH/5GQgCDdqBErGs4gQ6A0m51bbiPSk2yXCLZU916MEEkrtxYtXCTG944HjcCGE55WWljYo5UGpcrDzcNilVaeUGiVnI5WWdbbMpESwrm0pAYm2gJgbQhiA+mk6J6eRfz8lwCIiedLoerq3mlMtmhBIDQgGrLDKF02dmUFqFcHMolWg0oLhE26xSKEDAOQAQCizAESmj1PeDKAxpODuxoAx1hiiwGqNSqG21hjMFSgwz5pM9QUsEtRf+up/SbzgjffLUhCYgEEHwjJQo+IoqtUqSZb4vg/Zo2h4VAtUs4oWHC584TgUxYULK7VaiTEWlJxL1zY9z7t24xJFGgoTz2aEkPF4eHLSTZKEUppkmUvELM2nn+3NsjEAMMm1nM1mvUla9wKqMZEoXdc1Cghj5VKdEDYc9x1LWmUqdebRUTKVw+GJVRqACXQIFTGFVLt50UT2aXQOpxVyrZ0XekY7P/epmYvGgMsAzrg6gisACBADJFQE0VgEitKilFi0bR4aBMBCRacUkFsApNTGoy9UkkaL2lpriedoS7EoOJcpAAPKWKMxV6Bf9ld/ib8BOCHkx0a0CZE8y7Iky4b94WQ203Fk9bDse0kS1etuuVzr9IZ+tToYdAgxs9lMmTSTSZ7H+/uPhHAvtFkYhlLK1dXV0rnlarUaxzEhRPhlAH/zwt5xbzIdj8uh8AUkyfDRLvFDdzg8ydPJdDo1ipmcVUpkZ+eo7cfD7vSo1wmCmuKT4Ri6CVrtgfWoaBsVAoUsc3Jr0UDR1/hnGVhxxMw934UnDIh6fOaTWcbFQYdYRGQEBJt3pCUEmF90WkZtCNVgDGgFMM9st6CQoEUONiNILQBmMTyRGI9GzfvDMWJAgqU2lwQMaAXGokWrDBiF+Or//unp7E9iUTcJ9hUzwS8a55eFRfPzvMa5KF/9mbHo/T7j9XMB8QjqTQADKgZgMBlB2ITjHlzchGU6Sjt/FR3+2BWp67pprkolzhjjlCOilDJO42gaxWmaZRkAUErjeGYMVKtlpYyUmQDrea5gNFeac14qlTzPIwTWlvxqtVqvVjnnFtFzHM/zGBNBMC/LYq1VxlittdbGGIrTRqMGAMPhcDabxXEcRUmepyPTzuwq8y+ArZwcD4fTQLsXPj8B33/683rPmG7kn8r2Z+2i5vNmgBFAsASAUkvREgCkp+VuCAgGFNE9jdjJU/Kkjw1OLQX12tNpOY9epru8xHOFKXKnUwADjAB3IQzBYxAKePTJ3f34VgUeVkQiGA08Jyz7WkstdZIkWZIlWZbnaZ4rq7XUkjHmChEEJUIAkSqVM8bSOEdqksymaWrtbDiOKKVa6+3tnDFGKSqlAIBzx/McSmmr5THGXNcNgiAIAt/3HccRjG2slZCXXCGEX98QjFIOxc4CM0trRwNIo3hyjm7vxw/7x428mmTuX/fovxDOdk5yFpMDAAAuAQBAAMYMtUgJEGagyJOhlhdVa6g1BilatOiKx3uwfSKWTizgLehS+GlSXxRT/RXjlovwd22cXzGhCggB1wWjgAAwAQzA1VqPzVol+/zRvWTwWa1ll9uhywwhiljTG45VnqdpmmSZlBIACCGMEMEYABAGHnLCCFijFfF9d0YDSqkyhgEDQhjlSqlIRq7wrCVZbrQCRDQGsyxXSg2HY/iibbxIB2k1qOv7gjHHccIwdByHc+553qVLZYp8FufVanWzucxp2TgcPHvn/tOf91lzAc4s+ebUJl8EtwluAIBaJAwIsZzaooCdcoEZBAbEAMfCRAdAtSsMAJBTOj+rPOksqBgbVjS85Opfazy3rW3RFv+Mq8N3IS/cxQZAgZYJVUOwUY3ZpfLMUmdjifuuSuNhHMcGTK8fF91KjAHGCCJlhCCljkOzJBNCEEKMMYw7ZcaQUDXNmGCMMIsWDOEeJ5IBg0xKhgwJIrcAYBCllNJoiqFFq5QBY84kXrTY7VptZ1pLAKCUK5UrpQRzaw4PfRL6gnvO0dAm/EJt63eUs/WrTO2TMKf/FYG0ZwepRSIMWkAEwYAAEg4MINOIDIkBIQyiRWIoIgCGoYGCwgtDIMGisB1Pnk7qjgPwU6S+cOl8XZJSv2IDetZabs+KrxpXNwoYA2PA8SHra5N0MD+2cgxu3HBGyLTMZvujaZ5OdaE2I0GLSKgQSICctSL1fE64CSs+WhtFkesxSh2ppXCZ67qMsTRNlVKIyDljglgtGWOIqHKltUZEQSnVnAiurUXUxhhjDKIFAGNREa61lkZyzpnrglJWSuY5jw5o4GWC5Jm2/SQg1cp6pcyrC6X3RTX23AVJDuo0bM6oLxjzNVotkVqkHBRYRgA1KosMkVBDKAABSoEAKerVOpTCKTMvergCAUTk3tN1dcFfcvWvOV40V39W5DEYA0QAENAyScd7TO55ZDrtdVQitU5G6SydxcInjLFMWuEyQgAtAhJ6xtURPV9wTRkBbXQQun7gWa2ZJZUyEGqtSTmTnsu4EFrrJE6FIIwjIcRwog1SgsaC0ZhbSgGMYWf11QowYFJrAIJIEam1WhmATDstYSk96mRB7fKNd3+XlS7PUjfX6RcKxD8B80vNWyG9n/0LALEkCJYCEovCgAQgDBhA6BoAoNwStBSRESDMYpGnfqqSIDlV1xHtgr2/qGz7ktRf4rnBFZCquV8gy6bd4/0SecScJFe9VCkpMc9BggDlAjAgSeFqIkCQUkop55xSyhhBYqi1k9kk8P1r16+jtZ/duZNLWfLcSrXkCDdN01QmoJEQZkJujLHWKqWkshyRUaq0znMjTuO+LeLcH1UQvGGU0swiIUA59yhljBHGjEvQetJ6fvOmdW8kVGQp1H16sqC++iLSWtg34TSuwRQ6+qnGPsuBARbkXeyVzIACKBVtYQxQhlB45oCABamfuBeB0y4xdmHl35d14F/i+SIoAWaQ5QAGkiSZznpgOmElY6HMZ1kmKTDXWJTaGmLActellCIBQjkFIIwRtIiAaTYFgMl03Go13n77G4PB4Ps/+sFg0Kv67trqG+curJ+cnHz00fZwOFxqLW1sbZzfvDSeTDq93mwyAQAhBADkeZ5kc0laawvGaK2l1mAMpRwRiQFjjIMUGROEEUKAs97xyOqGwItKi9kQfAYiXfi8z8rVjXr6LqAUGAZgQBgwDMRpwwm0Fi0Ct0Cw6KCMFqnzhR3myXAdigsc5woBgNFfoAb7z2TxzfFVS2tZNM4vDQuWAn1GJVsvmOcX/rwLxq8XjD+aAnfBL0GaQGP1glP+vzy898m0995Ksl9dnXgmkSNSF+VSQ/q+RCSJdNCiUnngeFkmqcXhcCylnGqP5KQcBsI5uXHd+f/+s09vbm08cqJ3vvkPh8N+/6SfTtJaULt/e3uptnLt0o13fuvcydHw3/xPD7bvPpjFyiK+8ur1KzeuDA5Otu/vIkVKqTKz8xeXNq8sDaf94YGSWjPij4eR53uD/oQ7gZZyOLbXLmXlVdYhlakAe0fWNsyMED7jT31etSD6MF3E7X9GD5ib5E9pMAfIFcSnJgB3AYGlC9ZDecF989Mw3pd4iecDY0CmkCYAAEEVLt4UF67chKW/H8+UtlhbKjWXQ+ICpcg5R+pQpJTSPDeDwWQ4HsdxqpTK85w7mEwjleebm5vGmIO9h+Vq9bd+57d6vd7ezoExMBiNVtZW3v3Ou+/82jsffvhhnqbf+973quXq2sZGUHK++xtvL6+3b33yidb6yrULSqmdnQfxLK7Wq+9++zv/9X/9v+UYfPyTT44O9sKqWN9cfvudbx4fHw96szzP28urly9cq9fdSRcaS9wYpvVfH2P2ghCrp39M/vTPovPTHNL8pQD/Es+OReZAZGANyBygCBEF2LzkMHZzMmgjPRa+QbSxlaxEkZF8pIezMeU0TXOtJVL0Q1+4riGQSi18xrkulbzRZJArs7m+3Forfe9//r4xBnWSRePY47/zW7/xg796r3O4V69X83h2797JG6+8/fd+4zc+v3//7qefl2oBUt3tdq9evVgqeeVqWWv8V//qX//T/81/2agtvfHGNz/46AdXXrkgIY776aVz1+7c3m5sNZaWlluNlTFxtyELK850TMAu7IvyouM4JsnTj7vO04+n8unHCynhV0tifblR/HJ41sJeL9rZ+YwXWiTAEwJAgDMwCrIYTlLgLpQbmIumln3qGCScZqm2djxV3cNIUomUckq15RSpUiRVICUikYHjeB46lPsuu351Syn14MGDja2VbrfrBFyZ+Pz5FcqltpkyqZRyNpn0Tw6Cbwdb5zZ+8MPvP3p0/xvt1yi1OzsPlDLf+c53HIf/pz/998Px0e///u9qZT2n9Lu/97vUsY929zdb1/myryXfuHk+qGKvO6pX8o0W68wgydGvYB796lP8yyBb1PBrgZlwUTbT3Mn3HEb0En/HgAs+AMAECA5+CRx/7kmqt6BabxsiZjMzHmbHJ/FgmCaJtRjkOWSRBMMo5YyIPDVZotFy12UySxBVqVKqlEqBwz+79f7tTz6sN8vXrl0KQ/HNb74xGvX+5z/8d1tba+fPr3kcw7L7W7/1m5NR7w/+4F8tLTXeeuvV2WgifCZtIgThnM/iWEuLSA/2Tsq18Li3/51337WaqhwazZbGbH19dfPCsjTB/u5xaMfnVmyaxorM9ZGnoqgJ+7OfFz3PuXn6R8HTP0UZjF9tXAs6t7/EX4NnLdL8tZrnXAJIMGouvDABTFSnU6uPM5SBSWpY5spKAOScSy0dz0nT3FrMlbLWMsfh1ChhfJ+XAm61rJar1Wq4Wq+m8eTatRuOw6WU/+7f/fjg4KDVqrz55s1MRt/5zruf33r4Z3/yXqcXv/7mmytLK2sbS8bk5y5sbp3f+PjjDyeT2aVLV8ZRbW/n6N133310eOfjj+9OeqoerJ0c9Qmh0o4znU1nRkpk0GuVa0wQIDDrggi/nJl85oZZT7cenn77Ugj/+uK5vbtnle0WRIkV3CNPQefAXQCAbAaTAXQGvclEhuVmPTyPhBMcjsb7Uulqu6alrTeb/WFfS62kNkRLjSVOS81yrULKYait3NxcbbdXWRmUUmmaXr169YMPPvgn/9U/Pjo64py/+vp1jzuv3bhx6/3PyuXy0spGr3doIH7llRthVVy5cuVHP/jo448/V0qlaXzl2oXhcLq0Ubp8deuzD3ZmE6w1lggIcPLAgSSZnnSzqlOisldtbHpBdZKA/fKiEhe+3kX+8wUGRPbSr/4SzxdGAfMKNg5hCZSCNAGjYDqNhO+3qhuBWT7pDGf9iDmwsrUWTU9c3ymVKkmSGNcAQJZIJkgQWDmVaRq7Povj+OjkhFNPpbNquX7/7n2VpvVyWUr5+s2b4/E4nc30sjg+OfmH//A/+/3f8/r9ZBolyqSW4oVLq6NBPOxHFANXuLnKlcovX7+EXH/nO+/++Hv/YtjVadwXQmyt1/wa9qcwGE2a7arNhqGnXV9kI6jUFpq7XjTIgj1GLeDeRD/9eFF/Bt/5vz5/X8LPFyR+cTyvPuTPep1F579ovOj7sp8XYfEULFo6i5BwgAgcAsyByMJsANevw+0/ezTd/X9evXpxNBoR1L4vTk5OQlesrK1BulukpruuSynNsizPcwAgqao2eLWm/rv/7p9oG/VGI0o9xvzx9KBSqVhp45lCS1UOs0mspX7tu960m48OFWE+CKWIQuvkMXjelDFRqpQchxsDjDEwZhpFfrheCoKT7kk0jYbjcbNZb7Vagon3H5x0H4gS2tULWbW+fuvzjX/3ER+0XXLybPPwrFgkqD+vNpsFXnL1l3h+kECeWIh+CHEPhr0Tj+NsMplOBpxyV7DQFQ7nVieUEchAGZXJDHPMVW6UoZwipYCUU52rnBAqhBvHejgctxqNSS/2Q9fhfDqdlqv1xlLj0fa+1oZa7pdDqzkI5TCwmoKyRvEssypFA7lSihEGBJIo92pHrddeEUzMMG41GlLp/f3Ddrtd9l3/nMdsxljkcLm8jMtHcNzR7lcvOOuXAPt6mXz+duNF+2kXCYQLe789o8BnUqAEhAOxBCBQa8B0Pxv3d85dqjsO9xIuhKDUMmaszob9tFay1tp5btZpI3ECJKyWASI/LLeby+OoqyeWUu/CuQ2UGZamiFhbKS2twGQyklly7lK7XLaT2MhMpEbpPCeMGUtzBYGHxhiLyAnnnue7LmNMVuVoMtrf71gLoV8eT8eUUt/1ut2+zChvxEyl8STFUcevBGvL7f0Td/Zs0/DMeMnVX3hn2Bd932fF16Wz6iLw05JpWgEVEIYQqyHoQ2sNMbYcukHAjclTo5gAo8xkFltthStcVyBSyqnVljt8PBwTMn61fJ0w9tmn927fvnvcm2ntCWC/+Zu/6Qryox995AR8ebUelDzhhBLlJE6sxlqlpVjDCahKmS+w2hxprYtSU8oYq7NUzlKdM+aVgtJgMJpOp0FQIQyiaeK5QcjoGPdoiTR4M0sSy0/OrZaGx+UPu1/OfD7fdfjSAv8VwoveYRZW+F3EPZ5R4hMOCHIa140AKeio65rE5FlqmMOpMTaLImoTYhwhDOWelppRZhGN1mmaSil5Rru9E8czbjnsj6f3Hjyw6DBQ7394xyeCImeCbG/fT+R0aalx8fLWxvmNV19d++P/+Bf3Ph9S7rmuKdVKXtDwaGX9AimCcF3X9bxACIcxL+A0UZG1eO7cuW63a4xCpBR5GIYwSzMiKC9xW0njHMxopZbtuzOAF+ttWzTPC6vc/FKS+EtCf4nnBpcBKDAGKANCoH9sZ8ODZgUcTq3OrSUoNeeSEBY4BIBQh6eQKqlMYrSUk9lMZpIQElRKVk8cz5tM4u1H+/XqZqt1/huvVB5tf9JsNofTYRRlW1vnr9y4NJ1O33/v07feun7UnR4e9igPFIlhWyUZQi48hwOA1poxwrlT5Mn6gb+6osLQ/6f/9J/maX7r1i3fDz3PUcrcOLfJ7VrUx0hhQGuVkCdatVdPyMGX41h/zlz9eV7sFC+8ENKzCrrPep0vK4bweVWAfUb8NbXQfmEIAgpASWAeAIFoMhgN9ldDwggAWAogBFBkWiMBCwCdTidLMkT0PK+gwyKhlQiiUvA8Lwi8PDWH+8elEi+VGhevn7eOzQZy6/zFixcvnxz0bt36zHV99IJcESkpJcwYRj3Hscwg05lGRJnbzIAQmhDrONShrNc7TtNwMpnt7u53u31re9vb25TS2TffuHsf//i9z6kTvfvtzcvnN85duvTub1/4Fz/6FSf4K4GXXP0lnhsIgLFgAIQLeQ5xNJlO+2EdHIci+o5HucU4ncWzcRrHxqpEUSkl5xwROecWrdXWapunKUUKQNJUWcspxUFvMBH6279+0Rho1q9GU/nZZw/u3912uFerLslMy8QqQ1NppdYOI7lRyVSXAooEkSLR1lIrQRIkiijfD+/duzcajQBASrm2tpYkycOHDx/u7cwGl2i2cuGm/41vvTo7GT14+LBy1QK0vuypfQ5gT3KwL8sctdACvPAPnvH6z/jFi56GhZbVRdVLnpN0s/C+i/5gYSP4px+OCYAH0RDOC8im2Sy/v95wNZej2NZD4Do56U73uplFr1n2HDbN+lUajA2f+DURD3EwyBqtisXEjpFVji9dqx88GIf0giaZDCZ3H3x6dcD+8//1f3H30aM/+h/+7c5naS1op2qo5CQnx6wcp8akI0J8fzZKyiVarnHHLRtjolGfECIcBw2xHE/63VkeDI/Ovff+R//4//D6/+ef7+zdE+1Ly/Xl5XPnLK7+ds1VG2s2HtrPD9n+Ye55zf/Tb/b+f39VnriCzQCt1gEdjiEAIAt8cOw5MdDnm870kqu/xHNDngMAOAwMgLX2/v1tkh1T5u/tnKw2yYXNtgJ3GuUomG+E64pSyc8hcV2fMZYkUZZkVlMiWJbF60tLQam0kw+NzjMpvdD7xqtvlYLaozu7JycnYVj3gm6STbljHA9pUWXNIhMEgDFOrSEWzWwWK2WQeEhIpjXa3GSEckfJlHN2ctI1uXvh2pt3b/eyLtfSmahqs5R95yrWhDrs24edAMRGtz++2Gz7AkYpCAEqxzwH7gAsSC/7yuIXqxj7gvF3zgvwjDr580pifdHOvCJ+hjgACsbjbp50K0FlZXlLeBsujXqz6eGxAt6KpffoYBjXaCDlKB23fCoVZlpa5BZtnKfNetPzEsfjaRp3OoeNtdalq1dk4p4cHOZqb5bOlpfb+cTZ393VNhJhjpRLabW1eWqYq6ywYIwyxAovTxNlgBjDRC4cxhnVWoc+irrod6NuN7n66s0f/Oh7euB2p8nNV52txujVV/zJRH68bfcG/uaF1Xv7n62dN/Uy9A6B+EAYUTn4Pqjsa9N3oMCvlK/+El8vvOhWE0pCKObtB7fv3AFS2txaKzeWiMd8EX/0g790gtXv/v1/kkrn4NGd0M/H9z4cxYYwj1MqmO/Xw1Lgmyj1WOA5BAAcB5vt5vLKCiNi/6Q7O+5YXOmMOha9tY0l3yWd0Wcap4ioUqMzNMrkqUEOUlnQNjYKWTkbSyZyIKpVCVrttaMHR2hjL3Ao4vbt4wtX3l27epGL9ijbFyRzcBK64uQkA5k7FMOw/vmD+mu9wVLVH0zUKGXEB8jAqJ8b/f2VpKkvcvUvibt+JWfmReIZ53mh3/sZr/OiO7GqHIwDBMDEpnv04PyFi9Rzbt8/bDfP+Sy0PFzevLF1de0n70e9Kb9///Bmo0K9kuu700TmSoV1H6kn/LDsVs+dW1EqNyS/fP2ytvLhgz2O9TCoVsvVu/fv9sdHb7zWeuMbr01iLzWHqBEAgiCgNJQ2ogjaKGK15d5G+1qfzIBONe4FNe/ixYudRzOtp16VW80++fj+9Tfe2dhauntbCldsLhvK6fYhv7sbExtdbWnfhwk5v3/84eUryxttGG0bBYJQMBkI7/n1zPsbASkSD4vPS/ztxpPv+lf5LEJzBcAAKOgeHQCqKzeuJJE9PJ70u8PtR/uC+dX68gc/nHx+9yQIlxy/2e0PjSHCDaXUyhCKngLFmFhZ2nKFzwSpVsuU6t6oo6VeWlpjgjmOE1ZdpdTx8bGUcn1z8/zWRVCMEFYu1yuVhu/7jAlEtBbf/c3fuvbqt1dWr5fcNgBIKxH1bDIjjFVqvsODzv6I8On6qhgc71ZDYKRMedCd8t0ej3Oz0kzrvLu15sZp6tPxSlk7HNMcGFlor/wq4yuhJf9d22W+7gGwi96XX4ZZF6oBbG/fbjaXKqXaMPq03tpYWVq6e/v7jJk0Tg+HB1IK16+Xq7Px0dgtC98tZ1lWLvvVan006yClcZxOp9NKqbK83r5z+5HWulptRNOMYO54tN4s54q5UNp9dKyU8+q3tgDAWiqYqzVTsQHQqJETdxTno6ivrSe8sjbUcagQ7qVL1zrjj4FA2Q2VKUXR3o3L129cWFm/6n62l13e0B7X2gbdqb+yQj17eKkBTl5WeadSZqVaab8DFQGuA6n62vQ4NC8LTr3E88WgB8nY+lXoHh+uri+nado56jZaK5vry1mSpLM4SaJyuby1taW1jqaRMQSIyKTs9SZxnmtrR5PJcDzu97uO4xkwvUHHal0qlThjWabPXz5/6cr68nL7tZuvfuc73ymXqzLTF7eucsoBwBiTRNl0Ok2SxForhHj0aPfwsLe6vrmysWW1PukcHx7uB6VKluvJbGKMcQX55M73yyX9zVeWQzd/75N0OJnWwzQoOd1ZOM6qNutviofVclUmQx9Usw15BoSAH0L6tbPAi1+Fr39dNopFz/iiuetzyrd/1vMXwTwnGW6Rjur6cO0dvPf926FvgnD5o9uHl65cW29xNbqt4kFCK+XmsiVk5+hOZWkD45J8KP3Q9Ti2SqVp157sDPvDZONqQ1bb118tywfRe/+hlwhx9OgRSSesdnB0Vx8eRrcf3HPcUrk8JEa1V+3Dk3vnNzjX2WQyi5IGxRbynsEZ85PjW/fe/mbDYzvKZsvuGx/85CPHksvXGnFcFXUhqB58jAfv0dLvHt38vfR7/6J3VfCTfVtrNs6v7Ved6tGIbcPlJJKX+sOVN/o3v9U5+I/QYiumCofHcK4EvUW6+ldMaiNP/PsSL/EcMBnApAODUQcAAFQl8BghO3sP93b3VldX18+tH+11J5PJ6urqxlKFAVimW0sNY8x0Og1KpXLVJ4z4bjlNEop0OByqPPf9sFqtM8Z2d3aqbb9UFuN4sH/0qFJpra5eSFP24LODPM6ttZVKZW1taXm9XSpVCCFxlK1tXgortY8/ufNge3dpZcl3Rb+7x2hUKpVUZgFAuGw8nj7aP65Xm+2Vdnuz6YYmTfuhyM9teJs1s0SSKxVmqJfMfJ0E7RWn4sq0B/XleR+FrxG+buP9pfC8zFHPy3z1dcei5/UFxHHe63VqFU+mscwyzwctk+PuERGs0ViRWmaJ3DxXFwwOtz/izDiUyiizUjMGqYqtpWGwFAaB4zmHh4edTsdx+Nb6ervdllpXqtQtmY2NVrO5vL56wXFq0Zht35lojVJqa7WBPM1jraU11Biot9f9YPmoP52MVbO10mgFOusmwz0DrNsf57kSoZ8k2c7nBw4NpNWiTCyT/f7RsL8f8KgiJnrwSJ087OfjR3vw4LO40dAXtjIRgSvgcLqwYuxX88N+FWL/W7yanw++YvPzvIazyKxYrcNke5LPJlsXtxIZTeOpH1RqQdChdpbEm806umwwStNRSjGDtFep0DSeaKkqtYY1stPtUuaXaissn1RKlYndHYxG7uHher3Zbrd/rfwuwSFx02+8/dps5DEh7n2wN5ro5rLjCt+Amc1mie4OZh3uRC4jDhNSWuo4tfpa4Io0M6ErDIF0sleunp9Fh9qQUs3tjeBgbzyLyWjWk3QZjNvvTo8O941pxbE4GQ9nJ6Zx4dx4WP/gR+PXf929fk7s3Id0BNnXrabLV8IC/6Kx0P/8gnWqF+3H/rKwMGfBQL9/FMc9wlbSKDGpZBAYE2utUVDhh1Rip9f5yQ+/77CYZKOgrRmYJFVByUtzkDbzwoag9UbLEYKlaTqdTk9OTqqOV/erGxsbXFnPd3PmHB/Hw+7R/uGAERYESwwEA0apJVQJAdwlVCIYkURDmWXr65ugTBJJIALAcE7bpVWkXSKYze0sN929LBpm1bb/wfsjhzvjMd07MMubENRaFa/FY3b+cmm0I+7fvR1sH1+6Vj+3oj88pEELyOLOjV9B/Eqk/ncuoPUZ8VWTel60k8+kcNLZTyaDzsF+qkVYrjPIu91jQ8zy8ornVUrEee2N0vGjO929ewHOtJ06Trt3nBkDbtllLkF0xlNdL1ljIM9z3/fjOO31eqJeIuXwnbffAkG+/+Ht93/8EVUXCQ8zJTNNpbQGCCEGjHF9QbnWMtHaMjPIk0GjtWylE3i2MV7bvvN5rdYY5CZX7mSa+0RzzrPIOTkaX3x968MPO1Z7ZT9YXkanVDEeUuuich0HM207E7H9wK628611eftEqgVN17+yIC910b9DIM/pswCDXjroHPquJwgEjuO7QsoojScG8iTPHu3vjodRvV4PXAL5xKGZ46CVWjBWDctIkRAS1qp5zvb3D4Vg3HE2NjYYI91u13Vd13N7h53xMIkncTSNRpNJo9WqN5tuOUSNjLBMykxG1NGUo5YWDON23O9sO9Ra5EDCRnszkYhO6Hmex714lkqdhOUyo/6d24/Cqm95omlSrvvLzWot0A0/XQvNiqvT8bQzPeSVRjRZ2d+eNdrx2nqev+iKc88bL+n1JZ4b+kcns0l/Y2Pl5s2L58+vuYxNx1OD8sKFS4yxo5Pu3t7R5589ePDggUyjSkCXm3UDeaVSuXThiuM4lNv2crvkl13XBUIO9vYYY6urq6urq1tbW3mef3Tr04O9gzAsr2+ci2QyjZJEJsNxnxBRJL0jWs45RY6IQJiAeNDZjqbTwaC3f3hs0JXWkdJeuXy9vbxJCJFoAy9g6Gzf39U6gyAlfsqYYjBh6qQtkmvL4mqdhcI1LK4tr4JZOzwaCj9utKn7dSMdJn6VES8qSf+sfuMvSxH4pfzbZ17Kx+5KM08+M6dTUvz7rPPwvKAWd195Jizyn4chxDEoArMUqm3oPYLNTXAZfHDrvVpp3ZSWd+JKns9WV5v9/p7rLtn6751rN+nDHZPP1pdsYMXuQ0UcA1A+nNFhUk1Hpe4xEdQPmLbs8Ne+NTKKOEuNq3Vstl8ZzJy+bPybf/fxr73Z3PvEq7abK0sZxUNDujIZvrqyLCuy33WjbFpecbdvGyph7ZxZWYbUmnJZ7HY/GU68sr8sRFAvXf3+nx+//h06+ezX/sOfH/693+y8eZXc+2hYd5p7n372T/5h9V//ifj+zmpg2u3+p5cupVN+3Gm1dz+NzOGILMvkjcr0kISj7m80/IeOe6CpS8AFcAEYgdxADqAY+M8YG58voKNFtLno/J+/nr9uW9NXDX8n50/lwAQYBYKBSsF3wXfh7iezaZS0223f9R89eiSlDIJgOpk6jud53qvfJoSQTz755Ic//HHn+JgA8RxvlsZ5nnIHCTGIKFw/y7IHD+95nPe7B0opznk0TabTaa7iRqvCOV1aaU3H09ks3lrZWF1evXzxaqlUMin4rs+YYIz5vm8tJpEsCk7XKpVvvfWtm9evLq82a41GuVoeTqO9vaNrrzYq9UY0TTgPatVyHE12d/eXGi2PW4TU95mlpRT8wRh7g9ghabOkV+qpyMHzGx98PhvEwnOoYEDM3Nz11Q92/pV09b+D/ucvsHRymnNGnsbqvzw8t1ezwEOrzPxf4QMoKFfBDeHR3bvCFzduvkoRJ72BlbrT6eRKtVeXfd//t/9iu9/v37h2w3F4t9vVVsdpajUFUD6DNBrFcd6otldWWp7ARiMIQ7fdbI6n07vb99NZTMAwro3JwKgkSh7ee5grRQgJQ7ayFOQqz5XJMt1eXf3Nv//b73z3Hb8cHh2c2EwHnnfp3Hq1GjoUAaDUXIoyPDkY1lvAOR0NYorO8toS43Tn4RFaG3CNpuuHhvjNziyITG0WOUkSVQK55I0a7qxSXb2zQ4cT0wpTl4E4feVzSv9VG56+QHyt6OzLxk/bpwwwAAbADDDzi1uvvvZQCoQPACBcAAW+D3EHOgePVjY2qvXq8eHhytLS5urq3s6O6/ulWuX2ndtRNL1y6cqlK5eklEqZarmqlKKcBg5fXwk51YZAWK83Go1m1eWYhK5gQhwfDx482Ol2u9PxcDY4LlW8/vAk8JwkmmaRpBZHg4Fw2VJrLQzLea5Gk0m/25+MZoS7fqlkrKRWJ/HAphFSPZ5GldYKKy8dPuw//BycgOqM908iilBvlm3mdI57a82g7kxLrhR++aBrDVQJ8ccpA+babOjKAeSgsJrNRm9enPgArgB2qriZ023+mVndgs/zOr/4vJA68H9bV/ljjk0ATiW34ldjgBlQZM7hjfkyJ+FFC0pF127GgBgQDIiCg3tTkLPX3/it405nOp1+6613Gq3aj977k1jGx71eufxKo9YAgP3dfaWM6wprbaNRS3PjOHx1qXbSmzDGJrP8+PBwOthv1a5Wy34QeM3maqarrueHPttcb1+7sTq9NQnd5etXb148v0Xceq7yjY1WbzSZRtJyCoYdd3rdg5NyI7PU1IXjUT7oHfuuT1lw0J22lzcaK5fv3r+9+spkfXN5sl0+2OvCBjger7HWwc7JpYsXjk9SwnIgzt7+9ELFOFZGOtA0mM1isLN0pitBAOn+ty4u/y+fN9OU5ASMAWXAFO7nr6ok/7eVKl8IfoqfP2bd5nTjBCAGyOmvf2shQKUgfFAKXBfSGRzubjvU88vlnd3dpUYrcLze4WGSJVmWASGvvr41GAx2H+1yh9frdUSUUhLCkHKrE6MGg5OTaBqdnPT39h+BiQUx/ZO96XQaZZnWWko5HZ9wTIyZMQJxPGmUKlkiB4NBOXBLFSfTWmo7m+XDcbR/2Dvp9gkjblCulILQZXo6ZSjjbJJk0g0a7Y2LnYNJFI/K5ZBAqDNiUU+j8Wxitrf3Sxxfu1RrlRKLkYIc1KwZRC5JediwpBkKt0KSumtUfkzlQeCawLGMnJpjDQCAYAu57rM6L5/1/L8mMPaFrMhn3Ni+NqE4p7ya/eyEmzk/ZwAKgBgw5Et7rhddHUUISFNwy5COwG3C8EQ+ur+9utx8sPMwl7Jare493Dnu7FfDst9cD+vlWx88lFJevHxREHX3078yxtQatXh6UmmsDSad/tHeaDQirEy4UFJtLbUcR/74Bx9OZ75SJo2Vtendu3cYgQcPRjs7JJ346ehwPZ55jZXjo+GjXQX11dAvC+YyIXzfH6IdzVLBmCtcY4zvskmePvj8ALxV6tGgsUbR++yzz+rNatVvBE7ieU46nUzHMsom4+HeK9fO5bcPo46tl32hRq1Kfn556tOtURq4BLZWSrOTqbY8VqTkaKsxSigUS74oWfHsXP1ZafCXo9m/xaznBYAs+PWn9tq/3Zo6AGGQKxAuKAVCgNYyi0+a5epgNFpbW+OUHu7vj4fjZrO5ubn56NF+p9dbWlrZvOxMp9M0TQkh1lrHcRSYNE2VikPfPX/u/MrKEue8UvLC0P/ogw+SJLty5dL5i+c5xYO9HU6t74vZZJbnKkvk0tLSu7/+rjJp53h3dX1d+P50OnUc51tvf/vdd77TbreTaaJUrmXWbJYpx5PuHjBAF5gIBXPv3P04SqLl5VVjiMpzzjljIpO2d9xpVt3QNVYnrYYHauir0fUtKPmQpnk0njZCP01T5rYzbCBais+/Z/kLwi+WCr3opAUb2MLogudFAF8SIZ2ZXh5zzZ87koVliZ6XOvecutMsHM6C66gZhACTfWi2AQw8uP/Dep026mnoeXe3HzTqbaflWfrIo2mJLS01LiYmrFVoO4QdeUDVSXulFpssM6xOjte2NvI0Z0pdOPeNT3fJeqvVbnaPpvZhf+1P/mr7732XX3/jnHWx2lmv+s6g41949ddbK2u6+6er6yv//q/uffDj5PLWDXV45/ODbrvcLE0PoTQ4d+7tR7f7KmAaD47jVd5v7B+l1699q1alMN5+7fq5DzZKQXwvHL1HN7aOjo7XZn7TDW9NSDxZ/vPv33nrOxuWnlBNe/uJK5Ik6sRxtVQ7DGruez/Y/tEnO+c3fHXS+cGfOP/tP/r4j+/+5//ykJkcqmXTmRG3CmICuf9s8/+ssS0Lz/+56+rrIjq/xFcIfhn2H0F7E1wGo2M17A/rzSaltLO/u1xv1pthZ6YlpQAAhFy+uPXeD+9s34vkpDTodVAmUaoca6s1RzDQhlqlwrA8Hvct1tdWlkqlGTFw+cKlPB7e+fzzWTa8/OavvfGGmx4/8LxMOYYBdHrROD5Iolaj3hahSDKnVG4e3DvSGnb2d80s8kWaTjuHx73KUgSgfF9Y7SRJRsZTWo7OrVXv3xoBVCwtueX1/rRbr/vVstp5eNJawgc7Q8RgMhtMYnp8PE7TY86nG6wGdGV9rWkpr9VLVa80UcMffT7VdnT9wvLOIcRA3DIIAq4PX80sp1+oYuxC5vG8uMcz4muj2y/Cc5qI56aTP2uXGAJCgHCBAcSTQe9kv7Ta6I+7uZqVWVmlndH4MJv1JxO7e5RY91Ng9dHJtLOtuYk4yUsO0VSiNNMEOM2pMa1W6XDQQR7U661ymRV+ON8nh53hzk6yeuGtdrvtVu3mBfVX96a727uDw5G1Wc+WiO8qYvzq6uVrpe3PH1KaJNH4cOf4O2+6mc6qYRO0HfYOEStLSy1l00meH2/vrjTZsUg16pl2Yrt0/9H+hQteJRj61TL3+eFhutxe1WpmiAC3mqs0YLHnOYHvM682TbTrh15laW83PfjQeeXK8Gp5aTzB+wNot8HNweRfUYvs151oXuI54FlX5mQEy+dApQAMOkd7kPeOj7VOkuZyPY8H6TQVkBruMSbGsR3s33eCtVAQTRWYmTITnWVBiZdK7mcPx6HrlwXxHE/rLKywWdJxPKNyGA6HmUzqzXq1WUfLpdQX11bWzqfVE+/BneOTg6HjgfEJ92ESjwgrewEz2kmSgVI5mClgtroeRmNZ84Xv54RCuV7KpItJJo2VXnTjxuYwslqUZkgnsZtKYlFqrhPjj/re1ubquYvune0RiHpkqpXKfr1d1xyZ5HaEmdUTKfb7NHWuX5xGl1d6rmmlCggBAhCrn6O5fZn4xbq7LDj+vDqiPiu+mrvml4DnVSvuGSVOpcD1YTKCzNr7t++AZpVaUKmVDGEmm8moA6gZL1FRafg8qK4I17VZNDra90Re9l3PYdxDBkawqtSWc0I5b7ar/lJjNPq02fSG/aFweGupwpFePHet1r68f3j/qNsxbuR437Q4HI+nXk68JmnUKqVSenLUv31nhwBBRK2zSq0ENGkvV7dHM9cVHKNMu1E2nc60NjKLohK33/zG5f/lLz+rVBqSbKrp7mE/41qmatTpyU53tXM0KYflNN/l/rJTXRvEuyt5DjlwDrXQORnIfjaOckoqN4bD93V9vFqrlyc0nQFjAF+e5+Xn44WE0LzE1wzPuHW6ZZgMwPeht3syGRwtr65ev34xrPjdni7VguO9YeCUassXE1lKsmSjVKpVvPu3P9kefVQNRHurXaqgUnGUyXNbNzrHu67LSqXAVGpey0v6cb1Z+/gvu57jLK22SDatltpGkZODrqkc9yOiS4QIv9EqJUl0tHuv7JdXKsuzSWfv4T3PoX7oySihfotxE+cpGCePp6Puo4keyW7Un+qS49BsWl7lpRLR2cSY9Pz1G2l0/d7OH5edpN1i2Ux1u8nOw6NXX98qeTQVrhecG5w4w35Wr9LAt/Wyk+fJ57s9QkS9Tbon5YOublTkpSYeTG0M1A0Xpht9ufha8sdnjVD4yn2+5rkDwoc8B1fA5x9/stRoXjy/JYRIk1Rpb5roLMtKtaWVrTfPXX3LrWylOUxi45brfthy3TDPzXCcKWDCLzeXlzNJHa9UW2pR1MP+icORCZXG6XQ6FT5rtqsA0OuMptMpEwRxc5YFkvILNzbXtiqg+9m0T3XmYbbSDDTMjEo5dxhjivqHo1m/2+31elLF5SrRVs5GceAFGxsbUjtJFtWrbP/hnVoTllbOH/fUOMb2ilcuhzrTViahjzdurucqnSa2XLs6nXJfuBVufUgdmeWDQcWjLoEI1h+eMCK71zaTwMOZgfz5vd/n/PnS1stLfG1hDIRlAIB7d29fv3y53WzuH+x/fv/z2tKatVy4fqXcAnRYFdIYbt2+3+0OueMFYSXXPE3BgLDoxKkyhmRZ5nles96cTqe7+9s80EqlrhtGSTSbTbTWFmnglSqVihdwZepJSrNcl2rBpcvrb7/zymvXrpQQm1X/m2+8QrWUOtva2qq3VurLbS+sU16yWnNqL1/cevudb9x4/bWtc1u1UgmEUMqc32odHj1IYqgvLRGvpHlpeblcLfuT0WDU784mx0vNMEumSZLVGxdyRUwOWs5k1DHpSGXjEqUeg/pGcNghWXK0WsrKZRLHkH5VS1YwUagWBAAgXSB4LLTAs8ffPmkNXpR/Lp64mgFQZv7Dk374J/eeRXm5ixjaouPsGfPqF9VLX2ib+JLCnp91n144zAXPu0gQVSOoXYA/+58+Dtz6+cuv3/rss2kcpMZZ9vc+uPN+tbTqiks2op9/+nASj2688XaNPPrsk0+Bzla2Kt3OI5eVuOeFfpBOjl2a1Btr/+n7RzyofeOqvFjbC4XipQu/88rW3b0HPz68Cz7lyWpnNwiCLMJY5RKHjZNkVq6dnNtkyXBf44XpMJgqNg7e/tGtP/2d30DrVf/sew/f2GpcfjfLxtM0n1EdhO6K6+4dTbpra854+q0PD7+/vkQp/eHRzoevvPNGufHa/Z/8x3/wnXNbK/7UHwM9fvjZ8Nd/779aX7EfP3x/5dKVxCVOYG2w/snnUWKpcAfXLmW1pVuPeq/qlfOf3dvfusyXvPSE86UWnXwlqZ35T1TIWtT+4aeWyJl6X5BiQeRPkseiJVW4/udpQAYIgdMc0KdcHADc52T2e9Zc4peizs+HX4Yshjt3Prl08Xx7OZz8oKfy/Lu/8Wu7j/5qeXm5FK4cHe0NxrKy1HrtwiuGkTvv/Un3pLu63m43a2nSz9NUxZyXKkpF5ZARA2srK6VaaTL5XLDc49avRx989uDeowfQJoEztuaAuUPHy4+Pjtxwc3XZ05E0eey4teZWzQlsp3MItlquAjHoitlhby+OjpB6JGY1XqlW6zoaHk0/twkGlMqTRGa0FazUhK27Qva7TR8c6/huYzqOKOHMLdVLFSeA7km3HpjVRn4yiD1ROjqZNSmTGPQGkyh3Hx3G4Ifj4ZhhWK0Fs8lxyVlf26JHD60TfBWrybKlEIw5JYZFpFKQ6M8QzKyomCnAnvLnAukC0vLE/DrWgCGPufoXb/b4x0VRQYtI91m59EIskhoWnP5VzWX6VbFISvIF3P+kk8fTt7/15sO9k15ncOnKhW+9vfQHtyf7jw7cUnzt2jubF9aE72vU+zt7oVtV+QMHeT7LOTpW51bqLMoAkvNba1TAZNyZRR2dbpduVKzW4Sopr0I7Cb1GhVARm9Hlq9633910PolGkeHGpEwak6OZrJ9rv/JK65//vz+axLlVQ8dJhJswAcrMhpOZ57TKNb3SKEk6M9mwWVkFaZJxLwhaDpsyNtporOw9/Ozk9u/4rptkXn947DoizZjOykTw7snwytayoONHB8orV+/vHYEjncA3w0mjvWas3N6fDAadmiPLNabiQbXS8Cae1vKr6W1j6xWw1gKAtVYtWMz5E0VwzRMxv48F2oJoT39d1Hm6fDoDRkFu5qQOANnpD0/SsFELBctFJLdIUF/kS1p0/le/okiBZ/aePKNleKHiZuDhgweleo06zqPPb5Wr5Vaj8fD2eDoez+IJOOXlc8vVRuuzz/aUUqHLykutbc9jFjrHxwQz13cZkNlgZHHs8Sv3t7f7g9x19Nry9MqF68rM9h7uc4+3llYAXJWqeLarAdOZZ3RizcDSwA+V55Q8TomJNY6PhjLSjuQ8mslEGb/eLLX1SB7nu/3h0PCSV2rVWBnSaTIbxAJw7S04+SHVSXb15vVbf/DDvb17YbUKfnXQub+ytjocZ/3uUSJDmY1ffX0tJGZ398Tn674LlMxCakM9ai7VXFGaYJmJkEwyAJVEo/rSKHTY5rlyb/SME/o3ArZSN4iFvIHZgtD9aDBf/fNNAedbA8HTnJ7Tr4ofZvLpxFjzrdao0UqFxoBRcyI0p1tJwfDhNN/bW0BzpwP+acT504+LBTHJC3XvRbHfC07/svCit6RFXF2NTO/kYHm1/XB/GyleurDa7x7NRocOId/+1psZKe0dHOx1ZhTpxsZKvem+/2++R4zyPTKbRAbS0A0ZMbN4XCnTJElO+qnn1MplVXazIPDu3L/9+Ufjer05HarJ8YEABWSiqbvzqfreD/bd6iVrLUT315bLl8IL02l0dDIdRj7QtufrpOunmVhau+JVXnPznbsffw/yWW8We8uccfHw/s7Jg+7Vi1vNOtiSt/8gPX/+KvIf/fij75Ubl4IVL0qk53mNCj86Gp6cRNF4+BvH6xcu+EvBoOq6V7dKnpcTonRrXK17lUrphw+zigPUo1LyKEsuB+n5ep4eQO/FvpZfEqxeBgBbEE+2oLkkCQ2cUjgYsNYWhM35nLTO6LxYfKF8+nWCwFiNGq3KQWrUaI0CZYBaUlzEcltcv7hdUR7sZ7GI1DGjTz2+yNxoFwn8Tz/81cOXZFQYdrvTwf6bb7wipVQmN+DFk0E/StZX/fWt9b2RvL39cGX1wm/8/dcFwMffv39wtI0klvmIkJhT6fuh1RlnWbt1rtS67i+XkVJmTqo1m6fwwacPe49WqmGtXE5xFIU2MeG4tVIlEHBaq9U3wxKtOa0Sp66oDAZ3p1PbLF/c6TKWm6pwGw6vlOtNZ9VOrLl2Sc72kkgSI6rl5bqv0vKwVWfDe7C2VIt2A1dUr1+++P5HDz2kN7Za2bEfTyYlx9F1n1KeJaPd3eObVy9dXDE7J9t57kRoGg1vuZp5rgQTp+nUSZLQqUeJG0nlsvjCkjnpTPZY+ekT9yUtrMKaxgKnoCuAn6OLhgAAiGBO6dxai2jJWV7c6TMUVFpewP+IAItGZ5hzMEYrjcUgXPJYajBg8FShiPJFqsDT4TL91ON9+fQtYFHb3IUW/gXn/10T+O98doug54fueDIZR1Gj5IWuHw96NrNpmrbbKxMTCsfrdXV3Z+d7f/Eny35OiBrN9rnQLre+b4y25XIFqVMqL2e8PZrNAl+2l4RXqTG3fv/uAD27db56+caSMJGk0+ZqOjzIv/XW7/urGzKflmn/zocfGpKG5dmvf3vrap382Xv39dHhG2uwCtOTh7dm5pjED0uVRFFr+9Ppww6P+xVFvEapSkbRaGdjqTGigexG15rNXfwJDD8th1s96hwf71zeWmqGbBAbxr37u53O4KLjOduPHsxSnmVRs4yuS1bW3Vibk8Od43Hk0rUUw6WGOdh7cG4Tr5y/8dHwV35VLwCMEXKmqwN5ugTveQXXBWut1mAR0AIAPinVIz4W4B369OtIRGNI7hquMc+RUmMIGIAQiEWL9jHmxZUXcHWlnk5bDn/6+dMFUsbXrUP2VwWff/r5q2++OhmOdw8eLi01NtY2tqOxMcoPA6PMyuqy9c2Dg5OHDx8c3ruXTh+BnxFmsixprpQIKoIqKLPNc+udHj3qjh/1tecFVzdXms0xAbdaXc6iOx/f+sksD8o3N9r+CfcOS7Wlg73OwcForbqhtB0Ph3/+px9vnb985bob+vXDW+93bh+g1ks0Szu3+9PBSC41S9N8Nq44XA/TzvDuPu/PcihX5IOHgwfTH68tbUT9IRnUQkFWQAU0qub7J9Kmalbxlsfj2cnBhIfeo93kuDfJ7Cp36p5Tz8dHu7sPs2yi2JZ1qtcurSYnY62WsHrx6ta5JPr3d29/v7G1CuB92a/oKcAPbhl7SqWzfC5IF//OxXIDSBFOxeYz4ZkQ0HbORefUfirG58/Yy8paDfCYsZ9drZ/QL1z/dJzEPJ2/EvJ4eNY+Hu1wgZ9zEBEAQIuIaK21aK221lrUvNiDirLeOTwu8w6n4tAvUpHAI18IIrCnV3i6jHF6TQSwAMUA5vLFM/bxXpTxtlAqIZDnoFIAACYen1fx4XAva204eQpggChYasOf/+Ht3Y//dau5mRmPCNFqtKwcjjoPHJoMUuZyz3VFqVQKw3Aym+w82h0Ohxu1LkWqjGKMVSqVUqnkOV5QCqpVnmVyeam1sbnBHUKpFa5QJh8MjrMssVI6Hi1X3cDjwHKrbfek5IuyTOTBw51PPvxxlvWvv7r1T/93//j/9t//P5K9o6pxl2yp7DbHhM+w1EvN6LgiXHcymQghCCGMkOl0qpSqOKC1dRxujGKCpXlKKbVWb9SSXs4ol5ec7JUqWy6z0jdf3Vb5jTfe+OzT3u5uTkIR5Ud5frxeXV+tnLuXXMqSSGvdrJcdgfu7jyaTSatW+f3/1YW//Cj7cDfgDYcYiIZ6aYNub8NyG5QCo8AlkMcgGAgGnMF0Ab2QBYZ8teD8hcUnCgG+YKbFkSd/OKPz4teCGM7+FhGNAVjgPlykSz95hZ89nxALAMbg2VFxKnEAIqI9kyPmnkHy01d44kZf2JXoAumA8bNzrLVWa4vEGGN0zmyOwOaxQEWNTkVA5QBnhUF/ATzZAcKeHYKFNEcJAIA2AIXJ8FSvedEqOSHACID7uGzW6RewetEZDwAYxBMIBcQxHJw8HAwGhHuAIaVeyaNGjpJoqmiyuXERKY3jWa+/NxoSAHCFajW8RqXBGLNoKVLHcSzY8Xg8Ho8fPBhoKXcbtfsP7uUmRatd36fcLrUqSZJ5Dm+0KmQE4+5Ya8kISSzPIpKnWVCt/dY/+kcrK16cDg66w9/99j/IrkVNITzpCO6PpUyMnwKJTWiUsWgppf1uP1f5aOBmMnNnRMsMOVVKIcXZLOMULaWtZplLaq2sCT8IiGVGZ1YD9vv9y5cvP3r0EcnJ6lJ72MvWV9eJJDXTqbaa+8cdh/AssVrb1tLWbDY72usH3kol4JMZQA4c6aQHZR/kWBtDOCIwYABGQRwDAJBnLGWxCGqRq6kgdWkt/iyFwxPqN1o0aMEWS+CLZP/4BzBgAe3Prb+ziNQBENE+QfAIAMYAc6H42dr5QWItAOTxnM4R0c7JuPjXnP76BRmE8qffV9hTqQGtloDMGGMIALHaIhoEREIUGjFf/enPqLvz44v8/AbIWfVYAvKU2S6aBXL6n36yR8yz+/Of1dYABIQLzIBRjyUCwqBzop2Axim4LjAGK+fh9g8ODw+3K65oVkPXrSswRo6mo04mI8F4UJLVasBYmESZRa2Umk6jNI0rjFlt4zhOZZrneZZl02iqtQ4CAsakaXpycjKaDICoclgOq36vczgcDgVh66ublVIwHQ57g5FH6dSpuUQMRqMsSiql4NKVZeSJ8MnDzzJEFMxlRHmeJzW2WkvtdnMY7UkpCSGCiMYqc113OiZLS5tiHMbpjHIuGOEOHY7HjsNd1y15MLE2juOWUavamDQV1eWGlbNZ6tBYELO5ubq0Uvpo0k9mUcljTTGolThm2pC4k+auzxq1kpQyGo7bS5srExAjyIlpNMloaN0qBpwYBUkGSWyIS4AAqYIhkMaLXsyzvd/850p/LMvsGX1a/diX9iTHNmAAoLCHo0VbrFUCVj/mpqfi988bIi7YCKw9o1go6BcAKAWqHx88VSsAAAiZ7wvWYoHiz7S2Z5eAJ7j6olD/wJn7/AxYS8AYNIjILHraIqJFTS0S1ICWoEUM3FOzX7HRnI55kXOxkLMKUVyZ+RsyixMPyOm/8zjC06qVfMEfLDBBPLOZEBUQBpSALkZbDNVAfYUeH9n1C5hMgbggBHzy8feFVd/85jeXl5Ycz8uyLIknk5LN86DsC8JHWmuridRZkiRpHEdxlKaptExLHSWRUcb13UJj4pT7viMEa7RqaZzH+YxSXiqVWs0aos5zlU5yq6nHKzkakuaZgmCjCsYwQhSnqYlH6Wyt1rp49fxH/+EPjCtmCgdx33Occig8z17aDM+/+QqldDgczmYzz/EOjg7e//Gfbmys+aq6s7eT53EYltc2ltJ8JqU0oC6ev2gYm4xmo1xNc8EBbSp7BDTHqG8qJb57/87RDvd9JxpP0RqtdbI7bS6vRtOI23i9UaN8uLnEfUyd6GCZkUazOhrEIQnLQeYwJzOJRUooyUFbUy4o82/ApFssH1aQR0FIBjQA4M/I5caYM07+mIosWAvGPJYI4LFS/WwC/E9pAmfiNzuNcfkpWSM/ZeZP3qhwCsB847BPDpgtMBNaBtZa4MYoMNxYa4uH8xxSXFkXfgewAJYQAOfpFn4vebr2PU4oACgAowHInIqUWZxnXuzKBHI1V9R/yXWwYGtYFK5pDejTW5/9tQFwGAgCMgIOoFN48OHRpL//rdcvLq81tExn0wFa6bvI6iyeMSkzmqYnvX4cx1LKLMvyPAdi0FKZAVK02gohfNdHRJISbbXMMsYYAYaYUaSCEUQEQoy2xLiMmDQ3ViNFzinX1gbU60/6g94kLLvlqm+t/ezezid3txkTRPgp1XJGwORc6iyLpsm499ED3/fzPAcAtxZS6TgY+KzKHZuqSZJMWyuVq9fP+2VXqXQ6jVzXt5SOBqN7O3sPJjHMzFTbTpq/9vZrUSWvlsqDo0daauY4x72D5mr1cD+xaM+f35pMJqNhb7Xd5sxhgiXlKIkyjaVyfWtvr59llAlYqlW2h9TzKtRv5IRVGgEYqhTMYigv8M0tfL2LckwW6PZzUj+zZltrCZvTCTxBRTjXkx9T0dm36pSbndLYnKIoffoSXcRtKD3bL76oYz9BonOpYS4X0Cc3E/P4usXYikudHrJ24dSgNhYsWuBgLSCS4u6rzZ8+81S0pk+O5Ox5ewvsbEJYRJvnBE6puCD1RWk8RQRQbsEVYMyc4M2L19UpAZ2DAaAEHBcAwCiQOUwP4dIl7B7A1mWY7MHDD+9dXqm9dn2j3+/PJgOVDqyOpJQyk3Gq0lxl2XA6jRgjvh9Syi2g1RYRfZdQTq21FCljTEoppVRGGSM551LKNM0NGEQ6i2M2IsOjJM9zQghqm6ZpJpPc5JxTImWZ06kAxowv3FKpNB0nD7cP6iYklAHnXsARLRAynmYPd46+98P3pJRCCN/xLKLj8DyFcQU8RxsltOYnR+P337+V6UTlylp98fxlx/FODvrHnQnkuS9cMEiRWsnKpbDX2UmHPd8px8moHFZv3rwYJd16syqAEDKzJo/iyerqskrHP/jRjs66jVZtNBkdHMudg5OSw/H6VqxfRc6ExFlmSlVKBPjh8ywEtWidz0ldPqGoc1NYf4EQODOHFfYqmFOgPdUTrLVYVC95kp/Pf/CerWLu2d8iPubJAEDtYws8KTaUJyTzs/viKdWdknwxSPtYgF9gljNWU5wzO0QkDItKJo1WQdTACpPV6QzOpX07V2mMMcV9F/j+INBaazSe1haLc7Qi1tpIPn08oxyMAWLAGMgJCDZ/okXXX8SlnzXzTxSZSwqYAN8DxiDPIAXwCIQunMzMwceYx53x4U69YkeH2x9/vmPyme+mzKSTUX+WSMs8MEK4PgHqcIdTH9Ea0IBgQGk7RYXKKIWqWFGEERdcILYYk7VWMOE4Ik7j2WQWRQoRSx7nnAMDRVLLE8fxzCgNfF4O3Qyz2agnXCKIW3bLUlJiNCNEWCSUusI1ILrDJFVU5kZqMACj0RARHcfROyf1sJykIpel/kDH+cl4OGUuEUKY9MgV/t5udzbLAIjUlFrtCvbJJ3cuXlwVJk+mQxOBcF1eZZ9+dsuhoY1tDjQejwbDJM1Qo6uU+fSAtKsrFVaVWH313W/gZweeUG///W/fftRggqUKJp0BMMhzY2KicnDdp7+X5xWvMSf1M88WwmPyNgYIsU9KwmfycGEhJwQQ7Rk7fUyrtLjOs5H62TULEfrsvowVJGtPdfU5hZ/RsDEG0Wptf+qOpxd8vIM8HXh2AiISSpEwZASqDcCiVYuYJ9gWiTe5mlO7MmByUIZYA2Bg4j9dsNfaKFWwdKs1GgOyMLhFTx/ORCEpXF8KhIH8jDJfsD4nHFAGjAJGwPXncmCeQ+/hdPuT8SyedA92dDIe9x/mQ7N/Z7Ifp6DSpRptVmkQcL8UUFEz4HZPMiF8ITwgJElTo9Bam6bSCY0Rj5eKAWOttWDrtYrruuVyCABAvDB06YQita4QUkow1hBAikilgtgw1ENpEVgOpYavGGPAjMp1pv1mkM5yqXKVK487JbdcrbWMMV4Q1RpunudBEJQqFaWUtjqslANvqdOL46SPSINyLSgFeZ7HUcLQZ1QQcH3fQUSKKLPYZcyxYm9vz9Fx1Q2ziUp0phKI8tGSp7sn+0srFwkSxy055ebxAM5fvIzVxtrVmufJUSSvrb2OB2zvcG8QealhVHJZ0DADkhPh/k3o6sUtmNUIp0ksms4ZpiCECeIKIlwiOEymJk9Nlmit0QDTlqoctLaugCLuxeApBRogANkCfxSXT98CmE/OBvTYPG1tqp5g3U+E36vcWGuNmW81lOJc9rYWwAAxjANjhHtYrFqSPpYCAADRammttSwkjBiAwsNpKacus4SSiouFKY+Rx6YyOM3DzxkoAHAff6EULebQgi224mI+M/0FiUpLa9EAGFMVxhiprbWoNWqL2mopbRgU1dGQMFAKshystrmBSWwQMTekUPjz02ShOgAAKDtPCjZmbg5YwCRgagAJMDJ3wBoFKgWtYCsYeG1vbcvbvz+ZDsfHh8fHu/u9Xm88Pep0eoSB53nj8dijOJjIar286lfL5fJsNos0s2BVripeJU2SRotPp1PXp2itlLHvOwDg+0RKVKfWYWlTQhhngjBSC7JShX3r7WUFudaZ53igNnu9Gb6CaZpyzgGI53ly2d06v5UkibheHY7Hm/RCFEWlIHA8T7Bh2V+LlavLmhCS1KtJktSqZUKgFASbS+UonXkUCCTAIJFJNQyrJUZ9WDrfwI6O49hy9LxSNhpVK+2RbQgtEp5LmWltCSGaljuz5PJSrq3tzKCTx9axWZa10laSwH6lEqVsrbxGIhJourrSSpJofdmtwKx3iMuvvXJ4/ODowWdbJcUDy609iknggBDKDSzPVVBm4xH4/jPX4T8L9P4pMW1RErozd7bpgkkiANC5rvsY80sIYbU2CiwaLa0xc5+WIUUIHRgDlsx5ZMGcn3rLRUmmCyXUwr2HhcnQQmHfOpUdij6IAABgAZAQQgpLOjGIhYENlAJESy0izq2NBkwh2yMipcgosYiCIyOEMsoZFjEk5Ivz/KQ7nBEAM7erF2AugIE8A1sIR4iEIAIyBKUezwZhCGC0Jq4LUiIA5AqQWqKsBmAE0tMJMgrQWodZSy03YHKiEcUTlnxiwDwRWXM2EYU3ftHaQTPfvM7qRhai43K77Iessz/7iz/745OjA2pxNpsdHB0QAq4vkigbZSMEdF1XKQUAaZ6KVBTGWkQsurUYMIQwQghaq4zRWqs8NwBSSo8zRGSEIKWMMUoppxQIQWozya0tVWsOpYiWM8ZqDc5cFU0T7lAAYIxNp1POOed8Nohv+JfyPE+ShDHGObd4LppGzMB4PHYch1Ka5jmiVUo53PGdFkCLMYaISZZlSeL7fq1RG83yesi3ltrGABgzHI/rPl9dbaVJ6rrEBZMmRmvtOI6UNslNpVRyXWGt50xpnucOofV62fXbzKtsP5olsxNG03KJOCIDq31PbW15vd5xv0vzuDfoMova86Tg46ZfEdQ63FIgxBhSBCw9Ox5TtPmCfr4odKrgiKzgl2eRJGdfP7lh+AEBQ5QC1KpQ3a0FtKSQ0ObAeSS9MSgXONX4okDXBWvTPjbX2SefpFhelKLWVmuNaBEJpZRQAwSRIlpLSBG3QoonI4wIQQAgz42WmjBbuHwIAUKIcInrgBDACRD2eCrNF21iZxxenHbkK/pvOj6oFEgO1sz3Sk6RChAMVA55Mk8wIAhKU0qN70GeIVIkOShjcgCaW406MYwYIGgpWlcYzm0xEo60uJdWkBrIARRAbiAuJgRBWWAEFMxV/UWY94curIM5uAJcAa4HzTpb3YL1tTAeveqyt5rN+u6jR3/x3ntLKxvLq8uffPLJp59+6rthqVQ66R6VwyqJIt8XEBvKEMAoZQzkiDrLEpklGQHCgFJNKWUUCcGyH9pTI0shoEktrbKHh0qpDOltpNJS7TKfcid0q9VlmI6nACBcUa830zSmlCplShyDiheNx9paAMMocThPU7sShvWyqJRKaZoDGEopAGitz11alVqDMa4rtLaIqJRCxP6wX68uua7b6XSstWF4VSmjlJJWA8BgYD3P01oDQJZlrnD7Y+QO11KWKg5hBIwJy2XBWK7U5UvNpaVmlmSDwQAgckNwnWyrZUqcrC1j3eVS7iqlzi2vrtdVkuVK54QQEmcOJjIWVEBmfsEWS0/HF8h7QQhNIf0yZYCwM6v1Y67++DwLBIAx4JQrBlLrM26iDACgMRZxznytRbCgFwSJ/Kwbr8DCR31COvjijmUIIQDAGBhjrbWEWERLqCGEEEKLp7MSkBEwFHkuXBJWgSCkCYln84enFAlB1yW+B54PzJ3r5ISAMfPtRz3RPpl8UZ4vAmOUAdeF1IBMQZnCDYi06IjgQp7OxX5kQAhoBSonngAmgOWgJKSKwAwQNSoDydzezqn1uPVdcDhyityCMZAD5Dk4KWQEUgMugdSAKbLun6B2gIVcPSTAGBCAHMCh2qUQeLRaB0LgeA90ZluV0srG0toGTIeBz8jG1sbGxsbdO/ezLGu32/VaPc3jZrNBBw4i6kxqpWSWSSkTq5VSvgDHQU4tZZQYzjljjGnGigQHZYwxSksttbZWa21tpC3ao6PJZNaN09jzvHiSB17oV+1sEhtQaOnq6uo0GgPAdBy166Ldbve7XQCwSOv1OhiVZVk5FBRxeXl5NBoBACKWq1XG2CxOPc9BxHK5nCSJ67pSSsdx1tZqnU6Hc46IYRgCAKJljDGXOY7DhHH90BgThmGapq5gftcaMIKJ1lLD8ZwiAk9LzZiytlEul2Wmc1WnlOZ5rpR6/fWlNK2EYSgzP01Tba3rujJ7BOlenhovKLnMMgLg+sTh2bNXp2LkCxa7M9LQC6Tpgq5ZroAYQAREpNSQs1jU00Wj1LzGmHBBakZzIERrDYiozlg62HkIJ7FoUZsFpL4gnWaRZL+QQTEJDAhSi5YYY8BYC8iBEUIpZS6olBpjlDLaIqeWcksIuB4IFwgDY0iWWAMGkRBCGAfmAnMf7zi5ATBzC9x8JGweHvt4bKdusPkPBIgA1FgYD60BlUPoA/PBuMXMnD5rPo+fc1wwBnwDMYPxtNg3gBIQzPoeeA4NXPAFERysnPve4sIpkAJ1wSro5FCY8Z6k9iL25qlwiRFAkNkADKKmnFZcKAnwQ4gnIKWM03jQG2XTIEkSx3HSNB2NRt1uN45jlZtMJnEcR9NoOu0bBZlMCCFIwaXEcSgAdRlzrXtqtTFaawNGS6lUqrUFY8ypY5QWChRjwMAVQgeB1hItEiArKyuHh50sF2gdymmWiIOdmeM4iI7O2KgTjwdSGaWldFm50+kQQj4ZTrXWW1tyOBxaa8fTYaPWCoLgpN8FQmSWtZeXp9Op53mzycT3/bWN1sHeHmGMMdZo1OI4lVkGALWWs9Ramc0mmcyUUpcvXp5MZkkSBUHJ87xKpTIdTwv3QRiGhBEHNSFEpTlSqpTinLtCEEZcAbWKxzn3/aZRRkqZq1wwcf1qPpnkwBJ/iujrnNtBAkmmS96irIgFKNhPESRuHr9uuoDUCTEAwApzDiG2iIs1Zk7txhSyGS3SWjilhBUGMDzbUZSa6+poH5essghyYcTmorEv2hoAfsbZXkBLi8KABWsRCSJYrbUICecgXIgBsgyUUjazmtpKySK1RuETpGvQagBqrTUWTQ6KALhz0b2gRpOfKjniVHU/87o9MRJ2WjmLEuAUpQYLNssAMwyrQAAEe7wjAAC4EOfzjYOc1udThhLGWrao40t8AUKA6wBjQBmEIeQKIAUFgFQjEqrAcGDpaVLAE9S+WFWHKjeUWwKEMSAMGbcuARfgcDd2XddSroAZwyjnibTd4bgtdbfbTbLIdV1l8tFgkiXZmI11lhgDDIBzyhiz2hKKACCzCACklAAgtZRSIlItZeHOAWMsWgKEMAJIKCO+Q+I0YUKvtuqlKU7HEYC9fHUziWbDsVRKhX6wvtoeD/ta6yiKN1cvqDyNZ6kxKtG40lqJxtFkMvGCCue8Wm+fdIcEOOcl369rq4gTGAMarBfWx7M0StU4km7J29kfJBn10OkOJ9K4Wqk0zWdxPIy8k67s94ec0iTLhmPsdvuUopXTarXq+/5wOLTaOp5TrVbjWZxFESGkVqsJIcbjcZym9Xp9qdU6OTkQQlBK2+12lERpHCtjtja26sswGM2iTE9morUFleWSypu+/4vlTj0NZ6Xi5gt1wYt3hEWLrNhm52a2UzovYAwiGmvxrKSsMaCMMkZZQylSfUrq1s5ZnDZz3/hTb6kXDMXi051VYPDMmX9mULAWOQGLBgqntzgL7LFaS0Ra9Li21qocKAKhhbpuZlNKEjAKivw1Y6BwIKocUwRCQJlTp1oK1sA8yw1RG+QMiHhMRQa+IMnn6WPGTlPUWittwJrZwPHLIE5D6Oc+DwBfPDZEMgKeDwAgYu55QPC0avepyUAaYBwMAHONg1YjMDCuAkOADOnZmM6oHRYX2AocTQhh1CJFVxCKSAhQaWc5GkYIgVkMgQcKQGtHW++DD943xhzuHxNg0+mUEUEpV7kplSpSSy11of1mSZar3GpLMGWE5SovtGUlJeccUAvhA8CTYcuUIloMQy2E2doqvfLGFUrtzs7Bxx9+Ui6b3/3Hb06n04ODg9ls9ua32lsXRRRFH330kVs37eZ6ddVN03x7e7u25twonxsOh0cHQ4t0bamUziqMsW5Xra14nHP9cAoGciYurtdNMsyyhPjkykYrsvbhw4cyT4PAWV5pnZyc6EiGobuxsgQAKk1d4cZxXPK8GaWO5wymkSChlVQmaJSlSEzOTo6GnlPKskypTAiMY1CKZEk0m5A0hVk8yHO1umyH4zEAxLPZ8aGq1fRwOI0Sq7H6mpCeK4wluLiw2iIUEWr2NBXKmMdxlk8FIgUEph/HmRes0haGkyIspQhwIKSIiQZjjNZaaw0Gn9gTrDl1fBducblAkFgEq59+PoXCSX/myS/GDeARPE1ZpRQAUGtrjMnzlBCIZ27BvSmlFDn3aOF7V0pCBsXjIcxDbiyxUlrGMI0f528aaU+tj5ZyJJoYgmfaxNyz9YTqPldeGFADhoBUoLW2RktJ8pT7AgiAAlCnBpgiMqfg56x4Qz5wcaqwkPluneVzT37IgBhDjTWkMN0SYF+wFxQawV/roWXUArFCICPIKOHUojaAJpGYT7XJ80e7h3fvb6PFzv7h9vY+dTIwxPVFvV4vZHjGWJrHSpksy7TWRXazUaZgEgQJE0xbzTknhBBChBBaawsIAIzRU4v9fDy+GzOWl0PYWKusrCxtba3k8SD04c1vrzCx9ckn8OMf/tivxxdvbnmOx0vDcX/2zm/+FiFkMBhM/uAwrMMbb7/OOf/Jn/7k+PD4jRur73zjggHzh3/4h5vr4euvvy7lW7c+vXXv83tvXl95/WpLKfX+Bx/4bvrON97ZPd/qHB93Op3rl1duXl47PDzc399tlv3V1dVONTzpdl0i3rx+uVHy+t1u4gSry+uccy1xOp16TrC2tmEU7B9OA7/abLZn8SxOE8aCwC+FYW13/67jhI1G2fHKk71RqVRy/cDxmrNBP0tKDnOFv77euHnhSnX7AE7uQ7j8DMSyCMYAXxBAwrkBABY4mrHivZAs89KZZQyI4JwTJgAU5CnEaWYUIwRSBUi58InWaNCo5GdI1BgAUAv854tKwHLpWNQqNxa1UYAUKVLCQDEonGTWIjEEi7AGink0TzI/C5uz1lokakiJYxlJXQZ+CM0mqzdoUAUds8EoHU1TmVGLniEsnUEUq3LNMCCMGZ5Rt+DbBYfM597HIg6PEAwr4DOYxHObPCm0dwYKgBHIzvKHDSgNAEAoMQB7J+A4ZjgjlSqcFeGe28nPnNsAYIAZAANCgFGQ56By0DkYMt8IRkODiNoSrsEAEcZIqRWYekjzFLTWBoEiIj3NunepUSC1BWP0EylMCShCUeYcgCC1WqLJ0SK6rvV9eu/R4V+991dZFhGTo7a1mmO1UsYoZYbdI6WUMUpri9ZKMIjUKOUykWXSFUJqzRhBy7RBzjyptOvyPMsYZzJXrZo7mUw8z8tVzhgRzI3TWRiWOV3KSVdUGaU6n+V14p9v1IAN6v43BoPBN298Y/v2/aZfXy43rbWvXXrlx7u3S6idar7crPffen10mK5/oxrU6NJ/+Z1/9s/+OS0lV25ekFL+Pfvm97///Y3LvyG13rj63f/+//4BLUUrzeb16zc1H77//gc3z1fefX1tMpn9j//j/3CuCa+8cgPx5h/90R/t7e389q//utYXDvb2/uK9v1hu5t9+69tSZn/4n/4TE93f/73fT/ObP/nxj+/fv/+NN8rffedb0yj5kz/545tv1dfXz41G1Y/ev+Vx9u1vv3HtSml3d3c6nf7O77y7tUaUUh/duvWtN1/h3InGfSPqXVnjG0s/3AEL4K9IwKdXW3IWOM8yMl+HWlsLFqk1FoACaEREyuebqTFQxI8oxQCAETI3lRgDSllErRRItFnCtGTF4jHEaKutJRaNAQPGaE0ALMXHUbKAaGAemMYWKB+Ldp1MWWvRArEKAQA0aAAwIIyCJ3zahBCiCSJaYgrmcEbqp5Ww0EpLHEupLerVKQWgwCsDGbsUZWp1muTWojGEUpqnOREmzwmAQUlIdmp+03Mrmp4rFibPCMBpqQACCMCKreG0odLcV0mAIFgEA0gQLKLUcjxiBKi/DG7RqbMQAU6lLwBgAOY0N16dyma5mQcRAABaqxUpuPeZFEYIeMy4gbUKkAEaJHy+Q0UpGAF5imDQimL7RQBgFAuZxNpMZ6BysKhVDozRYT/udrvTaEitZpQrG08GibQJgDmzl5+9L8ZYsW4ACCFg0YIxSgGlSCw5S5SknFJEpJQwUjjGAYByZJwxJTin42gcllkUDfvDfu9wIoyoNJYAJp99eq9Zr3dmvQubl0aDCQPmOI4gotluzuJ4nAwpd6bT6cbFzdFopK2TZHpzdXOptTLujxuNhsODjZXzMrHlcjlO02uXbqhYXbl0Y//R/rVLNx482HOrJsq67fXa1Vc3MtsvN0mSZL/+D771r/5fHcdxXNdttVp//r0/97ygVqlU69XucHzr1keO41Qqle9+9zfu378f+uHNmzc7vd7du3cmg9GNf/g7cTxD5Hc+vL++vnr18tWjo3P/8l/+y1KQ/Df/zX82Gk18P3ac6a//ve9Mx8NHu53pASDaPLJ+CTnni8JKfk5aVCFmE4LGoFFAafEWABAf13qHOT0WRjlWRLxYqxFNkVZEDBii81yBYtZDYYkBIMQYA8wYTa1SyLnOFWH8cTL5WdK7MWAXZdgsGLrONQBYQKAIMFeSrbFnYUGIaIEYaggBtEgcTcgXLAIFtRMCSKGgIMotpZpZZgEEAT+AKHKJypRSUlpjBALTVOcpEqJ0hlYAUuQagQC1FB8nz1ljwMwgTyEnBoAwAYwBc4Dkc/ZuTiMZjALDQGqqT311VlttZTSBsUtVee4meazzn8bkFcaQYhdQClQOSs/Db7RFotGAAUVyM3eoWIpGk7qfF3EpFNEiUApFVMZuB4wBQ60l1j4Zw8OZtVYTq5TRVks9D4hKYpWmaRSNkyjRMqkETjaNJGZCCCiCphEpIWfbK1pEStEYxohSlBCG1LIitZgQBODcEsKK9mkuAAHCORcuI4wAGLQomEBEzxW+r7bWNpZarYOdfhzHfiiC0spgMvnRj37UaDS2NraEYHEcv//++6urq++8/XZvstsdH2qtr16+qHLS6Rx/dOtAuGGpVPrggw+q5XImJQA0GrXd3UdJkoXlcOv8+Xg2++zTT4sstyuXLu3u7m5trE2n081z59ICudRav/HGa71er91suz757ne/O5vN4jR2Eqe11FobbTieAxZardbmuXOc8yRJVpZWbly7tnt43+HUrzevnr94vH3scKdS065fu3ixRum42WaU4/KyICQp18OwLCZpWp/qsmDCoozBpMDDp9PFoiIo/It0dGpsRo1gvxiWjgwBUKImGpgQZ95ryxgW+3ShTApuCBLiGg5YWK2sRcwRXWstEoJnlFhQe7GdEwAdL/CfL0gmNQoBgLDTccwviowAoYhACMcnsrytmSsKT7katSgEcAcLpQQQ0EAcAxMQBDxJENI0T5VWYK31CRKuZQaMaIkWDS2ewMwDb+xpxi4Yo/McFVOIyA0SQqhEypEAILGcIzmVtcwTpIXWEkoAQGrZO5HjEa+Wabl+SurmNOruNJUdDCgAbSDXoJTR0hZXVQoLxUJq1Noqi1KitdAuIyGUUsoEqBzQWqRIGASOtdZqaoGYL7hOGVc5aK0larRIiVHSorXUpUHggLqwe/Hu3sN7ShnqIQefPBHwMBdeLAJAETNHKRLCOLeuEJRSVjhaz/ZfQjzHQUo5okVLGDEKEFFKg1YCQJJkrSoi5O3l5jiaTiaTWrC0c3BAmNJaZ5kcj6NGK3vw8CFaPO70qtXmJ3c+LFUckxulTXu5znnpcPf41q1Pg4qu15vlcvXhzs7u7u7lixcrldrO3sG9zz9HSm9cu5GrvPvRrTt37qxvbl65dGX7494n39/t9XpXr14Ngvr3/ufbBwcH7Xabe/b4+PgnP/lJu91GxEqldOfOHWOgvb7KCPvg/Q8cx6nVapubm1LKvb09BiRwnEub5453dzmn1NLL589Ph/0ifvRbb72VZMnu9natUdva2hoMBv3pFHXGmGFWynjgQlsBuOWfV9rkqTgLMP8pt1T2RDnWs2/nvFwYxpHaszXNkSISQhiDohQkYwYtGkKkRkFAW7QWPW0lWkqNTE65+ilJzIe4wH+OCwR43/+CUkICRItgMaQuYYQiJfNMb6W11lLnC1K0GAGHU5eBR1EwFIQwBgwgS8HAqcktB5lZgwatAQM6KyQcUgQCWYkWAR2c6wNFgg1gwYVVagiDRBLOLdHAFCl8E56hZwNSCqw1ShXuTmLRGmWsVoZaQsAaehZsp04JXp2y+jyHXEGuIJM2V1ZrW0SOE2OtLfxqBZ1ba1EZdN0i1BQAwBSw1ijkFqy1lBlr7eP9kEBugFOLlgAFJogiYLm1ijgBtFp8uVk92rvXO3yEWhtFQt+dJsmpSWRelQTmdQQYUmoMUErBmHmCKqdaz+2dAKC0ZoQopcg8etoWirqUEtFSypM4MVWxsdoMfXdv52A6jZrVTccJZmnv1ke33nrrzSvXrr33F++tra398R//0f/x//zf7u3s7ew9uBFcYyS8cmV9PB2vr5b29nZuXHut0qr9wb/5g3/w278tpf693/393qA36A2azebNm6+vr69/+PGHVy9f7vR6V6/ebC+3Dw6OLq5d/vzevZWlNauxe9L3fX8ymrWby4whAORp/sEHH12/fjUMw/F4+uMf/vDmW2+e2zwHAO+99xeMsQsXLlGkn3zy8agzeP3NV69ev2ip/OjWrXZ9dW1tzffDw0eH/e7J2traWmtzNOjtbj8IPPfq+Tf7oxTSQaMUtGo0zaa+aA8mQMoLnWSLAszJqYnYavypL7Aox1qUeS1iPBAdjoiEcQfRkrlplIFFFKxIdwFESxQlVEmDWCS0GCQcrQCSgTo1AxV66lmVeFhc4AnJ00m9FJpiJVlbsEpCGEHEaigYAcLAKFDKSAmZNEppHXNjviioIBICglrmAiKlFJkwlFpqrVKY55BriCeQ50pKbS0iUERubWYBCQG0xGpLKWhLKLFKkYJqjLGUzhkVWgvGggRCZCYJpchcTXNKqQU6r4cDAIVyq62x2lpELbXWmlPrCuH6blCeR6GfRdoZAnDa6CbJweSQZ/OLSGkBrVLzvdoYMOb/z9qf/1qWZeeB2FprD2e405tjyojIoTIrszIra2CxyCIpUaRFjZbMbqnRsAA3WrAE2N2AYfgHw39Fw2j4B8Mw2rIlWHZbbfcgSmIVxako1sBijcmcM2N+EW+8w7ln2NNa/mHf9yKyqhKG0X3iZeC9l/eee++Js/Ze61vf9y0KiSNT3v+dKGIYBogeRCTyht6QBEQ2jvpyIQRExjxiQzIfUoMGSInAQl1TOYa9fdjenhGQImGC3MDZNMYuigS8yHa0phBAa0oBYuSUkqDwZbqFGEIAa70ftNasNADE6AEsAKcARaFTSntb9Rdef31rXPYHO+1cvvWtP9vd37528/lf+7WZ1vTNb37zMy++GCP/8i//ypPDJ93QvfnlN0pdDoP/4L07V27MIvj1sC5pp22b7e3to6OTcT2eTCYPH953rm2agjTt7u4u58vzxeLxo8d/82//zYf3H965d6euAavmt//+v/+f/+f/h89//vUP3vv+f/gP//179+794e/9yRe/+MXJbPZ3f/u3/8W/+C+tts71/+gf/aMP7t37yU9+9NJLL7/x5ps3rt347ne/TZquXLn26ouvVFVxcnT04iu3CqVKrY+fHLv+3v2753t7ew/uzYHHfQ9Hj5YvvPDCsIbzdhgVqCd0Zbs66b3DHoXWC1PMfn682E9Bt9WlbdRPGUMkEHqq5iYl2S9uslETEBBh9lfSBpiZc70vyiqQ7C+QErAkBkWJQaVEqBJEuXylCw2sZDNUSp+y65qf3z8fFZzVaVqTUoqA8mZSFJfdZ6DIpgATCEivBlKYSRkAF103QURkJVgYUQo0ADAzsiRsV9pHcD3zAEopZSANJCQxQmFEhFCjJgQmZQQAmSEliZFFJEaEZ2sHZgAWjNoCBTKGlUIs8yKKiMjAkjZ/SJPWpIyqjCprPduG0m6gltyZz/QbzkU+QPTgPYQggwcfAVBCQACRuCnHUpIgyEESIgCcLyBuYLb8b0/MlEGyvJEyb4C6nAZpigyEhIKYHF5st0JUxQ7KXaiqoizJkk0BtNYVaNmEOuYFb6MsjJybkUQSmSGlkJICRtn8AUQA1kROhIBQIUXyQYxCAq1LGtejbt3tbU13d7djjATEQN/97ner0eQ3/8Zv/p3/0a/+X//pP/3h978/tuPXXnvt9c++/v3vf7/v3CN3783PfUVh/G/+u//P//x/+R/MZqNf+ZVf+df/1Td/8sGP/s7f/tvPP//8fLn8l//tv9qaTl977fWDq1c/fP/93/s3v/fyCy9f27v26ouv/vC7P/Te/6Wv/fpkgiLy+7//x1/72q/2ff/Gm1989OiImX7hF35BKZOSfPTRB9euXYsxVlV1vjiv65qImBkFiWhra8so8/Dh/a/81l//+OMP7zz4aHu7euPVVzXVq9MP1qtVKPClz3/2o48+ePf+h7du3frFX/+aiLz11o/t6LPj7dH6/JyiqaowH1ZbO1sA4uTnx0Wtfn4cXe5z+Z8PLvd/obyQX6DEsOmAiygR2gTJhUEyUJQQvPfMnpkBI4qklDJzJqUkkkRSZjKrJPkr6zCf/og//+vnvm8AqC2PS5jWtDXWW2M9HevZSM1GCNjlL6HelKGqZbqtZ1vFp51Ha37mVVhRYs9J0jAMF31gpbU1ygBACIEjp+wSwSSiEJE9wWb/5JBSjDGkxBzzp3ZOvIfBc0hh6KL30cfomZ2TECQk8ZFDkMsvETGm2N0r9q7p0eypgaznp20FnWlzGX6PwAlCutCEBBSRmMknzBwht/ovCE4wb9OyCfMmLNZxNUDrcIg0eIpx85US5q8YKaWMhGNeT/Wm+ccppW69mp/150cQnHO9QwiIAJS0tcaYXKUISkgpO8akELyPKSXmmP055ML0j4CAyChFpPPTtbUKVS77lVHGmMIUo0ldVMV0OrUAHLvDJ4d7O1svv/YFID0Mw/Hx8WdffvkrX/3q4H2MkZl39vbeffvt73732yLYNv0bb3zu5s2b7330HiKGEBaLxT//5/9cELe3t999++0//MM//N73vvfi88+fnJ3969/5g9/93d8NKW3t7HzjG9/4xje+8d57771040uP77T/z//Lf/fN3/1ByXtffOVXfuf/9Uf/4v/2b7yPb775xpUr+//Ff/FP7t69/5lXPvO1r31tuVyenZ390te+9uWvfBkR/9W/+pcM8Mqrr/ziL/3S17/+9RDCV7/6laIojDHf+c63XO8+//nP/8LXvrTmTo3Ma1967cXPvRhUuPvk7qtfeQO5Oti5jglnk+LW1YNyJJUVl1r1TOw8+2US/twvxLz90E/JVSxwgWJQCiWFEoNSoFhg6V0cvO6AmDkz+N05AqCIIQ0XVAeFggPHn9F0IgCenG9oNJd3bn7tuvr5BocSN0QUqzm3qSyAIFqqSYFSRmsEAhQWSAxsYsWc7Vxx4A0izQS+3dja5exUmVz9obZMEYYOXA/NUsvFg9YxJxukibSlsZGiCjHGJsIgiYdnsCsCFDw/morRkpCZM5OPTAKAg1Gb13UiIkLokYgBeHKQsqbSGKNzucEsSXavqxhBEyDAdAz1BbR4SS+IAIMH7y+8bghIAWkWh8GBGyAO6AKGyohsjEAyyJ3fQQ0d6swmx41tvBZE1KRdm9bRp4HzIowITHJ9l5l1StR11Paybsg7xZEmfW8LSgHe+eAsmf02QoyRBw5pPq7HAMCcBLFt+qqqum5dj+sQQlmXfvDKGAYYT6dd1yEOZWGTMGnE6JxPZETpEJESC2sOqb129drBwRYAb21dx+3WbtkQ1Pp0UR/YX/7qzpW/89r5+flfvPPn+1f2v/jFz8y2t9umfXz00enp41c+d+uzt//6Rx98MJlVX/7KG2O79Wd/8PVb1/vf/Ku/XE1GRPr48HQ22/5P/pP/1T//5/90e3f34ZOHv/QbvxEp/vi7fwr+PHaT/+g/+vv/7F/8tz/56IP/CZ+//qUXfvnxmz/4wQ9ea24mdfurv/a5r3/967/7ze/c/OzrONovZtd+9w9+tHvt9RdeMIt1/Y//0//06//qTz++2wXcfv/u6byX0f6Vna2tnzxqH/dPijtnv/Ubv1UYc/DcV/7o3/7bdaw/88arf/rtbyPitf3b85P28Mnphx8+bJbh8699dj2s/HTvxksvp6RebE60gTjAh0ehrEsAQJSh89rSuJ72rt+ZCRE4F4qiICLvfe6JDEHFGIdhUEoVRXHB+xTXC3NyLmirrbYphSRilPIAISS97iJfHK5VkPPhDRqTNWuQPtXp9Zk4BwC+KBU+pUlAgUQJbjxtgECRBoVYGCJF2pLRSApYAAmYcfCMKJwQFaMAEMKmBAUglsstzqMywo7WKiuo+ZJCkG1quj5bRG4iRERijCmlps0J50Zyf1kIBNdkEi8hayMApAgV4s5OjZjzfMzf5N14NEIiXVSqrLLYDrwjZvB+8zay+iWWoH9qyfxkqTUaQxgAhOIARKwBpBArECWBiLogC2aQUJKwIsLcDyRBVAqyqXVeTzGp7O4rSRIJRnJOiCR35lHQqBQAEiZTagTsus57v1qt6lIfHByw97mxOwyDUialUFWVtbaodpmjUkqhisx0wadOKY1LCwApBYWotS6qIoW0cQ7AVBhVVWUxUt575qhQQghFVYy0Pjg4aJqGCPb2dgbfNY1zzt26dasoirfeeqswxfbu7sHVqzuzrUdH93RpisI0zfJk/qjruvPFYmur/I3f+I1/8k/+yUsv375z584//Mf/U2vt/+n/+L//23/v72kL/+v/7f/uz7757w6Pz4vR5K/9jb/yuTfe+J1vfOP11167fuv5X/rVX2/b5k++/d0vf+UXXUpsx03T1vX0l3/51159dVGW5Z07jw4ODn74vQ+rqmraYWtr+uWvfJnJo8gwDF/95S+KyMcffvi9H36bwL75uVe/+MU3i6LQWu9sbb3//vsnJycvv/zy87duaa0/fP99/uxnr93Y16Wez1d37h0dH652dm5cu/bydV1FZiIwxoSgJUlRQBXNrFLr9XpnXBaVffzoMRDtXb2yXgydDKRgOlMxRu87Y4xSyjkXYvLea62tKa0VYI7MRUGWE1Sg5ydJsgdQkjRs9g1EgAsDZkSMn4J4CwqnDdU03z3ISFrEf0qsI3BC1OJCRgVRUIMFYxIqsASKgAAwi+g1uC5lEDxmQn5ur3lAhbnKzEwUAQgBUXi5yj9t+GGIkltffbYXI0BEyqg4syQZWn1ht3XZmSAA2Jp4EVQKlVK2JF2hAk0G96YXpJ3NVrq5PrYW0mQt2BpQAzGQhsjQNaA1MAB7GDIfroTykyNfYgS4KNe1BrYAAxglSgnZhB0owyApY6u4uQYimdyjFPNmeVKAKSEiCkDPKV2keT6yYJJAiJyXHkSOEXOvz1pmD20T9namd+7cXZyf1qWuy3p/ezul0PdL5xwQVFXVtzCbjb33k8mkdy0iMrNzLu82AGCMMSaXP0xEl4kliiRJmsAU5e7+bFqPERMKmqJ86aVbIYSH9w9TCi+9/AIz/MVfvOP9cPv2y67vnXP379+/9dxzIqK1RYU/+MmfT3dKH7sIA2h/fv4kTuMLL7xQKfWNf/1fvfrq1aY9vXljFofF4eHh5z733MnRO9PpZPD+uVc+1zbt+eLJ7v4oucd3Pro3meyuFqvPf37n9Hx1//7Dr3zlq13H03H9k7945/r169ra5567dXayfPz48e0Xbv/Zj/7szTffnNUzrWcvp5eb0Lz8+mevXt0DsCJ454Pn1+frJ4eHt1+4+cLt20+OT9/9+P2dg73PlRaNenJ6fPXq1avXr67Wq8dnj80IZ3p72c+DLFn38/nh9eeul7ZfnC9W65XrHQBMJhOZTgEgUAnRDR0dP1n8+MdvKYXsvzAajdj75bwpqiJf5/Foq2maj97/8OrB9eOHD4uqunHjxt7e1bKs27ZlXqNRXdfppgOOKEIMLIngQlV+GecAkHVLPydys1Esbpj3iIAM7MF/imOsQcURVBIw4qPahEGklDwCByEGRERizv0lBvQMzCAICUUAQ5IEKAlRAREl2cQzgKCWZacuUQoESbypIbO7DqQcpLIhegGOLjzhcghl9EkQtyaFUqKUUga1JmOUKpCAChOf7ViKgFIIAIlCAuKkXEtK4SabEEkBRIgAvQeIFyBiuYnzvO3nKQuZYxsHCBE4QGQGiIhMNgGDYVCYSzOAjdMApyQhbXhEpDMncvPPxAMIZis7FJTkISUkor7PMscEDMystCCBNlKp6soN9Ud/9PF6dX7z2k2A2PdNSqF3PUdWqEpbphB2dnZOT4/hot8WUoAsNFBq85swmKLI21pICRG11daWWpwxxXhqp/W4rDVEJtBlZQBoOp620/75F2/VZX1ydvb8i7euHlw1ZuKHITIT0Pbu9mQyOT4+nkwm4zHt7u6WY+3c0lTmN//ab07rnTfeeMOvO/V2urK///yLt/q+/eijjzT5f+/v/c22b04X+o/+9Dt/9a/+/ZdeeulHP/iDpnlw585f/PZv/4Pr169/8MF7JyfN3s7VX/3Vg5RMVc1eeeWV/d0riOqjD+6sV/7s9PT8fPXBex9de+Hay6+9UJZ2vjy5e/xhv2qWzbyamLKsC6N+4WtfWM6bb32zqSaj6XQ6mk3KrVpEjDFd121vb9++ffuP//iPHz16tOjMyfJxWdvxtNy/8Zwty8O756fnH0wmV6xeaj73Moyq6vrB1mzLBO8X54+ryq4WK2vlV7/2St/3MR6tFtK7JClc23keQM7mp8Ny1S7nrrnfW9etDve3bu1OQuoftz1E5ul4fL5cHB8daR81X0B5qJ/qZp8dePxpM9IQE5JwxEvzUlIgjPQp8pWYhIhTBCMANvU9lmVKJL1LeTu15Ubdmd1thoi5EcWMyWfBFmY7EUlAWiQQC5OWHDAhbXZ7ERAEvgDpbKkuG0VwyQZBnGzFyxVts6gBAMB4s/2DUqCJyXCGLnPqm7PiDd7OJILesYioTfnwlJavACWpQEhCQFISbcT/GuIAfoDIIAxIQBepPnggBg1gLSgUpUhEKAgQEmV/HcmWjwl51V0sqeETnAVMiIghYWROHkJA1kBM3hMDc2TEpBC1Jq0JgD7zmfIvfnD2wTvvKKNu3LiyWp0en54CD8MQi6JQCpOkjddakvV67eNgjEkphRC01k+hQhLI2JstRiiFKQSxKgoINN2qC2MAOPStpMDASsn+/u7p+fkPv//9z3/hC33bI+KVK/t/8Ad/9OabXxm6jgFGo9Gf//mfv/G5zy3Oz2OMzPCd73znV//SL4QkJycn/+O/9TeaZXj77XePD49/9Ve/RgSHh48Pjx9+4Qtf+FL9pR/84AdXbt44XTyxevzgweM33nz1S1/62vxsZ7GYtc22KqrJ9v7bb79d1+PZbPLwrXfRjF546bUvfGn6wXsf3b//pHWrkLAspx9/fFju6K5bAZX3Ht958OjBgwcffHj33f39fa67sd36q3/5r43LsQceYMA2db3XZdmtu7Iu9g7GiOrOgwcPHj2+ev25oOaqwGU7r2ZXRxO0VE1GV8b1eLpVVCM7nY6n0+uT2aS0pSnMauF3pjvGFGc11HV948aNtm3Pz8+ZOQKsV6trN7a7bi2kZrPJc7cnn/vccx9++PGiCZMtuHajdsG1TV+VejqTm7dvze6CDmQue+PP3i7wTFX5aeJTAoKNZnyTwAsjAKRPMT9GFEkbwSoGSDb1TlC4KRAIlQEMmG0kAJCs+C4zZ4AZQpCQEBgioIigysydPG/pGVCNn86Wy+dBQUtCmi6zysudeTTKqMEm2i9+L5QZ7woQkUEg5gmWDGDkqaElZlIxEYLbNDfy6S8/b6FYKUmJgAENiAhHZIY4QBzAO8lIPCWSpz7WQBpKIc06al2iMAD16QJ0BRTRkgULIM3TD5tVvZuTsGaGSIm9hCSekSIwcdsRSgJIpERXUNdUWq0txQ6+990/PXr8+KWXb6fUp+SIY/RRREhTCqnv+xhjN3QAMAwDKokxZuFaFmbnWn0ymRBQjFEpNMrY0sYYY4wFJhRhjojBDwkxWKu1htFkcuejj27evplS6LpuujW9c+feZDJZnJ93wzAdj997773JZPLg0aO6rl3fnx4vR9Xo6OjspZdfapbzk5N59PT1f/WH3/7Tt95//+E/+Af/4D/7z/7PJycn/95/sPjSF770z/7v//Vods2o0a3n39iqt37y5x9cvTr96IPHq1V7ePy21to5t+58084fHh6HFLa3t8/mc0T14cd3I0MIKMqUU31+vKpGptwqj85O3n3/3dX61IUwb06qWfHw9GMNerxXfuHlL+zvT8ppObJjhiUP8PHHd7/93W//4i/90udeffXju3dRYVWNnnTHo7JacHf/+P2T5b1JNfnM868e7I85QtPO79+5e+vWLaB43Pd7OzshpcXpum9dUZnRpHjw6E7f91aXSYJz/TA0bWNXq0UKTmHpBldV1c5Ofe9ecG5eFKK1SoGn09Jonp893p4YnXkSm1vkkwIbvogK+ylycom5NvxECiByAYv9zKEScnaJyuCQT5EiAZw1SJTIAhEpFFQCAGQBlxgERSTGTMtlHza6erkYSiO4oXmLiCIRFMLNyBnCTR1b2kBaa00KL6BEAEFIfd6GceN9vcltZNPWT7knLNmYHRW44WljKQN8mhAVFNl192dYPcWEUxbuaABQmbWazW2ChxCSSCLKxHoAgNSpzKVBQlUoAwAqa1TpmVWYsyMIa8poQdY5IDz9aEoZpsC9OCcRmDcUHQYmiKK1FDUopUqr67HWmr7z796588FH02ltLT28ex+VRD8457AoJElKwpCMMd26y9FrCsXMebxpURRJEgGt1+v8Gj567jnGmJmCSqnxDEWS1UBkUJESmIxGV67ucYwhheeuP9c0zcHBnrb2/Xfff/3zrz+8+2QymYwmk9X779++ffvD9z+8ev1qXZYa9M0XXn98cq9b+b/4yUff+973Xrr9+qgYPff8qx/dm//O737r+c98+eHxn3zj3/5A1HZZ30qyhRHuffRohNV8Pp/sbh8+ObRlyWz7vheUUTViZKWorqfRc2lLP/Dp8WmMsFw2KQQ/cNd1qTLHq/Pv/uA7P/ngHe87MTLb3WbicqJR8IM77z7/3Ius5fGjB2+88ZW98fTbP3w3e1cOXUek67IOIYish+gPzw/JxvX6/Ohxc2X/2sHWdDYqnn/xy/P27K13FydtlYqkEK/c/CwQvffOtx4/fvzSCy986fnnFarVarVer9966637Tz6+efPm7o19qrVaLhvXvvfBB3VdlzROgkCagR48evjg0YM33njj6sHVUltE1HBJg7nwjX32fs0/fkqkg4IsbH+Wc5vT4E8xkMpQHyEBkk4gkCIkTL4VRMyqMqUwk+1ogMpnsreEhJFBRDaurNUmDQGEfC/nfR6DPCuCyXk6AYIKSoOxoFAxc7owmh8aDRcsvaxpZ2YR4FEQRGNQGUZBYkCTgKFbp6fXh8AoVIqBSJVP7c1z4Q0XaQIz4AY+VEgbbXn0+T2nlCT7b2RDTtcnAMgGtwoQDSqNpGF8YZ7NEQBygJOIkLYigheanA1ih6KsCi0AJGaOG84ci0iKm0eWCom0tqQ11TV843e/sVzOd3d326Y9mx9du3YtKLTWDimFEJIkhaoaVSmEyWTCkYE4pURE2uoMmQCA9/7spM1VulHKBceRbWnrqp6Oy8KgMaqurSbu+7Yel1tbWy6EW7duGWNsWQ5D5338S7/+l7qu++xnP1uNRkPX/fW//tfPT09/5dd+JTgngs998cWjk8evvPiGtfSjH/3kL370UXfOv/Vbf/Px2dsffPDecvnnv/mbf3l/99HJ2Yn39rf/7j/4xh+/9fj+xy9cG/27b/7BL/3iL3aLRdOIBauAbTk2xixWi6Hrtnd3SZfRD5PpTnaYS72bz+ejapvBKaO0pfv37//oR3/eNEtbWmWQAb793T89+Ox4a7zz6ORJEHd+uvrun3xvvR5u3rz9zX/3TWZeLpb/5uu/t+q6W7duta7frrf9MNy///H2lUphCOh97N798N3T4+PPfvZX9/YOjDHr1QpFyrJ0Lpyen+5fubJYrDYOnAqVMdWomm5N5bFkYzxEPDg40NaenJwIYl3UVVVpretxPRpVVVVdu3btuVtXs6RSP3VxFdit/FM6xEX8I2LCsKlCCeiicU8EW4UAgAsb26MIIJ4SypWtp5x2EZG0CYPFmp49M2wmjatuqSAPSPvkoJiHQ378RkizIQgBVAicKIlwpJAwZfEZAUTKL3d5hvwqhiocNqxVQcwf6/LdbR55QT8CBJRAigA1CyFg8sKDpCQuarhI02FTIDAAu1WZMj9OgqAQMWogksioLRRK2QjeJzuEzIo9mZvsX6VUIs3MkTQDQPYYywVJQpSEcUAAUJTbY4IKgJn0htp+bT+kgMCcRFJCEckUoMakEIb1mofOhITDALoENKpWPgavQAqaGITpVLsm/Te/8/VhWOzuTrTmYYiT2e7gWRUTUXF35okIQKWUQmjQSh99MdVnh440rVcdM4ewsXadjrdCX5ydnRRGYcEqeDLti7d3p1tj0Dyft9DWH310XhRsaaFSfeXN6+V0Z73q7n509PHHd9crL0m6bhiPx+PpwauvfObddz86Ojm7erC37t6TlGxZT+H8V/7Km9GfToqbf/vXf+v87jqI/O63/u1f+o2/cr5+d3F+N6SX/uP/iN8OggAAxxZJREFU+G/sHexICl13rFVbTdRANL7+3Gnkruv2r80ODw9DkK9+9Ze79fr4ycPT4+MXbt/UWoUgsaW1X8+Plt2wunF7m3moRsV6KJ6c3z1rHi3Wi3Zod0f7zkGMcOu5N1bNYYc8qrf+9R9+3blgjPn99/41vAfvPXi71GNxSZL6/rvd6erFl1679vjBg93J6KwwFMlF6Z08Xp6BPcc9c+/ozt1H79POsHRnQzofweQ7f/FHmusqTa5enabUGpPu3fnw9gsvPHw41zrqWs/b+dHZo62dvWzRLwVKCtNyjJLYx75pbt+8eXx47LtuTOABmj7pZ/VwVufoeBqQORKcbPZplKemr8yAKmtlES5sJHPZ/6wiBzMbBgAFlFJPpzI/I8Ex5pJ0iRchDQCgLuA9uYzDzY9PuwPPHptdNH+fX0g2bxUuRlDh5UMvyvR88ks8QkTCQESU9EZTy8xAkAJ4eDYDurggAGuOeVdHEFRCGimRMpgCKQQvoAT7BDGSJkYlPjJAHkMoEjDXCADgKG16eEQEiGqzKoV8QfP+jJd+fpICySadAEnCHnKrqxiroVEpSAbaVSHMQgmaVspyZAtqWy5MefoE3nnnrXfeuTMZVQDSu9Y7T0SkNcc0+G44g5RCTsKLokDEdh2jX5PixJBSEhFTmKIsECHEfjIZCYprG+akrR1PxyHJ3Y/ve+ii1+Px3snRST3WO1Pvo97Z2xu6+PZbH965c28537hZrVfd+eliay9Ox/V6ve7Wqzt975yzVlvbTvZ0jP7ate3Dw0fT8ey3f/u3f+ff/u79w8M//OPf+6u/+Ze3t7evXNu/sn9ltTj/8dsfKEnbs9l6vZ4vl9vb24UxHREArNdrTeX56WkIoaqq8Xi87tYKldHalOrt9z5eLBaqSPsH+5955bnT1fmf/PEfHw/nxpj5vK2qiiN1a18U1dZ0YlIgRb6Nbh0zv2WOq8hRQ9l160pVo9GoqqrxtL59++a1/f1/8/v/cjyu+9BPppPZ9sQFN5uNU6T33333rHl8vlj4OBQ7xXI5P3s0v7J94xd/7WsxRpeHWGrdNM3R0dHR0ZG1vFyevPeem27tXLt2TWsN4LuhvdO8c+327iuvfHa0XVhLL37uud1rs7nrHSallbbP2LKWhcDmLsOLyEEATgMBX9zfF31rACBSaIQDEiATX0avJJSnwSAiLKwYnw5euERrkREAqjFfBuclqwRFenc5sy0H2NMFBEhQSBmJBBiy+xUm3kD3T2cnIgCAz84wfBn7F2fL9vLydDXZvDdWAEAoCElAWCCfcrhwws0joi663IDB5ycqI6TAMCKiYpx4SgGVkSColGgQ0ECMrcsiUNEWLioXRMSAIhtNuFA270IgkqfAxDMfjRk8s4hwgJQkMmRMVJIMjRuGyBAzdAiAjAIUfdTcgYgYE7d24N6Ds2996wePH5/tTAEAYsxPUSG4ruuapiHQ+QAk14fMrkdAW4PWWkR570PoB+cy79U5Kq3FpH0MRVHt7VwtCnrYHPZyOjL7WushDsqpJGCt3dvZ+X/81396cnTiXOzWfrU4L0vLEYZh+Oxrr7///vvvf/ixQkmCfd8///zzL7xwY6tqfvSjHz333K88eHDnv/xn/+bNN37ltddfm/9w/sYbn3vt9deqojg6OTp6dLSzs7M13Tk6OooxppCaprlx48b5YnFydGRv3To4OFgtOlMUpihijL1z1pZZGPhHf/jH9x9+HHlwXfB+nR3yxtP6zsmJ1joFjIbOz9fLZTcaYUrKjGqIBDGmGDkQg3W9EqFJNVsFQYXe+/sP7zfLNsY4G01EpVKXAw/rdcccBVNVVVVF8+Xy3oMHj84eAbExBkWdHc1Tj3/wrW9WVTUdj+8/OVwu5+Px9P0P3z87OdPjoWmaJ6dS2vLJ6dXRaHR4eLhedUbh/v6Vx8uPHi8/mk6nkvDeSds0jag0m+zqZwV0ljKgRkoBZA8WYmb2VgNAFk9fhNCz7WWEp/utcMrsug0D52J0OeCGKgKXEQiwqad1cRF98my0Y97tL17t6W4fL4ZLQC4BsiI34rNxntlvefPeSEH101PlUI8XdcYl9r750W3WoxT4gjuQyTvP9uGf7u1ZCUuWc7vNMCjNxNR28fJhCuDS/S2lpIyIoC034yu0BREwSl+GNMCzfH569h1eJlBtAIhZmZMvNHMkAGmGnj1KUiLIzBGYNAOytZZ19CwF0eOT+U++/9079+5tb890caa1VVPjHPf9ECWpMo01mRKMQWMIkUNIAKy11soIJMHADLpCEZVCEhStiVeDMcYUxdnRihm3dqYQ/Y1r196796TYUsxcWh2CTwm292e9a7//3R/XdX3z5o1JNbvv75+fL7Smra0tW9YhhL7vOfqDg4PXX399f393ve6+8Sff+A//Z38z8rBszvu+/5M/+cO/8rf+1j/8x/9Qe+LoHUeIcPf+/bZ3ZVmuumEy2//SlStEdPXq1Q/f/3BnZ2c6nc7n86qavfrKKzHGH//4x8BsjAnOPTk+fvT4ESqJcUgprNaLH771w0dHj+bzk9ixKEltavrGe6+UKsZFWLqm70ajkTFWEvohuN4FtyKisvQpYaFss24wyeL8nMHfvnkTAM6as2tXrq1Wq6ZptvZ2J6Ptl194Wfvpx/dlNKpccGcnJ9PxVlVVQPTg0R0ifePGtfl87pwbVdWymbvQ3HvwsVJKGbV0ML9zYrVdd+uu6+qpvffxB+VhaYyZTCbduiuKgjRF5p2dXW2esYtIIhxZa0gbaRrHyHKBT6PeRDtc3P0XN6UwiKRMZUFBuWBlXcTphcoqWxpcjFWhTDgHgFJfTlP+hLa+KJ7W0putLH/PwJGANpxcJAFGpeTnM+8vU/RN83kzg/lSFZSnPuWPslFuJZ1d2SSXHxfHJ218nmYZl2uQiKDkzr8Ac9t+Ik8R3DQjCUUQtQYdARhNARQEBOoyPftKz6D9n8BKL7/3HkUkJ+qSkAMC5Gg3iMpoFTynFFglrRgNMqxKqxW6ckz373744eH3RtP+4Mb2ZDwi0CKpaQZWEQDKsq6qwuwm51zvBhSpjDGm2NwUXp+fn8fkZ5PZ1t4OMbjgQkrVrOr7fjYZuQAiqR7Tk8PzrZ3pTrs1ndbe++3t7baflyW99MILZ/OjofN+8KWtDw4Obty8HTmuVouiKjIQfPv27e3t7YODg8lkcvT40Y/fenu7tONpvbOz80u/+LXTh2F+Fr781S/PtmfNycnidLFYd3t7119//fNHJ2fvfXTP6vLll16+cfOG1vrJkydVVb35xTfPz88fPXiwWA0PHj2IMT45Pj47O8t15Wq1EnFlWVajcjKbudC//fbbnV8hYjMfiqKo67qsy27dMTN7btuuNz2iGY0UM2ldAgAzEungnNUlkQWm7d1xVRSmUpPt0d3jj/u+r0bVeDw+eXw2MqOS6tDL2emRUurq1eur9WK1WBhjDnb2b+6/NAzDycmZUtK2y9PT0yyyIM3rbjWajLSqjVLMsXUBMp6tRAmW1iil+nZ9cnZCANPpdFCRFej0TKgPHhCBLqgnsvFsA0QRvripN901QYG8nMeIkoRFhIADskgIF2OPL5SPl27V2YoMc2+cMafxkgjgokWcwy/PkLNwudVf3urZoR2VAEoKqLQACkciJZIdTAUAn82xN35sl5OkL9v+eXnZEGPk6e6dBz8iwKUO5tIQfvPEjffGJnMpbY581ATaCl5MiUqSACCwSMII4HP/nKlAhUowoPKijXQx6w6gVNnIYbMUEmGWHqYLj7ufao4MxOyQQaLPFvfCTACiFLGnGDfv2xZkChQla/d+8JBiK2hFP7p5m6tq7PBMlVrEc0rGpumWRkSlAFVE0ykIWoYYY2SApLXWutCkqzrqEMRMFJoQU/ApiCS1TYTDZH962+5D1Ft7+qOPzqoRfuaV5yUUT56s6nGdpB1Py+vPXT98+FZVVaYoEqb58mxrZ/rKqy+enJyZQp2eni+b9rnrV69ef65tmx/+8Ierxfne3s6XPvvC7v7unXsfPXrw+Eu/8PmtrefXPPzoJz+6Pp627bxb9bB3UBT1YrV+cny6u33l7Xff/uCD9yLz4eHhycnJydnJcrl88uRJ34fVamW1BgBl1OOjo6qqrl+9Op6WRyePx+N6Op0cLzrBdHBwABw99yGEclxORpMkabVYYUJbW87jOn1kjkVRlWWZRLTWBRaRvSabRIwxWEjTL8/mJ93QicjD+w8Pdg6CS6ft+azaP3vcvP/++6oIJZXR+/F4ikq5vvfRn66OT5bHSblVt1isz5l5NBmJyGyyjQpd77AsiYhYlFGOXeuCtTYhrZp1jNGWtR+GB48el+Ox+PknDDCCIALC097aBiQzvIGvEADl6Q0XQsocstxS5oTMggQpJX7KHLvYQEXsJ0BAANjYQkd/EXrPGFcBgKUNzgeQU/bNYhEYAIQDKpNfFJWRlJAIMlUeNgDfhUFSrrH5pxPvp+vLxVLCWQqiBFX+vAgXNg+IggVcPv0CuhRBrIVRIQoYi6hQayQNIkikhgiaefAQIghiQGQUShp5s13nMcyoBEC6gRERBVABkSjE3O4In2Iw5IFTAmCJCVKeXJ42JhaSQjal0loDxr5frbrVMn3fJWdLck5h6fee5xSaYfHkdFEgolLKGGMLncntvvdFUSAqpVR2gPI+lqVFRO8X9VgTjVIKy+Ykm8kCAPhzsjaI2bu+Y7VVIywmouu4v3/t/Hjt/SApxOin052iwqZtIvtxUZelXq3OO784ODi4+twWGrSws729XZblw/t3P7pzp+sGIpjMZlt70xD649P7p+fz7Zu3iso8OTp9fPIYm/nOzt5zzz/vgvmzP/vB3fvHXUjp9LzvpWmaGKMyymp7//59RNzd3e3WPokUZTkdj733x8fHhTFbO1uvvvHi+k8XScLR/LH3bmtnyuybbnXt5q2zo5M+9MN86PseDY6n4/F43IQ5AKSU1t3gY0zJxRiLolBl3Ts33Z2ORqNhGDrvneutpv39fWB2LiyXTdM0vuO7crcsa0Ts+37lV0WhjDGr1Tq16cn9Uz0tEbHzg65tNRu1bdv5IaVUGRN97JsegxKRlNJsNiHQtdmJIYaI64WXJAcH+0TDvHMRKKDSz7rdxKB+auvY1JmfMlFJMLEIAMFmZDYxIEdIhMibhlw+mFEErN3Uosws+ExXzF9Oj7qI9py4jp7NjX/uW9i8SclFOSLRhgaAP4PS/yxif/nLCzx+g9InZBTceObkHEGEGTWKXBjp0DP8QgWiEJQCZUAZ0jrnI8BoIGvXFWsnzqMkTAgpKQAgzdkcEoAvRsFTthKAhClCAsk2vD81QuMpRkCIIjEgi0jKYS4gZApyLACMSimgwbWPTh4fHt/147djHJ6/fuA67vulT4shrndnk8VqTUQFFoQWUQMS0ADaSxqHGGOMAGR1jYgcpfWhac9Go5HW2vtIBGVZiqi+d041o1F15rrxuAyS1t35eFru7IzH0/rsqAUAF5yt9cHVg9lse2dn5zOvfMa5fmdn59qN/WVzpmu4dn335gs354/NgwePzs9Pm7Y9ODgg0m2zHI0mk8lkMptVo9svPv+Zk0fDj37wo53nrl6/fr1YNjeuXVuv/Z//2fd/9JP3tvdvPrd/Q8QcHOx1XXf48KELYTabAMBsts0c+/Z0Nh1XVZVrtKIoUKnlsvn4449dcLu7s4/vPvYwCKbF4nQyGQ1DJwZ1IgYYm9qWJTMfHh/uXhllXrD3HXNMCQFSUYxTSpLw2rVrk1m1OH2yHgalFGnKw6QODg5OHp1ZXeua799/eO3KjfFWOT85wiKNx9PlsmmbttbjeTOvaLK7uxt9ZOYsNOj7PqWUelKoJChJOAzOe7+3c7A/2+oit8uFMUbH8WK1Oo5rIqjMthv6ypDOHtGbW0fSUxoMAcAG1L30M1aIljd+SYrg8OwpZ14uNWIAffr5M6jW4cKomDE3jZgRAFrr8x2MeZLMxc09CZukmi+g9fxCq3UBG8UIZzIKCwOkFH4ma8hLxqfMhHva+cshdIEWFnWCp5hCptwRCv78s2SDVA3ASJaEUZCi27APtIjSSXtgw2xi9uU+v6iPnl75ACKyPMug6MbsDzH328CVTxkHzxYaRb7mCq3Rqtgs8DHGNpjzxWI2qRjXO1ew8R/b4m1d3r2a1GqVuvljrzVQRCxmdjaZTW9TWK86a8tuPaxWXFrLbDXZvgl97/PdjAo1kUuuUMVIXWuWjQZEY22pQzDBtVqXoZpDBaLUEzxMSbqm0xO6t/xoFHHnxvaVLV2kURnHL7x8+8mTYdlMzKTRY02VjhFGs31EXKygeOJDbNSkJx4OxvV4XGutk8xGVXH9lsTYR18/PjqPkc/mj3u3fO2114+u7vzx/Xd///d+/+D61Vd/7dWjk5PZrTQeV3v19OSoP2uTTVgoINLaMgNcubK/XnVt05RlWepSzRSiEMPZslfFpHHqxu3X3nnnncbNUxh5jwOdFEVhrR3VdTEqulW3bJYoZELvU9e45Y0XDtq2f/Tg3o39m9qv/XSwE3z78Nsxxr3d3bSQGOWonU9wMnQemJ4sDutybGs7Jg2TjnRpdZ18mtqrN55/+e7du6fnp9uzaaD1WTMgSgjJud6nGCkmTNbvDSmlpDjqcb0TS+578ejstESjVuvO2npnb2tY+3Y5AKjJ7g6i+kRsbCip8DTYLljd+fYCBogEmoEIEgB9ciLk05j5lC04pYtb9rIZtvn9ZgcmAglPd+Ncom56yLxh34pAuuzY8UaTx+mTUyX/ex6JLkdKsGTzOQR4OgT6p44giBEJKAUkwug3UJ9SBIwMwIiMyIyiBBgqe8H1e4aQAwBELBu3JgAEwA0ocDkuJ6+PcJHjJEYAQEYCyAqfFCBGWPWxqiamVI8f37//6F4bP3LqLMV5MoiIKYD33WRSTbemw9AdPz6ZjrcAoO/7lMhanW1nGCCEELJnJaIC2MA6RKDEsFGIIYSm6RUmAKjHdVinIKgtEJbed2ElotFS2SxXRvntqhqZYmLG29vVYnH+ox+9N5rt/+QnP+m67tatW5/5zGe01mdnZ8v5x6oKALA4P1+sF0qhMrkKG167/cuinB/8qluX5fj689eNKvrgUpy882f3Ul+Rt00/11vwpPtYq3J51oYQVJUMTrTWoQ99aPs2TKr9YiSSktY6iQSfovMwDOvlgCoppcrakuUKKj3TdV2v4nGM0bm+dQ3okS5xy9jCmFmloi6oB2vLGHk0GhFRN3Sg2dZjRIkDuHXEoAwbitSFbtMjQgSAxeo8JQnnYeHXKSXSdH56PgyD1rq05Xw5D0VrrR1VI63JRxVSn6fchz5oItBEeiOBCsENISz8EGNENH3r+n7lh2iUqcu6GhXLZfOJUL8Mufzj5TdSiuaLuUoAiSHlYpWfzpG4zKIB4Bms+hOHCMvP+DFsng8AiCkTZwkEBAVT3IAF2f/iss0nIhw3zhsMnEXpiPJTu/T/z+PTVgcCAvxUf9ufPZjzxQCCXJtsUAoVN4NHL5Y2zCyhrNUHABS8lNkBbICGZ183X6r4TJvz4iMiAHjcEBgYBDExA3NikW7g8dg2bfvo8OPzs7dodGLHneFVZ0beZ8M8djZFD33vmqaRYLquW6+GshxX1SRGQEHKHpghXWKrOmqOHKtYVMpqbSpTJBNCz+xDEiLAULg+EWu2VOAoGLTWlmVZrAty2KuOKE3Hpdku/NqJkw8/vBuZbty4vbO3fzZftk0bY9za2YoU6rpUgxnrqVLI4MuyDKF83PgtFZzzh+thDHp3ezehuTc/+7M/eqtt1csvvNaEsw/ufVRMJBa+GorVsCjruqzrQieIEgKEwbng+vZU0saqP09KjTEyMNS5h5KSMxEilYQFFiMz00XbxiBDZPactNbKIOiw6oQsO+fWXWOMuX71qtVl6JswWNClAPh16BKHpAFAnFq2jzTZlNJ0a1qWtm1RITVNMym2lVKA0HWdiNR1vb29PV/OSUdhSSkVRVGXlIfkjUYjtAUArNerJH2KfUqJRPeuHxe3bEmefN+u+r4nT1Cb6CNiAoif3NU/WaVf9KKwUBlF2oR69n7+2Wz28imfFkLJPdMxeuaGjhdxhQKIwBccnv7CZOJSSZKTAj/kd5t3OUSRjAX8D7WxX05QyYlGFswDAPDPD359KRPKoysuWAYZOX8WC8x/1+YCWsDNcpkbHBd1xqV4bnMxhz4XRPjM3wAApCIRIoNKnMGGyMIsTKAQ+7Qc4mkKZ3XNE5P61CFuEURljVImelnOG2aaTXYVmtLqRgIwSFKrRcMRMCHE7DB4wXNI4l0ghkGB910JpVKirSaqVeiVkq1qJ4TkfWiWLZFmBpdS9F1ttwZ36mAYiJXBvl9GoNFsZiM/f2X/6vWrzbJ59PAhAIxGoyF6gphcM++XVVWQVqvVwJoTpG+985Nr127Uddlgvxpiu5a+7x88eHDe4Quv3Fz71fJ8ycB9YEFYrZdT42uYVmq8SAvyNUeSpAaIzdnZBemDUVBrrY0mRLtlEyalTFmXfWpCSiG0Z/MWLDOTUSNQgKL8kGIMKQ3bMylUgSr1fav1ZDybKSlUsTI01WRdcILGR2BGjhwxGFUIpmpUFKYAEGttLsJH1WixWIQQYhGdc845U5jCFFbpvu/dUqR3RhmTKgBILULZKaUkhKwvVETWIltMEZnB9WHwXmtbTSoA6Pru9NwVpvhEqNsLiG5TqF+gQXrz30b4BZc7jN/AbM/u7T91O34ihC72c3pKugEAYHnaqUYB0hsGm9+0l/PJc9YAAJCJpZfLykVOsAmY//4H8sZpCzbY++btftqE2cvP+ywF6Jm6Gja4eq5QEMVxbtSRhg0rDwQReZQ4Pn3uZVnu46csMTFPXNnMm2AWYBSk2oKtfOeWhe7bojeJK6UKNVWj/b5vmHkYOkFRqiwKGI/HMbIx0reBdC2i+jbwEAlAa5tNB/GT3iRVhYiKNAMqraEsNdGkGhVPDk+Zo/d+sVgopUajiTHALGv2kQGUV4Xqhu7+8V1Y1FTyy599wbm+7ZcPD+8en59ev369Huu+b5rFHBGPzo5ms+3RxAzcQeQ+NMNqfb5eF4UBAJE0Gk1SCqv1enpr1siD02bV+bUtpwYLFdVI09J/yNhHI5iMSayh9MIBUjGxZLXKmCczEWmtlVJOJe+7STUZjUxTYQE6JVmtV/Mj0VqXtlJKBZ/9RVWMcSgaUxlbFsPQtW1LpCslo9FIqXEIARxXVaVJpxQ6HhSZnb0D7/3+/n6zbF3vgNh7T3pj70FEZVkCQORIgRgYIxHrEJ0LISrOarkY2XOX3ebK3GwjMsYw82LZltZqTZNJpUlXowqA+1617YnC9IlQn12MXpBPNqU0EBOISELhJCISFWQrcnhmM3964+OnjIa/2B/4k5DYp5jcwHAxKYXlsmEnABDhKcc1d+Py2T6llP7UQz49Rf8E3HDxffoUxR67i2ddYBCXDYXLzVyeqfnXFyIB9JgVtPnHi6Zj5jLARd8RQ3qaRn2irCBQ2dMzz43FnOigoWa5PHn46Cc+npoJkmaOCqAm0MC2G9ZN48rSbs+KlGSxWBfGDB6SGHFpcBGdSEIBIq0R1cYOm1BQKQVKFd2wSCloWwF4FwJzNgysJ7NKKcXMp6enwzAkcVpYKU0WMCTvkiMa0J+vV5NCXbk5O+n9fL0EgFCkaGPUA4y3TVl89N6DqjKrbtWL2zWzelyCBW5pu9rt+/bJ/EwZBcR96JNEAHjUn8QlX9m/Hlbu+HC9f+129EqTZq2YSemiUBUYLlCx86S5mNaZjiIizrlhGELsI2JZ28ix7ecAQ98vR5OqGhlbTrv1gICScAgxeg9EComYls283rKz6QhVymbKoGHv6s7jB0NwrneurusNQ5QhYRYyglFFSisA0GRd3yQJx8fH2uqyKrXaDEHvhq7ruspMSBurTWb4AgNppRBVKDSWHDdGcAyg6qpCfc69Le1oMpZUee8RgypwujNaLILr3SdCfVxf3EL0bFkIqc+BjYkhCSQEBEkMl1Xcs50q5o0N08856ILg+dMcOMI8z1AAAPmCQu8DX7bT8WKQO8DlkKoNWQ7gYtb0/58J/KcFegqbpeqn8MX40wD/xXnwIrYv3uHm0hFtkhcBAIG0SV58Y+DnLTSmSACX0xQzdyhf4c0Dnpk8jQAghIkIEUWAWS5QAhzWH57M7zx89MPxtpCBPqS+D0pExbO+7znGOMQB4HyxDiFJcru7++vV0vfJ9UF6UcqIcBxgvDsVwZSSjx44AhEiEWhbWmYaj2vSHHmIMXZDy52vihEqY0s9mRW2pKIwqLAuK5EEZNpzVB7cGKLnYkcF3c9Pl4/PDquqsGPYUePpwViMW6zORrOqtBoNIiZlEAsUAG11oQtNOqRgrWbiqjCLdReSY46iwGXBraSUlO/8+ep8tj8bBjFCQXUMEWjtYRhVI4nnHqigwigTpG/cIoWkjJqZ21DX5+fH6+40xqgDDLwqy3L3ysh7H5JAjKTZGEVEXReryaSqqslkgpZjjBq1996SW63OlVIKmSAOwwBEkQcUdE6JyPHpE+9iVVXOOYaYkpRKTSaT0pYxxsgxN6GNMjFCCk4EgTnGmGQoTGFLK0IuSQistc5ybF3acTU9LR4lcRxRGRTpG39uoilMMZnUxuAnQ/2SDXZhlri5xXuIsNFgAAmIIH/qmMjMov+U/5UAkPlyP77IvfVFArzpuG12wiS4ca3LCLxcEGmeOef/kMD7Jz7CxTt6ltn6KRVCCPgMG2cDJQJsnGGevsPL86Tq2adfPiD+9OKz+dHksbIASZ6mCflvjkQaOCIDp4CIqAweH77frI+ia6rJdtusTs7Pk8NpPaZm4dmPx+PJZNKH/vj4HNhv7+4Pg18sVpIwtKlQxdbWDntKozSdTlJKzvUuuJhStnnnkqfTuuu6JE4SkSJlEHvV+c5jL30q61GUmFRMCYfer928MDONKjiplFGiXHCn69Pz4yfdUA9+pXVtjLElVSMjKS5Wp5lFW1oC0iKyWi1CCNW4tLTFOorgsmmYvC13ytqOVBE9F/X0+NFpWZb6ys7Z/GR7+8rN7e3IXfQDR+p7F1IL1tta2wk9unsHUZWlLcsyel67NRCM9Khp5lVVMUSRUNdFBD8/PxuPx+PSJnGooCyBqCzLkjkycEppsVgwuAReax3jcHay0FAyFOPRVClllOn82mqtLUji6XS7d+3ZyZwhkoamaRUaoGSsAYb1ep3N/JxzIlKP652tncVq0XUdIgJtPAE1aWZWqNBiYQoXnO9d0/YhyXRr3PfLVdfV09KMeRSrCB5MbJpmWk/x//2H/dhCWYLVYAk4cmSWlDbAkVIKcVwGBghJ9wF7h72TboAQ5MG5JoJCidZQaCgKLEtQgkoF+JmEExHXnQ8pATOiyh4mABxSOjrVIYiPHCL6qJNgZAhJKiMpSUoCxJEYAMgwAMSlzaONLoFDFBREO/EcCEATEzEpQQBGlQYCZibIFtGi7KZTwH05DL4qiiw2Z+Bh8KNRRfoibaBPfITQ//zCpFImsmdmY5S2kKljpGmUpz0SFQrHI7ucz6uqitGfJo1osukye4oxam394IMUzwJyl0dRSXbvRlGmUJJQMKUgXUkYlBEpdbyyW6Xu6M79H4q0PH3n8OFDP8StrS3v4/LoDABG1SwPvTMG2ZKEZGsLxG3bljVnt2ylVFVVVVVpWyrElKRpHcfYt25+thyNRtuTbc9xa4+895HBWl0USiQ4F7wflEGtdVmWIYTlcqmU2ppOtbVtPG8Xg2sVotnb2xpNsOF5McHVe3vVzIi0Pq6ttQqrFApMZkVvT8stAGjbPgUsisLqkhkmMyVJ2qZdLToAmI63jKlCCHZcEtF6vQ4heO9DCHVdi0hVGREZBt/3vTFqMpmNRhWRXiwWl6t5SpK5XABgClWX07YNwaW6rpt23nWLvb2thk4ie6OKuhxbMhgtAJAGB8usfgthY7mZy/4ddd37WJd13/fLZSuiQgiarLXjXF0DgELlgnMuEMEWjLuuy/SYTDDLquFqW6FChSozpPKzUGEKBiUBZL8KIdIoQUR0CbnKMoVRqPLZlFJP/B2FpMcWikKMAiJByfqrPOdPiEgREJIyKvPGRYRZYnZi1ZveUf4lAHDE0KNYyaha3JiZ5sExuTWqgTAl0YbyzAdJmBKkzKgVSQCokgQlyASQHGTbiY1rDEqKCp5usxm6zgJYVAqHlhiAYgTQFEmTgE7c85qZNpaJwMAYJE+hxJBSCkk0IjKCVrqqUKFiCZsI541s7tmA/9kjJQEEIlJqI6fNIgIHfaEUac2IrAFqNrUQyJ4qlcLeFQSamdcrBvTKBvZ6wwm61NjlXI6NJATUpDElSYk3aZu3MQ6l1aPKuG5+cv7hyfIjbfx8/l5ZllvjcQghiZ9d2wXP82ZJnopClWUlBntyAKC1Ho1G27tVNoHjPA+MdKbIKVSaSIzhAqpJVZf1aDKqImudBJUMwzAMMYIxJk8gqHXph0EhamuLogjOtX1vU9rZ26WwTq4LIXrvTbamZuNSg51VShBHKUCIHEIHTLaaEpREVChwHACymWgUKV0IQ+xsSaNqVhWjYRjW3Sq07Wg0UkqVZSHSxwhKGWMKxKAUlCUgorV6NKoQsevWSk2i971zshn4UxuFgqrvTySZbj14zwBAQFU1MUUxqUcxFhgUOzgf5hKwLsfT6XQymoUQoo8oXNuxqlRGSSlshswrZawtgQk4Dx/BbDqQJGU3LuaIqHShlVMKMQHk2SFFUZTWLodl9uNVKAKKmQNHETFGibBCVKSIkDl2XTsMw97OFiI6SWnZM0cibYwirctJwQx6OgalwEAi4hxI8DNdNxZDcumRBARstUCErHVHARQJMVfdGBxo2DSZEBEi0YVL4uABGBkkRlBKiISZk2yMIn0iEZYkClPwQCgpiKAkAGQBxPh07JSgwlyjZsV7HiDEXKeUfEgAYCmKoHiACFqXiIgpk23S5gKjKsuYQ4uI+GKCjQuOLAIAbaruTYQzIn5KsZBJPWqzoklWEpCgHZWm1DqPZtOgrVWFAjCRF6C0qQTFxAjVJEliZblZeCDOCJ5CpRSKQEqQhoSIShEBJUkiCRC1VnFIFkFJ6NfLM3fnbPH2APegAAu6GhVFodJqFZKzpTa1KQX8OQMoz9E3fohDWdtqtFWPS4BEWhd52qZgEgGOzJDl6kTATLrvhzicLxYQuQRAxBAG54IttbVWa0ukc6NIEHfqejweL2IchoGZFc60tqOROBeyDCIl9oMvKtsPPYrSUIsIEwOzj94kICZbasSqMKCMUgYTSeRIQEVRoUYR6YY1RyitHbrB+8EYY61WCokoRlaKU+KqKowx3nNKGIIwp7Z1mkfrIXYrF2O01palStYqhABJUu9cdAGVitaKUip6AKtHxQg1rectBlXo0uo69CnAAACEui6qi6aVMHN23Uy6NsaMRsiRIsfQecohnzilxMg+ekkCCH3fe+89xxQCABRFAQAuBO99ThO01ojMzCEEjl4CCiZUpiRQxmTxQoxZBSEppBij1rqqKtIUY5SAg3O6NKw1E4pBbtKGDpXTEspCUwABtXFqTKhJmIgINKExwhFUHiFC7Bkw5VjMYhcgkgupFgCA6y5UscJagyBjpnN4k/LUFsYs1rAWmCkCSwAkEEFRCJGEKCEqDHgJbufTMZCW0LEqsa41KjEqSYLkiEijUimlwI6zqSIAJ/Qcy1IRQYyslDgXjFKkKYRgwEBGtj/Zifi0bT07TwJme3XeLHOAQw/RgdYRRYICRLNeAwOoShFbFPGew8AAJEzgE0Sb5KJ0QgW0GXI6GSVllNaAIhsdsKC2UhNUk7pfHd198G4bPiJ7CGNvVHv11s78rPE+1OOSAQa/Umq0vz87i04QQwhOAmmwJdlSl2W5WJ1qAiKdDYVAsiVmUihMEEJwvfOdFxFllamK1bojgJQcABdiEJVSYEzR9vPovfe5ljFFUeSys2+ciNS11ZZQBQZSaDTQ3sH46HGzXjG2PedyYGa05TBUnmgzlpcsqig6KAU8cExRoQHi6KMfIgAoUxUGg4spJIWmtCUwOOdWvSMNRVEhSt8H53rv2VodghQlVlLQFHLNoozRWhFACAZAK4U65UaT4pSappWutbs1i7RtT2C3pleJ4Oxs7paLojLjeqoMBAmbEcjEKVGMPAyDtZpAk9ZVUcXIF9a62VRQOHJ24OzbPuXxvQCKIG1m4w16rJkhY+/KGAAisqBJWBiBUvCegWJpy3Fdj8fj+dnZMAwhpXFdTyaTjPx13VBUBsVrrQJmEiYRRwYAhQhaX97fzNx5BSxBhAmUwZKQiVBQYxC7sYJIAwJAQkAEBYiXWpeNmhUQse2RL1BtirDpHyfoA8JG8cqCQsCIaIkHDaCBAWKUkAgAMvKECi/nVF0Q0VIKIsAWwJaslQf2CdCUhVKmxK53DvpAlgxW2pYo4hwxM5GWi1kpgqJQMXK2ms9RfOlvAc+Q5H/qyKrcJMIxIYomEgFGxqC8sCBaq0XQVgpDIgTfAmoNTK4bUiKrSkmSPFqvgTUQ5HsCGZMIEG/P+jzDXBKjQk02chyGfrIjVa0X53dX6/dBHfemVbCeTAiYe9dorcfjWqQgAtKQRIqqQpSgg1W6GhWjUaUUMnuFAmSUQkEFEoFjSiEyaM3KVEoZYC2i+r6PzDqk0XjUujbGrMyTvg9EQKTLskzGAEDTNGVZ5j4wIva9ICpTaw+dDyERFLoem6kxZjy2wOw9uD5wZKNMVVfDMAgjRwFA0Sq5oDL6OGDfR4hsy1oppVTqe5f6gUobQlJKpSS2rIpC9X0YhqGsbcZNUkoXagkE4AgrW1M10SIqpZTSkO9UxYpIIxJKJNAX6Sh7hqEbmCk5I4R97wBoGJijBMY+hUCbap+01trUtRkGSJxizDkjmMLUUhs0SAiQRCRBuigM1cWsW0FESzo3LEUEgNingKIkGSPKGKOUaI0KEUVSinFomhBsGI/LejyOEfo+iAiMLZHt+9C2vfNBOzGp0pw2rxIDppQEMdexF4EoghJDXnLkUrZNAKjAWuYICSUKIKJnYgEi4AwYp2frW0EEFv20N86bhjmKDAPnNAERSAkJWgVKQTkDz8AJfASTODl0F8x8FOF4scokAeYAYX97kmQ5hCfL5tiF3qCp1HZtJr0+Dsl5ZpUqO54aPQXQILx2W2VVpJSY2SiVOPkYWRLyxYB4epYXBOZT5sZvmLuJWZJWIIgSJca4VVFkLi1UpgjJsQPX96bUokY+ekKLYIxGYezWjiHuzkQESQPHBBBiZDFJRIpyLYIhOOfDZDKaTCZN0867J1Q/mh/FJ2d3WE4kDsN6actgd3abZmV1bYxarbqu86NRpUkfHZ2MxwfEpAwCibVWKQzBhRC8j4gpKcxW+bmekpRSStZiIrLWjmuK7Ie1T0aqqgoh+OQjcwiidSyMMaYqa0CRvu+7rst0zlwANE0wRkbK6EI57hQYjuD64KUtx9rauq9Ss4TILIiFKsIoheC8jxrIIKZoI7BS2M5djISoQkgKKXpALK0oXWoCYIBhGEIIOVSMMYUxHIE5Wq1HVTWZTFISPwwxrlAVhiwDcPIheRQBIsQCMvPfsVEggtrouh6HpIBJKbW/P/GeV6smJxSaNERKTtCi1UYEgw+u7/W21loTWGOM9zGEBAB+8FSWxCSScs2YTVmNyoM8JOXGM20qyqIo8rxjBo4ATGAVkiatVYxRa9Jah6SC7ziyUmKMmW5NUSEzV0XRu75v+5BCaUvuAmnSzMQCngEYYnafIeILuljegofAuYbLxqZIgCQEYIwkRmBMAhERCFJSKYHZoHsA8okW+jBsVpCcLFyEPQYRLQCM+YnGiCLSmuyUa4ZhAOrAZ2sXAM+EBMwSL90qmTOq5NSjdjg8az/qh8eoXGGqlmcKq1De48jJKa3Lrq0VVcBaRFr3lf39fUmCCpUyHIKkcIGpAQBgNnh/Guo/N9IhhYQoDEwkWf+WIVk/vAMA43EZoGqbeQqu7/trV7bH21+az5uiKMp6HFw6OTs5vP+ENLz62j4iJubAbr3uhqELIaQknSdmbts2+njt5rXKXB/W88f33sMr74e+7xjMVLXzdui6Uo/XKyKyRAmxHIbVerU2qtC1Zqah6+q6ttomCSH0IWT0DUJweXsxxhijjCKFmpmyUn29Xg1dRKUgQlEU29vbwXkUpZQKwgpVYQpjMKuStNbaWgugtYYLanBwnhlDcElF0EJGocOhGxB8WYxANYpTLRCcEU5u2esK+tDFGJWpRIoYMfoBAIZVJNJKKdekvhkEpS7r8bgCAGtrIGqbxvtgSyWCiEZEORcy6mBMpcxIMCpVGFVChD5ISikkRVCh1pp05KhJi8SEAQCGIeoYR1VFUProlQJrS0RxfXDSMrNRBZG2ujCm0EQxxhRi9Nwsl8YYq1FrHWPse69QDcNAUOYKMQezUipf88Gv8y8RUZL46DdkZAKDajNezQPl1phGRhalMhKcJ4gzQIwRxRpVBQ5d5733eVSrJqjrqigqHUAlTiEIAGOeBpZfEpEuylTvM/TFGjJ0AsTMWf1USPKAQpsZ6nmQetjktZnKdkH2hCDpMll4di53SoRIKMBIGhkJs56pqIEZIoCNIEFiRLKsmVMym9Q/Xw+UJMnH+PZffCfI0SBPirob7VcioVsu14s4erEja6m0HPu+PY0OoycJeHi2nZJYrYuq2toyOZGy2rZt2qAsuYknlzKen3/EyMpsPks2z04pud49Wn6nLi2rbTLTNhw750QS2+fuPHnr8OGT0Why9eBqjPzOxx98/PHHRhUMWmsNRCltZsIzs0I8OyYGbppGkiC8NDa8mJ89fvjeaPttk0bj8S5R3ZzNVUIby9XD9fQ5Wq26cQ1VtT0M7H0sCrOzdfD48ePxeDzdGjNACK5bL4ahJ63LeiwpAIDWyhSV2Yydi84lY6gsa02MaJZuvl6sl4KmMkqpsixVyKuDAYC2Xwuus47dGJPv8vwRtC5DbFfdwlGDqMal0oWJQgzeQdPFzkVXVdNKj7uVNE2/s11qRykpQSWiYufbNgQXbNQpScxjsMlypG4Vm+XcYhxV1XQ6LaoKAEprVzH2fQ8Q8cLDh4iUMQRgjImD7p3r284lR0y2LKsRoja6iNZaraMRA0DD0PrYWauTuBij94yyqqqiKEYAerVaGWNKW2qrRaAbYowegGxZO7dMSZyErsv29jwej7XVvesNm5xFbtZWpXSe3QugtS6MAYBuGDI+Z4pCE6FRz3asgaAe1QoliVDawGoAEFJKwccYox9CksvVhKMH0EkS/tF3zhViSMl7H3WtjPKDZ+CqqiRJ73oCglVZFGJLsjUIBhecJCyK4viJzkSC6BkAlEECAqLVwBwHAK7LclxqQTRGiPT7R8r1/TB4EI2IKQl7UkqFPpAFTaALQBUYYl2Xk1nFobfW5lJ5vV5rrbO1iuvG3g8pSZ4cNp2Ol/P2D/7gD/Zufj+EEIKTERaFMYWIpBijUbNh6AAiADH4olBFUcUYC7PdHC23J9e+9MavXJ29uDiFZp5Ka+eWq6pq+9A7p61NScXoEysJ2ymFGGMmxuOFb6UqnPc2hcJ1vLev5uuf3Ln7+7duj5/ceWc0KUgDabJbZQgOUbZ2xsvHLXvemm6Nx9PlvDk/P/dDZIa6Bo4AxNEzA2/WGEERFBQCsGPStd7enfR9m1//9PRcBFPAYT3084CIBwcHsR78MIwmk6qqlvN5jHG6tWWtXa/PEVETmaIoy5II2qadL5fboyshhAgRAIxRyuSO5lDWHSrRXEbPwYXowYUQYzxpkqnMztZUKWyauQhWo0yJ9d77qqoy1gAAw+CNUVpD3/fD4LWm7JeMiDFGjl3OVAGgbduLFCPMdmfMsW37whRFVcTou254/PixCpNRNbPlNDWpbduQgqrQWusBSENVSFFURDoFFdrkOxYJWtvCFOeLhVLCNe8djKtKrQ7j6nQtwQydR8StnSma4FJvlCmKohyXAw/r1XlZ2q2dKWlIIQ1+SCH5GFGkGlWlLV1wBLX3HhhIEzPn96+1LgozDB4AvOfCmLoct03rvSfrtdbKjAioXbapl6oYSVJV5SLHFBKiQjEAEFzy3u9dHWcQ3lobN4sXlGX53CvTYRiiZwDbdb5pWmaosNA1hRBIa47QL1tJqq5rZbDeIVRJnywLEUlJi2iGSMBaG9K07BIAMxvmWKK4lIJLToiIlLFAGIIaYszFfGaxb6YFATOD2fQAFIBcGBI5jNEIoGHgwFHnDkoKSVlSFlGJpKAMT2ptikTYjqc6+uHw8HC1WiWRG9euVXVdVcXhkjVaY8UYSRRYzaM6K7fnMTIDq8JY0mQoeg8gSqP3A0A0prBWR1bMjIJ1XUafXHJJnLUaNCybsxjp2rWXBt9xJKs1MwkjEiJViniAlgzYTdHAzMwpSRJrtEoSUkzgl40/PTk+PTsuq9V0a+z9EFks6P6sTZh8jMuj5ur1q0lCCO709HS1Wnftmj1prVMgIA4+iSSOF3OjmTmCMkrVFJl958vShiR1qRjIqGrofL/uXOu0NUYVWmvStotdv2wJSClDoDnyelhX1SiPZxwGH0JSyiQGa8uu6wAg9y/zWkmajMFh5etxLSTAYG09m41ijKvV6uHpsTImJdFaF8XIRx9ccOB2dnYAOmb0fqNyD8HxpjenrNVExMzexywv0WS99zFG0jqXjVm5MQyDMaowxcXsR9RazyYzzXspiWtcaAWTsaQUoNY6LF29OxlPrNaZC8SgAU0qpqCzJ1CnAUC56Adij845F3pxzIw6jyQlhgS5swgAVVHgZBaSa/tWKbWzs2OGYt2t113nnAOi0tZWlwAlMwXnhiHmLFUTCW4miBJRxnQZmDSVZJNyQqkoMIQoKGgEdNRGDX64cGQSFCHKvu9lfm7f9sMwGGPy1UspnZ6expjpNJySKERtTWnKZb/Um6eSBQ1AfvCL8yYpU1WVfvSEfPQiYoyZjiDGWFVKRdW7QEBaax+hHLOLglEkiDKIvVZGUgoOU3ZlynS1CxRPmBVqQhTvPRMbpbS2iLizxfkb3zEiKmU4bhZ+ySbqZKpJoUt+8uTw3p2Hr75yy0d3evbu4eETa21VNkVXldYqerWubYBO0O3saWPwbP1kvvqgbBuOsRxrGteicBh6xFTXJWKiLCIjslT3fbte+5FUZUnjnak1dDJ/dP+jw+99963QF1/96lefe/kXB47EVBjs+5QYUIF4tOWG6MocOSUE0RqICAYvIpiwtGQK1JpGVVWM9GxUHx/3zrnkBIDKshqroktdTs/avm+WvXMuhKCSyQODogetJUZQhlMAASAiUxlToEJMJCGFtu+HYeg6mE12iTVBTG7TgEg4nJ6e79+cgQdPUa2HfHO0y7Ybuv0b21ZbVEhCIhKjDyGFEKRnZZTWWkDcMITkRqPRaDQJQUtCJYXSoExOk7Awk70dMMZIkrYNDMCRk4jW4Ho3DJ4AUgqIqLWGzWjNRKSM0SISo4hERKV1oYE8xxRQE2mwCQUJlVIh9qwUEKPKMQPGmHpcp7YKbujnHlgjWtKsBHRUzbxTymutxSSAgJKY2FPQEIMklhFAjJGi53Q4MMSiQKWUGDQmw+xBmE1hPPvgcYi+LC0YDSGEHnSl4sAAVNtxqkTSGpMahphSyhNviQkTIyMCpiQhuJB07gq1bcvMRdfl1mNRY4yhrDm1EbRXtowp2tqmBeQFHSCRFmAwRmUZpcKNB1xZlyg4DAMAhIApBUFlUBsD2UqEjN4y027wq9UCgEaqIrCCUtZlaNkIaTK9xB4Ji7piwAi8WK1ys9EodCH4GFrpWLSWMnod20jEiBh5AGtlE+cgAkKAAixgjNEac/KMSrTWiBJjurZriDAFdBpEIoqIqFmFolJZltWoWA+nT57cf3L08OGTu8vFypgniLhY3kvcRClOz/qmbQno1i2KqTg5Oln3pzfdjeeevw7gi0r8ipkB1qx1NKJMURijyrLqurWIdN3auaKqqhip73vveX9f13XZLtrv/dl3jh81R4+XLz3/2Z2dKRHXmjwwei6U9DGyA7Ia0SQREQbRGhXoDZahy4gIySWytqxiPcKtnbKyEZWYQvUtdHFgpjBoa3UcijN1Wts6pRC9JyBrbXLIDEPntSXk3ONNgim3b4qKmIABSMhqa7VdD+s+BOXWuaQHAq0hK6dC6vvekiZjjLU2hAC5k6+pbfpQSlmWxlilFDA71/khlsZmCE1EfIwiGQE24srQM9pU1mMUXJyvvWdNsFVuMXHTNEMcTGU0VaKlKMvl8jyEUBTFBdFOZ5xJl1YpAwAxRu+d9y5G9p6nm1l0HFJKkjIvLGN7+cYXEQICZYATESwX69AGZiQmFgghcUQUhalyLQKsZISjkRpPRmWZiIaud1oDphgjZ4aJMmILG0IvSiSG4CVJGmLUNRVVURUVIg7DcL7ocoJDGgCmSdYAUBTFeLxF2nrvh84PftCc8uw0SQICBCQo0cc+tFaXZV3iGL33IgEAEXU1U20zmEJ0z8qkwnDXxSBYmCpijBRFEmkUxQEYRYYhZuBDKVXaUkRyi2GkpsAh956MMdmRqu/b2WzbhcAMxiht9Xq1znM7iqKSFDTGd0i8RlKxauIoSWqWSyJ99frVKHi+Og8htLxQMpmNr1ncih5EkimUsCqL3CVgkafzEhFpvRqACRG1UqUlpXUIfhi62ZSjS1Egrw2SlLVlVVUe4nz54Oi0O1ueHB0/PDl7fHZ2Ykv93r11URSrYaUrTXVc8fl5f26MwfmfjNZV07TrZa91163O79596JaJomEJTlI878ZTXUqpMVNNB1QqJen7dUqiI2EvPg3Hkup63K/6s6Oma9J0XO/u7062C02+HNeDj27gmkrb+db1VVGselLMChSQIcrz4VJkNqMQA4uKSiuOQ3AtQOy69eJ0ba01RnEEYwpIkFIqy9E6hRIYgJRRKEpEEsSUQjP01ajQZBliSC6EZJQxRunaMnC24g5t8DwM3RBCaFIzxCEOXhlTjCqyVFVVPa5R4UhGVVGQ1n4YfIy5F7VerSXJsB6CCUVRaNIKFYpCRGYGyQRSi6i01nmMJACFJNgn58JqtU4pFco0LQKAjz0nMaXRSotI7v4iak1lSkkCRNDRJyBSJhLFZwZXIDPEGF2PIJqIogdOZIwi0sMwYJFyUoCIITlm4MhGFRe9VUgxRA7AMSUQDJy06xNTIARrNfMIkQRTaqrCmpSQQAMM1W492Tb1uFydamPM+rQjzQo1EBWVKmtrtCmqAgj6s36zNIiBgUDrbujiAOOxUVJwjH7wLKDEcKAYo48DABhTGKM0W4hMmtgzISmliHA2GY0mlR6tnXMRPKpUWq2tgc4716qwpZU1RSEYPEVIIZPb3TyhQtKEgJl3mOudtnXEgIgJY36fzJBS7Lo1ka6qIrNZFCqFSpC79aBU0Efn386jwpeD6sLElnY5rIzW27Hx3h+fHUZm8cNEZiXo0WzEaASk1Jo0oUoiws9M9gYAgNyiFBFOAjlFjDw454QxJh9jTBFcF7yPRVHE8Tha+ot3f3Q+P9Ell6UdT8vzKIkTIMcQnfSkq8iAiMqosi49nK+bKGK2r25tTcrTJyf3PrizWqy3tkph8i4I+RD0NEkKiTqyO8raWmFardbDetCgUwc+puCCMyG0gsGUZdEu0wcffNCtu7/8m38Ncd+UmgDJal2I7gCor3wtJNEzc8wtOqN1bbUYpNowSKlt1wYX2sIk0MyRTVWomgEGFEw6CCc90RM10qQZYpatJBFJ7KPoPAsCEUHlG10prZRCkxRoROl7t16vHbq+6VFUKIMyyoxGW9OxKQxzLGtdWotoRBIBbTT9HkIInFJZln7wPvrkEwFhiSkkBnbOKVTaagIqisIoVEr1fQ+g67oGoNVqvV6vuYshpEW3Sjgiy5FZIYbWxS6yBRw8MCkASeiHGCEWCVFRqUtJ68iKNso+QhFgYOGeWWttRMUYYkxaW0SFolIQU+i6HscY27ZJQVDhZDLZ3rW+GJYn7Xo1sAdVIFmJEEK0dmQKU6CVGHm1GGKEoRviwBEIIHeKExADsTGyt7fTmj60QRKORiNTKDMxQOzaQED1uI4+DusBoi4Lq6QAn0IfWLHVNoWUXOLIwrgxQGKWhCkJcAguzwwDcokj29pW1pDmalLUddnFBbGWgAA2I+cKjQuu7/tRNaonRbSKu3XAOKrL8bhuMq9ORERc3yeRbGKxfNyMp3VZWkkpAhijqgKB6pSkqipEWSxW3g1lWU8mMxf6ZugLa/S95ifWlszRuaBpb5zGUaKP+OD0dBj8qltobbFxUFyJ/oaOTAZjTAqTVlH6zBACAOD4lHLTrYdogYispg4ix4hKjDGAyRaFsrZvXWDvQhhi7Lx/ePbwo7sfCoYqmLaH1bCaL5vpdFwWoyQJjRGlIoA1ShXGs5/A9vnqOA5rO6NeTQD70RbUo0m7YoiiSUgpQvBdJE0llUqZGKNSVNfjEBxESiQpJWYa1sn1iRNKMAK4Xg0f9/dnB9/a2927ev25shxzD0A2cjw9Pd8q98qqNDPjvc+IsVFFVVaPF53CGUUDOq7W5/P5UTXqVBE5Qtv0aERQdJnKyiCiSKvJhjYwxyRp8B4FlTGQZDQuCEgZ1KitzfUeAMB6vcroWgZ4rbKaSgKyNU0mVVFUk1mhCQbfoUohLtPwjMAdQClmSEDJNQICSpTkYPMsSTBhSIEK4siRo0JljEFUKQ3jelxa27uQGic+KWWCwxB6LFT0DECsZLnsNZEyCMCiEI0iIN/5JKmoC10VdVlzRjQAQgjOOecjAyuUcakz7J+NbqOPmrTWeohOJ61QMcVMEdZaj0ZVmuhYFUQ6+rknb62tZgYNGmWrkbJjDZYkJeeCWwyuC6MrpihUXHsGSL3EjteKOfajgtAgonStl4TFTJWhREyqsCEERCxUkZT4wH2TOmxNlVJIZGhYDxnTLVSRILkuMWeVEDLkmdkJFYoErXVdFrsHu9rC4FfMcb48E4wpYAQCIGZMQYA0gUTP3ngdADUqo6ypJuO6HpclV2fLeXBBIXbRS5LcrSDQklQKkiQpVtaW2qCkAIiSgjFmNBq52Hvv/eCbpinrcmun1m0cklI+uPlyMa6bqEfWGB/C6RPnvddGjYtxoWvijpQrSw6CKSVM3g9Ba60UoiilkDVI4siMzNeuXbMWEDG4/uzk8eHhYbdekYYfv/VoMpnUxSglSUGUMtZqier49PjJkycioahUObbZmntra+u8WxFRQhSlAFEXVepd06zXdzvvvbb63J271kmSGFemNM2jJCnomgoykZ1bu5SS3td97/u+N6qqqpkdaYhak6Qe54tloUtDpm+dD6m0dYqqWbY//vG3Z7PdL/Kbs90rzdpNJhNmfe/eR+q5ZT29sntwAKBOj/18Pg9JKBTf+d4H08mNqtgej7YOjx4eHR1de85PFO3tXWcetNW21NEyonTd+snRg/3qmut7yJNqmDVpq60YMUrFGL0PBLqoDCK6Pvjoi5oIGIgLU+AYjRQr6fqh36tn062xMUprStiLccrqoVuxaKMUEKEgc2ThzCiJETIfjiMnSllKUVVVs2yIQVLqh4ESaT3OzVFjiq5zQ9cBUanHAER1VEqdrkJKqSqMIsU85BZxjIlDsGwRRYIwc1LJUhKTWtcWRaGtze5IyphC28IoSS7GJJIQURJ6H7VlZQwmDMnFGAUwt+01WWOMoB+NaqW2XOtWq1iWerwzNkb1SkRChIiCQMBDbJdhvQpXPmsKA84UthXXB4h6OPXJIF2hqpoUo6rvXR+aYYmsuSqMj13b9xp0oYqcuwHrEIQhoCgWarqeIY7H47qaCMq8ad2Qcl8tH2Vpy6JiiJJkvV7jOZoCfVyXliJzSL1RFeXxO5ycS5p0DNFYk1Jq29aKLqc0ruuiMgmDMtPggvdeax3chngTYyyKCTCv14NIqMsaUZzzTTO3ul42TWHMZLYNRbFed4JSVaPETo8t/t3/zf9iMiqKolqtVjHSdDpFxBh9XtqzT50tvcIC0+z5vc/cuvFCNTH7V7a3r21vUwkAroPzk+Hk7OzJoyc++hdefOH0CU8mEwB4ePiwaZrVavXeO+8dHx/Xmj7/+mvj6db56enWzk5RFJmP9Z0//+Dk5LELjVC//9x452rdtnNPLBXOZrM8oKMqKiDIrKP+qGeI06tbdV33fU8D8KBPj5rH70tRKaUC6lSMlLKsLZe1NiPVdV1RFDFGQdzd3iaiyHx+eBhjRFEGR4jGtSlTiKNL411z7cbsueevDjAszhejaqREDXa4enC9LMvlvGmadlzWmOTw8DC5RETjaa1L3SybPvSgQURmt7pKj10vKIUkNQzs2nTy+GRnesAxKqOUEs+RNOnSAvN0XGfuTZJUmKIqipBSN3RAAB66c+9aSQnbvvG8ripz4zWzf+VKWZbBhWx7mvuuKSUXnIhkylpwIcaIKCnMhqHLEpQM9jAzR45rCCFk0ks+rLW3b9/GSd80TbfuBj+Utpxtzzjy4ZPD8HiWeSmRsw0jXdCuFEqKzIgJjRTGVFVV1lbvDJkTwcyltTmdLq0NjYsxKqWqUZVbx957FKQpN02zu73tY0TE6L0yBgAWi8WV/RuIanG+cg5TkuBC7CKVFoOEEFy/Wb98x33fYzJFoabTrWpkBr/23gumvnej3WJrb0up0A3r4KRvXT8PEHWpp5K99JlzaZPbSltbWmudS+W8ZxKR9369iMvlsizLuq7X63VKaTKZaK1BD4i4oZaiYKG01sZgNUmarNZ1Smp9ul6cd5JUYapqljKzLbNIyroc12Ot9bpb920vIi64bHfZ972ILB+rkNyXv/Lm0ckjWxJQdBi0pocfDqjc9v5EVQo0FKpYr9bLk2akKkTUyaHTqLUi0n3vQlgaY0prU2I/dDFGY0xatltbewb98fkhGrmG18bTOj44e3iOZ6dn2zvbQz88ePBgb2dn/2D/+OiY49bjx4+Xy2UOdde7s7Oztm2vvFhVs1iMO9WvySrPKUbWWl+5aQYMuPa7Vyf717bZ8qCNTc4JBBcyhQByz15B5DidToc4KKVy27lt+9BK4FCOVVEKgIjayFRihOjB22UxLnZ2p8MwrFarxs2LorBluXd9z3sfXBAHRlFdltUQh2FYusT+/8vXnz1btmXnfdgYY7Zrrd2eNpvb31u3blWhCgABigIhWgRFmRKlcBOWrVDowW9+8j/gP8APdujBDssOOdyEbEuyLZEOR/DBIkESjCApkASqAFR/+za70+5uNbMbww9zZxKiYJ+HvJkZN/Ps3HvNZozxfb+Ptve9ap5pq4HhsDnsNoeTN84+/vTTmZ4Rw36/34oBosNhaowi4pxzCWXKUyqpsc44xyHEDDkygMQpHg5RJTVrZ4fdQbC47KwnJiYgVCJAw+6gnDHGKFallH3f125cM2+YGShW7kJKqWndcjlfnzZSpD4NcJz25xACZx2ixBhREqqqa1JEFMJRg1EBKUVKjLGgpBKt1qR1CEEp1bYtAIzj2M4rsFratnXGcWYGPj09/eLLwSgFAEapnDmlZIypyv8jaovAam297+aN1X7Mh7qERCSVUrWfMUZdAAFLKYfDoU7RNekiBUUUqlKkpFR3K2AwxnRNh1gI0FodY8yZ4xQzRJu1ZAGA2uZkhsxc64IQ6qQAS0nHOCEp2hJKUQZnumUPjesGHadNTqHKDlhKERTkowKy2khfKXymYQKClJKIrgpLfplbVrH5GoWRSwGlRBmkDKAhM4gora3W+giZM6aAFEkxcs6stTXG5chpLPs0KoPTNJUEznnROI7jcBhinoxy6JJDTGVkZmc6NGW42dxubnNWMU7mgDM/88YTEEcmouqW1XnikYvWhbjVUxnHPhBl73PmnKPWVjVmZPSewYbb8Xb4+nB7e/vpR1/t74MDHqbhN//cnyuZr148OT9ZPLo8KXH8g5999Pz58+1+O/YjMyujrLdrs374tnzr10+NMXq2Oz2fAcDNzc3hsN3EF+J3XqXu1BST9tNWqWQMafaKSBlXrX8AbIyjlobhwJzHcSwlhRD32+24T0T+wevnADDGIeasbEYlgkIaFmfaGPKz7Dpl2xYASgks02w1a7MfJgp9UShOgQvGjjztlHcmx7HfhtffPLm4uCgJb69vpxxTKI8evDZfLp9/c3VztdnutmEUt8qpoIaMuVqGxDg3nzeH2E/COQoij71MNxOR1eCVCXC8mhJgqRW1lFKKlCFWLWdKqZRijHHGxRhFJMecOYaUtYau69anSxTpD31m1lpLKbUZC8SaGs4cpxxjfNXKLiVZbY/EKoYsGQCMMkaZPo3RAEUWEedc13UpJSmFM4ogKtU0jbW2XgfWy+WX0iulYszWKmWwQs5SOYLxKhbs1e5TiahGGU0aEUlTSSXmWFJaNF29kU4x5jwZ02itsUBhUspxPo4AgHVhcUaT5mmaCHSqmkVg1zmTDWcUKHXxiGBKiV/iB5VROec8HomL1lNr501jBQsR1bxkrYUzjfv7qggD5lJhfX+aFMYAXEkqZSzhqPbjoytNRKy1pRSuidqCXASIUdTR8s/EGqYpaRJgSGMqRZRSBBJGyTFzBgJttdc6H3ZDzAcMmEIRLDXxAkUpUwya2axtujL2YTfcoBJjXEohR51GpT1IwcqMsdZChBQKMCnUSYoO2yI2sak3KwWsc4Yhxxiz9dbaVoTCfdryNq8b1ygAkPv7uyEctvnBmcxn7enpPKX0RjprGkw8rE/aZy+effX1V/v9vgrCrbVd17Vt++CR/uCDdwAAMb32xmvr9frjDz/+8MMPlcKT1SqkkSPfD/d9GOfzLuSsVFYGQ544MiqVORL3TdMAgZs1REAE3tupcXkCa91+3wMAq+BnsD6f24VFDFoT+6tS+oH3SikzJwDKYz9N0QVEpYxBdiWlPBY2SvkVOaO1QjFmPp+/9dZb77/3XtsuAIiLuru7Oz19+ODBBZH96vNv/u7v/t2f//yXaA71sbCt7ajJHL3X3vqxuBRKzpCjlH1gpjxBhuwXCqW6HagSMDhyztkVVQen8NIORExIkuLEmUBnVAVV0ZZIQ0ppvw2pFG89APbjxJmttxpoHIMUkaSANQgC6RzSEAN3TESICiCjCFBVQOjV2Wq/38cc0aByKnKc0kSWKNX8k6OGXBOlVGLM2lrSmqeJWWtFBQhRASeAqg9DOM7Sxj2WEML8oRYEQtJEqBQBueISJJGjcKAlEMTqzVQKcyGjVGWWYBFESimZImdnZymlknCKmSE2zdyZZpqmaeAYK29bAVc2AwPKME2oHIpwitoSEYlYq72ghBBEIDsFQChHQ5vUoNGXFHI8ujowhPSnc0oEpQ4mS0pKKUGsRrpag5RS9VpZBFGjtkRglRKVeMwCeUJVSp9yZhEliK6BzFS7FSIorJghhKyUOjk5vb+/Hw4RKkQCXSqSgpy/vtzsDnmKy+WJ1vrq6mZ3MxF635LpOjd3qJCYUkgplJTEKk2AOqUUc+Qbttpu7gartdZ6mqIUdF1HbA+b3Wy2QChxyqmUxgzAMO0lBtj3PWk+DJtxHIG4H/dPnnzJzC+evRjH0Wo7n89TSv3Yx22UO8m7B+NtyDkON8PUTqIRBvLszy4u7u/v77fbcV/CGIYplW3s9+H8TWeM44HHcWyaJo6xH/vVYkVat21LlDNHzao9mZUkGuD6dmwadDOYr9uz19puLlvuIwxxG7y1QCBQQg4pJaPUfNX0V/eIRqEhbUkkxjGjceTA8BRL1+Bs4cnTwJPX7eXppYLVYnGGIgT65Bw//Hl48eK2VpsZMllqusa3NudslABkb1tNLMLTZjceYkmKMzLLNAVEAQJBnVUhBrBUSkmJy0uqX13tVQKdpU9J1XNeazDGaEsZcpm4adqKQ58gZmKDLhfe3+8rsqvyBkmTkNagU0haa2OoEoxeyWaW61Mg6Ps+pDCmEQVDCMooSuCtLyXFKVZV1RTj7f0tMEop9WSLmXPOKquj24cIq2QSJeYsY5mG6M+8iJAmUQqZAUApVaQMw0Q0GeeapqnHe22AJxSjzJGqnLm6wVJIQwyIyAIpBRRxzhij9n0g26hQGBiLZClFCgCjYONc7XTWBr61toY07YdtCL1Soi051VjvUFCTfUkUBMRjnBYJEkLOBaAAkxSFCJzxpQ0q16oplfKqzIwxWmuZCYilSJyYdbZEKKRFhylxTnWkypyVUtqaMgqXMo4B4EBEYUw5M2gi0PVqVrunChXw0T/TuYYMrU+Wty/2m7vd4TBZb9fL2Xw5163e7/f92PPEMXIcgPQoIrppmlRCjMM49qIInRIqnCMRKSOgM+u8Oey89YQat8UvWtPOscHG6YeP/clq9a1vv7nf7/t9P5/PF6tFzjmk4L03xsxms3rXCiHEOH3xxTc/+sMfZ46bzeb6+n42+/TFs2sgXq1mV8+fl1IM2hBwfx/i3rRtCzGYJK22QqnVVlkJ+x5iHlWxcVKmoCAq8d5y15SAr73dWc9okplL5sNt3AXZi0qclGiUmtVchCPrrulcF9UhR2YozoH3rcISM5dUfKcZ8mzl2PPzm2/udldN0zx48NqSHvjWH3aTUmr64/z3/vbv/eSnf3x58YA0SRIGNgpRGcQimJMUVGiUmZH0W1UkVfGYJqMMA7AmrRQmgIJylNRnRaBZIMVUH3ptvVHOtjmMIlqUKXEqQMzEU54a4wBsSpgrxV14HEtI6cixgGNMfCoJEY0zprGvHmWiGvulgSCU0MwbNNi/6HPI8/m8s412GiUVKSKYc8xR6bZVqOIUQ6BUCqESKTklEQljeDUdRFRKY9VW1NOv3lM0aaWUFAECZZQnS5pRUFvVNAYAqvgCALJyKFkQASjm7LVHVJn5dnu9aE+UGCJuumY28ymVlIqSgogKsLLw681FQObLJecpM1trF4tF0zQV15V3WUBF4BghYfaHIUfiyTIfe+mvdttjMm9RKEiEACSl5j/x0XMOUI0u1bdTu4+lFAAkxDhJzJMxqhTrW+3MPMc+50iAoBBYhP45tnAcxxCCc6ZiagDg/v5+moZa2OecUWHMGQCuv7w9uzhxjRsO8dmzZ8bhycVMaw36aGQIIYz7USXDEUrClJg06JOLBTqVp5hzzlNExJTKfN5Ya2ue7GLRblNw1qlkChsDKw5KMF08PH14jsaYmddppED52ZMvnz0B58zF2UXO+ebm5tn+Wd3Hm65xzn33Vy7e++AREdWPJIRQpNdab9rcboBWayMGKOdsOYm2Og7bLbPVlgAklWU3t1oj4j2OKY1AqnGGtAUG7BBbLA/21rciXMrYh6lMqWhwTctjzCmP42iMcaZRWWCgXNiZRiExAwApNOAsQSmprM5sBnZrF+Pm5ubGOYdorm+frOxbzjXPnz53rlFgn774skga42GtPSfOOY9hBOCYh+rajnEA0Fbr+bLDgqkv/T4BRautYFEVFpersBARsSTJuUxTCCEgqvl8tlotvff21MYJQlN2tLkJu5gnGDhDNOo8QIhTLKVUoljOmTTNl005fqlSknAChcbpesk6LjyttLa1eZlCbLpuPp+PfR9Sqs35xWyWZB+nWIG2zJBjJE3trNU6hzA61wBA0zTW+mE4MNfo7XoiIikEQNKkFI6hr43xerGvhYMIzhatSI2rSACACklDzJlzE7IQIYpKY+wa4zUZMqadNXOHSc3LnMgaY4ZhKiXEQvaYDyyCqLVmQymlaRhiHCpraLuFEAIqmYY4DcV6xQWYIjNljHGiHEmUiAjyMRIMETMiIpJIZgaiSosBOQJ8a8NcqfrHsG1bIhrHUaFRBkVEzBRjqXQdFJNGBCbOUKRoJFJUNzitWxHFOUWOVaoIIClVrbDjXFIqAAFFjfuUc5ZFu79PGnyUcBh2jx9fet8aYw56iBxLCCn0wzToqWVWKKRNVWRYbTufnan5MKEkjbheLr31d3d3h2mYzZoVhxJU2BVItr8v1/G5tvz2e4/W68Vms/nmm2/qaPGTTz769NNPF4vVdtuShs1uE6c4n8+dc4jIwOvHzYO3VvP53BgTQthtNpvh6f32djf1+/EZZ53A+zP1Wney3fbD7r4xapomN3dWWyI6OztrmiakcHj+WYyBYVJqBpmHQ85jJtYH+PhsdrpsT5j1OKppn6U4CY3PM2ecVUFrq5VWaWrAOWqi7BrnRTBOecpZg9akSZF2BKyBcj9ugaZu+UgThvHw5bPPz8/P7zY3KEoZBZQfv37pjANIzJzSOI6qlJTKOGtb5VwIfc6As8Vs4V3T9Nf9MF2HEnk0IsKOLVCRAkhASil1GA4ppSqqWa+7s7OTtm1z5rEfAcjatum6pkloimtcQV2D7ct0vPPXFvF8PlcqoYBSmgg4q5gjkW6cO0KEtK6FJQCEkEKYZu3CWuuMSaen+/0+x8haa2uBzW63A4ama1AkpWKcWa1W2/k4jr1IEcTFYrU+XX7zVZpiZKYCoqqG8pg/IYjU970mUqiKlBQSoiRjgKH1rp5XJQ3KGGOUaxoI4zCUzEcSW86ZgMiQ1vp+2BFQjpwnbtwyJen7bc45jRMqZwy99JNRqc24cWRO2loA2O12deDKwHc3w3zZka5eNEwMZRQFpmAPIvwynuAYeo+YknAGZRi0RlFwRAWC1jrmXN1s3trFYuGcG8exJNRKk+ZxFIAIIETaObcd+hy5FMk5IhrTGtI89mnROmM4jCENqRr+REmOrC3BADnnzBFFdXPnslMZDXZxAJ7r+bJpGtd0zjRkGmphdjhsYuQiUoJgKcAGgKrbXW/vb1123msCfjo9b9Cdzk9fv1y//fjtP/mTX/z8xfajLz7rms7a8eKtC4WJ4HqJzme7sLQNo18t/st/9I8YYBzHIedD6z95/s3hmWnb9nS9PGKDD7nv+5zh5ov8idxYu2vb9ubm5ubmRkT/7MdP7nJEnCGiEHlrwcC8UZyz6xYc4NmLJ99+990PPvjge9/5zslqNZvNPvzwyY9+9KNPPvlk/6KfzRYYZea8Uua0e9NmyzsmgAXOnDZM3Pr2Otzv9jvfamfKLo2mU7rhbbz2eqU1ABmlGhFBlaQMoYw3P3G+1brV3szIz2BHtiVO5X6aPv/88xzZNc6T77r5brdLIe0PulusDLqrr26Z8mK12ABshsmM57e75/nh4fRUxdDfp+H+RUqDbRxRM772Fx8oMz59+kVK5nL+5ovPr+MLl0EWs9npo85asiaxPhRJ5Dc5Z231rEM9y9OOOXLc42E7NXOzerRiOGy396aj9frUWzcczDj2qDAOU2Y2xpAmMJ5T6YdAmrAzIglRAIomYBgOw26To9a0PrXTVPbj3c3mfrV4QEQplH4vOGIJGMbQ7zdNky4fOgCJU1E4NurEWygpIbicoyK78DNUZbfbhZDbtjW0VErFDWVCRKeUAq2VUv2IOedSSOvWKi3ZAACqmaailJRUGtfOLk6uX1yXUh4+fNiptc5N6BMCEfuYCcscxzR+XSIG64vWloAYcplCHqIzClQDBaRHBQ0gxh4A6GQ1Q5EqUAUCp0TNiSjt969CBf95Ew5Ehgi+9SAYSkGUEgtzVsYoLOeny8Vs9uGHH5pm/ezZ15fn52Hc/+DXfuX6+nqz26SybxoTxvDgwcV+v9fcCoahH0gjARk03tgE5f3332rb9sNffPzFF0/vnm/OLx/ub0qOOc6gjCb0kzK2H1OOtJyfTDzdXe3ahX3jjUeztgVg67V2cv3iy7w5u73dlVJiTEp541zmoWkMoeEMOlW4ojHG6GW3Dv3Imc/OLk7XpwAQUkCUkgp5pZRyhoxSnGl7vf/ww48vHi2aprm9vWXmMaVilBJcL5f+pM05pzSKJN9o6ygEGKbp+v7Ztr89HA71znN6enpxdoamhD7U8RIizmYz7311vff3+2+/+613/tK/9q233z07OZktZmkcLdl333799YeXT6+e/+GPfvTVV19t7g4KG9sSZIo5V1to7Ys6Y5zDppkD7KXIOIaYozGdiEjCKU2cNQqmkhFF69oVx/nS5BynHJ1Txigi7sdxs7nd7i0RKVGSuA9he7+dpsHqFp1oS01nQ6LDlMcw6kJaa+boWw8s/X5fkkhIzNEoJ6pYT3GI6OJyecoZatZCcBsF4OaGbJx07vsgUwLOr59fHmCjxCAiGkctFlHoeBp7NJY5Nk2jT/XY9/v9Pju2ema9RsQiRnIWlFRSKiFPnFKCBIJiLXnvnTOs1BAP3nqyxJyZmTR1rgOA7XavlGoWXUo4HKaUpJQyxThrLWTImcOYpPSa7m9f7HPOVpNpqG3b2aKtKqzMUi3oVaUHBMekJaUAYJomAsolxTjFqJ1xDBynOA15GIblctk0zeZuk0ry3h8OB90W5tCPo9VtMlhSylNmgmooqiR7erlMtdaAx4FZTciUWimpV2Gbx4ZGLKUSI+llEMSrMdurn1Siq6Do6v4oRmsd43g4HF6RmKurz3v/k5/9xHufc561M+tt13THrL7DIYQ+M6/mbYG02Wzmy04p9ctf/vJb3/qWMQaYu3nXODfYWEoBJmWwlFIK1CFlLdC891LKcBh8S5w55tzgfLU6+/rZWDVpR0WTHNkt1YumgUlGUZ1ypmnRzFWnGYbN7tbdcszr+fwImTNqmnKO0SlF4EmzYKlV3xgC58yaICMZo61drNu+78dpZEpm5lxjmoJdgXe/8+56ve7m3bybjyEsZjMgeLp53lzF3WF3e30bUrCkz1YnxpjxdPz22+9+7zvffvz660qEMxuGGNJs5e9vv37w6OLNN7//+PHp9fXtJ1999uLZi91u15c+lQJURHLhGkeBpUjbzuqwNOaBM3MGJcaZZhpp4innXAoSUeutODbULS67PgAQN43xrXbOHOKGdZ4v51iUIBpRccpKpaZxZydr+0i3s5kzTXIl3ZRU0thHzkysZ2etM1qElVHtDP3ioFmN46gM7fd7CNPp6bokiX0sUrStdEFOYUxcrNUnJ+vFoh2mCYcmSSLCECQlLVVZbFCkHA4Domqa5iAy9oHAaz0BZSRoHEZViUspFSqsODIT88AhYCklRzfFIYWCC6MUZmajTOOW4BgRd5vDGILv2rP1+c1089Xzp3Hi1s8AqJRSkpJkQsJJcY6kVPMS8CnTEGuWG2my2mbDtfP06imso0REpY1SYlIKiIo0ceZUkteNatSsnXnrk0qqUW3bWmuTKpX6qpQzyuTMKGjQ7NOEKCXJqxMZUQSFRIMI0J9KAVJ1vHkcHx5X+0sGHuljOBm9/P36o7esABhFUDRKyaWUogFWq5OY4263a5rm/PLy6upqinEcx1RK6Pfz5fL89Oyjjz5an5627eLm6m6aphiDcUZrzTl778/OLgDg2ZNniDhbLLS1XdfUv2S/3z9644ImDQCkwRiVY+7H3hg1XzbVvDyOKoWyvb6XUjhzzYdh5vl8TkTTNNXXn3MWQZ0nIIC0FYppCIfWWy0yHYbrfD2Oo/V6rbpIbFBprYkhjLmkHeaiLc9ms5JSCuFwONhZS9pCTVfiSJr9TGufdRvNDKyTFrvPvvqku+3W6/Xrr7++Xq99S8M0LVazt9989/nV808//fTq+VV1ys9ms7ZtNcOzr1/sb/f7/f50OV/MZvvtliJnHp5/85X33lv7zluPNoe7J19/eX9/bebKKK1bm1xXyVAiEqd8yLsYo7eWwKex3+Y9itKatLY5QimSh6xQJSOKNWiwC5JgjcGucUwgkpwzZycnWE5zzJnZWg8TNwYzw8nJAuejyBTGg5K0XHYc+cCHw3QggsaYZTdPpZdSaDbjR5knmHLjGmWMEcrONFko4gQA8+60ogi3U2LO7YxU51o6u++/nkKlRVcUUYFEIiBagiQV0zA5EZEiSjkR1Y97Kcfzx2oqSUrRqIoG1/oWNEgR0OCMg6M2iWIEgARQrFYayCijtZY5Vv8zEdkjEEa01mmUaWAGLgm01iUpjqSM1k6IIKUExLWbrUmjQgYmoePB/jIXQUSIaiSOqm46QSSI2eXD1dA1Tb/tt7fb2sDvt/356SmtVI4QJ1BYKE/b2+1wmMKYKpmLQFW1Se17AYgx5mj+Ba42a0REwJIzvvyqTfajA/tVjPd/famjFGW1xspYFeaiFXivlVEz245937az89PT+9tbzrxcrmftooJYz08ffu2enS7Pz9eXRrmbmx+642RRv+xo6tvbe+/906dPUxIpxShzf9gjYtM0KMq31jUGAJQyoQz9vldGqYUi4lTSNEQR3N6O01DtrbpOZx88eAAAn3/+edVEZQEA0Ltd7hJCDru7CeyUd/Hx6fnrD9/2rb+9vd2/6OddFxpM/TgNk2bGVGKMq7PFwzcff/u99/t9f73f7z/9NMdjFDIqVWjSDrxHsgosRJi0sNFqDGkc90+eff3FV5+tl0tjTCUWfPn55/e394fNJsdJiRw2OyxinNpu++22d8ZMw8QPL/vt/ubmJo0p+1wlnKgUA/z0l798/uSKEx92SWttvXfKJvBUOb+hhMhxinbhu1krRVIpRjXWWCQ3lpLyREykCAOCtwRAlIkykWHgEFLOWRnUyvMkMiZkdtg4v+CWN3e7+2dbRWMKZRwDovF+oYkcqrHggwdnbdMu2tm+L4fh0HnlHp6O2/FmGFJMJMCRtvdjSZKH3Pe92c9LkRiPvfQNHXZXsDoZ5w8LICjnFMo4Js4BxZFWSUaM2M0NihwOBxSjtY+HyDohYinYkCWCLACAkGXYRWUKsUaFRKS11ZpKmSlRqaRxLEBodSklEenWIyLO2rYkfv78+bAZ5vN5NLzv+9NmnTULFoXkfds0jTKqSEFUAHUZQ40rRSUxxkS56lurDbnqU2sUHNHovZ93c1SYpjiG8KfvzCkl0sQ5i8gYwlp3WU0AmiMHCIfd0O/HFKRR3bEDCCgipKVe47XWgkVEJL3KC+AqaDuu8/96Pte/cG9/9aNzzhhTDauFhQica9br9W//9m/d3N1cXV0VKWdnF7e398+vnt/f3/93/u3/3nK9/P1//Puo8IMPPhCRTz/99OHjx/P5vNY1zhltZw8ePHjv/XemYRLEn//059Mwzudz41ycbq013vtjfpkoRKwcmyo3PAwbZ1wIyThlbUvEnCmFZK2t4sgqbW7btoi03quZyZE1T1C0CiDTFE1TZl4t2oVTzqF79ODRzeZmmyaj3ZBSv+2dGKtt0/lHjx598ME7p936dH26D+NhtwtSIrMyRmutukzEQPIqAy5OOU+sbBGRKcZpiiFUj0a6ODvrX+A4jsRwulwb54yiaTgMB7hLO84ZBfv99ouvvhjHMU/D5eXl/X5vlOmW85BSzPF+u2+6xvvlIVynJFxjnZjRKK2tpLC6fLzZbKxT3s8I9Jh6ZtztDrN2xrlIEs6aQOOR2aidMTHmnFkkp5RLEc4YpcCuH4aYQooeZjPIY542MefsFioVjBM5p3nKoZTMTJZu7m5caDLlvt+PoXdGkcasD6uTxWEYnLUplDgxRfDWO+fGmxGxRtcBac057/tRBKXLZKHTRghC6oc4KSykrEbNEAFMSmm/7xEbSzDtJrc0qKgUUQqUUimkIsC5TFPMh6yMMg7JEjC4xkkWLJKnHEMkTYEKGlQqae2NgynG6RBjppKKyJHtzTSpJuUIpEFraDplW4pTJK1EJMaYkrgGtdbCUEoRe8QQH/OCFABAESkpJWBNurRFiapqWVQoBe/v923bNq7bb3tU5Iw/7Ibz10+NQU8jZipFUkBJRhMoUAwsWFJkIAYmbbUxSistiMBU8GW+AiBpQGVf1ep/ennX/ei/SQd+4/FlKWUYhhxjZi5Ft62Zd833v/+9Tz//fLU6qTPF+Xx+dXWVQjg9vTy/OPv2t793cnKSc/7kk0/+4A/+6c3Nz9brdYyD1fbsYgXEy/Xy8vJyNpvtNocvP/9yGuLsZB5jJk2YUSl1eXkeQiqpvERfGGUwTllr7ZxTCiHTvFlmZqOUwkZb+2psAQBnZ2f19TvTxClrVIqLKaiF83Tgk1l7fvnQKUcAZ2cngrK9vfVuJihKFIpSqIxxy+V8uZ5Lwsb72WwmiJXCZ7RGVDTLpUjOpaQCABgRQAPBJk9aW6X9EMYyRCLa92GIV7TT+/0emJfLtbV2mqZhmoD56m7y2jaNC5HRyJRBU7s75M0mpxTagftxTCkBketmMZNDk2NOOVRVg7XWWltief70+WF3UE617UAEs5mtwvJ+30+HKfQJi9NEHIkji5LMAEyplBKoCAFAySqlVDY5M0w9p34/7DIWSUGAzfgiEZFB1RpvlEIudmaNwcNuZxCJwZJdnnSPHp0plGHVfnk7moQ5576fHBosqiThzHZxUEaVVGLkWnoopdzcmMYTRa0JTfIzIm0JFCKt52dFkqqnk1LDIQ/7IQ6ZiBBZRFRQ2uqxD/UabG3DAFqjURaEc844IQMPuwmYCIgzxylq0EpZRMU5jONYGNt2FmPc7A+l4KxtGSbSYInilMFOaBIRIxatNekqKYmliNZHGrxYBDpmTtfRFIowgG89IlbMK4BorcUJANSiA0UZ5bwX5myUYebd7lC1/Ry5cnKJrBRlmwro56y5hutprQl0O/OcgX1l7x7D/gCgjtlqHQFHQRH9C+f8q18CwMXJahxHJYWbI/RaE3kLf+Nv/L9qkyzm+Mc//vF+u1UKLx8+/Lt/5x/knLfb7cPHl4fdYRxDaxfTcHc4HIiYSMeYYx6eXz3/6osvYozL9fr6+jpOuWnmIvLg4kFJqLU+7AYAcI3zaIHJrI1rzPZ+n8reOQOgm6Zp23Z3GLTWTTc3TtW7TFVwnp6eHg2I1U5TIseSxWCa8PThYrU4+f63v/8bv/G9aRq+ev6FEvTej+NoxImUvo/TMHXz84uLi7fffXuuTpn52e11SinkiGAICEgYk4hUbnRJBQWNcsYY8vTnfu3XvvXtb3/84Yc/+uM/jtN0uj5/8OAiX8WnT59ut3sAruPQMAzMMI4xGw4pAWfvW22tM+YwDHe7OPb9CWuwLjMOY1J3Q0rpwUPNmSsAKIRglPNtmoZYGmRgCHAf7kUS4jnOVAol9ftxH0rAWogygyRhw7vdruKugWMaExFV2NuwGWatb7WPMUKKKTNlJk37HVVduiRDjohr3lshS1brcRz7vm+ak9rMb1s7j6BQdrsoqSjXgobCBYje/t5503VGKREFoGOMxrjV6mS3uyvSt60Vl8bUcwQPM2ZSzZw0iBRjjBT84ourr26/4gzjPmlLKRVNljOkUbRFzjDmMYREMwtMRFzlNExcgsznc1W6UPoYoyhRqLLNQ9w451zbFDFBgvUemDjC4zcvjTIiuN/3KGqxapenTUoEUc/njTFGMDFXqoSICFuoXh44ZuYqEUFm3zRaa6MMoABDbctzZmOU1jqE0I9j4904ltqQzzkrUQoVkRJRTSPElkC3noxRFd1R87MBABWaP5XRUeXsFaNS9S3H30ckrY1Sr1R9NeAI/1RDPsYh5ggAi9lsPl9Wj7AxJhQxSr397tvVQeytJdK73ebzzz9dLtclpc3dJqVSSlmu1/PlkixbTTFGVKJt65xjzofD4bNPPru4uJh3bt4tRz3OFqt+P5YkGaK22jhDBDmycgoRc74nU3VfYL13romRCXTTNdrDOI7OuZpoXtm7zrnbfptS0gYA83iynm3LxANfnK26U6OWqBpcy7qMOJf5fNiUwFrN2werWeutt26P9gAJChBsrjbX19cnq1XZhhiG1vqgurubO61JhPp+dM7Ml7Zk3W9HfLuhmxk/bV/HNx8+7pKMXTHd2cWZnkXO/Vg+f3L9zYsYGYAALKtWFREANemstQ48wUyffJeWy0fONaXIzfMbtZ/8TFvmmxucpklrrfWMwURGVRrbzhocF6sHwzAAMyLqSZ/MTjAJvXUXD4rYliQoaXt9V0LXjq0s7PEUcjBCnqYRIPvWu3N3t90UkcVqoYwKQ4Ai1usHj62IkDZNQ1prFZqcs9bL6fom+TKbzU7eWLpG97InAcw471LXqLOzFt5p1cv4JBHxdpY5I6ImYoYpQil5gptkStPM+2FKg3Tzc9HSj6NxFMfEmbXWI2bmfHa2Wv/WfLvdP3/+9Pz0XBlTaepqqc5Ozqy3n//s68VJW8NwNPgGFbDufLct101jhjiprCSLFDHODNMAd9Z5u9sMBHnezNtOFDoisjA/3O9SSt6fNLOmJHjt0Tv1MKlioN1uk4UXi4WgEJCIAWasBPE8jWE/TZNCaRylUsZx5ExGGVVcGtM0DElGEQEDBJSEm04J6izTiZkZ19jMwyHeXN2vl2ujGqPcyeqk7iNVHVRS6cd+GoYQ0mwxm81mRqkYc5FSDdpN18UpjuP4/Oo5CgqG+cmZ1lrPNZFm4Ir0VcYQkEgZDj7390ko86xgZ5xCwwDgDaBgnFDEoihElVK2duW67WHaeN+SBWsIgEBnFIlTCiicuZQUY44xppJK0grndzeT1RxGUQr3/TNEtNrGHKeBj7WPJkzIzG3ra2GcShkOhxSCtmA1pdQzO2Ec+1DddFOIDDDm0HSlnTndent+ft513btvPrzabPb7fX0pVmsAiDGHkC7OTmeXi8Xs7HR9ioj7fqutVuhKOOjWL/yqUetPf3E1a2dvPHhwerp2y+V3v/vd9XrNzB9++OFnn3x22O1E0Np89fxm0T69v7/f7Q7tTDdOoVIfX/8EEU3TFSsuh1VDBR0zkHXL+bx6IZRSFXGtlHIoqRQRtNq2tr27uVOoUkgn33JVrlgfuyKl6q6ZvvLtsDSmaZpxHL3377z1oB/n3Kz2/SgFh0OUiMs7sdQ65bgFhai1FiWhyBQSojbG0Iin0wIA2lnrrZ8mn1LSVttZW1nlSmEpknO9I+TF6vvVhp1znqZpvx9R1fPq2PFRiKyVQmRgZri/vs+cjxpSgJQSMANRjhD6NE1TkRIjSCkhBWt9SSGVUhNCtNaLRTvvfNsuZrPFcj4HgJzzvu/HcURlpinPZjMROeymnDM2yOCMIsFknOrHcUxjVXGHEobDQJqcMljMy0Be0ho1GdIaBZVSJYkxStMxCVtrPZ/Pc845xpKECwOA975xrj9kEKkhhEkJU9Zak2ZtC2QuJXNOIQQsMYwlhHBysSqlhHAEV9T02FJKkQ5zjjHW5lbTNAodZ4oxMrzkdmeu10l+lcQQY0GVc66Z5yi43z9XxlitjTIxx5JLSslanZk15FIk5syZKWcCYuAYJzqKeeWoJmTQWodQbwGCKDnW8XMBYM4gWKZpyDnmyKUUribYyh2CGlVe0wdFQHLOKFhdEIJ4TEmtGTtwXOoKFRGUIgxsjKq2TmutMmYahjGNMccQdnWSf8yuwyOhMMOIiPp//b/5D7755unm5vp/+O//9t/6L/7gRz/+Z5qIMqwWzR3TrLVhHEXK7fX25mq4mm1a7wXl8uGloADs8pBn/uQv/Oq/cf9G//3vf++11y5ERlLx7XfffHgGAHCz+zdvrw5fff31j370o5/87IcplTjxvFtqrR89OlsujW31U/uZ985aRQFP5rYpTtClnIf7rXPgvDCnEA5j4ir/5EmP46hJX5xc1Mmq1d4TzR+KMUahAoIq5KzsKqZFzllrtE62/R5y2Awv9vv97fPnpSSjujBFqzs0BUzMIiEkpYxGQpQChakwZJY09962JucsKooBKdMUDhJQDhlFtLXAsO/3FZAWwtjvm5pz9M/950opY7bb7asSsYYMFBEpZRpiPQatt4hYAZPKKCXq1XM/0KGEJIjWg6Aw8CRYt8KcuXENAOw2uzjE+nC/Qin0+94UVx+ytvXee2buD/vN5s6uSOr76IxSCgIQEQJqskBAoAEIEVEMkdWkSy51iH3MD0aswe/30319gpVRiJhKivt4OBw4U63SiYgh1zmoJtjvewBdqzxJQkDKFM1UvVxE5IxxXZNC2u/3IQTmk2ouSEHa1hhjSpKSyn6/hz81Nmc4ZvhVc86RxFiOkInJTJwZVahSzrpB3N7fXl9z0zWISoqkkkoqyiCKAgBUUv/PKFM85HEcGbiWMCIiKABckkjlX4g0nVPKiEAY615Q4piYuesaouPLqRsoAjKy1kdAGGfOnIBBRGJmpVT9OSBkyseshSIZXw4FmRXzNE111BZCSSnZXpciOWeGSj1BxATVjEEcXrx48l/9g0++9yvf+/LJ56WU3W4zRP3111+u12uFxlpAySguR77eXi9WrdU2TlzCPQo1qn3n0a88hU0J8z/54aeff/7h+jx/+MuHKQREPLs4u7y8nLXtw8vLX/7cWK3PTs4fXr62321j6j/56subu6fyetzspjzx4TBMkUnbApSS2ITjuLN6AICUglJKBPt+36Rlzpk09Krv9+PN1V3TNMa4DYejZzgVVAgMgtJ13bJxYeQpTtbyOKrVovvy/nB7fUPaIzqlXOhRa50CUuZh2mLXkM0KFRoUKVJMEQaQHQ5VBZU5tl4yy3CQVPL+flMHoSml3W7Xtm07aw+7KU4HYFJGWauBK/P8qOiqj8gx5U6OT0kppRRRCq2tKOUCAEopY5rdZgQA5yjnUDuOxRZoI9ZwcwWceXu73dO+tiTjEFNJKIgKoYC22mp7f72r8GDvvfdtSiHTZnO4P1+vF6uTCuTKMdeaOY1JF8qZc2YAHg5RIbIOETmlMaRQ2yJTDU4xqJSqbaR6mwAAfUzjxBgZAOrtQ6QUDCJiPTEmZUAZRZpyzolTkZIwGVQiMoYx5+w5A4BpzGw1SynVb7rZbOLE+30vRRFYpY7O8lpcMx/nZM4Z5mP1LsdrhSJNRwKXwmrOtfYYMiM3qAyKYL0aHJ0JRjlnKl5GoZIaZJI5qcAAnOspXZf6cQWGENpZy5ljjjU+MZXAGazXOea6COvnXiPWFapu3hmi2qgqL6MN67f70+2G+kvPOjPnnBvnXON2h0Nda5lhd7PjzDXxOtdUJSIiRkH9N//mf9I1LrPcXX3x5OsnRCCpXF+/mKZhv93+pd/+SymVzz//lEjP2pOn3zz/4R/80zGMh2F4+s3z06XW2ozjtN1Oz7+5+uKLr25uvgLYMeDz509DSI8ePBiG4cMPP5yG6XA4WN3e3Gx+9KM/KkWGaWrmKBgiw+FahZT7/XgY+iJKExSlUNDuoJSiNaPCnNkZpRTF3qKJxhhg3W/DZrMbDlGS0zrk7WBMbTalOrEHgKHhGxRNdBgGgmk+n592l3cvbu6ugSfWlrSGsYemwTxpADgMIC7W0wlRlJEavZiZFYr3uaQUYzSOjVLDJHHK2loCyqJjKnnQohy6BlOpjV6eYJrqI1gPm7xarZg51fRtBsEajSnMhoGLIGdCwVKwXuSK5bEvSikCDIGZgYCAaeZbbUkEsUiOPOZpmiIAG2OwUSmIMsBZgJgjxJE56gyZMwAQrMA5tTpZWW/RjJqytQ6ASkEturYA9pt9CKUkYQbIwZhJUClE5lwklSTH744iggpVOCa6St0s8oHr21gEgaHmBAOwqISImRVTtJbVpBi4SCEiY432mgRQYTvzTFALGYNmuZy33lprtzmPY89Zh7GIYOtnh90EBPV1vGq2IaLPvqSSSqqddoWqbgfjOAKR1XYcx5hj09QAP5dKghFe6XwAgEBrracB625xdK1mBgKVVeVXVaHey+MdAKC+Dznn6l1HhaUkALi9nVCEGYgAiOpSFynM4Jyx2tZ/bFUTKFSRJ/hTX8c/CMA51lHl0DSImEIYx5GISkGjDBkqUmrAGyICc+YIRPq3fuvPA8ec86xtn315/5s/+O75w9O73fPQ97O2ffPx69fX1/Nf+UEI0rmOI63X5+v1fD1fhzHw+cX1vXz59Yuvn+1tSyZJbmnRLc/fPN3v94LFGLPbbK6vb+/u7oZh0GSZ99dP7sdQRJVmbsxcOOeyRg0OsrJRV1JnGQsi7ietlMtKxRjHMSKmSvPrumQtlzIBw347MnOi0vcjZzJGSlEipLWuzodxm1cX2fvOMuWcQWfjcIpDhkhka3KzYBAksEWkMO0ROiAkzYhovK4zjMwZk4gkwSKqpDQiWmUEYlZNQkHWIhy1j2CngihmnPa6Pn91hb/sGzU5QzXGv6J8M3MRcarjUuBl2HMqgCKsJI0hTqw1KSwlCWcsCoHBOVe5YDlnZp6mMIagiYDJatFaa6WFJMaYsqSQgHSemDmqSWjIqlmulqvTy/Xt9ss+bBmy1d5aW7BIkVk720y7cRyBdQolRyayDDVZGY6LYYRXUbUKlfW64iW0tpVaf7zPK1cP1YoDFJWAyBUFwOCBiJgYCHxrm8ZpTSEVRGzbRdM0fd/f3t4KSiYehsN0oP12m1JZL08Ou2m73Ycx1RX46tCDl/12AKi68TppyypDzQdGJMGKfyxSvPcvnr0IYVTGpFQ48yveOemckiIC0kRA5ZgUw1prcC8jhl/N5+B4n9eWGHItvkiT1toZR5oOhx0QGaVq01dA0KAIcUipFJECBKgQEtR5YX0f6nvIwKiOZJyQwksJgBCRMqoMwjlr7d988822bZ8+f3r1/AoVGm1yzkQWFepPP/+wMSZP036/77fqxf0L9wnux9sYp7adff7xk9vbWyDLmRW6u7tDnPI0TT//+c9DCk/vSyl4d3ewaH/luz84X5EvNg+Hm5vnq8Xq9dffubu7+/L2VhNYDQFlHEfXNFPMMSZQqhwix6mo4NmeLpcOHSrpHOUIAxzGYSxSw0awXsbKy3KLWcJY33QqBQmcBl9QlIG6dCvoymjDoFIaQirlMJRSROiwizFySKUUxZEFK/aIlUFBYBbT4BQnRCQGZRAskTUVLzhuQ/U2ABCiGDHeNynJuE1KqQk5xyyCACWFKeej8PulTuvlNQyxakLl5YRZRIoUzPzqMKn/Uqn/Ico8kBY0pUgCYt0SaQaFwxBzzsNhYGZtdUmoxFjt+r4XUSjoGqe1LgU5cxhLHOrKNAAQxnEcteuMUer8cj0Mg0KfI5UQ4sR5yLbVjZvnCMIqy1TvElJKTghQlEEQqmWqCKAQanzjjTc2d7vr6+tajYcxdvPOaltlApnr/baAZETMKI1qNBhlJENm4CIS0pizLNeXd3d3dVBUxd6ztnXOSc4A4LrmQtvXHrz94tltEdSgK/QOReoah5cSV35JvHl1zjOzkGhUtdc1m82aplmtVgAwHIbMWSQUKUorhYoVQ2VoARMRaTr+bQbqJYL5qLojDQBYoxAAwPs256gMGnCkQWuy2iujUgh1y6jdBCig6BhZm3M+HIb6tyl1fGwIiJBQo4hgQRFBQNTY2KZxbpgmIm1MpfhkzrnpuqZpuq47Xa+rQK329ayeKYX69/7e77Zt2zglgnnny6ejn5FpsLavD5up6+bPbu+ZLbEOIaWUhulwt7ljik/uF6uThV/Z/f3+0D8tI59ZP7NnZ7/5zosXzyrfXymzWvnM2RhD5I2Zh5D3/ZgVFEyJJAOmNGYNlosmnvnWr/xG8/PpICqTjjHmIslYQyzTNGKRy/MHOfPYh4QSUhqHQKBjzN1aRZ6kFEYsWbmmM0QqpTz57b4nTa1vC0A8WJ5angoHzlG0JgDyVhcpzCpPOgVBpXQiYGTSgMSZ88QSujiOWNvUKWk2xC7003hnCDULczFaa7E6ISKImmU+humicQ4A+GV0bt3+CQGFigjUw/wYUi/HA6rUrUFyzuY4+BHSpElXQXnXzMcxRMqZM7HOhXMEhWzJY1EpJYCivFFgEBlAS2ERZRoSyUOc8pZZg3PqwcKfrE6UMi9e3E9T1OSttUR2vfYAIAUBSGQ0xqUgmgT0gKLIVPqloMI61j45OzPO1e0rhLClrdFGW0I0pRREISIGrGeRcaoKtlW21hMqEV1ESsplGIbb29saz1wvRKmUlFLjGiliSYvGOmeZd928W7949oyh+meOhzkzS5E6OkBBpbDuqrWDbbWt8PlhGsZxrP6T8/Pz7XZPoLPJrjFaHxV1BBTjxJyZwVptrSdNcYrTNLlFQ0Cka88S63kgIuvT9X6/B2AUlUoQQW0Jhbz3yqjawsw5oxyjEDLzETVbh4UuAQCRBg9Vwvzyqi91xyFiZ9wr/Y+3trReihDp6+vrw3Bo2/a11x7t+77f90lbTZ6I8D/4X/1HNat8Pp/Txk85B4dgWbBvjMwxSQjbZg1Rf/LLr558eZ8zL8/NxYOFqPDkQ1UknZ2dPHn25en5/N/8t/71mKcvv/z07im88dbFYmWZokjp9+n+ery/HVdntpvPD7sdEzDpGKdPPvtsGiZZlvlynmRsnEpJIOuZXjz7+hZY55xjzFW0/Cq1G1kfAU11KsKgNSEqW1sdwACgLZCut7WSuN1s75frORoEo37zX/pzv/jlT28Pu+YOtNXmZXJgXWEAMOUdMCxWRyp41ZaiQk36MBxyzo1ruq6rhsGcMx+AIddBC1SviNVaU0mijALgcQw5Z1PRxcCL2UltKdc+c71+E1EmkmNXV0rFEhMppULpRQSVqhNQIGh9285mJVUkRgoh1D5Z/ey11t57RAwhIKJrHACEMeSca6NIUBTWsmhcnaze/tV1EVktFoK42WxSCNpa733Xqfv7vWb77MvbsMfDbgIxjuZ92PjGlSLe2mmaYkrrk9U0TYbBKLc6WV1eXnz0y49re6lpmkRcSgkhGaW896mUCrSZraUeld7rGCOa0rZtKsku7DRNdeiIiPv9/vz0dN/3JZTL88v9bf/ky+vDIVqana8fed9++tkvSFPXdKRpHMeKoyupKKNqB0FrrVCJSGVOdVYL4vvvvWeM+fTTT6sh7MGDBxnVhx9+2DXdYrG4v7/POStjiABSqC7XWjHXPQWI2tbXJAZlFArWSoGINEDM7JyJEQ5j8N4b3ewOh85A0zQMnHOs9jlEIdCsc46RiEjr/X7vjDk5Odlut1VrVKczx14AAwDEadJal1Tqge6c2d5v16en++04jiNDfuONt1JK19cvKl3XegIA/T/49/9NIK47hLdnaRx11dZRJu2ZYIhDg93mbvgv5e/3+59vNpumaV577dHzm2+AImb5+usvazX70Scfvf76Y6Oat9+8OLtcmEaGeJeCoGCO7L0Pfcq53+8H0lQQSykoxhklMlptNYAxiAI5M2fOGabhUDcxXeO4NVXquIwBUVmDhKqOI4mZgMYSEdEYrApNKSnlDMQaZGVnK9c4g4t29qZtt5kWWV8rKanUcymnHFLSRMa5xsyZcxxy/bCxQH39CrUSV9tmKUmOR8gxRgQAwmPcIiJy5inmVIIrDelqpa41nrjGHA6Hau2a4tT6dj6fD8Nwt7kj6721QpRyZub6SU8xksaXF1Sox1QpJU7TGMZ6rtYx8nFgy1jXP77kk8eY60FnjMmVfFwYNBCRb33r2zCmlFJJZdbOIEO/H70tmvQgYZoySpmGKSfKmYEL4GisFZF518UcXeOstddXN23XSSq76WCMgUuIeYoxK1TTNKC1OeemaYwzu91unCYkQpEEYJRSBkvyQBkzFoMAcHd1p4wyyoCF1rfOuDAmSzaaIwZfa2KGYThscDObwTCOWmsirRNN05RT0UaVIpSBSKcYtcmIigjq3vHs2bPlel2VS9v99vb6tkjR1grp7Wb3apgyjCMAlMxWlVe2vAqvUIhEtJjNhjTUsIdaJhwrBUkpiNY6ZmBRXdcpY4D5brNpp7Z68kkfu/dKKeOwlGKtrUMQo45Mzru7u6MA46Ui4PgaYi66VAZWNc8opTRRP/Z1p+v3PQMfDoNSKuc8RQYA3feyXK6artFaT/S0cdSgUCxhTCOWSF103Zmab3FMElwjJkjb2sVq9fnXn1pt0CnQuenMNMTPP/5yOV+en19++osnoexXZy1ARqVjnHaHjSZvPY19P02TcSakVERyzmEMRkvpE2shrbGAzhqVa/0s9kKAnCSmyMCKKmGfDDCXUrKAFGLRBMSECusjJSI5c4Wpo6BzBvexUYqHaZDSOdf3/RCnJCUFBBDUqMmR1mEsGdgoKCrVW6i2dt51McZ936tU26yFM0PtrYNIKQDQtm1IIefICbQWEAhjSiU0rpvP5957XueUSpyiYDHKSWOMUtM03W/va15HPf2KYFVrhRA456ZpagJ4wSIoNSldkaps45BCVafVa6pRqhCg4Cuy+qsWlCpVkXpEI+acpRQtGhGJtDKqpJxj7ve9e+CMMnGIxNS2MhQmJspkjMlRjCFCQ2wiD1VMDgDb+339yX67P1+tSikM+bA77Pc9ylGaqizs970yyqGrqmyjVD8M0EvQ2mpAUWjEGJQiLMCZrbZeexGx2hZdxmFs23bsRyUqjFlb23rY9n0MEVquqlXmnJnCmLIkBgMAKbLWHHMsWaNOGhU3TKiHYUgpffTRR03TXL+4rqX+fr93fpZSeCnXKVWFlXPmAqoONV8SJhlRKWWcgZeg23pBExQp4rVGVVIpKWUkb61VWqd6AYRckqSUakZFRfrWgIracpZS0stmbRXq4rGCP9bxVCn+tQHJDMwoiC/H8qUUgSPBojpQSimkEQD0//x/9r+/ODt58ODB2dnZr/wrq4VvL5fLufNNYxWATUVx3hX56KOPNneb+bohzV3XpJQIaCy9AnXx4GQYppyHOOlnT168//7y5GKmEABAqYaApuHq+fOnvvWqNJlYRBrB/TAqVCmV3e6gM1XpH0RgptSXHHi73QtwnhiJtDEs5eWOrs/mi5RSCClnIFUqGqWUIs7EmIFYa02FpSTS2go8PpknwQhQVAnObJX0y+Z+m73XlV4ypAGA68VPaz3FWCQrVM6ZacohJCkYQmGmUpABUhJjgIFTElQ0DIO1lrQfpsN+v5/P5++9/94bb7zxV37nd05P18Y5YGaBoR9ijs44YbVcLgXlw198+Pf//u/90R/90b7v29aXVEQK1uiC41wnA4C2VETJkZWuACBxyjFXjCEAAEOREmOuvNTq0wYArF40FBRUqFJJ+BLhTETMjMxxiuk6APNms3Mybxo3bKI0ivJEbbZkERSRzbFuSSQqEejGuZij1XZK46PLh3/5d/7yJ59+8uGPf6qU0Vpbb9brNWdmyEoZ9NpPE5EmOAoBjTHOWhSgjAxQRKlUYqHsOAQG1qWg9jZNJWJGVnngJKWWbzW9tpSCqKyzvm1RsF7+FCIppEwEhEQCWWlSpb5nR8alJlqsFmM/3t7erlYrIlqv1wCwmM1sM7feE+kqxdFaWzRgQUGueqe6Ao+9OqIYMwFUwfnRUsZcIDVNQyExMDPh0edfUKTKGbCpB3WpTX5UKJiIyDhjjEGl6vosUmoYY9Xk149MKQUEGgiImLPSr5jcIKUckbhFXOOaxrnG1bAN1SAAaEHz+ZfP/uhPPuzH/cn/e3Fytnrz3ccffPDOBx+89frlaeNwRTjZ5dXVlaiRbC4Yhrj5+ks2pjk/dzEeR8YAME3T02/uTtf7d7/1xt3d3TgkTUxaA9Dp+XK9Xk877ZqubVvXuLv9tuu6Usp+33fL5eKkdR60palPN1e72+f9fbtVtjx58my7vXfOaW0RSmFGxL4flUJjjPcWUXlvm6ZxzmVlAMC32vvWdqqanJzDaQPA3M0b66n1/sGDi9dmsy+++OLnuyu/8CHG3X4PDFrrIjIMsWm6EEZhLAnDOIiItzMRAUZNqghyhjhwSinm5L2dNc0wHVIql+cPfvXXv//rf+7PvfPOO6vlCgm9pxCk5KK0WiwXhHT6EGYaJgZL8L3v/Opf/jd+9Z/8gw//9t/+Oz/84Q+LPiYBWa3RmFRKZtbH5xvxpUDqeDgzSx2yA1QIL+dMRPgSOVREXklKiIAKiYh9lZGoVAiBmadpMgWVcpLMNDCxAHtgH0ahksDoUhKxdo1DbUhrEdluDkXrmHNJ5fzk7K/+63/13/13/91PP//8P/k//J+//OqLMCZnvNbUjwEACCQMk7G2ItlrMyWlpJSqyFRmloBJFFmeBggpk+a+7+tle7c7tK2v4uX2om1MM+1iP/bDkAR1NS8qozQqo5QgaqO4iDYKBdEoIq0UI5Eco52EoMQp1gaY975IqUTqlNLyrLHaKoUEhPVOTPWwPnI1mJmBpUhdfiGMdaJWXk5MAYCAUgpjSFUyVABCCJqV1pojVjaWMphSPaUFEUkpxJq3RVTvYrVGf2mtq2kzx127YG0EAmgCysx1W885W29NMqJFa902nTFGayooQBkA9H/33/vtw+Hws5/97Id/9MPbF257++KbT77643/0jx48OPnWt9/84Afvvf3um8bQ7e0tEIMGM1fOOY360aM3povovSfQ1s6uX7z44z/+cb8fv/7y2eM35+MYNjeDQmO9bZr5D37tB5eX61a/XnU8ReTq/m4+n/uuVahcM+/mjW2om2PXQogw7SAn+PTTZ//09//pj374o91upy0BzIHJe3+4fvb49dffe+e9i4tzIEoxlFyAiBqbUskcSymoCgIAsUgh5ySUk7k7d3gC+jROZ0Pf3t78tKAii1I4CQACGSVMoqZpQqy53EdeT0plmobFYqG1rr3WIqVI0Zq8b8/PT995/y/8+q/92vvvv3+6XpKFPEH9+PtDEhBFSkR8S8sTaAkAwL8EFZ608G/89W//+m9+++bF8B//3/6Tr7766osvv9ztdjHnqufvmmYM+1eS6SNNXSTnLFrnnGsfjplTSYqVUqrUx4I5pWPbVhALlJSSoJRUUClNVAWe0zRZ3RoFKaj9beh1Gg+FYwJIp5fNdIDtfsNMJSUsuYiklKxxmXOFSX/wwQe/9Vu/ZRp87513/vLv/OX/4r/4GykF3/o6lO3mDUNOJQNArTgQ0VovpfTTYEuDKKVgVEJYOErAMk28Pu+Ax2nKBLTf91VoGPPEB7Azq5SyWk8GrK6jxFRP7FdgdtT1kxMWUQCEqIiYQKpclHOV+nvv59VhUT3uRKWUVJLJugYz5lQQmTUZApFSmyBVCgEAjMeTX2cd6xRdKaOUWI1FjGKtNYoqmVNKpDIiVng2aeEMUgT1cSVnzrWrp15W6fDPAThHBV45jhWQ6tQDkQgyaDqOFOEVIPzVzT/HzEyIIqkAgJ6tZmcPzhYni/PXL3/+f/zPL4jWw2SvNuUb3Hzy47/3s9fy2Wo5//bt9oWeAUG2WreLtsOFt/5wOMyXp2+/+e7FxaNwyKfrhz/84R+Nfdju79u2jS2MY9lsDt7T5eN1KsE17ubq7vr6Ogrv971vvbbaex+TNkYJJUSx1kt2kpRSHdnd6enpX/vrf205X/rW3t1snr14cnd7p7/1euM6M2vvhz7GKYWitfat1xFy5hAmzrw4ac8vTxeLGRE0du1EtTp5zuemaU3eLDqn1J/MozHm5u7m1UQHmNu2FcjO++cvXuz3/Wqx8NakUryncUyN01hzCAlEUGs7ny3+rX/7r7dtu1qtSirDMFHQwiUXzjmnmJq2MY3JMYZew4nKAPElmFQDWAICeHgBDy/a/8X/8n/ywz/a/OynP7u6usoxA5ExClE9u/nquMUwA4CtNz3B/aGmi4omHWPsx54zV5lnTVkNKTCDM4Zeii6998Mw1Jlt7cYrpaZDZhFCVFrHGOfd3FiriN54+1HO+cX1CwDY3BwAQKFSRqXI/b43SiWti5Rf/vKXP/3pT5fr5c3NldVWazLKXD48X67nVVSLKQFA6/0wTXe3t92s7bp5ZsZsGRgwS0JWKBmU4uq9Vd5sNjulsCSpSvKUMo6FZ2yUm8/nBCVHUkpV7eBxZsF/yklSXspp1DG1LlEhgpIKAYSUwmazWCxizK33OXOo+VlJsi5Vr1qVjITIXI6k65enN77MeKq/oxC1czX3spRiiYxJADBMGQCUUgSUSnn5h4h0xdYTIJAGKSQgmdnK0X5bWZi1P3f8pgD4kvPMklHqDlbLZDy+A+VIiMg519zLV9MoANBPv9hYa9vWv335nd/6wcP58xeLn3w52+/x5OJjs/yvDtOndvrDD//wvfffWMwahsl7v17OG7UMUxjD/qNf7hvX7ffjB9/6/r/3P/5rXGS76197Y/nag3emA2zvp5vrm9ncfedX3x7D/faZvbq++ulPfkZWVzdWP45a6yyt9xqAlRWNPmca90WDt4upvu5XSWaISin0nQ7TYTMdRLBiXqmUYRcNIioFwMao2WL26NGDk5MTIj7d8ny5nMo0cVSrkz3kp5ifTOF7nT49PffeN12zmB1zadq2tZ73+/1//v/8G7//T/5J3QLiFH3rlVLW6pyhXq1LKdXX9X/5j/+vrjHz+Xx1cnJyctI1nVJKUPb7/TRMs8XMarvdb40xFxcXVturZ7fTNHnvz87OSOvdZjPF2Hq/vDjfbXfTMFjvH7124b3vh3G72b771jvGGYUqpcTM1vumaYxSfd+XUuoBVUTGcUSR2sg1zlSuoIj41hPQFONqsTDGbDabnHO988+7Tlu7vRuHYWpbr1Dt+76UpJRpnHMejTGbzc41brfbOeMuLi/OL883d4dvvnkawlhLiaZplvPlYrX4i7/5L/07/87/aBgOi8Uqxklbu9/v27YNUuoF9fd///f/s//0P7u+u5nP584ZNI4z54yKTCkAlCVDKWWzObSzdrPZVTyeipUDSafnq9lsNnEMoVRIOxE5Z0iTOoLfSKGq7teMTABKIYCueGzKmUgLibBYpRHRWquqnJYZRaz1xmp6uYBBUFttrIbER6Tsq7AqRCAahuFVB7S1tmkaQSlDAQBUijmHMWQGpZRSijlX5gkzliS5sNaMgiWBaRy/5MnXN+robPlTyqtXuGo8gjdIa62MKkWqsF9QSNMxyxFRaVU7DojIXO0utFCsMXsNrP/1/+n9jHaph3/8u/aHvydrfPTri5/44YPz15USDXR/m157952T9qTfp7G/P4FHYGn79bhT8a2LbN92X3/zbLfZ/vnv/sqf3NpoaVn6Zx/9+OF3vvOTDz+/+einL9Y4qnH13TaNZX+TxiKg/S7kw82wWCz2+z5nns14mqYxBKstfm2mOEmR29vbcRyrlUUpNU1tSoWIUggioozhnLW1Zw8ohNA0DlEtFlf/8r88U3j3b/33/0J8A25QXjv3AHB9gH/8D//oJz/5SX8YZlqfnpMynVLh1//CIw0wZdjdCmc+W9p337p4/mRttUXEMQSFOEzzZ0+ezRaLMhbbNM6r3W735Kv7EpLWrHVBvM/5Y5GSSuHMqmsy50cPHj1+/fH1ixfr09NPvvh4NltM05BS2W2+Pru4b9u27/eIarfbPXzwfAzh7uam1ttvvfXGzc1dSulwGBbzxen56dWLq2maFKn5fN7Nu37bj2M/TfHk5EQZdX97n3MG4UePH2mtnzx5Uq92q9XCGHN/v333O79+cnZ2d3d3f39fo8LfeOO1+XyuowWwm7saOGoBLABsQCiWiSe7cM8/eY6Y1stmtX5wejJ3bn51dZdSORwOy+XyyZMX1/a+bdv/1r/0aw/esDmurIdp8MJg1OzskdremxRDKunydN55rZfncZjm3muLMde818oFXxPRLJpZSydnZ+PtrTFmDGHuTB0s800edgejmsPVTkoxpA1O6/myM6I1GJWUyQpq3zQ5FM5gTQEDAKMBYyznGL03U/QAoLTWzkWlyKggpbRWJ3BiOtspVjPVMRYtmifJCgAAqzCw9vaUUkqh9SEOpBxpOoSSYCTSIaTWGSDImW1LTimQMeewWqjDAbWlzAw6E7Jxxwu8otyXvtXae0gBRELMB9fgtDsKJUCpKqGrTp4sYp1mYERqvW0a0/d7pRRorq6BDFk5VTCh1srqnBEV6t/9//wTb201ynQN3E2blc9v7l8sR1k/mKf5eQeh6+avPXpjsVjcLTaPH7/5zjvvcIanT5/ffXO4ePBofXZ62O6mPHzzifXeXKfxFqinFJlF4jeZv/jsl/tf7MebO5GxaTqj3Hp5+s57b0wH3u0OF97L446IRE6ObZtjZr2SVKXgqZTzqplRClMqt/fp2FU2qg6Zj2LyVAAAgGOOjx6dPXrt4ic/+5P/6H/3/3jv/YsY42wxq7KK50+fHw7Uthfn5+qVOfyLj7dKKefcvu8l565t/9Jf+u2/8Bf+fNfOCmSt9ayZ/2f/97//t/7W3+r7HpWq92ECOj8/PWx2zFAd9VUwozVTo7PWGEIpstvsttu9Uqam/IiQlIqs4xzz2Celco6cWEIsIRVMLCApiggCkDW2zo0JtdZakapdJQBumq5pmvm8U8YYZXKO+30/DMPJyUnbtnWsqpTS2h7lliKaaLFYDIdDrIF1qXTGwZ/1pZ3WJYmqFpHp2bSZdruvPv8IdfOHf/iHMcRSymq9urq+sto+fHz54U/+Sdu21mrftofDod5dV4vV06uvGPLZyYNpiL6ly4eXnDkz5xhrr+vYcDbOGNNxx3zQRN571zhlTONcVZJZDdZa5/y860SEyK7Wi8VitV6vq7mV9FFYxsCIklKx2tZhWB37BRWkiNVYy/XGNet2Rppa45auM0Y1nRMp43hAFNco7xtjzHbcvpLQ1NMWiBAxx1yvdUopq5E0MYMmTS9ncnUCBy9/6ZwjIlUTmkX0y1G8ttRKW3U+TddUYVz9LlA19q96q1XsX621gqXIWILpx2PI9MtG/XEHUUZbJQWVUQCgv/78WdN0Rx/MAxcPu3wy+9Z7P4DHj7/obzdXgu3i3Xe/E8bw4S8+ny0WIiYldXV189ln3zz7+sWXL56tVivjlH7yZdu2TYPf/vbr+69/yc/scrl8OPOL99/5/Pb2q83dm2eP7phPT85u7272+/H8BATDdn+LaqUM391vzy/PncUQwnI2Y1AAEA7Je5+zptp2ikEbiyIXb+mSkzLKGisgKRZARkDpFTPXPs27737r+7/65hdf/fSzzz7+5rMvphg1Ucy5suuUUqfr07/6V37HGLNaLmuYpHHurcfq+d3qZAWa4PFbb9YW2oGhJSCA733vex9++OE0DLvdLjOvl0vrvSY6Pz/POVttZ7MZEE3TpBQ2TfPV86txHOfzeWYmq0HryKyce/r0aXUjucaFlDa7TRGJ09Qtu/v77dXzW1TKObc7TNvNGOM0hpASGtMdDtMwDYgIYLVuv/7y2cteulir99v9GMbhMDjnSsKvn7ywWpdS2radzWYvnt8+flvCmPo+KYWHQ9zvt6vFmCPf9vd/5lL31jddNztbGOOKBIPKe6sBlicnFbHUzTrfekRh4AeXj0Kfd7uNtrOTk4uch/1+75rZct282BZkaTq1OxxSGYfpTpM9iqOsZgYIARmrvwCVqvqipmlqJnRtTTfOkckVnFqJqAC6cU3TNOfn58YZ5wzR0V9UX/84jlrrVFKesvVWKRz7IFhiBG9tKWXWNQ8vT+s6RKVmK/f49XOs5CmiOE1V0HbaneErzS1AYa50UYXmqJypwj6RVIpS6BXWIQhRFXkBACjElJL3vqpl5JUlENE4qc5rpXDu51CB+Zm7Rv6FT6R244AIalCWSN+PgsnPrNZaijIKlVJt6+Yzf3a20kSZ2TnMkXW3dA8vT/u+Z+azH3w3bu9WWp+//dZspfeff1juv35E84eXb9/f33/1xU2O9IsPP//is6vD4XC/3Tsnm8PN/fa66ZpGmRgjM3ddd3hxO02T7eb9fF48NSKvLc6+8/abD777541xf/fv/Z1/8A//3u2L27b1RcKS7dOv+08//vzNt4PWNA7j5cVlkVJKOT99KOKsbe/vb/t+BIBpuvfenz5otrf36/V6u9+mkCrH73R9GqkvKVtrvfe73fM/+UlPNP2rv/Pnp81x/lxKAaIco9Z6eboExKpzapqGmQkgA7QzsASR4bCBQcNqATOCgWFzBwDwm7/5m++//16dwWhrnzx58uWXn4PVOWYAIKIQwna7jTFG5lm70tp3TXc4HJzqDDrOpMTst31KiRk4k2hVCqaUS0FnOuIewAKr1i6MahQOJaUUUmkLQ7VYAAoDkXFusVgN0yBAbTtDxH68maZJUHXdnEjv933dCIxrUBlB9N5ba1+icmJJxVoNANM0wZ/11e/Hi85prZUxGKTxbtF2p6tZszwiboio5HTYDVpr15i333zvww8/PDs7+/Xf+P7Nzc3V1dV6vX7v/ffaE51Surg468d9hmmzm6y13raQ25xzKSVWDH1KIpKZSxm7Lmlr0xEdUUgk5mgtMDO8zDqvDfMq9INQi1h4KXdHIpotZpoo51y8KKNSSn6GRpm+D5ooxphjXC0WSikCOAyD63B11uac9/upaSzPWkQ0xoyTlpeDz7r7AEARmYaorS0p1U1KRDyA97516uWswQJiyhkrP79qmV6qXKUcpwbGSUnl9v42TnHRdNbbnLMmjZWkh0fpTv1TVZiUUkKlUkp2e4+CvvXOuDhRrWSNUafr9ePLh4gYY5wvDTPrD37w8K233trtdn3fv/H22/fP7NK5Bw9en12sutWjqy8/3X75+f4+SHBOzcc9brebxYw12UbNzx93pZR+uw8h2MYuFrOZ1cYZeb05Hcc3z04Xl4+u2tl8v72+vb7PPHz01epkpkSdLs+tJYUKmKchqnQWD/ru6ZRSCmEsQ1MfPh4WKewuHpx9+sl1SXJ+ef7NV88Xi8U4jl9//fX77/vnz58fDoeHDy/vb+/lbUdm+PnPf+69/53f+Vff//b7+902y9QPxfjOeltKypGZGQ1rrUmroae2bas6qopJf/mLLIhQSuN9ndifLCgC3LwonOHRgwcphe98//W334TM8A9/7+bm6opIlyLG1CNFXgJhMjNHDmiabt6JMqbpvPdTZuPmDx+/nXMUwfPzU2utabpagCjTNPPlGRAANE0D5E3TNahUo4z3qJRyrkUEAF1vgK3XwFJKhswFkpQMoCpX0Vs/a+thor0lTcqYacjeCmdKMXIm72dGNTlnezwk/8WvmJlIx5wrTOrBarVuzHqmJ4BHjx6FEOo1+I033yAi55qbm292u51vfQjBentxcXFycjJrZ++//17fj+vl8u6t3eZu5307jiOKevL1fb/vpxg554pzMsZM+33MY0rJW7utXduciSikBKRQUCl31JMVjFPOx1R2gQnYM2Wq5x4VctqlUkpmAJiGabfbceb5cn75+qWzVpjX86UxqjGu9T5OA3buwYMHFX3hnKsGB0R8+myfQpimKZXCIeX66ZYSk5icp2kKKRhllFHOuFdndS3oEBHk6Misutfj+LP61EVERGsGA9v9Nkiw1s7aWa04lMGKElOIRyU8Sh2pVBF3zLEWkl3TNU2TG2Dg1vtSZLmen1+uASCk0DiDiPqv/9t/dT6f930f47Swj++W3cPLU2391c3dSbdavv7u7/30o7/yq3/+x3/8c6K2ab0zq3EcN5sx55yv883VlddaM7W6bVTKQI8uzlFG+OmH2x/uvrl8FL777esIy24tKAfub2/GpnO/+iu/koLsdruc42KxGrfcdWtEU0rWeiaiQihdM3/61dXhcBDBq+d38/nckt/dDUpcjOPd881wMW1v+91uP2/Wty/2nbtZnpQ0TfO2XXbdvGuG/e7Bxdl6ubzevliuu5wRUZWURAQVOqfqm15lJLXP/+Lqipm391tnTJX6/PJDk1Ky1r75xhvW+zCGu+fx7Tfts6fw8ceffvLJJ/P53Mw7rbXCAsIMYJwzzonImmZVUD1bLOqH3c3ny+X67MFZBUh561FhN18SgVKqJFwuzxGxlJQze29ns5XWWnuOMXrvu/n6KDVVSKRbv9CaXhWiJycXzBDCCEQnq5VzHZEOIVQTGKpmv++NcbX+77p5fRBrGNmfudRJ6/3YDzeTt3R5fvqtN17jOFDqtda/8Ru/gUpSKMYYbQmY2ln7G9//7cMwWGvfeKAHPmoHGODy8u3dALMWpgE2m8PJ6uLZs2ut9ebmZ9vtXkqpyh+lVNd1h8OhYvyNc0RU09rqIK3I8WZb34ECqJRyjWkaR1Tt+cciFgGVwmmY6qUAAKoutUpJz9957XS9PFmsSkjE7I1Zdh0inp6+Vru/0zS1bVt5PszQpyRScmaRMo5hv99v7u92u8MvfvGxlDJMw3AY6g185CAixeuXmsVXUGwQkVxKyZmIuP51AARQSsmcavf3qHVXiLk6nYtSqIxSCMIMJMxgDIok0jUslq2F3WEs0pB2FnSRYjVlYGvBWw3EWhulRBD0r/76d3a3ZTXPpPWiURePzro1fPnh3dU3X8auLWQHf17Avbi+ZXBts+KGnj//nJkuL9/c5xefffL0W2++bby9udp8fX972GzeeeudX3uD/B//cPvZs/6D99zlhSP9rUdvzFaLb/IhjGU9dpJxux0//sWnN7e7fnPvZov3v/uatXYaJte4aZoOw938VIUeMoBxZbHS3mPBHk1o5lgw+Rkl2Submg6t59lKD/HO7EwJBYsIowZtQGHB+9ttH8JqpbTWs9mMq+GcyBjzcLVwznVd17btNE1d143TNE3T8o3lcDgYZ2KMu92ua7rl5fLytfbZ0/6Pf/zjjz/9+Hf/3vzu7u6zzz6LcXrt0WuPTlallFh7ipkFpWKMNHmlsCR8WZrCYnZCoJwzmnw9yRGx9a5WghmzMcZan1LIOQPQbGadc9rCNE3WegLtnJMiR9OYaYxxOcdaxbXtyhhVB2xN09VfTtOklMk5zufLGMl7a61lzgCragf03iP+2W25iblwjuMIrPZ7uL2+T/0txe04n9rWcwbjlNZkra8c4tkKHpy19cmml095ZiCCkxkAALLf3AwLh+MurlattZbzUXNaHWNd12mtEW0ta633s9nscDigSH1DlVLVxAtElWyj0HAG0CxSUuJXmJfaRTuyYo/jw6aKav/m3/pbZ2cnb73xxu2TZ2malGCrtbf2wdm7L15cl1I2d5u6cTjrrNO6tYjKWk1aSyn7vt9tNvu+v73dAoC1WqGqgCpCOQxZo9PWokKJ8sqRycycczUdSSmpJAISopyzEhYjVTcRYyylEIGgFEwIguWonwGA2pkdDwNpYoAiiSzkPMU8FWwUQAmJTQZmyKyw5MQKhCADkv78Z4dpmirx81btYN59fZD7/a3W+rDdPdszXZz87t/+vd//r/6JgPLez5vl7e1d03UhlAevvbboPj2/fLS/ux/u7wwaSWp7u/3kBN8mvDifL3/wA/Nrv/LRjz/6xf29HbO2/TRNz57cbm/HaSjffHVze33vrf/N//Y7F2dn2tqx71GpTz766Iuvd1lsVol8FLf3S9Z6GuV6dkKvf2st2S5PTNd541c554uL9flFt9/vl82SGc7Ozrpm3u/Dzc0OhBbz+c1uEycoJStOuWTntXMKSAPAFKP3vrb9F6vZybDe7nbe2pRSbQtZ6997991vveMB4Pr29g//2T9TRr3xxhthDLvd7vT09OHDh/f39/v9vh9HKWUMoQKq51335rd+IwPkHBFRI5YozpmY0tRHANKaBAQRiKgwc2ESH1IQlJRQk0OlSio56wwTA2hvDWdBlSGTMdZaTKl2r733wJQ5ApP3rTEmx1xb0MDUzJpxBO99GBXUgRpD7QwddmPTOHT0Zy51YtDWg9Waedz3G3+nYt9Z1bZeKRPjuGyWRBSnGk7kpgPMVjAxtASWAACGDDN97GsODM52Ts/Wq8ub603j59qYWu/UkqfegJxzIQwxx8xsra64SwDwxjh3tDlW62sGrhd5bTVpIlQAUKBAPQKrFtYQcz7shqZz1voY4+Fw2OFk81BUOcSBS1AFq4VGwvXT58+BebPdAQAhusYrpQKMuZRaY1eXZQ2I2O/3SqGmhW991V+FkKZhaPSSiJioUrTqEB6OjGettWYRTIhaaaVyzsbUNwErjq5SbpRRIAmqSO6lFrBCYEsplbQNDPVCx8woCJyZo0gSYaDMnKstH1GBAP7+P/28lkkvDY8REbfb7e3tbd/3Mcb5fP6f/qe/66ytbWoAEGARkQJnZxfOuTdff/yLX/zi7uoZSiHSjULTjIvZ7OHj1x8+fIgF7+/3WuvT9Wl/dvbJZ598/OHHyiirrbZ2vV6nFFbNRX30S5FxHLfb+5ubm91uN+7l/v7+8vLy6uZGa904d7fZzNp2tZJx7GezxfX1tVLqX/srf+Xd997OObNMjfda67ZpDofh9u5Ga9u0frif1qenjXO1QQoAiKrrml9dnGymoV3MLt5e3NzC6nWIGT79eKI8AVBt763PwbdABDnDH/3Bz/7wD/9wd5iabs1oxgmTiLV+e3g2jmPO+fb6tmrvuqZ79OjRtz749aurq0ePXqszsPl8vtvtEHF5uRz3khJq0Dc3d4tVi6a4BmVvEI+N6HoO1LkJWXCmSSXkyNZrOKogRUlTTV0ihUC7xoQx5ZxzhNmiZZgKjt57yPqwyyI4a5kjkaYpZqWawzSgKFEKiP+b6/z/z9diYbWGrusuL9fLpgMAVImIZi0sZrM6uP3gu/NhOB7mGiAD1JTTgYFe6oL/8T98+h/+h//b58+fa00A8Bf/4l98771v7Xf7//xv/p8ePn5coeBGmS+++qJqhPksG+fmXQcA2/2+lHJ5efnw8vKLL55u77dG4aqdFZE4HB49enTz/Ord1x/axeKnv/zkyyfPQOvOdOtu2W+322spItVDklIax7FmIclLFaq8Sm5FBADr7XGAJ8cjunbI+kNWmjrXeE8iMptZo1QY+wdvnADzFKNRppQym80AmJlDcEqUJj9zngE2Y4oysUkQTKVK3N3drVaL5XypjDLGzWdTlYFKqaJm9NZ3825//2Q4REQsRYlgHDIzvPbaa4cJD0M/jmPTuG9/591PP/0wM3vvTVppr/Uf/MFPlMEqM35x/awkaduWIVc1IgCMo3zrO9896pCoxvTk2jid4iBYxjAqo8BayTGXOIkgxH0Y1d1VzWbb7DZSsGu6h7/xrxzuJynGN+3J6dn5+el6fYqIVbVdRUo5c0nnKb+dc06xbO/3y+Xy7v4GhOo+6htbprTbbpq2Oz+7SLkY67bbkQjmS6UMCpTEMfGUORJAYjo5W7atBiiG2HvfeB9DGsbd05tftsvFycP3/GJBh8O+b7qlevd7vtW+/tv1f+2Mg/OHj3/zL3qF2Pfh5u6ulvfTNN3ecUrFOT9M0+XlQ2vta49ea9v2008/v7+/f/PNtwFgu32aUrq5uYkxfnf5Qdt2X376JI3y8acfKyNNZ1br9o3LD548+frZsxeVVbJarc4vz2+vb4sco6keP37cNM2LFy9yzt77EszqZGWtvrm5qb3iHPnh40siczgclAuZ437bL1YLY9q7m001nHDQAGCaBgOy5JJF2z/7VP//9dX3I1EOYRQJ02wmItO0OxyGZYu1O/3/rezMeiPLjvwecfZ7b+5MkkXW2vumlqCRMTZsacbWywBjwA/6hoa/gd8kY2CPZNijGUmt1kjdUi+s7upqsopLZjIz73aWCD+cTEqyRgZ8n8gCi8l771niRPzj9x8MB08/x/v3H8YYlRIG6eDwwJWibznFdLtadl03HI8Xi4UQwjkjQLiynEwm8/n88PDw29/5Tq6MaKlzOjpxAiJ88DLGejgUUkq0WyXMaLTdtOvp0DjBBCxtrxCLsT14POSqv2pvBpzssTydHqWE4ElwQ+0aYIjMxJyYswCWUwp7T/I/1Kjl2R76cCd9F3/gJ5soxB4F+AgoUeq+KEbOjIsDmxkbQoCKMRaFDIEAxI2ktg6rxq99AwCeonI0LGSIJDEa2Trda9EZ6ay1RYFCclFppZBQhEAAbK10RvlCZtJx2/Zt3Q9GxWQyf/z48fnLjVjwaFQeHI/v3z8B8H1qN5vN4vJl2vTq4999SURCSqVU2zTMbG3PADGF3CpozObowVuw74XOjyP3yqW4RGQ5kNPDUTmwWksppdW6qHqllNVV6Uwf+NRHAEC019sYgq4Gh0rKrhM3N+1icaGlfPBogrC3uURQWtmi0Fo6a3zvbVGcNnNjTIgJmBBQpmKxWOQSZQi9UiqEVBRWwHK3P0WCSBSjJ+CQDk8LxFZKCSC0DsTpevHi7LMz3VyrUdWurh7031RVVUyrQkC3/wUEEPOZU+y+9RSl1oWVjOlEj4uq2Gw2VxcXXy8qqeVkNPn6q69P750WVfHuO+8i4vlFI8Tm6OjearVq6+CM6NvUBx9CmE4HeTC9eHHpYzOZlUzTV++r6+vF+fl5zh1Iiaenp+fn51Jz2/bed5PJJKV0dnYWQrDW9m166623jDO/+93HuQxT1/VfwF9MRke//uiXfdiklLque+edd8bD4w/++UOnur5PzpWHB8dPXn9bSpRSW2NyretPr30h+f++tNVAHCO1bWuE6Pv+2bOzZ198cTie1puaIJ6env7yg1/++//w/bOzzwDgP/7t91zhhqOhB5RKEsHV1dWnn36eYjw8Hg8mjiIZZ4SBztfjyWhSDpbL5aCohsOhMsaAGIxGR0fzy+bZZrNJKSkW0/KhMAoRfegGB6p2deM9SozKGOdUOQq63njfR4BqfHQw6NrUXF8qH2XaxcD5BpUQohR3eZO7mhbsURCIGFLaHbb3TyD/lHFCaikla8FKgXLRVjgajV24OCods0opEXDpIATQWk8P3Bfnq2V/0/qMuOwLnzDhvcG9w8PDb779jWpYHR0dla5kTlLK3hbZRi16n8PG4XishND6VYrCOdf3yTcRJXJibe1gNlutpkKQMlAOxMnDA2Hg5mrZ828636lqei9GyhndaiJzvjBHNZ7apt9uev/lz38DAFpK44xzzmqbZWpu3G42m/PrF6ubm67rNEqjRFmWUoY8SigKZkxhpwr65IsUYzw4nGZhkJQ6xjgcVmeffZEPbEACEZXZYWfKkYI9QLKqiryVcWJn+qbpSKiqqtxgFGNk6d1gXCnpSoeMSilji5B2yoTZbJKhWjGG1WrDnNq+VgYUDDd92n75Ig2mJw9fO3qEBNCsYT4BJSACxAgxv14CAJhPjMZWgFKijGVZVEMCs1z2TkeOkgJItIvLFcqNBDsYlEKI8+cvfvaPv7i8vF6tFoeHh13XrVa3Z59/1t4m8lFr19ctiNRu67Z2Su3KJ0JAXW/avrfW1m2t487ZY5/jUcZgjBRSawttjGz72hiVUrpZvozUee/Pz5+z6KXE5XL56NGjozmuFqtBSV3Xdd6PJiNlBLPMI/7/9wp9UCoBCIm6LEstJQDcrm/HxXh5uwGi01P19Oyr7/0Vv7y4YeaqKqSS8wkMRuAEnt4/1Eb/9Kf/oCW+9947RVURxeyUcr24jLGbHkyLorh3em8ymXgfn37++WBQvvXWW83Ptxxl0/mDg+lkNFoul4vFwojJyLuJPmqVDMgXNzeLy75ftus11DDkBStl9HgYVk393EgvuB4T7bZoEELnwzPQXXvMnwbwKiXce8L/0YMoO5ubEyQbpYTI+T8sYpgNFDO2bRsjORERukKh7uvLbmFTLWw1m0xKNTSx06ltwm1oRVI+tU2zJt8oil5rfcUWEa9eXu2PaeyM22w2s4mBncExjcdja21IYVxN151YLK6VUiBoubkKoVdKXFy8nJ7Yvo9Kubna314+yhIBanByCMrromv7vudtCqkLYXPbwm2dNaoppWK0qeuWovfRg6ecYyiNI/DMnP0fJUopDCOmnpswijH6SCEFioQSQx8Gg0G7TFrrXBMCIeTeGXMyNxnTl7VTfR/yhJ/NXJ72RVE4ZzKrbDAYWHVbVZV1djgcMjOQttqx5i6KSEYbawx0fhVDODqdP37tnTcqDCn5SOPp1FZF1g/PJwDZMA7AKKA/6DQYqNG0GqLFj35z9cnZc5+ub5b95fUytM16u96ut97H58/PYqCPP/7d0dHRk9feXS6XP/nJT1ar1f3794lotVo9f/6cabO6WM/np85IATQYlCG1tJep+uibpqvrtms6oojMXdfkfomstTRGEQkpabXqUgreU9+3zIaIQkiI2PktUawGrqj0druSmpUxRaWF7IUCgJg4SJkicfAe/+gW//j6M/+cq1aZc5clurPJ5GB2MBq5urZKqcPD6fxwMptNDg6nADSbza2xiwYun7fzo8I4GI1Hb7399tfPv9Bkcx5ECZGbmkrnrJRuNLDajodDIvhgcf3hBz9/+vnT//SDf/PRR8sxy9feOHHOzW7VO+JkNp+Y7UxXhVLq6ddXP/zJ3z8/e9qnhIj6aOI7LxSJ2Pptu1156aNkEcJOMoRZkCMEMmd+YZ5RuyIC77g9es+fudvYBQAidqllxcwABJEihyAI2r7u256aqLUuUCejLGqmIAMOQBwpwxNbHZ7M7x1VkuVmqcg3g4m1VkpNFNu2Xd5crVarlNJFrwHg5moJQNWwKl0plLi5ukHuh8Oi7wMivvHGa4fHB6PJ5F9955s3S/mjH/1Ian18dLRaL4bD4cPHD2ez+fQ+Nn6rzi+3iDvYZS4RcTYPQsvCSFsp7o5O55z5O5l5kDISmE21TonJ5+olW5Rd12mpSeyGiUhKSq2MEaQQsQ16cb24urpql0sAkCBQygix89wnL7p4N5jyIz6/TFn8nCd2jN4oRxCPjlSWW2itlVG5g89aa6vknAMAawulBBEVRQEAT8+utNVZFt62iQi0HZ0cP1qObp0xnFIr5bLzq/Ptbk1pxO8XeMrwACER622QKNve/8NPz3710SelmwTUy+Xy299+WN6Wm2rz5ttvXl3dKKXW69XR0ZFSk/ff/zYn3sw2xyfHpRscze9pWdiyjz1ZW0jAk5OT6cGw69aDqfO+c86UrnTOzeezsizrulXKNNvtXgIAOQWdH0g1LFAyQVRKZd+YqiqUEVbtkOyRuBw5rXWMXkqUcifDzjkR2NuSUv8vT+k/d5Wlk5gSM0GMMZauvHd6L3GaDuzhvelkMnrvG+8pC3/1/b988vpp/i9E9PlHV19+9dXj9ePF4jqk9OjRI+B2tVrXbT0aueFwmFUiw/EYjseL6+uzs89Xl+ePHz8eV8XBdKwgHs3e/qfN5977F8+2z57/tq3rBw8evbxo781a3kpG2ccwneq33jiJQMaY8/Vizb2P9Xqz8U0MqpECkJQilVPiMYMJAVKGeUmZQff53MKwWwVjjHfjgXaICBRCIOvQIypgTNCDlMhKtnUIWHTgXDWbTiZFUYyHwxCC1LrouuNXwxYMuIFRKoU+jleKuiusmu12ebNcLBbXi8Xi+rrtey3lZbPromfm6IU6LEPdb7ceYs9BM8fhcHg0P3346P5kNHny5MmT181v/vmVd7/x5ttvvvrf/u6/X1x8tbheffXVxbMXbV3XalNz7pUnACnBkQghCJXbsVkp0XZUDgRkkZ5IkBgVISIySiXLSjfbRktMiStrreu11ig1AHCQzDKLfBgQUB4daURe3l5pK621cteOm9RxPvrTDvHLnKGIglSM0TpJfRTKC0GMLQJsu7h7+iRijHfsHlAiG6RpraWUiJjF0hatUhm9orOp3enp6vHjVjjnnGu6TkodMCHKtm2dM9zvYOxZiUUQKYJQQKGI3sfQX1x82azbJ0+mA6OkU8++eNZ13jnTNXE6niplSjcoimJT0yuPX9Nah5Az/+qVx2+9/jqWZde3PCgnoeXp96a2kpE6WyDA+L333n/8+BVb2BRSZid861vv+9hlMd9sNpFS5t44KeXJybG1mogePDxKxEwpxmitlELPj2a93ygjDg8PbCnbfqOUIIrGKmDFnAi8AGecsNaG/l8+q/+5iwiEYiZm5hCCHMrj45PpdDo/EIg8nU5ff2386JV7j07wzTdfiwBPf7sWQixWq8uXV48ePAghtF1HkYbjqu1rlG5+NB9Ww7qu27Yl8JPBQEv54vIFJ1ZKPX78+OT+yXq9/s0HL9YvBYD7uvNPP98sbhZPf7vZ1g3a2xhjYh4PhymlYljl8TMdDyXystts6poIqBUEVCFm3wUWgkNIzLinSudOkT8N4EMIu3aXfQCfu0oUO0gAgISJOSnQknW7CV9LuX26VOrWGEdERWHrus1LSdNE7yExbn3s+5bAKwPXC0+RMrshhFTXIfRJqAzSIGsL5gQD49Rou7puN2lcjXwHANJbqDch1NiI7tPfPS3dWycHD5waXl/VWlYPTl+dHowPpicvnl//9Lf/WzGolLtiQDSbjsrku5g7XQHAlabvIHB7l5C7y0MKhe22O5CaGYkUMhEoohAJ2jpSBCGIKPVtaJouBZZS4nXdt/2L60WMEaUk71HKvu9ns51RhjJCSpW7nYgIU9E03WBg5TYoBTFCClFqTL2MgYQQxihGTgmklBGoTUhCRp/6lG200rqJMUboTC6r5FgAAH75q2fD8ceweE0Zt1g3UYgOALTc9K0yzoQ2c7gzly/t260bTsSbe3M3UX5Q1gMVx0OW3Cy3pXFqNpttNpvJZNR1XZYDAVgA0TRdUdgQQtd1g8Gg7wMAKaVvbm58Q8fHx4FbowxA2G63w2E1HFYAImcc+76fzWa6kM65TDs0xnx7+i0ASCl13XY4HALA0dFRUVgi8N6PRqOm8VX1r6uJlMjr7dbaApJ5732YjIQQposddTCejrvON03ysfuzkfr/6xJKcBYatnUtR84Yt+0vtLYky5eL7t6x+3rhDycmErz29qhZg5baGDM7mB/fOwm+l1prVyxvl6v16uXFy/N03jSNtXY4HEIkUGJ5dfPJZ5/9/IOfpxDu33+4XC4v150e6uFweHgwfvcvv6+UyhjP1aVOKTXbLcXuxcuXpVH9ZtO27XJV696ItYK6BaGoi8266SSrsiWtETEXselO4kJEe/AL7Fj9KAC01pnWSbRjq+XU0nbrGVmykoiUGLQIPa+3TVfYr5cr3zUEIoV+T7OnTgjyEDshpQIhIhNXCSWXqeh9LyL0EVKCphExSpWUU9L71moFLKtifDA9vl22QCtMKLWejGbCwPn5ZU7u/PrXvyb62Gr7q199VDebb7z/7nf/+t/NjnFg4NOP4X/9+EOlbHv39sZKAnSmym5VQmpE9uVErQIDZv4xZu1uJKI+aRosFiBEEUAgYueBuQQPHSdA4EREIWmGoUbmCKBTo4f0jffvxehTCkBdSB2npCTmYlIIgVOKuR0AkerSIaZNW4CAEBQzKmZgNXR5dCL3RQFEmPNmE7ApJdIyi8nQoJQsCrl0EQAUQYwQ+ghRMYrb2/arlwzQgVBACCJrEsoA0Kqs9UIABAbA/K20TQKlbjZ0q2Q1FJdrX029rvhbp52McnnxJQix7G6llMFopdRyyUopJcRynbJld9yujXPz08efffbJ1dXVbDJjrhVAV3fIzLGt3JQRY/QMHLqtD+Hg4HDoIHEtRaRI3DV5UxJaiEa9+OSZcWY+m8sekVGRWX51ZYQbKSc3kpmrIFOdANKjyZG1ljm1qbcT6y+3WkrTeh04ESCiRIR9JSkPdEUC9yHrrvKSUuJ0NJXZz1AlYwSAxIypePJkopV2jTJSigG8MjMAu2XEKXhlZuBKfPrD/+qckik12+1f/83fqM+evfjwQ+OcRH25WAglyrJ8AcI3zXq9JoKw9cz85adPI9HtxRUzkhKSJShjnCtshdbOj+5prQtrrbWnD+elc9Y+zuATyCG6EEJA34fNZrOp65vNTTbOWS6X1uoYY0q8Wq9C0PuG6JRNZlNKkUjqhLv+NEqYiEAyiihSqpVSJESM5L3fesqUHsGmGJR2WPnOAwyttYzct/1Qy12fS+Ido44VMzOgsZqZpUyEIAsdAgCAckqxUqWI0d9srgbLwaPXH3z3+//2o6+ebrfN6aNHr77+qu+6//HjHy9vbn7wgx/M5vNxVf39D//uo08/fOXV09EBlgYiwEbdjh86lW8tTxVFvy8kM6JgIUREwhBjjmYEIu9OsMTMgHL/w8yw80uAOwsrKeWdSSIAAEwGp0AxhIDQ047QToioBKS0A8LmXoIcPzS3t7xnXzMzIqQAjLCu17sPymghsfvcvtvuhJO4t8VCH4gGA0ckgARFAS6jRa1SqvE76xzc+XtxRuKr7Nex9wkBAICEGOWcBQiNUluhDJgySs1CeMEHpa3G4/GdD0QIgSiaYwkAjKlrvI8SAJxx1lrkpLUsCmuMQkzRxxDalLjrOoo+ZxkZueu8EsJq3TQUY/YMp2yNppRRSrVt6EOPyF3XYL97Sl3XuIkTioAzM8lHSEIAgmx8UEqVA1MOiu02MZOTSinp631imYgB7uiFCL8P4lAjMmKSMqWQGqnBFtYYV5RWF1IpgYyL1Sr7De62fZUpkUAQyXfb9WJ1eR2bzhFwYu+bs//8X7bbZrvdmjJ2FJerpTKm6PvOFn3bku/6tk8hIbJMTETGKQ8CiFof+22TmANLKeU//uwXOXGjpSQAJURO8eaWWKu1ccYZp61WQjGidFoZzIq08XBsnDHKtH1r1SDn5ASAlPKu+OZTvW8WSDHGXWudELfLJUXK3TUhBN95ADBu10bJiXdt5DurxpgBz5k2w/vfRpEEuBgjMoMQKYVm2+TSGuoU444qBQTIKYXQt626rScUZymN2p4Z3hwfXPZB3CxbKXFT3x+Vkzdff1Q6f7Zal46I8J9+9l0pFIFCubcKCyjEfqIycIKUgJmF0pDd5wBzGLOj7e4pnLv5vZ+WuRV+b2a6s9ESAlAyk1AOOUiFhJoVCKlYAhJTFoXD3R6CKF/Z/n6dyGl/ZmTerH0kytC8nVlBSAA0x0JrqbUWQqTEIfRd14WQbjcrEAKSkChZSa21Rq+1fvXJEsReUA3AnFJIBJTH6N1Gt/9wimxz94EQQsgECqQEANGnpFLoU1ApyNzYAEAA1bjIS8ZwvCvV5AMhgS8KK+VsNpuNx+Mc0WSH3Rij9z7vmVkvba1NKZ8kISVmTiEE76PvYkqtEBGEYgyc86AorJXXly/yOCaC7CSVb4eAtLbDqtJa3tzceN/lAkcbdm8KKIdyUmoUQgTOPp7EzPmLFBJR7KqQbQxzL1dGjocUlGrzMpe5jEoprSWAiNApY0rnBkrJ0q2bplmvu6a7eHkxGk10YW9TW2/qnrxm3VI07YZ8FACFtWBBJsaQQkpb7jhgSKkPqe8ZlCmKoioK1EXbtm3ng8LBoJRSt75r19uUktbWOQMA3vvcOCwlCpeNGTCEvqgqZ4wyxnd+WExh73ufV45caz84GOdZut9y8i4m5/N5tv0pnQMhsi+Vcy47czNzNt26y/8BQaaPSymROWZjzRhF1CilM0Yp1bTN+cXF+fn5er1O/a0CcM5FZQqjQl2/3DbNel2uVjHGbaQvL14qpex2O2q61W8/+erDDwxRGWEAcLb6n4sPf1FUQ6nl6MXLqumUUe5uB4vo73bRPL32GmNzR67Mk3a/6gMTMDAAAAMiYhZySgmwbyvez14iaGsEUEoooQBlEoISMkRuvQcQQCK73gkhEFCgAJlyQZuZWTILRmYgKCcmL0liP1N3eRXv8zvI8tK+7du+9d67yyb/5vyCBRhjlJb6+FAIUMYprTWi5D3AJNvfCiWstdnhEIhCSp+8XIfAzZp840PfcWoT9oD+xfJMbZS+2dULMwAPEfvPMH9xRw/Jb/ztN5+0XSuECNy2/Y79LI2WIEIKUnOhdUiQ7y6Efjg83Dd4UEihbVuiNhJND8bFsMjZOyUEZgPzlIB28JMQQtM0dV3nOpaUmHMQUqMQkSi60jFjqdVdLMbMzJGIYuSyLIkYCTPC0CJHQoqiKJRfrTbtGlooy9IY0+98f7vcZZkHSQabMaIZOYfsKV43vttuN8vb1Wrlu6YcjPqiYCXW26YmkKaUxngAEfNSCUIIZFQKhFCaCKuKA9+2PWw7CiFGkJEwklIGoN+h76XOhiIhMeQ/gJGZI8HO9CvC0FkEJKS8GwOAitH72Cy+/EP/rDuAzNlnPeWVFCgkBgCjBIFAq/O5TGotcXdszPYBmCN5EHmNZkQBwhZWgJAS91vLbrwpcMycm/NijJvNZrte++jnA2mE1lrEKABSW9+2bVsvXx6w7rru9vY2xqiEMMbFGNerVScA+4BGDZxtL/s2xnE1HA8HVwoGk9H/AfoqaS58RT4RAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display fully pre-processed image.\n",
+ "transformed_img = transform_image(img_array)\n",
+ "PIL.Image.fromarray(transformed_img.eval(session=session))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Resize transformed image to a 256x256px square image, ready for training.\n",
+ "def resize_image(image):\n",
+ " image = tf.image.resize(image, size=(256, 256), preserve_aspect_ratio=False)\n",
+ " image = tf.cast(image, tf.uint8)\n",
+ " return image"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display resized image.\n",
+ "PIL.Image.fromarray(resize_image(transformed_img).eval(session=session))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "tf1",
+ "language": "python",
+ "name": "tf1"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15+"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v1/notebooks/5_DataManagement/load_data.ipynb b/tensorflow_v1/notebooks/5_DataManagement/load_data.ipynb
new file mode 100644
index 00000000..c71e76a0
--- /dev/null
+++ b/tensorflow_v1/notebooks/5_DataManagement/load_data.ipynb
@@ -0,0 +1,577 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Load and parse data with TensorFlow\n",
+ "\n",
+ "A TensorFlow example to build input pipelines for loading data efficiently.\n",
+ "\n",
+ "\n",
+ "- Numpy Arrays\n",
+ "- Images\n",
+ "- CSV file\n",
+ "- Custom data from a Generator\n",
+ "\n",
+ "For more information about creating and loading TensorFlow's `TFRecords` data format, see: [tfrecords.ipynb](tfrecords.ipynb)\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import numpy as np\n",
+ "import random\n",
+ "import requests\n",
+ "import string\n",
+ "import tarfile\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load Numpy Arrays\n",
+ "\n",
+ "Build a data pipeline over numpy arrays."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create a toy dataset (even and odd numbers, with respective labels of 0 and 1).\n",
+ "evens = np.arange(0, 100, step=2, dtype=np.int32)\n",
+ "evens_label = np.zeros(50, dtype=np.int32)\n",
+ "odds = np.arange(1, 100, step=2, dtype=np.int32)\n",
+ "odds_label = np.ones(50, dtype=np.int32)\n",
+ "# Concatenate arrays\n",
+ "features = np.concatenate([evens, odds])\n",
+ "labels = np.concatenate([evens_label, odds_label])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with tf.Graph().as_default():\n",
+ " # Create TF session.\n",
+ " sess = tf.Session()\n",
+ " \n",
+ " # Slice the numpy arrays (each row becoming a record).\n",
+ " data = tf.data.Dataset.from_tensor_slices((features, labels))\n",
+ " # Refill data indefinitely. \n",
+ " data = data.repeat()\n",
+ " # Shuffle data.\n",
+ " data = data.shuffle(buffer_size=100)\n",
+ " # Batch data (aggregate records together).\n",
+ " data = data.batch(batch_size=4)\n",
+ " # Prefetch batch (pre-load batch for faster consumption).\n",
+ " data = data.prefetch(buffer_size=1)\n",
+ " \n",
+ " # Create an iterator over the dataset.\n",
+ " iterator = data.make_initializable_iterator()\n",
+ " # Initialize the iterator.\n",
+ " sess.run(iterator.initializer)\n",
+ "\n",
+ " # Get next data batch.\n",
+ " d = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[82 58 80 23] [0 0 0 1]\n",
+ "[16 91 74 96] [0 1 0 0]\n",
+ "[ 4 17 32 34] [0 1 0 0]\n",
+ "[16 8 77 21] [0 0 1 1]\n",
+ "[20 99 48 18] [0 1 0 0]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Display data.\n",
+ "for i in range(5):\n",
+ " x, y = sess.run(d)\n",
+ " print(x, y)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load CSV files\n",
+ "\n",
+ "Build a data pipeline from features stored in a CSV file. For this example, Titanic dataset will be used as a toy dataset stored in CSV format."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Titanic Dataset\n",
+ "\n",
+ "\n",
+ "\n",
+ "survived|pclass|name|sex|age|sibsp|parch|ticket|fare\n",
+ "--------|------|----|---|---|-----|-----|------|----\n",
+ "1|1|\"Allen, Miss. Elisabeth Walton\"|female|29|0|0|24160|211.3375\n",
+ "1|1|\"Allison, Master. Hudson Trevor\"|male|0.9167|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Miss. Helen Loraine\"|female|2|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Mr. Hudson Joshua Creighton\"|male|30|1|2|113781|151.5500\n",
+ "...|...|...|...|...|...|...|...|..."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download Titanic dataset (in csv format).\n",
+ "d = requests.get(\"https://raw.githubusercontent.com/tflearn/tflearn.github.io/master/resources/titanic_dataset.csv\")\n",
+ "with open(\"titanic_dataset.csv\", \"wb\") as f:\n",
+ " f.write(d.content)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load Titanic dataset.\n",
+ "# Original features: survived,pclass,name,sex,age,sibsp,parch,ticket,fare\n",
+ "# Select specific columns: survived,pclass,name,sex,age,fare\n",
+ "column_to_use = [0, 1, 2, 3, 4, 8]\n",
+ "record_defaults = [tf.int32, tf.int32, tf.string, tf.string, tf.float32, tf.float32]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with tf.Graph().as_default():\n",
+ " # Create TF session.\n",
+ " sess = tf.Session()\n",
+ " \n",
+ " # Load the whole dataset file, and slice each line.\n",
+ " data = tf.data.experimental.CsvDataset(\"titanic_dataset.csv\", record_defaults, header=True, select_cols=column_to_use)\n",
+ " # Refill data indefinitely. \n",
+ " data = data.repeat()\n",
+ " # Shuffle data.\n",
+ " data = data.shuffle(buffer_size=1000)\n",
+ " # Batch data (aggregate records together).\n",
+ " data = data.batch(batch_size=2)\n",
+ " # Prefetch batch (pre-load batch for faster consumption).\n",
+ " data = data.prefetch(buffer_size=1)\n",
+ " \n",
+ " # Create an iterator over the dataset.\n",
+ " iterator = data.make_initializable_iterator()\n",
+ " # Initialize the iterator.\n",
+ " sess.run(iterator.initializer)\n",
+ "\n",
+ " # Get next data batch.\n",
+ " d = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[1 0]\n",
+ "[3 1]\n",
+ "['Lam, Mr. Ali' 'Widener, Mr. Harry Elkins']\n",
+ "['male' 'male']\n",
+ "[ 0. 27.]\n",
+ "[ 56.4958 211.5 ]\n",
+ "\n",
+ "[0 1]\n",
+ "[1 1]\n",
+ "['Baumann, Mr. John D' 'Daly, Mr. Peter Denis ']\n",
+ "['male' 'male']\n",
+ "[ 0. 51.]\n",
+ "[25.925 26.55 ]\n",
+ "\n",
+ "[0 1]\n",
+ "[3 1]\n",
+ "['Assam, Mr. Ali' 'Newell, Miss. Madeleine']\n",
+ "['male' 'female']\n",
+ "[23. 31.]\n",
+ "[ 7.05 113.275]\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Display data.\n",
+ "for i in range(3):\n",
+ " survived, pclass, name, sex, age, fare = sess.run(d)\n",
+ " print(survived)\n",
+ " print(pclass)\n",
+ " print(name)\n",
+ " print(sex)\n",
+ " print(age)\n",
+ " print(fare)\n",
+ " print(\"\")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load Images\n",
+ "\n",
+ "Build a data pipeline by loading images from disk. For this example, Oxford Flowers dataset will be used."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download Oxford 17 flowers dataset.\n",
+ "d = requests.get(\"http://www.robots.ox.ac.uk/~vgg/data/flowers/17/17flowers.tgz\")\n",
+ "with open(\"17flowers.tgz\", \"wb\") as f:\n",
+ " f.write(d.content)\n",
+ "# Extract archive.\n",
+ "with tarfile.open(\"17flowers.tgz\") as t:\n",
+ " t.extractall()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create a file to list all images path and their corresponding label.\n",
+ "with open('jpg/dataset.csv', 'w') as f:\n",
+ " c = 0\n",
+ " for i in range(1360):\n",
+ " f.write(\"jpg/image_%04i.jpg,%i\\n\" % (i+1, c))\n",
+ " if (i+1) % 80 == 0:\n",
+ " c += 1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with tf.Graph().as_default():\n",
+ " \n",
+ " # Load Images.\n",
+ " with open(\"jpg/dataset.csv\") as f:\n",
+ " dataset_file = f.read().splitlines()\n",
+ " \n",
+ " # Create TF session.\n",
+ " sess = tf.Session()\n",
+ "\n",
+ " # Load the whole dataset file, and slice each line.\n",
+ " data = tf.data.Dataset.from_tensor_slices(dataset_file)\n",
+ " # Refill data indefinitely.\n",
+ " data = data.repeat()\n",
+ " # Shuffle data.\n",
+ " data = data.shuffle(buffer_size=1000)\n",
+ "\n",
+ " # Load and pre-process images.\n",
+ " def load_image(path):\n",
+ " # Read image from path.\n",
+ " image = tf.io.read_file(path)\n",
+ " # Decode the jpeg image to array [0, 255].\n",
+ " image = tf.image.decode_jpeg(image)\n",
+ " # Resize images to a common size of 256x256.\n",
+ " image = tf.image.resize(image, [256, 256])\n",
+ " # Rescale values to [-1, 1].\n",
+ " image = 1. - image / 127.5\n",
+ " return image\n",
+ " # Decode each line from the dataset file.\n",
+ " def parse_records(line):\n",
+ " # File is in csv format: \"image_path,label_id\".\n",
+ " # TensorFlow requires a default value, but it will never be used.\n",
+ " image_path, image_label = tf.io.decode_csv(line, [\"\", 0])\n",
+ " # Apply the function to load images.\n",
+ " image = load_image(image_path)\n",
+ " return image, image_label\n",
+ " # Use 'map' to apply the above functions in parallel.\n",
+ " data = data.map(parse_records, num_parallel_calls=4)\n",
+ "\n",
+ " # Batch data (aggregate images-array together).\n",
+ " data = data.batch(batch_size=2)\n",
+ " # Prefetch batch (pre-load batch for faster consumption).\n",
+ " data = data.prefetch(buffer_size=1)\n",
+ " \n",
+ " # Create an iterator over the dataset.\n",
+ " iterator = data.make_initializable_iterator()\n",
+ " # Initialize the iterator.\n",
+ " sess.run(iterator.initializer)\n",
+ "\n",
+ " # Get next data batch.\n",
+ " d = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[[[[ 0.1294117 0.05098033 0.46666664]\n",
+ " [ 0.1368872 0.05098033 0.48909312]\n",
+ " [ 0.0931372 0.0068627 0.46029407]\n",
+ " ...\n",
+ " [ 0.23480386 0.0522058 0.6102941 ]\n",
+ " [ 0.12696075 -0.05416667 0.38063723]\n",
+ " [-0.10024512 -0.28848052 0.10367644]]\n",
+ "\n",
+ " [[ 0.04120708 -0.06118262 0.36256123]\n",
+ " [ 0.08009624 -0.02229345 0.41640145]\n",
+ " [ 0.06797445 -0.04132879 0.41923058]\n",
+ " ...\n",
+ " [ 0.2495715 0.06697345 0.6251221 ]\n",
+ " [ 0.12058818 -0.06094813 0.37577546]\n",
+ " [-0.05184889 -0.24009418 0.16777915]]\n",
+ "\n",
+ " [[-0.09234071 -0.22738981 0.20484066]\n",
+ " [-0.03100491 -0.17312062 0.2811274 ]\n",
+ " [ 0.01051998 -0.13237214 0.3376838 ]\n",
+ " ...\n",
+ " [ 0.27787983 0.07494056 0.64203525]\n",
+ " [ 0.11533964 -0.09005249 0.3869906 ]\n",
+ " [-0.02704227 -0.23958337 0.19454747]]\n",
+ "\n",
+ " ...\n",
+ "\n",
+ " [[ 0.07913595 -0.13069856 0.29874384]\n",
+ " [ 0.10140878 -0.09445572 0.35912937]\n",
+ " [ 0.08869672 -0.08415675 0.41446364]\n",
+ " ...\n",
+ " [ 0.25821072 0.22463232 0.69197303]\n",
+ " [ 0.31636214 0.25750512 0.79362744]\n",
+ " [ 0.09552741 0.01709598 0.57395875]]\n",
+ "\n",
+ " [[ 0.09019601 -0.12156868 0.3098039 ]\n",
+ " [ 0.17446858 -0.02271283 0.43218917]\n",
+ " [ 0.06583172 -0.10818791 0.39230233]\n",
+ " ...\n",
+ " [ 0.27021956 0.23664117 0.70269513]\n",
+ " [ 0.19560927 0.1385014 0.6740407 ]\n",
+ " [ 0.04364848 -0.03478289 0.5220798 ]]\n",
+ "\n",
+ " [[ 0.02830875 -0.18345594 0.24791664]\n",
+ " [ 0.12937105 -0.06781042 0.38709164]\n",
+ " [ 0.01120263 -0.162817 0.33767325]\n",
+ " ...\n",
+ " [ 0.25989532 0.22631687 0.69237083]\n",
+ " [ 0.1200884 0.06298059 0.5985198 ]\n",
+ " [ 0.05961001 -0.01882136 0.53804135]]]\n",
+ "\n",
+ "\n",
+ " [[[ 0.3333333 0.25490195 0.05882347]\n",
+ " [ 0.3333333 0.25490195 0.05882347]\n",
+ " [ 0.3340686 0.24705875 0.03039211]\n",
+ " ...\n",
+ " [-0.5215688 -0.4599266 -0.14632356]\n",
+ " [-0.5100491 -0.47083342 -0.03725493]\n",
+ " [-0.43419123 -0.39497554 0.05992639]]\n",
+ "\n",
+ " [[ 0.34117645 0.26274508 0.0666666 ]\n",
+ " [ 0.35646445 0.2630821 0.0744791 ]\n",
+ " [ 0.3632046 0.2548713 0.04384762]\n",
+ " ...\n",
+ " [-0.9210479 -0.84267783 -0.4540485 ]\n",
+ " [-0.9017464 -0.8390626 -0.3507018 ]\n",
+ " [-0.83339334 -0.7632048 -0.2534927 ]]\n",
+ "\n",
+ " [[ 0.3646446 0.2706495 0.06678915]\n",
+ " [ 0.37248772 0.27837008 0.07445425]\n",
+ " [ 0.38033658 0.27053267 0.05950326]\n",
+ " ...\n",
+ " [-0.94302344 -0.84222686 -0.30278325]\n",
+ " [-0.91017747 -0.8090074 -0.18615782]\n",
+ " [-0.83437514 -0.7402575 -0.08192408]]\n",
+ "\n",
+ " ...\n",
+ "\n",
+ " [[ 0.64705884 0.654902 0.67058825]\n",
+ " [ 0.6318321 0.63967526 0.65536153]\n",
+ " [ 0.63128924 0.6391324 0.65481865]\n",
+ " ...\n",
+ " [ 0.6313726 0.57647055 0.51372546]\n",
+ " [ 0.6078431 0.53725487 0.4823529 ]\n",
+ " [ 0.6078431 0.53725487 0.4823529 ]]\n",
+ "\n",
+ " [[ 0.654902 0.654902 0.6704657 ]\n",
+ " [ 0.654902 0.654902 0.6704657 ]\n",
+ " [ 0.64778835 0.64778835 0.6492474 ]\n",
+ " ...\n",
+ " [ 0.6392157 0.5843137 0.5215686 ]\n",
+ " [ 0.6393325 0.56874424 0.5138422 ]\n",
+ " [ 0.63106614 0.5604779 0.50557595]]\n",
+ "\n",
+ " [[ 0.654902 0.64705884 0.6313726 ]\n",
+ " [ 0.6548728 0.64702964 0.63134336]\n",
+ " [ 0.64705884 0.63210785 0.6377451 ]\n",
+ " ...\n",
+ " [ 0.63244915 0.5775472 0.5148021 ]\n",
+ " [ 0.6698529 0.5992647 0.5443627 ]\n",
+ " [ 0.6545358 0.5839475 0.5290455 ]]]] [5 9]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Display data.\n",
+ "for i in range(1):\n",
+ " batch_x, batch_y = sess.run(d)\n",
+ " print(batch_x, batch_y)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load data from a Generator\n",
+ "\n",
+ "Build a data pipeline from a custom generator. For this example, a toy generator yielding random string, vector and it is used."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create a dummy generator.\n",
+ "def generate_features():\n",
+ " # Function to generate a random string.\n",
+ " def random_string(length):\n",
+ " return ''.join(random.choice(string.ascii_letters) for m in xrange(length))\n",
+ " # Return a random string, a random vector, and a random int.\n",
+ " yield random_string(4), np.random.uniform(size=4), random.randint(0, 10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with tf.Graph().as_default():\n",
+ "\n",
+ " # Create TF session.\n",
+ " sess = tf.Session()\n",
+ "\n",
+ " # Create TF dataset from the generator.\n",
+ " data = tf.data.Dataset.from_generator(generate_features, output_types=(tf.string, tf.float32, tf.int32))\n",
+ " # Refill data indefinitely.\n",
+ " data = data.repeat()\n",
+ " # Shuffle data.\n",
+ " data = data.shuffle(buffer_size=100)\n",
+ " # Batch data (aggregate records together).\n",
+ " data = data.batch(batch_size=4)\n",
+ " # Prefetch batch (pre-load batch for faster consumption).\n",
+ " data = data.prefetch(buffer_size=1)\n",
+ "\n",
+ " # Create an iterator over the dataset.\n",
+ " iterator = data.make_initializable_iterator()\n",
+ " # Initialize the iterator.\n",
+ " sess.run(iterator.initializer)\n",
+ "\n",
+ " # Get next data batch.\n",
+ " d = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "['AvCS' 'kAaI' 'QwGX' 'IWOI'] [[0.6096093 0.32192084 0.26622605 0.70250475]\n",
+ " [0.72534287 0.7637426 0.19977213 0.74121326]\n",
+ " [0.6930984 0.09409562 0.4063325 0.5002103 ]\n",
+ " [0.05160935 0.59411395 0.276416 0.98264974]] [1 3 5 6]\n",
+ "['EXjS' 'brvx' 'kwNz' 'eFOb'] [[0.34355283 0.26881003 0.70575935 0.7503411 ]\n",
+ " [0.9584373 0.27466875 0.27802315 0.9563204 ]\n",
+ " [0.19129485 0.07014314 0.0932724 0.20726128]\n",
+ " [0.28744072 0.81736153 0.37507302 0.8984588 ]] [1 9 7 0]\n",
+ "['vpSa' 'UuqW' 'xaTO' 'milw'] [[0.2942028 0.8228986 0.5793326 0.16651365]\n",
+ " [0.28259405 0.599063 0.2922477 0.95071274]\n",
+ " [0.23645316 0.00258607 0.06772221 0.7291911 ]\n",
+ " [0.12861755 0.31435087 0.576638 0.7333119 ]] [3 5 8 4]\n",
+ "['UBBb' 'MUXs' 'nLJB' 'OBGl'] [[0.2677402 0.17931737 0.02607645 0.85898155]\n",
+ " [0.58647937 0.727203 0.13329858 0.8898983 ]\n",
+ " [0.13872191 0.47390288 0.7061665 0.08478573]\n",
+ " [0.3786016 0.22002582 0.91989636 0.45837343]] [ 5 8 0 10]\n",
+ "['kiiz' 'bQYG' 'WpUU' 'AuIY'] [[0.74781317 0.13744462 0.9236441 0.63558507]\n",
+ " [0.23649399 0.35303807 0.0951511 0.03541444]\n",
+ " [0.33599988 0.6906629 0.97166294 0.55850506]\n",
+ " [0.90997607 0.5545979 0.43635726 0.9127501 ]] [8 1 4 4]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Display data.\n",
+ "for i in range(5):\n",
+ " batch_str, batch_vector, batch_int = sess.run(d)\n",
+ " print(batch_str, batch_vector, batch_int)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "tf1",
+ "language": "python",
+ "name": "tf1"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15+"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v1/notebooks/5_DataManagement/tensorflow_dataset_api.ipynb b/tensorflow_v1/notebooks/5_DataManagement/tensorflow_dataset_api.ipynb
new file mode 100644
index 00000000..1c7165db
--- /dev/null
+++ b/tensorflow_v1/notebooks/5_DataManagement/tensorflow_dataset_api.ipynb
@@ -0,0 +1,222 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# TensorFlow Dataset API\n",
+ "\n",
+ "In this example, we will show how to load numpy array data into the new \n",
+ "TensorFlow 'Dataset' API. The Dataset API implements an optimized data pipeline\n",
+ "with queues, that make data processing and training faster (especially on GPU).\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "import tensorflow as tf\n",
+ "\n",
+ "# Import MNIST data (Numpy format)\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Parameters\n",
+ "learning_rate = 0.01\n",
+ "num_steps = 1000\n",
+ "batch_size = 128\n",
+ "display_step = 100\n",
+ "\n",
+ "# Network Parameters\n",
+ "n_input = 784 # MNIST data input (img shape: 28*28)\n",
+ "n_classes = 10 # MNIST total classes (0-9 digits)\n",
+ "dropout = 0.75 # Dropout, probability to keep units\n",
+ "\n",
+ "sess = tf.Session()\n",
+ "\n",
+ "# Create a dataset tensor from the images and the labels\n",
+ "dataset = tf.data.Dataset.from_tensor_slices(\n",
+ " (mnist.train.images, mnist.train.labels))\n",
+ "# Automatically refill the data queue when empty\n",
+ "dataset = dataset.repeat()\n",
+ "# Create batches of data\n",
+ "dataset = dataset.batch(batch_size)\n",
+ "# Prefetch data for faster consumption\n",
+ "dataset = dataset.prefetch(batch_size)\n",
+ "\n",
+ "# Create an iterator over the dataset\n",
+ "iterator = dataset.make_initializable_iterator()\n",
+ "# Initialize the iterator\n",
+ "sess.run(iterator.initializer)\n",
+ "\n",
+ "# Neural Net Input (images, labels)\n",
+ "X, Y = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# -----------------------------------------------\n",
+ "# THIS IS A CLASSIC CNN (see examples, section 3)\n",
+ "# -----------------------------------------------\n",
+ "# Note that a few elements have changed (usage of sess run).\n",
+ "\n",
+ "# Create model\n",
+ "def conv_net(x, n_classes, dropout, reuse, is_training):\n",
+ " # Define a scope for reusing the variables\n",
+ " with tf.variable_scope('ConvNet', reuse=reuse):\n",
+ " # MNIST data input is a 1-D vector of 784 features (28*28 pixels)\n",
+ " # Reshape to match picture format [Height x Width x Channel]\n",
+ " # Tensor input become 4-D: [Batch Size, Height, Width, Channel]\n",
+ " x = tf.reshape(x, shape=[-1, 28, 28, 1])\n",
+ "\n",
+ " # Convolution Layer with 32 filters and a kernel size of 5\n",
+ " conv1 = tf.layers.conv2d(x, 32, 5, activation=tf.nn.relu)\n",
+ " # Max Pooling (down-sampling) with strides of 2 and kernel size of 2\n",
+ " conv1 = tf.layers.max_pooling2d(conv1, 2, 2)\n",
+ "\n",
+ " # Convolution Layer with 32 filters and a kernel size of 5\n",
+ " conv2 = tf.layers.conv2d(conv1, 64, 3, activation=tf.nn.relu)\n",
+ " # Max Pooling (down-sampling) with strides of 2 and kernel size of 2\n",
+ " conv2 = tf.layers.max_pooling2d(conv2, 2, 2)\n",
+ "\n",
+ " # Flatten the data to a 1-D vector for the fully connected layer\n",
+ " fc1 = tf.contrib.layers.flatten(conv2)\n",
+ "\n",
+ " # Fully connected layer (in contrib folder for now)\n",
+ " fc1 = tf.layers.dense(fc1, 1024)\n",
+ " # Apply Dropout (if is_training is False, dropout is not applied)\n",
+ " fc1 = tf.layers.dropout(fc1, rate=dropout, training=is_training)\n",
+ "\n",
+ " # Output layer, class prediction\n",
+ " out = tf.layers.dense(fc1, n_classes)\n",
+ " # Because 'softmax_cross_entropy_with_logits' already apply softmax,\n",
+ " # we only apply softmax to testing network\n",
+ " out = tf.nn.softmax(out) if not is_training else out\n",
+ "\n",
+ " return out\n",
+ "\n",
+ "\n",
+ "# Because Dropout have different behavior at training and prediction time, we\n",
+ "# need to create 2 distinct computation graphs that share the same weights.\n",
+ "\n",
+ "# Create a graph for training\n",
+ "logits_train = conv_net(X, n_classes, dropout, reuse=False, is_training=True)\n",
+ "# Create another graph for testing that reuse the same weights, but has\n",
+ "# different behavior for 'dropout' (not applied).\n",
+ "logits_test = conv_net(X, n_classes, dropout, reuse=True, is_training=False)\n",
+ "\n",
+ "# Define loss and optimizer (with train logits, for dropout to take effect)\n",
+ "loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(\n",
+ " logits=logits_train, labels=Y))\n",
+ "optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
+ "train_op = optimizer.minimize(loss_op)\n",
+ "\n",
+ "# Evaluate model (with test logits, for dropout to be disabled)\n",
+ "correct_pred = tf.equal(tf.argmax(logits_test, 1), tf.argmax(Y, 1))\n",
+ "accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1, Minibatch Loss= 7.9429, Training Accuracy= 0.070\n",
+ "Step 100, Minibatch Loss= 0.3491, Training Accuracy= 0.922\n",
+ "Step 200, Minibatch Loss= 0.2343, Training Accuracy= 0.922\n",
+ "Step 300, Minibatch Loss= 0.1838, Training Accuracy= 0.969\n",
+ "Step 400, Minibatch Loss= 0.1715, Training Accuracy= 0.953\n",
+ "Step 500, Minibatch Loss= 0.2730, Training Accuracy= 0.938\n",
+ "Step 600, Minibatch Loss= 0.3427, Training Accuracy= 0.953\n",
+ "Step 700, Minibatch Loss= 0.2261, Training Accuracy= 0.961\n",
+ "Step 800, Minibatch Loss= 0.1487, Training Accuracy= 0.953\n",
+ "Step 900, Minibatch Loss= 0.1438, Training Accuracy= 0.945\n",
+ "Step 1000, Minibatch Loss= 0.1786, Training Accuracy= 0.961\n",
+ "Optimization Finished!\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Initialize the variables (i.e. assign their default value)\n",
+ "init = tf.global_variables_initializer()\n",
+ "\n",
+ "# Run the initializer\n",
+ "sess.run(init)\n",
+ "\n",
+ "# Training cycle\n",
+ "for step in range(1, num_steps + 1):\n",
+ " \n",
+ " # Run optimization\n",
+ " sess.run(train_op)\n",
+ " \n",
+ " if step % display_step == 0 or step == 1:\n",
+ " # Calculate batch loss and accuracy\n",
+ " # (note that this consume a new batch of data)\n",
+ " loss, acc = sess.run([loss_op, accuracy])\n",
+ " print(\"Step \" + str(step) + \", Minibatch Loss= \" + \\\n",
+ " \"{:.4f}\".format(loss) + \", Training Accuracy= \" + \\\n",
+ " \"{:.3f}\".format(acc))\n",
+ "\n",
+ "print(\"Optimization Finished!\")"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.14"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v1/notebooks/5_DataManagement/tfrecords.ipynb b/tensorflow_v1/notebooks/5_DataManagement/tfrecords.ipynb
new file mode 100644
index 00000000..a801b2f7
--- /dev/null
+++ b/tensorflow_v1/notebooks/5_DataManagement/tfrecords.ipynb
@@ -0,0 +1,261 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Create and Load TFRecords\n",
+ "\n",
+ "A simple TensorFlow example to parse a dataset into TFRecord format, and then read that dataset.\n",
+ "\n",
+ "In this example, the Titanic Dataset (in CSV format) will be used as a toy dataset, for parsing all the dataset features into TFRecord format, and then building an input pipeline that can be used for training models.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Titanic Dataset\n",
+ "\n",
+ "The titanic dataset is a popular dataset for ML that provides a list of all passengers onboard the Titanic, along with various features such as their age, sex, class (1st, 2nd, 3rd)... And if the passenger survived the disaster or not.\n",
+ "\n",
+ "It can be used to see that even though some luck was involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class...\n",
+ "\n",
+ "#### Overview\n",
+ "survived|pclass|name|sex|age|sibsp|parch|ticket|fare\n",
+ "--------|------|----|---|---|-----|-----|------|----\n",
+ "1|1|\"Allen, Miss. Elisabeth Walton\"|female|29|0|0|24160|211.3375\n",
+ "1|1|\"Allison, Master. Hudson Trevor\"|male|0.9167|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Miss. Helen Loraine\"|female|2|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Mr. Hudson Joshua Creighton\"|male|30|1|2|113781|151.5500\n",
+ "...|...|...|...|...|...|...|...|...\n",
+ "\n",
+ "\n",
+ "#### Variable Descriptions\n",
+ "```\n",
+ "survived Survived\n",
+ " (0 = No; 1 = Yes)\n",
+ "pclass Passenger Class\n",
+ " (1 = 1st; 2 = 2nd; 3 = 3rd)\n",
+ "name Name\n",
+ "sex Sex\n",
+ "age Age\n",
+ "sibsp Number of Siblings/Spouses Aboard\n",
+ "parch Number of Parents/Children Aboard\n",
+ "ticket Ticket Number\n",
+ "fare Passenger Fare\n",
+ "```"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import csv\n",
+ "import requests\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download Titanic dataset (in csv format).\n",
+ "d = requests.get(\"https://raw.githubusercontent.com/tflearn/tflearn.github.io/master/resources/titanic_dataset.csv\")\n",
+ "with open(\"titanic_dataset.csv\", \"wb\") as f:\n",
+ " f.write(d.content)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Create TFRecords"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Generate Integer Features.\n",
+ "def build_int64_feature(data):\n",
+ " return tf.train.Feature(int64_list=tf.train.Int64List(value=[data]))\n",
+ "\n",
+ "# Generate Float Features.\n",
+ "def build_float_feature(data):\n",
+ " return tf.train.Feature(float_list=tf.train.FloatList(value=[data]))\n",
+ "\n",
+ "# Generate String Features.\n",
+ "def build_string_feature(data):\n",
+ " return tf.train.Feature(bytes_list=tf.train.BytesList(value=[data]))\n",
+ "\n",
+ "# Generate a TF `Example`, parsing all features of the dataset.\n",
+ "def convert_to_tfexample(survived, pclass, name, sex, age, sibsp, parch, ticket, fare):\n",
+ " return tf.train.Example(\n",
+ " features=tf.train.Features(\n",
+ " feature={\n",
+ " 'survived': build_int64_feature(survived),\n",
+ " 'pclass': build_int64_feature(pclass),\n",
+ " 'name': build_string_feature(name),\n",
+ " 'sex': build_string_feature(sex),\n",
+ " 'age': build_float_feature(age),\n",
+ " 'sibsp': build_int64_feature(sibsp),\n",
+ " 'parch': build_int64_feature(parch),\n",
+ " 'ticket': build_string_feature(ticket),\n",
+ " 'fare': build_float_feature(fare),\n",
+ " })\n",
+ " )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Open dataset file.\n",
+ "with open(\"titanic_dataset.csv\") as f:\n",
+ " # Output TFRecord file.\n",
+ " with tf.io.TFRecordWriter(\"titanic_dataset.tfrecord\") as w:\n",
+ " # Generate a TF Example for all row in our dataset.\n",
+ " # CSV reader will read and parse all rows.\n",
+ " reader = csv.reader(f, skipinitialspace=True)\n",
+ " for i, record in enumerate(reader):\n",
+ " # Skip header.\n",
+ " if i == 0:\n",
+ " continue\n",
+ " survived, pclass, name, sex, age, sibsp, parch, ticket, fare = record\n",
+ " # Parse each csv row to TF Example using the above functions.\n",
+ " example = convert_to_tfexample(int(survived), int(pclass), name, sex, float(age), int(sibsp), int(parch), ticket, float(fare))\n",
+ " # Serialize each TF Example to string, and write to TFRecord file.\n",
+ " w.write(example.SerializeToString())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load TFRecords"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Build features template, with types.\n",
+ "features = {\n",
+ " 'survived': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'pclass': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'name': tf.io.FixedLenFeature([], tf.string),\n",
+ " 'sex': tf.io.FixedLenFeature([], tf.string),\n",
+ " 'age': tf.io.FixedLenFeature([], tf.float32),\n",
+ " 'sibsp': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'parch': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'ticket': tf.io.FixedLenFeature([], tf.string),\n",
+ " 'fare': tf.io.FixedLenFeature([], tf.float32),\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create TensorFlow session.\n",
+ "sess = tf.Session()\n",
+ "\n",
+ "# Load TFRecord data.\n",
+ "filenames = [\"titanic_dataset.tfrecord\"]\n",
+ "data = tf.data.TFRecordDataset(filenames)\n",
+ "\n",
+ "# Parse features, using the above template.\n",
+ "def parse_record(record):\n",
+ " return tf.io.parse_single_example(record, features=features)\n",
+ "# Apply the parsing to each record from the dataset.\n",
+ "data = data.map(parse_record)\n",
+ "\n",
+ "# Refill data indefinitely.\n",
+ "data = data.repeat()\n",
+ "# Shuffle data.\n",
+ "data = data.shuffle(buffer_size=1000)\n",
+ "# Batch data (aggregate records together).\n",
+ "data = data.batch(batch_size=4)\n",
+ "# Prefetch batch (pre-load batch for faster consumption).\n",
+ "data = data.prefetch(buffer_size=1)\n",
+ "\n",
+ "# Create an iterator over the dataset.\n",
+ "iterator = data.make_initializable_iterator()\n",
+ "# Initialize the iterator.\n",
+ "sess.run(iterator.initializer)\n",
+ "\n",
+ "# Get next data batch.\n",
+ "x = iterator.get_next()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "{'fare': array([ 35.5 , 73.5 , 133.65 , 19.2583], dtype=float32), 'name': array(['Sloper, Mr. William Thompson', 'Davies, Mr. Charles Henry',\n",
+ " 'Frauenthal, Dr. Henry William', 'Baclini, Miss. Marie Catherine'],\n",
+ " dtype=object), 'age': array([28., 18., 50., 5.], dtype=float32), 'parch': array([0, 0, 0, 1]), 'pclass': array([1, 2, 1, 3]), 'sex': array(['male', 'male', 'male', 'female'], dtype=object), 'survived': array([1, 0, 1, 1]), 'sibsp': array([0, 0, 2, 2]), 'ticket': array(['113788', 'S.O.C. 14879', 'PC 17611', '2666'], dtype=object)}\n",
+ "\n",
+ "{'fare': array([ 18.75 , 106.425, 78.85 , 90. ], dtype=float32), 'name': array(['Richards, Mrs. Sidney (Emily Hocking)', 'LeRoy, Miss. Bertha',\n",
+ " 'Cavendish, Mrs. Tyrell William (Julia Florence Siegel)',\n",
+ " 'Hoyt, Mrs. Frederick Maxfield (Jane Anne Forby)'], dtype=object), 'age': array([24., 30., 76., 35.], dtype=float32), 'parch': array([3, 0, 0, 0]), 'pclass': array([2, 1, 1, 1]), 'sex': array(['female', 'female', 'female', 'female'], dtype=object), 'survived': array([1, 1, 1, 1]), 'sibsp': array([2, 0, 1, 1]), 'ticket': array(['29106', 'PC 17761', '19877', '19943'], dtype=object)}\n",
+ "\n",
+ "{'fare': array([19.9667, 15.5 , 15.0458, 66.6 ], dtype=float32), 'name': array(['Hagland, Mr. Konrad Mathias Reiersen', 'Lennon, Miss. Mary',\n",
+ " 'Richard, Mr. Emile', 'Pears, Mr. Thomas Clinton'], dtype=object), 'age': array([ 0., 0., 23., 29.], dtype=float32), 'parch': array([0, 0, 0, 0]), 'pclass': array([3, 3, 2, 1]), 'sex': array(['male', 'female', 'male', 'male'], dtype=object), 'survived': array([0, 0, 0, 0]), 'sibsp': array([1, 1, 0, 1]), 'ticket': array(['65304', '370371', 'SC/PARIS 2133', '113776'], dtype=object)}\n",
+ "\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Dequeue data and display.\n",
+ "for i in range(3):\n",
+ " print(sess.run(x))\n",
+ " print(\"\")"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "tf1",
+ "language": "python",
+ "name": "tf1"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15+"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v1/notebooks/6_MultiGPU/multigpu_basics.ipynb b/tensorflow_v1/notebooks/6_MultiGPU/multigpu_basics.ipynb
new file mode 100644
index 00000000..feb50fbf
--- /dev/null
+++ b/tensorflow_v1/notebooks/6_MultiGPU/multigpu_basics.ipynb
@@ -0,0 +1,179 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "# Multi-GPU Basics\n",
+ "\n",
+ "Basic Multi-GPU computation example using TensorFlow library.\n",
+ "\n",
+ "This tutorial requires your machine to have 2 GPUs\n",
+ "\"/cpu:0\": The CPU of your machine.\n",
+ "\"/gpu:0\": The first GPU of your machine\n",
+ "\"/gpu:1\": The second GPU of your machine\n",
+ "For this example, we are using 2 GTX-980\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "import tensorflow as tf\n",
+ "import datetime"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "#Processing Units logs\n",
+ "log_device_placement = True\n",
+ "\n",
+ "#num of multiplications to perform\n",
+ "n = 10"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "# Example: compute A^n + B^n on 2 GPUs\n",
+ "\n",
+ "# Create random large matrix\n",
+ "A = np.random.rand(1e4, 1e4).astype('float32')\n",
+ "B = np.random.rand(1e4, 1e4).astype('float32')\n",
+ "\n",
+ "# Creates a graph to store results\n",
+ "c1 = []\n",
+ "c2 = []\n",
+ "\n",
+ "# Define matrix power\n",
+ "def matpow(M, n):\n",
+ " if n < 1: #Abstract cases where n < 1\n",
+ " return M\n",
+ " else:\n",
+ " return tf.matmul(M, matpow(M, n-1))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Single GPU computing\n",
+ "\n",
+ "with tf.device('/gpu:0'):\n",
+ " a = tf.constant(A)\n",
+ " b = tf.constant(B)\n",
+ " #compute A^n and B^n and store results in c1\n",
+ " c1.append(matpow(a, n))\n",
+ " c1.append(matpow(b, n))\n",
+ "\n",
+ "with tf.device('/cpu:0'):\n",
+ " sum = tf.add_n(c1) #Addition of all elements in c1, i.e. A^n + B^n\n",
+ "\n",
+ "t1_1 = datetime.datetime.now()\n",
+ "with tf.Session(config=tf.ConfigProto(log_device_placement=log_device_placement)) as sess:\n",
+ " # Runs the op.\n",
+ " sess.run(sum)\n",
+ "t2_1 = datetime.datetime.now()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Multi GPU computing\n",
+ "# GPU:0 computes A^n\n",
+ "with tf.device('/gpu:0'):\n",
+ " #compute A^n and store result in c2\n",
+ " a = tf.constant(A)\n",
+ " c2.append(matpow(a, n))\n",
+ "\n",
+ "#GPU:1 computes B^n\n",
+ "with tf.device('/gpu:1'):\n",
+ " #compute B^n and store result in c2\n",
+ " b = tf.constant(B)\n",
+ " c2.append(matpow(b, n))\n",
+ "\n",
+ "with tf.device('/cpu:0'):\n",
+ " sum = tf.add_n(c2) #Addition of all elements in c2, i.e. A^n + B^n\n",
+ "\n",
+ "t1_2 = datetime.datetime.now()\n",
+ "with tf.Session(config=tf.ConfigProto(log_device_placement=log_device_placement)) as sess:\n",
+ " # Runs the op.\n",
+ " sess.run(sum)\n",
+ "t2_2 = datetime.datetime.now()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Single GPU computation time: 0:00:11.833497\n",
+ "Multi GPU computation time: 0:00:07.085913\n"
+ ]
+ }
+ ],
+ "source": [
+ "print \"Single GPU computation time: \" + str(t2_1-t1_1)\n",
+ "print \"Multi GPU computation time: \" + str(t2_2-t1_2)"
+ ]
+ }
+ ],
+ "metadata": {
+ "anaconda-cloud": {},
+ "kernelspec": {
+ "display_name": "Python [default]",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.12"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v1/notebooks/6_MultiGPU/multigpu_cnn.ipynb b/tensorflow_v1/notebooks/6_MultiGPU/multigpu_cnn.ipynb
new file mode 100644
index 00000000..546cdc00
--- /dev/null
+++ b/tensorflow_v1/notebooks/6_MultiGPU/multigpu_cnn.ipynb
@@ -0,0 +1,328 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Multi-GPU Training Example\n",
+ "\n",
+ "Train a convolutional neural network on multiple GPU with TensorFlow.\n",
+ "\n",
+ "This example is using TensorFlow layers, see 'convolutional_network_raw' example\n",
+ "for a raw TensorFlow implementation with variables.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Training with multiple GPU cards\n",
+ "\n",
+ "In this example, we are using data parallelism to split the training accross multiple GPUs. Each GPU has a full replica of the neural network model, and the weights (i.e. variables) are updated synchronously by waiting that each GPU process its batch of data.\n",
+ "\n",
+ "First, each GPU process a distinct batch of data and compute the corresponding gradients, then, all gradients are accumulated in the CPU and averaged. The model weights are finally updated with the gradients averaged, and the new model weights are sent back to each GPU, to repeat the training process.\n",
+ "\n",
+ "
\n",
+ "\n",
+ "## MNIST Dataset Overview\n",
+ "\n",
+ "This example is using MNIST handwritten digits. The dataset contains 60,000 examples for training and 10,000 examples for testing. The digits have been size-normalized and centered in a fixed-size image (28x28 pixels) with values from 0 to 1. For simplicity, each image has been flatten and converted to a 1-D numpy array of 784 features (28*28).\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: http://yann.lecun.com/exdb/mnist/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Extracting /tmp/data/train-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/train-labels-idx1-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-images-idx3-ubyte.gz\n",
+ "Extracting /tmp/data/t10k-labels-idx1-ubyte.gz\n"
+ ]
+ }
+ ],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "import numpy as np\n",
+ "import tensorflow as tf\n",
+ "import time\n",
+ "\n",
+ "# Import MNIST data\n",
+ "from tensorflow.examples.tutorials.mnist import input_data\n",
+ "mnist = input_data.read_data_sets(\"/tmp/data/\", one_hot=True)\n",
+ "\n",
+ "# Parameters\n",
+ "num_gpus = 2\n",
+ "num_steps = 200\n",
+ "learning_rate = 0.001\n",
+ "batch_size = 1024\n",
+ "display_step = 10\n",
+ "\n",
+ "# Network Parameters\n",
+ "num_input = 784 # MNIST data input (img shape: 28*28)\n",
+ "num_classes = 10 # MNIST total classes (0-9 digits)\n",
+ "dropout = 0.75 # Dropout, probability to keep units"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Build a convolutional neural network\n",
+ "def conv_net(x, n_classes, dropout, reuse, is_training):\n",
+ " # Define a scope for reusing the variables\n",
+ " with tf.variable_scope('ConvNet', reuse=reuse):\n",
+ " # MNIST data input is a 1-D vector of 784 features (28*28 pixels)\n",
+ " # Reshape to match picture format [Height x Width x Channel]\n",
+ " # Tensor input become 4-D: [Batch Size, Height, Width, Channel]\n",
+ " x = tf.reshape(x, shape=[-1, 28, 28, 1])\n",
+ "\n",
+ " # Convolution Layer with 64 filters and a kernel size of 5\n",
+ " x = tf.layers.conv2d(x, 64, 5, activation=tf.nn.relu)\n",
+ " # Max Pooling (down-sampling) with strides of 2 and kernel size of 2\n",
+ " x = tf.layers.max_pooling2d(x, 2, 2)\n",
+ "\n",
+ " # Convolution Layer with 256 filters and a kernel size of 5\n",
+ " x = tf.layers.conv2d(x, 256, 3, activation=tf.nn.relu)\n",
+ " # Convolution Layer with 512 filters and a kernel size of 5\n",
+ " x = tf.layers.conv2d(x, 512, 3, activation=tf.nn.relu)\n",
+ " # Max Pooling (down-sampling) with strides of 2 and kernel size of 2\n",
+ " x = tf.layers.max_pooling2d(x, 2, 2)\n",
+ "\n",
+ " # Flatten the data to a 1-D vector for the fully connected layer\n",
+ " x = tf.contrib.layers.flatten(x)\n",
+ "\n",
+ " # Fully connected layer (in contrib folder for now)\n",
+ " x = tf.layers.dense(x, 2048)\n",
+ " # Apply Dropout (if is_training is False, dropout is not applied)\n",
+ " x = tf.layers.dropout(x, rate=dropout, training=is_training)\n",
+ "\n",
+ " # Fully connected layer (in contrib folder for now)\n",
+ " x = tf.layers.dense(x, 1024)\n",
+ " # Apply Dropout (if is_training is False, dropout is not applied)\n",
+ " x = tf.layers.dropout(x, rate=dropout, training=is_training)\n",
+ "\n",
+ " # Output layer, class prediction\n",
+ " out = tf.layers.dense(x, n_classes)\n",
+ " # Because 'softmax_cross_entropy_with_logits' loss already apply\n",
+ " # softmax, we only apply softmax to testing network\n",
+ " out = tf.nn.softmax(out) if not is_training else out\n",
+ "\n",
+ " return out"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# Build the function to average the gradients\n",
+ "def average_gradients(tower_grads):\n",
+ " average_grads = []\n",
+ " for grad_and_vars in zip(*tower_grads):\n",
+ " # Note that each grad_and_vars looks like the following:\n",
+ " # ((grad0_gpu0, var0_gpu0), ... , (grad0_gpuN, var0_gpuN))\n",
+ " grads = []\n",
+ " for g, _ in grad_and_vars:\n",
+ " # Add 0 dimension to the gradients to represent the tower.\n",
+ " expanded_g = tf.expand_dims(g, 0)\n",
+ "\n",
+ " # Append on a 'tower' dimension which we will average over below.\n",
+ " grads.append(expanded_g)\n",
+ "\n",
+ " # Average over the 'tower' dimension.\n",
+ " grad = tf.concat(grads, 0)\n",
+ " grad = tf.reduce_mean(grad, 0)\n",
+ "\n",
+ " # Keep in mind that the Variables are redundant because they are shared\n",
+ " # across towers. So .. we will just return the first tower's pointer to\n",
+ " # the Variable.\n",
+ " v = grad_and_vars[0][1]\n",
+ " grad_and_var = (grad, v)\n",
+ " average_grads.append(grad_and_var)\n",
+ " return average_grads"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "# By default, all variables will be placed on '/gpu:0'\n",
+ "# So we need a custom device function, to assign all variables to '/cpu:0'\n",
+ "# Note: If GPUs are peered, '/gpu:0' can be a faster option\n",
+ "PS_OPS = ['Variable', 'VariableV2', 'AutoReloadVariable']\n",
+ "\n",
+ "def assign_to_device(device, ps_device='/cpu:0'):\n",
+ " def _assign(op):\n",
+ " node_def = op if isinstance(op, tf.NodeDef) else op.node_def\n",
+ " if node_def.op in PS_OPS:\n",
+ " return \"/\" + ps_device\n",
+ " else:\n",
+ " return device\n",
+ "\n",
+ " return _assign"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Step 1: Minibatch Loss= 2.4077, Training Accuracy= 0.123, 682 Examples/sec\n",
+ "Step 10: Minibatch Loss= 1.0067, Training Accuracy= 0.765, 6528 Examples/sec\n",
+ "Step 20: Minibatch Loss= 0.2442, Training Accuracy= 0.945, 6803 Examples/sec\n",
+ "Step 30: Minibatch Loss= 0.2013, Training Accuracy= 0.951, 6741 Examples/sec\n",
+ "Step 40: Minibatch Loss= 0.1445, Training Accuracy= 0.962, 6700 Examples/sec\n",
+ "Step 50: Minibatch Loss= 0.0940, Training Accuracy= 0.971, 6746 Examples/sec\n",
+ "Step 60: Minibatch Loss= 0.0792, Training Accuracy= 0.977, 6627 Examples/sec\n",
+ "Step 70: Minibatch Loss= 0.0593, Training Accuracy= 0.979, 6749 Examples/sec\n",
+ "Step 80: Minibatch Loss= 0.0799, Training Accuracy= 0.984, 6368 Examples/sec\n",
+ "Step 90: Minibatch Loss= 0.0614, Training Accuracy= 0.988, 6762 Examples/sec\n",
+ "Step 100: Minibatch Loss= 0.0716, Training Accuracy= 0.983, 6338 Examples/sec\n",
+ "Step 110: Minibatch Loss= 0.0531, Training Accuracy= 0.986, 6504 Examples/sec\n",
+ "Step 120: Minibatch Loss= 0.0425, Training Accuracy= 0.990, 6721 Examples/sec\n",
+ "Step 130: Minibatch Loss= 0.0473, Training Accuracy= 0.986, 6735 Examples/sec\n",
+ "Step 140: Minibatch Loss= 0.0345, Training Accuracy= 0.991, 6636 Examples/sec\n",
+ "Step 150: Minibatch Loss= 0.0419, Training Accuracy= 0.993, 6777 Examples/sec\n",
+ "Step 160: Minibatch Loss= 0.0602, Training Accuracy= 0.984, 6392 Examples/sec\n",
+ "Step 170: Minibatch Loss= 0.0425, Training Accuracy= 0.990, 6855 Examples/sec\n",
+ "Step 180: Minibatch Loss= 0.0107, Training Accuracy= 0.998, 6804 Examples/sec\n",
+ "Step 190: Minibatch Loss= 0.0204, Training Accuracy= 0.995, 6645 Examples/sec\n",
+ "Step 200: Minibatch Loss= 0.0296, Training Accuracy= 0.993, 6747 Examples/sec\n",
+ "Optimization Finished!\n",
+ "Testing Accuracy: 0.990671\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Place all ops on CPU by default\n",
+ "with tf.device('/cpu:0'):\n",
+ " tower_grads = []\n",
+ " reuse_vars = False\n",
+ "\n",
+ " # tf Graph input\n",
+ " X = tf.placeholder(tf.float32, [None, num_input])\n",
+ " Y = tf.placeholder(tf.float32, [None, num_classes])\n",
+ "\n",
+ " # Loop over all GPUs and construct their own computation graph\n",
+ " for i in range(num_gpus):\n",
+ " with tf.device(assign_to_device('/gpu:{}'.format(i), ps_device='/cpu:0')):\n",
+ "\n",
+ " # Split data between GPUs\n",
+ " _x = X[i * batch_size: (i+1) * batch_size]\n",
+ " _y = Y[i * batch_size: (i+1) * batch_size]\n",
+ "\n",
+ " # Because Dropout have different behavior at training and prediction time, we\n",
+ " # need to create 2 distinct computation graphs that share the same weights.\n",
+ "\n",
+ " # Create a graph for training\n",
+ " logits_train = conv_net(_x, num_classes, dropout,\n",
+ " reuse=reuse_vars, is_training=True)\n",
+ " # Create another graph for testing that reuse the same weights\n",
+ " logits_test = conv_net(_x, num_classes, dropout,\n",
+ " reuse=True, is_training=False)\n",
+ "\n",
+ " # Define loss and optimizer (with train logits, for dropout to take effect)\n",
+ " loss_op = tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(\n",
+ " logits=logits_train, labels=_y))\n",
+ " optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
+ " grads = optimizer.compute_gradients(loss_op)\n",
+ "\n",
+ " # Only first GPU compute accuracy\n",
+ " if i == 0:\n",
+ " # Evaluate model (with test logits, for dropout to be disabled)\n",
+ " correct_pred = tf.equal(tf.argmax(logits_test, 1), tf.argmax(_y, 1))\n",
+ " accuracy = tf.reduce_mean(tf.cast(correct_pred, tf.float32))\n",
+ "\n",
+ " reuse_vars = True\n",
+ " tower_grads.append(grads)\n",
+ "\n",
+ " tower_grads = average_gradients(tower_grads)\n",
+ " train_op = optimizer.apply_gradients(tower_grads)\n",
+ "\n",
+ " # Initializing the variables\n",
+ " init = tf.global_variables_initializer()\n",
+ "\n",
+ " # Launch the graph\n",
+ " with tf.Session() as sess:\n",
+ " sess.run(init)\n",
+ " step = 1\n",
+ " # Keep training until reach max iterations\n",
+ " for step in range(1, num_steps + 1):\n",
+ " # Get a batch for each GPU\n",
+ " batch_x, batch_y = mnist.train.next_batch(batch_size * num_gpus)\n",
+ " # Run optimization op (backprop)\n",
+ " ts = time.time()\n",
+ " sess.run(train_op, feed_dict={X: batch_x, Y: batch_y})\n",
+ " te = time.time() - ts\n",
+ " if step % display_step == 0 or step == 1:\n",
+ " # Calculate batch loss and accuracy\n",
+ " loss, acc = sess.run([loss_op, accuracy], feed_dict={X: batch_x,\n",
+ " Y: batch_y})\n",
+ " print(\"Step \" + str(step) + \": Minibatch Loss= \" + \\\n",
+ " \"{:.4f}\".format(loss) + \", Training Accuracy= \" + \\\n",
+ " \"{:.3f}\".format(acc) + \", %i Examples/sec\" % int(len(batch_x)/te))\n",
+ " step += 1\n",
+ " print(\"Optimization Finished!\")\n",
+ "\n",
+ " # Calculate accuracy for 1000 mnist test images\n",
+ " print(\"Testing Accuracy:\", \\\n",
+ " np.mean([sess.run(accuracy, feed_dict={X: mnist.test.images[i:i+batch_size],\n",
+ " Y: mnist.test.labels[i:i+batch_size]}) for i in range(0, len(mnist.test.images), batch_size)]))"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.13"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}
diff --git a/tensorflow_v2/README.md b/tensorflow_v2/README.md
index 1626af3e..9b07cf5a 100644
--- a/tensorflow_v2/README.md
+++ b/tensorflow_v2/README.md
@@ -13,6 +13,8 @@
#### 2 - Basic Models
- **Linear Regression** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/2_BasicModels/linear_regression.ipynb)). Implement a Linear Regression with TensorFlow 2.0.
- **Logistic Regression** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/2_BasicModels/logistic_regression.ipynb)). Implement a Logistic Regression with TensorFlow 2.0.
+- **Word2Vec (Word Embedding)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/2_BasicModels/word2vec.ipynb)). Build a Word Embedding Model (Word2Vec) from Wikipedia data, with TensorFlow 2.0.
+- **GBDT (Gradient Boosted Decision Trees)** ([notebooks](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/2_BasicModels/gradient_boosted_trees.ipynb)). Implement a Gradient Boosted Decision Trees with TensorFlow 2.0+ to predict house value using Boston Housing dataset.
#### 3 - Neural Networks
##### Supervised
@@ -32,15 +34,24 @@
#### 4 - Utilities
- **Save and Restore a model** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/4_Utils/save_restore_model.ipynb)). Save and Restore a model with TensorFlow 2.0.
- **Build Custom Layers & Modules** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/4_Utils/build_custom_layers.ipynb)). Learn how to build your own layers / modules and integrate them into TensorFlow 2.0 Models.
+- **Tensorboard** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/4_Utils/tensorboard.ipynb)). Track and visualize neural network computation graph, metrics, weights and more using TensorFlow 2.0+ tensorboard.
+
+#### 5 - Data Management
+- **Load and Parse data** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/5_DataManagement/load_data.ipynb)). Build efficient data pipeline with TensorFlow 2.0 (Numpy arrays, Images, CSV files, custom data, ...).
+- **Build and Load TFRecords** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/5_DataManagement/tfrecords.ipynb)). Convert data into TFRecords format, and load them with TensorFlow 2.0.
+- **Image Transformation (i.e. Image Augmentation)** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/5_DataManagement/image_transformation.ipynb)). Apply various image augmentation techniques with TensorFlow 2.0, to generate distorted images for training.
+
+#### 6 - Hardware
+- **Multi-GPU Training** ([notebook](https://github.com/nebulaai/TensorFlow-Examples/blob/master/tensorflow_v2/notebooks/6_Hardware/multigpu_training.ipynb)). Train a convolutional neural network with multiple GPUs on CIFAR-10 dataset.
## Installation
To install TensorFlow 2.0, simply run:
```
-pip install tensorflow==2.0.0-beta1
+pip install tensorflow==2.0.0
```
or (if you want GPU support):
```
-pip install tensorflow_gpu==2.0.0-beta1
+pip install tensorflow_gpu==2.0.0
```
diff --git a/tensorflow_v2/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb b/tensorflow_v2/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb
index f1813c85..93c9e79e 100644
--- a/tensorflow_v2/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb
+++ b/tensorflow_v2/notebooks/0_Prerequisite/mnist_dataset_intro.ipynb
@@ -1,10 +1,8 @@
{
"cells": [
{
- "cell_type": "code",
- "execution_count": null,
+ "cell_type": "markdown",
"metadata": {},
- "outputs": [],
"source": [
"\n",
"# MNIST Dataset Introduction\n",
@@ -29,9 +27,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "collapsed": true
- },
+ "metadata": {},
"outputs": [],
"source": [
"# Import MNIST\n",
@@ -55,9 +51,7 @@
{
"cell_type": "code",
"execution_count": null,
- "metadata": {
- "collapsed": true
- },
+ "metadata": {},
"outputs": [],
"source": [
"# Get the next 64 images array and labels\n",
@@ -88,9 +82,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
- "version": "2.7.13"
+ "version": "2.7.18"
}
},
"nbformat": 4,
- "nbformat_minor": 0
+ "nbformat_minor": 1
}
diff --git a/tensorflow_v2/notebooks/1_Introduction/helloworld.ipynb b/tensorflow_v2/notebooks/1_Introduction/helloworld.ipynb
index 3517376c..c50c5279 100644
--- a/tensorflow_v2/notebooks/1_Introduction/helloworld.ipynb
+++ b/tensorflow_v2/notebooks/1_Introduction/helloworld.ipynb
@@ -37,7 +37,7 @@
"source": [
"# Create a Tensor.\n",
"hello = tf.constant(\"hello world\")\n",
- "print hello"
+ "print(hello)"
]
},
{
@@ -55,7 +55,7 @@
],
"source": [
"# To access a Tensor value, call numpy().\n",
- "print hello.numpy()"
+ "print(hello.numpy())"
]
}
],
diff --git a/tensorflow_v2/notebooks/2_BasicModels/gradient_boosted_trees.ipynb b/tensorflow_v2/notebooks/2_BasicModels/gradient_boosted_trees.ipynb
new file mode 100644
index 00000000..69716e85
--- /dev/null
+++ b/tensorflow_v2/notebooks/2_BasicModels/gradient_boosted_trees.ipynb
@@ -0,0 +1,604 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Gradient Boosted Decision Tree (GBDT)\n",
+ "Implement a Gradient Boosted Decision Tree (GBDT) with TensorFlow. This example is using the Boston Housing Value dataset as training samples. The example supports both Classification (2 classes: value > $23000 or not) and Regression (raw home value as target).\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Boston Housing Dataset\n",
+ "\n",
+ "**Link:** https://www.cs.toronto.edu/~delve/data/boston/bostonDetail.html\n",
+ "\n",
+ "**Description:**\n",
+ "\n",
+ "The dataset contains information collected by the U.S Census Service concerning housing in the area of Boston Mass. It was obtained from the StatLib archive (http://lib.stat.cmu.edu/datasets/boston), and has been used extensively throughout the literature to benchmark algorithms. However, these comparisons were primarily done outside of Delve and are thus somewhat suspect. The dataset is small in size with only 506 cases.\n",
+ "\n",
+ "The data was originally published by Harrison, D. and Rubinfeld, D.L. `Hedonic prices and the demand for clean air', J. Environ. Economics & Management, vol.5, 81-102, 1978.`\n",
+ "\n",
+ "*For the full features list, please see the link above*"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import print_function\n",
+ "\n",
+ "# Ignore all GPUs (current TF GBDT does not support GPU).\n",
+ "import os\n",
+ "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"\"\n",
+ "os.environ['TF_CPP_MIN_LOG_LEVEL'] = \"1\"\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "import numpy as np\n",
+ "import copy"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Dataset parameters.\n",
+ "num_classes = 2 # Total classes: greater or equal to $23,000, or not (See notes below).\n",
+ "num_features = 13 # data features size.\n",
+ "\n",
+ "# Training parameters.\n",
+ "max_steps = 2000\n",
+ "batch_size = 256\n",
+ "learning_rate = 1.0\n",
+ "l1_regul = 0.0\n",
+ "l2_regul = 0.1\n",
+ "\n",
+ "# GBDT parameters.\n",
+ "num_batches_per_layer = 1000\n",
+ "num_trees = 10\n",
+ "max_depth = 4"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Prepare Boston Housing Dataset.\n",
+ "from tensorflow.keras.datasets import boston_housing\n",
+ "(x_train, y_train), (x_test, y_test) = boston_housing.load_data()\n",
+ "\n",
+ "# For classification purpose, we build 2 classes: price greater or lower than $23,000\n",
+ "def to_binary_class(y):\n",
+ " for i, label in enumerate(y):\n",
+ " if label >= 23.0:\n",
+ " y[i] = 1\n",
+ " else:\n",
+ " y[i] = 0\n",
+ " return y\n",
+ "\n",
+ "y_train_binary = to_binary_class(copy.deepcopy(y_train))\n",
+ "y_test_binary = to_binary_class(copy.deepcopy(y_test))"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### GBDT Classifier"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Build the input function.\n",
+ "train_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(\n",
+ " x={'x': x_train}, y=y_train_binary,\n",
+ " batch_size=batch_size, num_epochs=None, shuffle=True)\n",
+ "test_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(\n",
+ " x={'x': x_test}, y=y_test_binary,\n",
+ " batch_size=batch_size, num_epochs=1, shuffle=False)\n",
+ "test_train_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(\n",
+ " x={'x': x_train}, y=y_train_binary,\n",
+ " batch_size=batch_size, num_epochs=1, shuffle=False)\n",
+ "# GBDT Models from TF Estimator requires 'feature_column' data format.\n",
+ "feature_columns = [tf.feature_column.numeric_column(key='x', shape=(num_features,))]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Using default config.\n",
+ "WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmp5h6BoR\n",
+ "INFO:tensorflow:Using config: {'_save_checkpoints_secs': 600, '_num_ps_replicas': 0, '_keep_checkpoint_max': 5, '_task_type': 'worker', '_global_id_in_cluster': 0, '_is_chief': True, '_cluster_spec': ClusterSpec({}), '_model_dir': '/tmp/tmp5h6BoR', '_protocol': None, '_save_checkpoints_steps': None, '_keep_checkpoint_every_n_hours': 10000, '_service': None, '_session_config': allow_soft_placement: true\n",
+ "graph_options {\n",
+ " rewrite_options {\n",
+ " meta_optimizer_iterations: ONE\n",
+ " }\n",
+ "}\n",
+ ", '_tf_random_seed': None, '_save_summary_steps': 100, '_device_fn': None, '_session_creation_timeout_secs': 7200, '_experimental_distribute': None, '_num_worker_replicas': 1, '_task_id': 0, '_log_step_count_steps': 100, '_experimental_max_worker_delay_secs': None, '_evaluation_master': '', '_eval_distribute': None, '_train_distribute': None, '_master': ''}\n"
+ ]
+ }
+ ],
+ "source": [
+ "gbdt_classifier = tf.estimator.BoostedTreesClassifier(\n",
+ " n_batches_per_layer=num_batches_per_layer,\n",
+ " feature_columns=feature_columns, \n",
+ " n_classes=num_classes,\n",
+ " learning_rate=learning_rate, \n",
+ " n_trees=num_trees,\n",
+ " max_depth=max_depth,\n",
+ " l1_regularization=l1_regul, \n",
+ " l2_regularization=l2_regul\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "WARNING:tensorflow:From /home/user/anaconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/ops/resource_variable_ops.py:1635: calling __init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "If using Keras pass *_constraint arguments to layers.\n",
+ "WARNING:tensorflow:From /home/user/anaconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/training/training_util.py:236: initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.\n",
+ "WARNING:tensorflow:From /home/user/anaconda3/envs/py2/lib/python2.7/site-packages/tensorflow_estimator/python/estimator/inputs/queues/feeding_queue_runner.py:62: __init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "To construct input pipelines, use the `tf.data` module.\n",
+ "WARNING:tensorflow:From /home/user/anaconda3/envs/py2/lib/python2.7/site-packages/tensorflow_estimator/python/estimator/inputs/queues/feeding_functions.py:500: add_queue_runner (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "To construct input pipelines, use the `tf.data` module.\n",
+ "INFO:tensorflow:Calling model_fn.\n",
+ "INFO:tensorflow:Done calling model_fn.\n",
+ "INFO:tensorflow:Create CheckpointSaverHook.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Graph was finalized.\n",
+ "INFO:tensorflow:Running local_init_op.\n",
+ "INFO:tensorflow:Done running local_init_op.\n",
+ "WARNING:tensorflow:From /home/user/anaconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/training/monitored_session.py:906: start_queue_runners (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "To construct input pipelines, use the `tf.data` module.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Saving checkpoints for 0 into /tmp/tmp5h6BoR/model.ckpt.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0\n",
+ "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n",
+ "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n",
+ "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n",
+ "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n",
+ "WARNING:tensorflow:It seems that global step (tf.train.get_global_step) has not been increased. Current value (could be stable): 0 vs previous value: 0. You could increase the global step by passing tf.train.get_global_step() to Optimizer.apply_gradients or Optimizer.minimize.\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0 (0.406 sec)\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0 (0.156 sec)\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0 (0.167 sec)\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0 (0.156 sec)\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0 (0.161 sec)\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0 (0.156 sec)\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0 (0.154 sec)\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0 (0.155 sec)\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0 (0.158 sec)\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 0 (0.150 sec)\n",
+ "INFO:tensorflow:global_step/sec: 47.2392\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 100 (0.301 sec)\n",
+ "INFO:tensorflow:global_step/sec: 605.484\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 200 (0.165 sec)\n",
+ "INFO:tensorflow:global_step/sec: 616.234\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 300 (0.162 sec)\n",
+ "INFO:tensorflow:global_step/sec: 607.741\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 400 (0.165 sec)\n",
+ "INFO:tensorflow:global_step/sec: 591.803\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 500 (0.170 sec)\n",
+ "INFO:tensorflow:global_step/sec: 627.369\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 600 (0.159 sec)\n",
+ "INFO:tensorflow:global_step/sec: 617.083\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 700 (0.162 sec)\n",
+ "INFO:tensorflow:global_step/sec: 608.765\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 800 (0.164 sec)\n",
+ "INFO:tensorflow:global_step/sec: 619.62\n",
+ "INFO:tensorflow:loss = 0.6931475, step = 900 (0.161 sec)\n",
+ "INFO:tensorflow:global_step/sec: 582.581\n",
+ "INFO:tensorflow:loss = 0.44474202, step = 1000 (0.172 sec)\n",
+ "INFO:tensorflow:global_step/sec: 587.127\n",
+ "INFO:tensorflow:loss = 0.46633375, step = 1100 (0.170 sec)\n",
+ "INFO:tensorflow:global_step/sec: 583.294\n",
+ "INFO:tensorflow:loss = 0.45393157, step = 1200 (0.171 sec)\n",
+ "INFO:tensorflow:global_step/sec: 590.375\n",
+ "INFO:tensorflow:loss = 0.44438446, step = 1300 (0.170 sec)\n",
+ "INFO:tensorflow:global_step/sec: 572.479\n",
+ "INFO:tensorflow:loss = 0.4523462, step = 1400 (0.175 sec)\n",
+ "INFO:tensorflow:global_step/sec: 580.282\n",
+ "INFO:tensorflow:loss = 0.4581305, step = 1500 (0.172 sec)\n",
+ "INFO:tensorflow:global_step/sec: 570.032\n",
+ "INFO:tensorflow:loss = 0.45298833, step = 1600 (0.175 sec)\n",
+ "INFO:tensorflow:global_step/sec: 615.6\n",
+ "INFO:tensorflow:loss = 0.4474975, step = 1700 (0.162 sec)\n",
+ "INFO:tensorflow:global_step/sec: 603.042\n",
+ "INFO:tensorflow:loss = 0.47046587, step = 1800 (0.166 sec)\n",
+ "INFO:tensorflow:global_step/sec: 598.262\n",
+ "INFO:tensorflow:loss = 0.46371317, step = 1900 (0.167 sec)\n",
+ "INFO:tensorflow:global_step/sec: 591.323\n",
+ "INFO:tensorflow:Saving checkpoints for 2000 into /tmp/tmp5h6BoR/model.ckpt.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Loss for final step: 0.46488184.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gbdt_classifier.train(train_input_fn, max_steps=max_steps)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Calling model_fn.\n",
+ "WARNING:tensorflow:From /home/user/anaconda3/envs/py2/lib/python2.7/site-packages/tensorflow_core/python/ops/metrics_impl.py:2029: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "Deprecated in favor of operator or tf.math.divide.\n",
+ "WARNING:tensorflow:From /home/user/anaconda3/envs/py2/lib/python2.7/site-packages/tensorflow_estimator/python/estimator/canned/head.py:619: auc (from tensorflow.python.ops.metrics_impl) is deprecated and will be removed in a future version.\n",
+ "Instructions for updating:\n",
+ "The value of AUC returned by this may race with the update so this is deprected. Please use tf.keras.metrics.AUC instead.\n",
+ "WARNING:tensorflow:Trapezoidal rule is known to produce incorrect PR-AUCs; please switch to \"careful_interpolation\" instead.\n",
+ "WARNING:tensorflow:Trapezoidal rule is known to produce incorrect PR-AUCs; please switch to \"careful_interpolation\" instead.\n",
+ "INFO:tensorflow:Done calling model_fn.\n",
+ "INFO:tensorflow:Starting evaluation at 2020-07-15T00:50:36Z\n",
+ "INFO:tensorflow:Graph was finalized.\n",
+ "INFO:tensorflow:Restoring parameters from /tmp/tmp5h6BoR/model.ckpt-2000\n",
+ "INFO:tensorflow:Running local_init_op.\n",
+ "INFO:tensorflow:Done running local_init_op.\n",
+ "INFO:tensorflow:Inference Time : 0.56490s\n",
+ "INFO:tensorflow:Finished evaluation at 2020-07-15-00:50:37\n",
+ "INFO:tensorflow:Saving dict for global step 2000: accuracy = 0.87376237, accuracy_baseline = 0.63118815, auc = 0.92280567, auc_precision_recall = 0.9104949, average_loss = 0.38236493, global_step = 2000, label/mean = 0.36881188, loss = 0.38619137, precision = 0.8888889, prediction/mean = 0.378958, recall = 0.7516779\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 2000: /tmp/tmp5h6BoR/model.ckpt-2000\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "{'accuracy': 0.87376237,\n",
+ " 'accuracy_baseline': 0.63118815,\n",
+ " 'auc': 0.92280567,\n",
+ " 'auc_precision_recall': 0.9104949,\n",
+ " 'average_loss': 0.38236493,\n",
+ " 'global_step': 2000,\n",
+ " 'label/mean': 0.36881188,\n",
+ " 'loss': 0.38619137,\n",
+ " 'precision': 0.8888889,\n",
+ " 'prediction/mean': 0.378958,\n",
+ " 'recall': 0.7516779}"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gbdt_classifier.evaluate(test_train_input_fn)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Calling model_fn.\n",
+ "WARNING:tensorflow:Trapezoidal rule is known to produce incorrect PR-AUCs; please switch to \"careful_interpolation\" instead.\n",
+ "WARNING:tensorflow:Trapezoidal rule is known to produce incorrect PR-AUCs; please switch to \"careful_interpolation\" instead.\n",
+ "INFO:tensorflow:Done calling model_fn.\n",
+ "INFO:tensorflow:Starting evaluation at 2020-07-15T00:50:38Z\n",
+ "INFO:tensorflow:Graph was finalized.\n",
+ "INFO:tensorflow:Restoring parameters from /tmp/tmp5h6BoR/model.ckpt-2000\n",
+ "INFO:tensorflow:Running local_init_op.\n",
+ "INFO:tensorflow:Done running local_init_op.\n",
+ "INFO:tensorflow:Inference Time : 0.56883s\n",
+ "INFO:tensorflow:Finished evaluation at 2020-07-15-00:50:38\n",
+ "INFO:tensorflow:Saving dict for global step 2000: accuracy = 0.78431374, accuracy_baseline = 0.5588235, auc = 0.8458089, auc_precision_recall = 0.86285317, average_loss = 0.49404, global_step = 2000, label/mean = 0.44117647, loss = 0.49404, precision = 0.87096775, prediction/mean = 0.37467176, recall = 0.6\n",
+ "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 2000: /tmp/tmp5h6BoR/model.ckpt-2000\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "{'accuracy': 0.78431374,\n",
+ " 'accuracy_baseline': 0.5588235,\n",
+ " 'auc': 0.8458089,\n",
+ " 'auc_precision_recall': 0.86285317,\n",
+ " 'average_loss': 0.49404,\n",
+ " 'global_step': 2000,\n",
+ " 'label/mean': 0.44117647,\n",
+ " 'loss': 0.49404,\n",
+ " 'precision': 0.87096775,\n",
+ " 'prediction/mean': 0.37467176,\n",
+ " 'recall': 0.6}"
+ ]
+ },
+ "execution_count": 8,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gbdt_classifier.evaluate(test_input_fn)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### GBDT Regressor"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Build the input function.\n",
+ "train_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(\n",
+ " x={'x': x_train}, y=y_train,\n",
+ " batch_size=batch_size, num_epochs=None, shuffle=True)\n",
+ "test_input_fn = tf.compat.v1.estimator.inputs.numpy_input_fn(\n",
+ " x={'x': x_test}, y=y_test,\n",
+ " batch_size=batch_size, num_epochs=1, shuffle=False)\n",
+ "# GBDT Models from TF Estimator requires 'feature_column' data format.\n",
+ "feature_columns = [tf.feature_column.numeric_column(key='x', shape=(num_features,))]"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Using default config.\n",
+ "WARNING:tensorflow:Using temporary folder as model directory: /tmp/tmpts3Kmu\n",
+ "INFO:tensorflow:Using config: {'_save_checkpoints_secs': 600, '_num_ps_replicas': 0, '_keep_checkpoint_max': 5, '_task_type': 'worker', '_global_id_in_cluster': 0, '_is_chief': True, '_cluster_spec': ClusterSpec({}), '_model_dir': '/tmp/tmpts3Kmu', '_protocol': None, '_save_checkpoints_steps': None, '_keep_checkpoint_every_n_hours': 10000, '_service': None, '_session_config': allow_soft_placement: true\n",
+ "graph_options {\n",
+ " rewrite_options {\n",
+ " meta_optimizer_iterations: ONE\n",
+ " }\n",
+ "}\n",
+ ", '_tf_random_seed': None, '_save_summary_steps': 100, '_device_fn': None, '_session_creation_timeout_secs': 7200, '_experimental_distribute': None, '_num_worker_replicas': 1, '_task_id': 0, '_log_step_count_steps': 100, '_experimental_max_worker_delay_secs': None, '_evaluation_master': '', '_eval_distribute': None, '_train_distribute': None, '_master': ''}\n"
+ ]
+ }
+ ],
+ "source": [
+ "gbdt_regressor = tf.estimator.BoostedTreesRegressor(\n",
+ " n_batches_per_layer=num_batches_per_layer,\n",
+ " feature_columns=feature_columns, \n",
+ " learning_rate=learning_rate, \n",
+ " n_trees=num_trees,\n",
+ " max_depth=max_depth,\n",
+ " l1_regularization=l1_regul, \n",
+ " l2_regularization=l2_regul\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Calling model_fn.\n",
+ "INFO:tensorflow:Done calling model_fn.\n",
+ "INFO:tensorflow:Create CheckpointSaverHook.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Graph was finalized.\n",
+ "INFO:tensorflow:Running local_init_op.\n",
+ "INFO:tensorflow:Done running local_init_op.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Saving checkpoints for 0 into /tmp/tmpts3Kmu/model.ckpt.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:loss = 584.82294, step = 0\n",
+ "INFO:tensorflow:loss = 560.2794, step = 0 (0.369 sec)\n",
+ "INFO:tensorflow:loss = 606.68115, step = 0 (0.156 sec)\n",
+ "INFO:tensorflow:loss = 583.2771, step = 0 (0.155 sec)\n",
+ "INFO:tensorflow:loss = 603.4647, step = 0 (0.160 sec)\n",
+ "INFO:tensorflow:loss = 605.8213, step = 0 (0.153 sec)\n",
+ "INFO:tensorflow:loss = 577.5599, step = 0 (0.157 sec)\n",
+ "INFO:tensorflow:loss = 585.297, step = 0 (0.157 sec)\n",
+ "INFO:tensorflow:loss = 545.26074, step = 0 (0.156 sec)\n",
+ "INFO:tensorflow:loss = 597.91046, step = 0 (0.190 sec)\n",
+ "INFO:tensorflow:loss = 600.55396, step = 0 (0.174 sec)\n",
+ "INFO:tensorflow:global_step/sec: 47.5449\n",
+ "INFO:tensorflow:loss = 539.62646, step = 100 (0.280 sec)\n",
+ "INFO:tensorflow:global_step/sec: 592.267\n",
+ "INFO:tensorflow:loss = 573.9592, step = 200 (0.169 sec)\n",
+ "INFO:tensorflow:global_step/sec: 573.943\n",
+ "INFO:tensorflow:loss = 617.79407, step = 300 (0.175 sec)\n",
+ "INFO:tensorflow:global_step/sec: 583.88\n",
+ "INFO:tensorflow:loss = 593.62915, step = 400 (0.171 sec)\n",
+ "INFO:tensorflow:global_step/sec: 595.888\n",
+ "INFO:tensorflow:loss = 594.5435, step = 500 (0.168 sec)\n",
+ "INFO:tensorflow:global_step/sec: 610.997\n",
+ "INFO:tensorflow:loss = 579.5427, step = 600 (0.163 sec)\n",
+ "INFO:tensorflow:global_step/sec: 625.07\n",
+ "INFO:tensorflow:loss = 555.19604, step = 700 (0.160 sec)\n",
+ "INFO:tensorflow:global_step/sec: 674.427\n",
+ "INFO:tensorflow:loss = 585.61127, step = 800 (0.149 sec)\n",
+ "INFO:tensorflow:global_step/sec: 652.597\n",
+ "INFO:tensorflow:loss = 645.147, step = 900 (0.153 sec)\n",
+ "INFO:tensorflow:global_step/sec: 656.608\n",
+ "INFO:tensorflow:loss = 65.438034, step = 1000 (0.152 sec)\n",
+ "INFO:tensorflow:global_step/sec: 660.171\n",
+ "INFO:tensorflow:loss = 57.25811, step = 1100 (0.151 sec)\n",
+ "INFO:tensorflow:global_step/sec: 676.676\n",
+ "INFO:tensorflow:loss = 70.39737, step = 1200 (0.148 sec)\n",
+ "INFO:tensorflow:global_step/sec: 664.916\n",
+ "INFO:tensorflow:loss = 63.969463, step = 1300 (0.150 sec)\n",
+ "INFO:tensorflow:global_step/sec: 679.204\n",
+ "INFO:tensorflow:loss = 55.910896, step = 1400 (0.147 sec)\n",
+ "INFO:tensorflow:global_step/sec: 680.936\n",
+ "INFO:tensorflow:loss = 58.16027, step = 1500 (0.147 sec)\n",
+ "INFO:tensorflow:global_step/sec: 670.412\n",
+ "INFO:tensorflow:loss = 66.20054, step = 1600 (0.149 sec)\n",
+ "INFO:tensorflow:global_step/sec: 673.441\n",
+ "INFO:tensorflow:loss = 52.643417, step = 1700 (0.149 sec)\n",
+ "INFO:tensorflow:global_step/sec: 684.782\n",
+ "INFO:tensorflow:loss = 59.981026, step = 1800 (0.145 sec)\n",
+ "INFO:tensorflow:global_step/sec: 684.191\n",
+ "INFO:tensorflow:loss = 65.427055, step = 1900 (0.146 sec)\n",
+ "INFO:tensorflow:global_step/sec: 683.812\n",
+ "INFO:tensorflow:Saving checkpoints for 2000 into /tmp/tmpts3Kmu/model.ckpt.\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Loss for final step: 42.740192.\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gbdt_regressor.train(train_input_fn, max_steps=max_steps)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "INFO:tensorflow:Calling model_fn.\n",
+ "INFO:tensorflow:Done calling model_fn.\n",
+ "INFO:tensorflow:Starting evaluation at 2020-07-15T00:50:45Z\n",
+ "INFO:tensorflow:Graph was finalized.\n",
+ "INFO:tensorflow:Restoring parameters from /tmp/tmpts3Kmu/model.ckpt-2000\n",
+ "INFO:tensorflow:Running local_init_op.\n",
+ "INFO:tensorflow:Done running local_init_op.\n",
+ "INFO:tensorflow:Inference Time : 0.24467s\n",
+ "INFO:tensorflow:Finished evaluation at 2020-07-15-00:50:45\n",
+ "INFO:tensorflow:Saving dict for global step 2000: average_loss = 30.202602, global_step = 2000, label/mean = 23.078432, loss = 30.202602, prediction/mean = 22.536291\n",
+ "WARNING:tensorflow:Issue encountered when serializing resources.\n",
+ "Type is unsupported, or the types of the items don't match field type in CollectionDef. Note this is a warning and probably safe to ignore.\n",
+ "'_Resource' object has no attribute 'name'\n",
+ "INFO:tensorflow:Saving 'checkpoint_path' summary for global step 2000: /tmp/tmpts3Kmu/model.ckpt-2000\n"
+ ]
+ },
+ {
+ "data": {
+ "text/plain": [
+ "{'average_loss': 30.202602,\n",
+ " 'global_step': 2000,\n",
+ " 'label/mean': 23.078432,\n",
+ " 'loss': 30.202602,\n",
+ " 'prediction/mean': 22.536291}"
+ ]
+ },
+ "execution_count": 12,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "gbdt_regressor.evaluate(test_input_fn)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.18"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v2/notebooks/2_BasicModels/linear_regression.ipynb b/tensorflow_v2/notebooks/2_BasicModels/linear_regression.ipynb
index 7116c477..45a16990 100644
--- a/tensorflow_v2/notebooks/2_BasicModels/linear_regression.ipynb
+++ b/tensorflow_v2/notebooks/2_BasicModels/linear_regression.ipynb
@@ -56,8 +56,7 @@
"X = np.array([3.3,4.4,5.5,6.71,6.93,4.168,9.779,6.182,7.59,2.167,\n",
" 7.042,10.791,5.313,7.997,5.654,9.27,3.1])\n",
"Y = np.array([1.7,2.76,2.09,3.19,1.694,1.573,3.366,2.596,2.53,1.221,\n",
- " 2.827,3.465,1.65,2.904,2.42,2.94,1.3])\n",
- "n_samples = X.shape[0]"
+ " 2.827,3.465,1.65,2.904,2.42,2.94,1.3])\n"
]
},
{
@@ -76,7 +75,7 @@
"\n",
"# Mean square error.\n",
"def mean_square(y_pred, y_true):\n",
- " return tf.reduce_sum(tf.pow(y_pred-y_true, 2)) / (2 * n_samples)\n",
+ " return tf.reduce_mean(tf.square(y_pred - y_true))\n",
"\n",
"# Stochastic Gradient Descent Optimizer.\n",
"optimizer = tf.optimizers.SGD(learning_rate)"
diff --git a/tensorflow_v2/notebooks/2_BasicModels/logistic_regression.ipynb b/tensorflow_v2/notebooks/2_BasicModels/logistic_regression.ipynb
index 63a6eba4..f18f4ae2 100644
--- a/tensorflow_v2/notebooks/2_BasicModels/logistic_regression.ipynb
+++ b/tensorflow_v2/notebooks/2_BasicModels/logistic_regression.ipynb
@@ -109,7 +109,7 @@
" # Clip prediction values to avoid log(0) error.\n",
" y_pred = tf.clip_by_value(y_pred, 1e-9, 1.)\n",
" # Compute cross-entropy.\n",
- " return tf.reduce_mean(-tf.reduce_sum(y_true * tf.math.log(y_pred)))\n",
+ " return tf.reduce_mean(-tf.reduce_sum(y_true * tf.math.log(y_pred),1))\n",
"\n",
"# Accuracy metric.\n",
"def accuracy(y_pred, y_true):\n",
diff --git a/tensorflow_v2/notebooks/2_BasicModels/word2vec.ipynb b/tensorflow_v2/notebooks/2_BasicModels/word2vec.ipynb
new file mode 100644
index 00000000..9cab69cd
--- /dev/null
+++ b/tensorflow_v2/notebooks/2_BasicModels/word2vec.ipynb
@@ -0,0 +1,724 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Word2Vec (Word Embedding)\n",
+ "\n",
+ "Implement Word2Vec algorithm to compute vector representations of words, with TensorFlow 2.0. This example is using a small chunk of Wikipedia articles to train from.\n",
+ "\n",
+ "More info: [Mikolov, Tomas et al. \"Efficient Estimation of Word Representations in Vector Space.\", 2013](https://arxiv.org/pdf/1301.3781.pdf)\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import division, print_function, absolute_import\n",
+ "\n",
+ "import collections\n",
+ "import os\n",
+ "import random\n",
+ "import urllib\n",
+ "import zipfile\n",
+ "\n",
+ "import numpy as np\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Training Parameters.\n",
+ "learning_rate = 0.1\n",
+ "batch_size = 128\n",
+ "num_steps = 3000000\n",
+ "display_step = 10000\n",
+ "eval_step = 200000\n",
+ "\n",
+ "# Evaluation Parameters.\n",
+ "eval_words = ['five', 'of', 'going', 'hardware', 'american', 'britain']\n",
+ "\n",
+ "# Word2Vec Parameters.\n",
+ "embedding_size = 200 # Dimension of the embedding vector.\n",
+ "max_vocabulary_size = 50000 # Total number of different words in the vocabulary.\n",
+ "min_occurrence = 10 # Remove all words that does not appears at least n times.\n",
+ "skip_window = 3 # How many words to consider left and right.\n",
+ "num_skips = 2 # How many times to reuse an input to generate a label.\n",
+ "num_sampled = 64 # Number of negative examples to sample."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download a small chunk of Wikipedia articles collection.\n",
+ "url = 'http://mattmahoney.net/dc/text8.zip'\n",
+ "data_path = 'text8.zip'\n",
+ "if not os.path.exists(data_path):\n",
+ " print(\"Downloading the dataset... (It may take some time)\")\n",
+ " filename, _ = urllib.urlretrieve(url, data_path)\n",
+ " print(\"Done!\")\n",
+ "# Unzip the dataset file. Text has already been processed.\n",
+ "with zipfile.ZipFile(data_path) as f:\n",
+ " text_words = f.read(f.namelist()[0]).lower().split()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Words count: 17005207\n",
+ "Unique words: 253854\n",
+ "Vocabulary size: 47135\n",
+ "Most common words: [('UNK', 444176), ('the', 1061396), ('of', 593677), ('and', 416629), ('one', 411764), ('in', 372201), ('a', 325873), ('to', 316376), ('zero', 264975), ('nine', 250430)]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Build the dictionary and replace rare words with UNK token.\n",
+ "count = [('UNK', -1)]\n",
+ "# Retrieve the most common words.\n",
+ "count.extend(collections.Counter(text_words).most_common(max_vocabulary_size - 1))\n",
+ "# Remove samples with less than 'min_occurrence' occurrences.\n",
+ "for i in range(len(count) - 1, -1, -1):\n",
+ " if count[i][1] < min_occurrence:\n",
+ " count.pop(i)\n",
+ " else:\n",
+ " # The collection is ordered, so stop when 'min_occurrence' is reached.\n",
+ " break\n",
+ "# Compute the vocabulary size.\n",
+ "vocabulary_size = len(count)\n",
+ "# Assign an id to each word.\n",
+ "word2id = dict()\n",
+ "for i, (word, _)in enumerate(count):\n",
+ " word2id[word] = i\n",
+ "\n",
+ "data = list()\n",
+ "unk_count = 0\n",
+ "for word in text_words:\n",
+ " # Retrieve a word id, or assign it index 0 ('UNK') if not in dictionary.\n",
+ " index = word2id.get(word, 0)\n",
+ " if index == 0:\n",
+ " unk_count += 1\n",
+ " data.append(index)\n",
+ "count[0] = ('UNK', unk_count)\n",
+ "id2word = dict(zip(word2id.values(), word2id.keys()))\n",
+ "\n",
+ "print(\"Words count:\", len(text_words))\n",
+ "print(\"Unique words:\", len(set(text_words)))\n",
+ "print(\"Vocabulary size:\", vocabulary_size)\n",
+ "print(\"Most common words:\", count[:10])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "data_index = 0\n",
+ "# Generate training batch for the skip-gram model.\n",
+ "def next_batch(batch_size, num_skips, skip_window):\n",
+ " global data_index\n",
+ " assert batch_size % num_skips == 0\n",
+ " assert num_skips <= 2 * skip_window\n",
+ " batch = np.ndarray(shape=(batch_size), dtype=np.int32)\n",
+ " labels = np.ndarray(shape=(batch_size, 1), dtype=np.int32)\n",
+ " # get window size (words left and right + current one).\n",
+ " span = 2 * skip_window + 1\n",
+ " buffer = collections.deque(maxlen=span)\n",
+ " if data_index + span > len(data):\n",
+ " data_index = 0\n",
+ " buffer.extend(data[data_index:data_index + span])\n",
+ " data_index += span\n",
+ " for i in range(batch_size // num_skips):\n",
+ " context_words = [w for w in range(span) if w != skip_window]\n",
+ " words_to_use = random.sample(context_words, num_skips)\n",
+ " for j, context_word in enumerate(words_to_use):\n",
+ " batch[i * num_skips + j] = buffer[skip_window]\n",
+ " labels[i * num_skips + j, 0] = buffer[context_word]\n",
+ " if data_index == len(data):\n",
+ " buffer.extend(data[0:span])\n",
+ " data_index = span\n",
+ " else:\n",
+ " buffer.append(data[data_index])\n",
+ " data_index += 1\n",
+ " # Backtrack a little bit to avoid skipping words in the end of a batch.\n",
+ " data_index = (data_index + len(data) - span) % len(data)\n",
+ " return batch, labels"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Ensure the following ops & var are assigned on CPU\n",
+ "# (some ops are not compatible on GPU).\n",
+ "with tf.device('/cpu:0'):\n",
+ " # Create the embedding variable (each row represent a word embedding vector).\n",
+ " embedding = tf.Variable(tf.random.normal([vocabulary_size, embedding_size]))\n",
+ " # Construct the variables for the NCE loss.\n",
+ " nce_weights = tf.Variable(tf.random.normal([vocabulary_size, embedding_size]))\n",
+ " nce_biases = tf.Variable(tf.zeros([vocabulary_size]))\n",
+ "\n",
+ "def get_embedding(x):\n",
+ " with tf.device('/cpu:0'):\n",
+ " # Lookup the corresponding embedding vectors for each sample in X.\n",
+ " x_embed = tf.nn.embedding_lookup(embedding, x)\n",
+ " return x_embed\n",
+ "\n",
+ "def nce_loss(x_embed, y):\n",
+ " with tf.device('/cpu:0'):\n",
+ " # Compute the average NCE loss for the batch.\n",
+ " y = tf.cast(y, tf.int64)\n",
+ " loss = tf.reduce_mean(\n",
+ " tf.nn.nce_loss(weights=nce_weights,\n",
+ " biases=nce_biases,\n",
+ " labels=y,\n",
+ " inputs=x_embed,\n",
+ " num_sampled=num_sampled,\n",
+ " num_classes=vocabulary_size))\n",
+ " return loss\n",
+ "\n",
+ "# Evaluation.\n",
+ "def evaluate(x_embed):\n",
+ " with tf.device('/cpu:0'):\n",
+ " # Compute the cosine similarity between input data embedding and every embedding vectors\n",
+ " x_embed = tf.cast(x_embed, tf.float32)\n",
+ " x_embed_norm = x_embed / tf.sqrt(tf.reduce_sum(tf.square(x_embed)))\n",
+ " embedding_norm = embedding / tf.sqrt(tf.reduce_sum(tf.square(embedding), 1, keepdims=True), tf.float32)\n",
+ " cosine_sim_op = tf.matmul(x_embed_norm, embedding_norm, transpose_b=True)\n",
+ " return cosine_sim_op\n",
+ "\n",
+ "# Define the optimizer.\n",
+ "optimizer = tf.optimizers.SGD(learning_rate)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Optimization process. \n",
+ "def run_optimization(x, y):\n",
+ " with tf.device('/cpu:0'):\n",
+ " # Wrap computation inside a GradientTape for automatic differentiation.\n",
+ " with tf.GradientTape() as g:\n",
+ " emb = get_embedding(x)\n",
+ " loss = nce_loss(emb, y)\n",
+ "\n",
+ " # Compute gradients.\n",
+ " gradients = g.gradient(loss, [embedding, nce_weights, nce_biases])\n",
+ "\n",
+ " # Update W and b following gradients.\n",
+ " optimizer.apply_gradients(zip(gradients, [embedding, nce_weights, nce_biases]))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "step: 1, loss: 504.444214\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: censure, stricken, anglicanism, stick, streetcars, shrines, horrified, sparkle,\n",
+ "\"of\" nearest neighbors: jolly, weary, clinicians, kerouac, economist, owls, safe, playoff,\n",
+ "\"going\" nearest neighbors: filament, platforms, moderately, micheal, despotic, krag, disclosed, your,\n",
+ "\"hardware\" nearest neighbors: occupants, paraffin, vera, reorganized, rename, declares, prima, condoned,\n",
+ "\"american\" nearest neighbors: portfolio, rhein, aalto, angle, lifeson, tucker, sexton, dench,\n",
+ "\"britain\" nearest neighbors: indivisible, disbelief, scripture, pepsi, scriptores, sighting, napalm, strike,\n",
+ "step: 10000, loss: 117.166962\n",
+ "step: 20000, loss: 65.478333\n",
+ "step: 30000, loss: 46.580460\n",
+ "step: 40000, loss: 25.563128\n",
+ "step: 50000, loss: 50.924446\n",
+ "step: 60000, loss: 51.696526\n",
+ "step: 70000, loss: 17.272142\n",
+ "step: 80000, loss: 32.579414\n",
+ "step: 90000, loss: 68.372032\n",
+ "step: 100000, loss: 36.026573\n",
+ "step: 110000, loss: 22.502020\n",
+ "step: 120000, loss: 15.788742\n",
+ "step: 130000, loss: 31.832420\n",
+ "step: 140000, loss: 25.096617\n",
+ "step: 150000, loss: 12.013027\n",
+ "step: 160000, loss: 20.574780\n",
+ "step: 170000, loss: 12.201975\n",
+ "step: 180000, loss: 20.983793\n",
+ "step: 190000, loss: 11.366720\n",
+ "step: 200000, loss: 19.431549\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, eight, six, two, seven, nine, zero,\n",
+ "\"of\" nearest neighbors: the, a, and, first, with, on, but, from,\n",
+ "\"going\" nearest neighbors: have, more, used, out, be, with, on, however,\n",
+ "\"hardware\" nearest neighbors: be, known, system, apollo, and, a, such, used,\n",
+ "\"american\" nearest neighbors: UNK, and, from, s, at, in, after, about,\n",
+ "\"britain\" nearest neighbors: of, and, many, the, as, used, but, such,\n",
+ "step: 210000, loss: 16.361233\n",
+ "step: 220000, loss: 17.529526\n",
+ "step: 230000, loss: 16.805817\n",
+ "step: 240000, loss: 6.365625\n",
+ "step: 250000, loss: 8.083097\n",
+ "step: 260000, loss: 11.262514\n",
+ "step: 270000, loss: 9.842708\n",
+ "step: 280000, loss: 6.363440\n",
+ "step: 290000, loss: 8.732617\n",
+ "step: 300000, loss: 10.484728\n",
+ "step: 310000, loss: 12.099487\n",
+ "step: 320000, loss: 11.496288\n",
+ "step: 330000, loss: 9.283813\n",
+ "step: 340000, loss: 10.777218\n",
+ "step: 350000, loss: 16.310440\n",
+ "step: 360000, loss: 7.495782\n",
+ "step: 370000, loss: 9.287696\n",
+ "step: 380000, loss: 6.982735\n",
+ "step: 390000, loss: 8.549622\n",
+ "step: 400000, loss: 8.388112\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, two, seven, eight, one, zero,\n",
+ "\"of\" nearest neighbors: the, a, with, also, for, and, which, by,\n",
+ "\"going\" nearest neighbors: have, are, both, called, being, a, of, had,\n",
+ "\"hardware\" nearest neighbors: may, de, some, have, so, which, other, also,\n",
+ "\"american\" nearest neighbors: s, british, UNK, from, in, including, first, see,\n",
+ "\"britain\" nearest neighbors: against, include, including, both, british, other, an, most,\n",
+ "step: 410000, loss: 8.757725\n",
+ "step: 420000, loss: 12.303110\n",
+ "step: 430000, loss: 12.325478\n",
+ "step: 440000, loss: 7.659882\n",
+ "step: 450000, loss: 6.028089\n",
+ "step: 460000, loss: 12.700299\n",
+ "step: 470000, loss: 7.063077\n",
+ "step: 480000, loss: 18.004183\n",
+ "step: 490000, loss: 7.510474\n",
+ "step: 500000, loss: 10.089376\n",
+ "step: 510000, loss: 11.404436\n",
+ "step: 520000, loss: 9.494527\n",
+ "step: 530000, loss: 7.797963\n",
+ "step: 540000, loss: 7.390718\n",
+ "step: 550000, loss: 13.911215\n",
+ "step: 560000, loss: 6.975731\n",
+ "step: 570000, loss: 6.179163\n",
+ "step: 580000, loss: 7.066525\n",
+ "step: 590000, loss: 6.487288\n",
+ "step: 600000, loss: 5.361528\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, six, three, seven, two, one, eight, zero,\n",
+ "\"of\" nearest neighbors: the, and, from, with, a, including, in, include,\n",
+ "\"going\" nearest neighbors: have, even, they, term, who, many, which, were,\n",
+ "\"hardware\" nearest neighbors: include, computer, an, which, other, each, than, may,\n",
+ "\"american\" nearest neighbors: english, french, s, german, from, in, film, see,\n",
+ "\"britain\" nearest neighbors: several, first, modern, part, government, german, was, were,\n",
+ "step: 610000, loss: 4.144980\n",
+ "step: 620000, loss: 5.865635\n",
+ "step: 630000, loss: 6.826498\n",
+ "step: 640000, loss: 8.376097\n",
+ "step: 650000, loss: 7.117930\n",
+ "step: 660000, loss: 7.639544\n",
+ "step: 670000, loss: 5.973255\n",
+ "step: 680000, loss: 4.908459\n",
+ "step: 690000, loss: 6.164993\n",
+ "step: 700000, loss: 7.360281\n",
+ "step: 710000, loss: 12.693079\n",
+ "step: 720000, loss: 6.410182\n",
+ "step: 730000, loss: 7.499201\n",
+ "step: 740000, loss: 6.509094\n",
+ "step: 750000, loss: 10.625893\n",
+ "step: 760000, loss: 7.177696\n",
+ "step: 770000, loss: 12.639092\n",
+ "step: 780000, loss: 8.441635\n",
+ "step: 790000, loss: 7.529139\n",
+ "step: 800000, loss: 6.579177\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, seven, eight, two, one, zero,\n",
+ "\"of\" nearest neighbors: and, with, in, the, its, from, by, including,\n",
+ "\"going\" nearest neighbors: have, they, how, include, people, however, also, their,\n",
+ "\"hardware\" nearest neighbors: computer, large, include, may, or, which, other, there,\n",
+ "\"american\" nearest neighbors: born, french, british, english, german, b, john, d,\n",
+ "\"britain\" nearest neighbors: country, including, include, general, part, various, several, by,\n",
+ "step: 810000, loss: 6.934138\n",
+ "step: 820000, loss: 5.686094\n",
+ "step: 830000, loss: 7.310243\n",
+ "step: 840000, loss: 5.028157\n",
+ "step: 850000, loss: 7.079705\n",
+ "step: 860000, loss: 6.768996\n",
+ "step: 870000, loss: 5.604030\n",
+ "step: 880000, loss: 8.208309\n",
+ "step: 890000, loss: 6.301597\n",
+ "step: 900000, loss: 5.733234\n",
+ "step: 910000, loss: 6.577081\n",
+ "step: 920000, loss: 6.774826\n",
+ "step: 930000, loss: 7.068932\n",
+ "step: 940000, loss: 6.694956\n",
+ "step: 950000, loss: 7.944673\n",
+ "step: 960000, loss: 5.988618\n",
+ "step: 970000, loss: 6.651366\n",
+ "step: 980000, loss: 4.595577\n",
+ "step: 990000, loss: 6.564834\n",
+ "step: 1000000, loss: 4.327858\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, seven, six, eight, two, nine, zero,\n",
+ "\"of\" nearest neighbors: the, first, and, became, from, under, at, with,\n",
+ "\"going\" nearest neighbors: others, has, then, have, how, become, had, also,\n",
+ "\"hardware\" nearest neighbors: computer, large, systems, these, different, either, include, using,\n",
+ "\"american\" nearest neighbors: b, born, d, UNK, nine, english, german, french,\n",
+ "\"britain\" nearest neighbors: government, island, local, country, by, including, control, within,\n",
+ "step: 1010000, loss: 5.841236\n",
+ "step: 1020000, loss: 5.805200\n",
+ "step: 1030000, loss: 9.962063\n",
+ "step: 1040000, loss: 6.281199\n",
+ "step: 1050000, loss: 7.147995\n",
+ "step: 1060000, loss: 5.721184\n",
+ "step: 1070000, loss: 7.080662\n",
+ "step: 1080000, loss: 6.638658\n",
+ "step: 1090000, loss: 5.814178\n",
+ "step: 1100000, loss: 5.195928\n",
+ "step: 1110000, loss: 6.724787\n",
+ "step: 1120000, loss: 6.503905\n",
+ "step: 1130000, loss: 5.762966\n",
+ "step: 1140000, loss: 5.790243\n",
+ "step: 1150000, loss: 5.958191\n",
+ "step: 1160000, loss: 5.997983\n",
+ "step: 1170000, loss: 7.065348\n",
+ "step: 1180000, loss: 6.073387\n",
+ "step: 1190000, loss: 6.644097\n",
+ "step: 1200000, loss: 5.934450\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, six, eight, seven, two, nine, zero,\n",
+ "\"of\" nearest neighbors: the, and, including, in, its, with, from, on,\n",
+ "\"going\" nearest neighbors: others, then, through, has, had, another, people, when,\n",
+ "\"hardware\" nearest neighbors: computer, control, systems, either, these, large, small, other,\n",
+ "\"american\" nearest neighbors: born, german, john, d, british, b, UNK, french,\n",
+ "\"britain\" nearest neighbors: local, against, british, island, country, general, including, within,\n",
+ "step: 1210000, loss: 5.832344\n",
+ "step: 1220000, loss: 6.453851\n",
+ "step: 1230000, loss: 6.583966\n",
+ "step: 1240000, loss: 5.571673\n",
+ "step: 1250000, loss: 5.720917\n",
+ "step: 1260000, loss: 7.663424\n",
+ "step: 1270000, loss: 6.583741\n",
+ "step: 1280000, loss: 8.503859\n",
+ "step: 1290000, loss: 5.540640\n",
+ "step: 1300000, loss: 6.703249\n",
+ "step: 1310000, loss: 5.274101\n",
+ "step: 1320000, loss: 5.846446\n",
+ "step: 1330000, loss: 5.438172\n",
+ "step: 1340000, loss: 6.367691\n",
+ "step: 1350000, loss: 6.558622\n",
+ "step: 1360000, loss: 9.822924\n",
+ "step: 1370000, loss: 4.982378\n",
+ "step: 1380000, loss: 6.159739\n",
+ "step: 1390000, loss: 5.819083\n",
+ "step: 1400000, loss: 7.775135\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, seven, two, eight, one, zero,\n",
+ "\"of\" nearest neighbors: and, the, in, with, its, within, for, including,\n",
+ "\"going\" nearest neighbors: others, through, while, has, to, how, particularly, their,\n",
+ "\"hardware\" nearest neighbors: computer, systems, large, control, research, using, information, either,\n",
+ "\"american\" nearest neighbors: english, french, german, born, film, british, s, former,\n",
+ "\"britain\" nearest neighbors: british, country, europe, local, military, island, against, western,\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "step: 1410000, loss: 8.214248\n",
+ "step: 1420000, loss: 4.696859\n",
+ "step: 1430000, loss: 5.873761\n",
+ "step: 1440000, loss: 5.971557\n",
+ "step: 1450000, loss: 4.992722\n",
+ "step: 1460000, loss: 5.197714\n",
+ "step: 1470000, loss: 6.916918\n",
+ "step: 1480000, loss: 6.441984\n",
+ "step: 1490000, loss: 5.443647\n",
+ "step: 1500000, loss: 5.178482\n",
+ "step: 1510000, loss: 6.060414\n",
+ "step: 1520000, loss: 6.373306\n",
+ "step: 1530000, loss: 5.098322\n",
+ "step: 1540000, loss: 6.674916\n",
+ "step: 1550000, loss: 6.712685\n",
+ "step: 1560000, loss: 5.280202\n",
+ "step: 1570000, loss: 6.454964\n",
+ "step: 1580000, loss: 4.896697\n",
+ "step: 1590000, loss: 6.239226\n",
+ "step: 1600000, loss: 5.709726\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, two, six, seven, eight, one, zero,\n",
+ "\"of\" nearest neighbors: the, and, including, in, with, within, its, following,\n",
+ "\"going\" nearest neighbors: others, people, who, they, that, far, were, have,\n",
+ "\"hardware\" nearest neighbors: computer, systems, include, high, research, some, information, large,\n",
+ "\"american\" nearest neighbors: born, english, french, british, german, d, john, b,\n",
+ "\"britain\" nearest neighbors: country, military, china, europe, against, local, central, british,\n",
+ "step: 1610000, loss: 6.334940\n",
+ "step: 1620000, loss: 5.093616\n",
+ "step: 1630000, loss: 6.119366\n",
+ "step: 1640000, loss: 4.975187\n",
+ "step: 1650000, loss: 6.490408\n",
+ "step: 1660000, loss: 7.464082\n",
+ "step: 1670000, loss: 4.977184\n",
+ "step: 1680000, loss: 5.658133\n",
+ "step: 1690000, loss: 5.352454\n",
+ "step: 1700000, loss: 6.810776\n",
+ "step: 1710000, loss: 5.687447\n",
+ "step: 1720000, loss: 5.992206\n",
+ "step: 1730000, loss: 5.513011\n",
+ "step: 1740000, loss: 5.548522\n",
+ "step: 1750000, loss: 6.200248\n",
+ "step: 1760000, loss: 13.070073\n",
+ "step: 1770000, loss: 4.621058\n",
+ "step: 1780000, loss: 5.301342\n",
+ "step: 1790000, loss: 4.777030\n",
+ "step: 1800000, loss: 6.912136\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, six, seven, eight, two, nine, zero,\n",
+ "\"of\" nearest neighbors: the, in, first, from, became, and, following, under,\n",
+ "\"going\" nearest neighbors: others, their, through, which, therefore, open, how, that,\n",
+ "\"hardware\" nearest neighbors: computer, systems, include, research, standard, different, system, small,\n",
+ "\"american\" nearest neighbors: b, d, born, actor, UNK, english, nine, german,\n",
+ "\"britain\" nearest neighbors: china, country, europe, against, canada, military, island, including,\n",
+ "step: 1810000, loss: 5.584600\n",
+ "step: 1820000, loss: 5.619820\n",
+ "step: 1830000, loss: 6.078709\n",
+ "step: 1840000, loss: 5.052518\n",
+ "step: 1850000, loss: 5.430106\n",
+ "step: 1860000, loss: 7.396770\n",
+ "step: 1870000, loss: 5.344787\n",
+ "step: 1880000, loss: 5.937998\n",
+ "step: 1890000, loss: 5.706491\n",
+ "step: 1900000, loss: 5.140662\n",
+ "step: 1910000, loss: 5.607048\n",
+ "step: 1920000, loss: 5.407231\n",
+ "step: 1930000, loss: 6.238531\n",
+ "step: 1940000, loss: 5.567973\n",
+ "step: 1950000, loss: 4.894245\n",
+ "step: 1960000, loss: 6.104193\n",
+ "step: 1970000, loss: 5.282631\n",
+ "step: 1980000, loss: 6.189069\n",
+ "step: 1990000, loss: 6.169409\n",
+ "step: 2000000, loss: 6.470152\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, seven, eight, two, nine, zero,\n",
+ "\"of\" nearest neighbors: the, its, in, with, and, including, within, against,\n",
+ "\"going\" nearest neighbors: others, only, therefore, will, how, a, far, though,\n",
+ "\"hardware\" nearest neighbors: computer, systems, for, network, software, program, research, system,\n",
+ "\"american\" nearest neighbors: born, actor, d, italian, german, john, robert, b,\n",
+ "\"britain\" nearest neighbors: china, country, europe, canada, british, former, island, france,\n",
+ "step: 2010000, loss: 5.298714\n",
+ "step: 2020000, loss: 5.494207\n",
+ "step: 2030000, loss: 5.410875\n",
+ "step: 2040000, loss: 6.228232\n",
+ "step: 2050000, loss: 5.044596\n",
+ "step: 2060000, loss: 4.624638\n",
+ "step: 2070000, loss: 4.919327\n",
+ "step: 2080000, loss: 4.639625\n",
+ "step: 2090000, loss: 4.865627\n",
+ "step: 2100000, loss: 4.951073\n",
+ "step: 2110000, loss: 5.973768\n",
+ "step: 2120000, loss: 7.366824\n",
+ "step: 2130000, loss: 5.149571\n",
+ "step: 2140000, loss: 7.846234\n",
+ "step: 2150000, loss: 5.449315\n",
+ "step: 2160000, loss: 5.359211\n",
+ "step: 2170000, loss: 5.171029\n",
+ "step: 2180000, loss: 6.106437\n",
+ "step: 2190000, loss: 6.043995\n",
+ "step: 2200000, loss: 5.642351\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, two, eight, seven, zero, one,\n",
+ "\"of\" nearest neighbors: the, and, its, see, for, in, with, including,\n",
+ "\"going\" nearest neighbors: others, therefore, how, even, them, your, have, although,\n",
+ "\"hardware\" nearest neighbors: computer, systems, system, network, program, research, software, include,\n",
+ "\"american\" nearest neighbors: english, french, german, canadian, british, film, author, italian,\n",
+ "\"britain\" nearest neighbors: europe, china, country, germany, british, england, france, throughout,\n",
+ "step: 2210000, loss: 4.427110\n",
+ "step: 2220000, loss: 6.240989\n",
+ "step: 2230000, loss: 5.184978\n",
+ "step: 2240000, loss: 8.035570\n",
+ "step: 2250000, loss: 5.793781\n",
+ "step: 2260000, loss: 4.908427\n",
+ "step: 2270000, loss: 8.807668\n",
+ "step: 2280000, loss: 6.083229\n",
+ "step: 2290000, loss: 5.773360\n",
+ "step: 2300000, loss: 5.613671\n",
+ "step: 2310000, loss: 6.080076\n",
+ "step: 2320000, loss: 5.288568\n",
+ "step: 2330000, loss: 5.949232\n",
+ "step: 2340000, loss: 5.479994\n",
+ "step: 2350000, loss: 7.717686\n",
+ "step: 2360000, loss: 5.163609\n",
+ "step: 2370000, loss: 5.989407\n",
+ "step: 2380000, loss: 5.785729\n",
+ "step: 2390000, loss: 5.345478\n",
+ "step: 2400000, loss: 6.627133\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, six, two, seven, eight, zero, nine,\n",
+ "\"of\" nearest neighbors: the, in, and, including, from, within, its, with,\n",
+ "\"going\" nearest neighbors: therefore, people, they, out, only, according, your, now,\n",
+ "\"hardware\" nearest neighbors: computer, systems, network, program, system, software, run, design,\n",
+ "\"american\" nearest neighbors: author, born, actor, english, canadian, british, italian, d,\n",
+ "\"britain\" nearest neighbors: china, europe, country, throughout, france, canada, england, western,\n",
+ "step: 2410000, loss: 5.666146\n",
+ "step: 2420000, loss: 5.316198\n",
+ "step: 2430000, loss: 5.129625\n",
+ "step: 2440000, loss: 5.247949\n",
+ "step: 2450000, loss: 5.741394\n",
+ "step: 2460000, loss: 5.833083\n",
+ "step: 2470000, loss: 7.704844\n",
+ "step: 2480000, loss: 5.398345\n",
+ "step: 2490000, loss: 5.089633\n",
+ "step: 2500000, loss: 5.620508\n",
+ "step: 2510000, loss: 4.976034\n",
+ "step: 2520000, loss: 5.884676\n",
+ "step: 2530000, loss: 6.649922\n",
+ "step: 2540000, loss: 5.002588\n",
+ "step: 2550000, loss: 5.072144\n",
+ "step: 2560000, loss: 5.165375\n",
+ "step: 2570000, loss: 5.310089\n",
+ "step: 2580000, loss: 5.481957\n",
+ "step: 2590000, loss: 6.104440\n",
+ "step: 2600000, loss: 5.339644\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: three, four, six, seven, eight, nine, two, zero,\n",
+ "\"of\" nearest neighbors: the, first, from, with, became, in, following, and,\n",
+ "\"going\" nearest neighbors: how, therefore, back, will, through, always, your, make,\n",
+ "\"hardware\" nearest neighbors: computer, systems, system, network, program, technology, design, software,\n",
+ "\"american\" nearest neighbors: actor, singer, born, b, author, d, english, writer,\n",
+ "\"britain\" nearest neighbors: europe, china, throughout, great, england, france, country, india,\n",
+ "step: 2610000, loss: 7.754117\n",
+ "step: 2620000, loss: 5.979313\n",
+ "step: 2630000, loss: 5.394362\n",
+ "step: 2640000, loss: 4.866740\n",
+ "step: 2650000, loss: 5.219806\n",
+ "step: 2660000, loss: 6.074809\n",
+ "step: 2670000, loss: 6.216953\n",
+ "step: 2680000, loss: 5.944881\n",
+ "step: 2690000, loss: 5.863350\n",
+ "step: 2700000, loss: 6.128705\n",
+ "step: 2710000, loss: 5.502523\n",
+ "step: 2720000, loss: 5.300839\n",
+ "step: 2730000, loss: 6.358493\n",
+ "step: 2740000, loss: 6.058306\n",
+ "step: 2750000, loss: 4.689510\n",
+ "step: 2760000, loss: 6.032880\n",
+ "step: 2770000, loss: 5.844904\n",
+ "step: 2780000, loss: 5.385874\n",
+ "step: 2790000, loss: 5.370956\n",
+ "step: 2800000, loss: 4.912577\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, six, three, eight, seven, two, nine, one,\n",
+ "\"of\" nearest neighbors: in, the, and, from, including, following, with, under,\n",
+ "\"going\" nearest neighbors: your, then, through, will, how, so, back, even,\n",
+ "\"hardware\" nearest neighbors: computer, systems, program, network, design, standard, physical, software,\n",
+ "\"american\" nearest neighbors: actor, singer, born, author, writer, canadian, italian, d,\n",
+ "\"britain\" nearest neighbors: europe, china, england, throughout, france, india, great, germany,\n",
+ "step: 2810000, loss: 5.897756\n",
+ "step: 2820000, loss: 7.194932\n",
+ "step: 2830000, loss: 7.430175\n",
+ "step: 2840000, loss: 7.258231\n",
+ "step: 2850000, loss: 5.837617\n",
+ "step: 2860000, loss: 5.496673\n",
+ "step: 2870000, loss: 6.173716\n",
+ "step: 2880000, loss: 6.095749\n",
+ "step: 2890000, loss: 6.064944\n",
+ "step: 2900000, loss: 5.560488\n"
+ ]
+ },
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "step: 2910000, loss: 4.966107\n",
+ "step: 2920000, loss: 5.789579\n",
+ "step: 2930000, loss: 4.525987\n",
+ "step: 2940000, loss: 6.704808\n",
+ "step: 2950000, loss: 4.506433\n",
+ "step: 2960000, loss: 6.251270\n",
+ "step: 2970000, loss: 5.588204\n",
+ "step: 2980000, loss: 5.423235\n",
+ "step: 2990000, loss: 5.613834\n",
+ "step: 3000000, loss: 5.137326\n",
+ "Evaluation...\n",
+ "\"five\" nearest neighbors: four, three, six, seven, eight, two, zero, one,\n",
+ "\"of\" nearest neighbors: the, including, and, with, in, its, includes, within,\n",
+ "\"going\" nearest neighbors: how, they, when, them, make, always, your, though,\n",
+ "\"hardware\" nearest neighbors: computer, systems, network, program, physical, design, technology, software,\n",
+ "\"american\" nearest neighbors: canadian, english, australian, british, german, film, italian, author,\n",
+ "\"britain\" nearest neighbors: europe, england, china, throughout, india, france, great, british,\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Words for testing.\n",
+ "x_test = np.array([word2id[w] for w in eval_words])\n",
+ "\n",
+ "# Run training for the given number of steps.\n",
+ "for step in xrange(1, num_steps + 1):\n",
+ " batch_x, batch_y = next_batch(batch_size, num_skips, skip_window)\n",
+ " run_optimization(batch_x, batch_y)\n",
+ " \n",
+ " if step % display_step == 0 or step == 1:\n",
+ " loss = nce_loss(get_embedding(batch_x), batch_y)\n",
+ " print(\"step: %i, loss: %f\" % (step, loss))\n",
+ " \n",
+ " # Evaluation.\n",
+ " if step % eval_step == 0 or step == 1:\n",
+ " print(\"Evaluation...\")\n",
+ " sim = evaluate(get_embedding(x_test)).numpy()\n",
+ " for i in xrange(len(eval_words)):\n",
+ " top_k = 8 # number of nearest neighbors.\n",
+ " nearest = (-sim[i, :]).argsort()[1:top_k + 1]\n",
+ " log_str = '\"%s\" nearest neighbors:' % eval_words[i]\n",
+ " for k in xrange(top_k):\n",
+ " log_str = '%s %s,' % (log_str, id2word[nearest[k]])\n",
+ " print(log_str)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v2/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb b/tensorflow_v2/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb
index 430e5bef..be88d7bf 100644
--- a/tensorflow_v2/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb
+++ b/tensorflow_v2/notebooks/3_NeuralNetworks/convolutional_network_raw.ipynb
@@ -217,7 +217,7 @@
" loss = cross_entropy(pred, y)\n",
" \n",
" # Variables to update, i.e. trainable variables.\n",
- " trainable_variables = weights.values() + biases.values()\n",
+ " trainable_variables = list(weights.values()) + list(biases.values())\n",
"\n",
" # Compute gradients.\n",
" gradients = g.gradient(loss, trainable_variables)\n",
diff --git a/tensorflow_v2/notebooks/3_NeuralNetworks/neural_network.ipynb b/tensorflow_v2/notebooks/3_NeuralNetworks/neural_network.ipynb
index 810e8fe5..a6d36146 100644
--- a/tensorflow_v2/notebooks/3_NeuralNetworks/neural_network.ipynb
+++ b/tensorflow_v2/notebooks/3_NeuralNetworks/neural_network.ipynb
@@ -111,11 +111,12 @@
" # First fully-connected hidden layer.\n",
" self.fc2 = layers.Dense(n_hidden_2, activation=tf.nn.relu)\n",
" # Second fully-connecter hidden layer.\n",
- " self.out = layers.Dense(num_classes, activation=tf.nn.softmax)\n",
+ " self.out = layers.Dense(num_classes)\n",
"\n",
" # Set forward pass.\n",
" def call(self, x, is_training=False):\n",
" x = self.fc1(x)\n",
+ " x = self.fc2(x)\n",
" x = self.out(x)\n",
" if not is_training:\n",
" # tf cross entropy expect logits without softmax, so only\n",
diff --git a/tensorflow_v2/notebooks/4_Utils/tensorboard.ipynb b/tensorflow_v2/notebooks/4_Utils/tensorboard.ipynb
new file mode 100644
index 00000000..bc7fd6d8
--- /dev/null
+++ b/tensorflow_v2/notebooks/4_Utils/tensorboard.ipynb
@@ -0,0 +1,350 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Tensorboard\n",
+ "Graph, Loss, Accuracy & Weights visualization using Tensorboard and TensorFlow v2. This example is using the MNIST database of handwritten digits (http://yann.lecun.com/exdb/mnist/).\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "import numpy as np"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Path to save logs into.\n",
+ "logs_path = '/tmp/tensorflow_logs/example/'\n",
+ "\n",
+ "# MNIST dataset parameters.\n",
+ "num_classes = 10 # total classes (0-9 digits).\n",
+ "num_features = 784 # data features (img shape: 28*28).\n",
+ "\n",
+ "# Training parameters.\n",
+ "learning_rate = 0.001\n",
+ "training_steps = 3000\n",
+ "batch_size = 256\n",
+ "display_step = 100\n",
+ "\n",
+ "# Network parameters.\n",
+ "n_hidden_1 = 128 # 1st layer number of neurons.\n",
+ "n_hidden_2 = 256 # 2nd layer number of neurons."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Prepare MNIST data.\n",
+ "from tensorflow.keras.datasets import mnist\n",
+ "(x_train, y_train), (x_test, y_test) = mnist.load_data()\n",
+ "# Convert to float32.\n",
+ "x_train, x_test = np.array(x_train, np.float32), np.array(x_test, np.float32)\n",
+ "# Flatten images to 1-D vector of 784 features (28*28).\n",
+ "x_train, x_test = x_train.reshape([-1, num_features]), x_test.reshape([-1, num_features])\n",
+ "# Normalize images value from [0, 255] to [0, 1].\n",
+ "x_train, x_test = x_train / 255., x_test / 255."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Use tf.data API to shuffle and batch data.\n",
+ "train_data = tf.data.Dataset.from_tensor_slices((x_train, y_train))\n",
+ "train_data = train_data.repeat().shuffle(5000).batch(batch_size).prefetch(1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Store layers weight & bias\n",
+ "\n",
+ "# A random value generator to initialize weights.\n",
+ "random_normal = tf.initializers.RandomNormal()\n",
+ "\n",
+ "weights = {\n",
+ " 'h1_weights': tf.Variable(random_normal([num_features, n_hidden_1]), name='h1_weights'),\n",
+ " 'h2_weights': tf.Variable(random_normal([n_hidden_1, n_hidden_2]), name='h2_weights'),\n",
+ " 'logits_weights': tf.Variable(random_normal([n_hidden_2, num_classes]), name='logits_weights')\n",
+ "}\n",
+ "biases = {\n",
+ " 'h1_bias': tf.Variable(tf.zeros([n_hidden_1]), name='h1_bias'),\n",
+ " 'h2_bias': tf.Variable(tf.zeros([n_hidden_2]), name='h2_bias'),\n",
+ " 'logits_bias': tf.Variable(tf.zeros([num_classes]), name='logits_bias')\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Construct model and encapsulating all ops into scopes, making\n",
+ "# Tensorboard's Graph visualization more convenient.\n",
+ "\n",
+ "# The computation graph to be traced.\n",
+ "@tf.function\n",
+ "def neural_net(x):\n",
+ " with tf.name_scope('Model'):\n",
+ " with tf.name_scope('HiddenLayer1'):\n",
+ " # Hidden fully connected layer with 128 neurons.\n",
+ " layer_1 = tf.add(tf.matmul(x, weights['h1_weights']), biases['h1_bias'])\n",
+ " # Apply sigmoid to layer_1 output for non-linearity.\n",
+ " layer_1 = tf.nn.sigmoid(layer_1)\n",
+ " with tf.name_scope('HiddenLayer2'):\n",
+ " # Hidden fully connected layer with 256 neurons.\n",
+ " layer_2 = tf.add(tf.matmul(layer_1, weights['h2_weights']), biases['h2_bias'])\n",
+ " # Apply sigmoid to layer_2 output for non-linearity.\n",
+ " layer_2 = tf.nn.sigmoid(layer_2)\n",
+ " with tf.name_scope('LogitsLayer'):\n",
+ " # Output fully connected layer with a neuron for each class.\n",
+ " out_layer = tf.matmul(layer_2, weights['logits_weights']) + biases['logits_bias']\n",
+ " # Apply softmax to normalize the logits to a probability distribution.\n",
+ " out_layer = tf.nn.softmax(out_layer)\n",
+ " return out_layer"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Cross-Entropy loss function.\n",
+ "def cross_entropy(y_pred, y_true):\n",
+ " with tf.name_scope('CrossEntropyLoss'):\n",
+ " # Encode label to a one hot vector.\n",
+ " y_true = tf.one_hot(y_true, depth=num_classes)\n",
+ " # Clip prediction values to avoid log(0) error.\n",
+ " y_pred = tf.clip_by_value(y_pred, 1e-9, 1.)\n",
+ " # Compute cross-entropy.\n",
+ " return tf.reduce_mean(-tf.reduce_sum(y_true * tf.math.log(y_pred)))\n",
+ "\n",
+ "# Accuracy metric.\n",
+ "def accuracy(y_pred, y_true):\n",
+ " with tf.name_scope('Accuracy'):\n",
+ " # Predicted class is the index of highest score in prediction vector (i.e. argmax).\n",
+ " correct_prediction = tf.equal(tf.argmax(y_pred, 1), tf.cast(y_true, tf.int64))\n",
+ " return tf.reduce_mean(tf.cast(correct_prediction, tf.float32), axis=-1)\n",
+ "\n",
+ "# Stochastic gradient descent optimizer.\n",
+ "with tf.name_scope('Optimizer'):\n",
+ " optimizer = tf.optimizers.SGD(learning_rate)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Optimization process. \n",
+ "def run_optimization(x, y):\n",
+ " # Wrap computation inside a GradientTape for automatic differentiation.\n",
+ " with tf.GradientTape() as g:\n",
+ " pred = neural_net(x)\n",
+ " loss = cross_entropy(pred, y)\n",
+ " \n",
+ " # Variables to update, i.e. trainable variables.\n",
+ " trainable_variables = weights.values() + biases.values()\n",
+ "\n",
+ " # Compute gradients.\n",
+ " gradients = g.gradient(loss, trainable_variables)\n",
+ " \n",
+ " # Update weights/biases following gradients.\n",
+ " optimizer.apply_gradients(zip(gradients, trainable_variables))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Visualize weights & biases as histogram in Tensorboard.\n",
+ "def summarize_weights(step):\n",
+ " for w in weights:\n",
+ " tf.summary.histogram(w.replace('_', '/'), weights[w], step=step)\n",
+ " for b in biases:\n",
+ " tf.summary.histogram(b.replace('_', '/'), biases[b], step=step)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create a Summary Writer to log the metrics to Tensorboad.\n",
+ "summary_writer = tf.summary.create_file_writer(logs_path)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "step: 100, loss: 568.735596, accuracy: 0.140625\n",
+ "step: 200, loss: 413.169342, accuracy: 0.535156\n",
+ "step: 300, loss: 250.977036, accuracy: 0.714844\n",
+ "step: 400, loss: 173.749298, accuracy: 0.800781\n",
+ "step: 500, loss: 156.936569, accuracy: 0.839844\n",
+ "step: 600, loss: 137.818451, accuracy: 0.847656\n",
+ "step: 700, loss: 93.407814, accuracy: 0.929688\n",
+ "step: 800, loss: 90.832336, accuracy: 0.906250\n",
+ "step: 900, loss: 86.932831, accuracy: 0.914062\n",
+ "step: 1000, loss: 78.824707, accuracy: 0.906250\n",
+ "step: 1100, loss: 94.388290, accuracy: 0.902344\n",
+ "step: 1200, loss: 96.240608, accuracy: 0.894531\n",
+ "step: 1300, loss: 96.657593, accuracy: 0.898438\n",
+ "step: 1400, loss: 71.909309, accuracy: 0.914062\n",
+ "step: 1500, loss: 67.343407, accuracy: 0.941406\n",
+ "step: 1600, loss: 63.693596, accuracy: 0.941406\n",
+ "step: 1700, loss: 60.081478, accuracy: 0.914062\n",
+ "step: 1800, loss: 63.764942, accuracy: 0.921875\n",
+ "step: 1900, loss: 58.722507, accuracy: 0.921875\n",
+ "step: 2000, loss: 66.727455, accuracy: 0.917969\n",
+ "step: 2100, loss: 70.566788, accuracy: 0.949219\n",
+ "step: 2200, loss: 64.642334, accuracy: 0.925781\n",
+ "step: 2300, loss: 54.872856, accuracy: 0.941406\n",
+ "step: 2400, loss: 64.342377, accuracy: 0.925781\n",
+ "step: 2500, loss: 74.306488, accuracy: 0.921875\n",
+ "step: 2600, loss: 40.165890, accuracy: 0.949219\n",
+ "step: 2700, loss: 64.992249, accuracy: 0.925781\n",
+ "step: 2800, loss: 43.422794, accuracy: 0.957031\n",
+ "step: 2900, loss: 46.625320, accuracy: 0.937500\n",
+ "step: 3000, loss: 62.517433, accuracy: 0.914062\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Run training for the given number of steps.\n",
+ "for step, (batch_x, batch_y) in enumerate(train_data.take(training_steps), 1):\n",
+ " \n",
+ " # Start to trace the computation graph. The computation graph remains \n",
+ " # the same at each step, so we just need to export it once.\n",
+ " if step == 1:\n",
+ " tf.summary.trace_on(graph=True, profiler=True)\n",
+ " \n",
+ " # Run the optimization (computation graph).\n",
+ " run_optimization(batch_x, batch_y)\n",
+ " \n",
+ " # Export the computation graph to tensorboard after the first\n",
+ " # computation step was performed.\n",
+ " if step == 1:\n",
+ " with summary_writer.as_default():\n",
+ " tf.summary.trace_export(\n",
+ " name=\"trace\",\n",
+ " step=0,\n",
+ " profiler_outdir=logs_path)\n",
+ "\n",
+ " if step % display_step == 0:\n",
+ " pred = neural_net(batch_x)\n",
+ " loss = cross_entropy(pred, batch_y)\n",
+ " acc = accuracy(pred, batch_y)\n",
+ " print(\"step: %i, loss: %f, accuracy: %f\" % (step, loss, acc))\n",
+ " \n",
+ " # Write loss/acc metrics & weights to Tensorboard every few steps, \n",
+ " # to avoid storing too much data.\n",
+ " with summary_writer.as_default():\n",
+ " tf.summary.scalar('loss', loss, step=step)\n",
+ " tf.summary.scalar('accuracy', acc, step=step)\n",
+ " summarize_weights(step)\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Run Tensorboard\n",
+ "\n",
+ "To run tensorboard, run the following command in your terminal:\n",
+ "```\n",
+ "tensorboard --logdir=/tmp/tensorflow_logs\n",
+ "```\n",
+ "\n",
+ "And then connect your web browser to: [http://localhost:6006](http://localhost:6006)\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ ""
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.18"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v2/notebooks/5_DataManagement/image_transformation.ipynb b/tensorflow_v2/notebooks/5_DataManagement/image_transformation.ipynb
new file mode 100644
index 00000000..82513157
--- /dev/null
+++ b/tensorflow_v2/notebooks/5_DataManagement/image_transformation.ipynb
@@ -0,0 +1,408 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Image Transformation (i.e. Image Augmentation)\n",
+ "\n",
+ "Learn how to apply various image augmentation techniques with TensorFlow 2.0. The transformations are meant to be applied for each image sample when training only, and each transformation will be performed with random parameters.\n",
+ "\n",
+ "**Transformations:**\n",
+ "- Random flip left-right\n",
+ "- Random contrast, brightness, saturation and hue\n",
+ "- Random distortion and crop\n",
+ "\n",
+ "For more information about loading data with TF2.0, see: [load_data.ipynb](load_data.ipynb)\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "from IPython.display import Image as IImage, display\n",
+ "import numpy as np\n",
+ "import PIL\n",
+ "from PIL import Image\n",
+ "import random\n",
+ "import requests\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download an image.\n",
+ "d = requests.get(\"https://www.paristoolkit.com/Images/xeffel_view.jpg.pagespeed.ic.8XcZNqpzSj.jpg\")\n",
+ "with open(\"image.jpeg\", \"wb\") as f:\n",
+ " f.write(d.content)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load image to numpy array.\n",
+ "img = PIL.Image.open('image.jpeg')\n",
+ "img.load()\n",
+ "img_array = np.array(img)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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bb/z845WVFc9Bjg1kSQZECQNkjQPTSAdpKsvo/PnzXLDDex841mhz5/bp5BkgSm/+cmNvbzw7nf/ulYX9mtYYhLarE6w5PscYQygBEF9rxcREAiFECMU74JiYxwjy2dXvZz8d/3I86QIAEELHN8THv2AkQwghAgBwxgTGRJIkSikCujWiC/NrnG3dub2dTCbn55K9Xs91GA1t39vJ5dOKqhCSzBdyU1Pl8mx6MG7t7h/d/OC9XP7r/RF0IUsunWJI50QC8hgynUEUsECBkGCJAf8hVVFMzKOLEAJ+7vw5noBjYh4jiBDi+KM9/vN40hVCjMfj4+/5V6wSIAJCcAgA55zSQJIxIUSSiGV577//4erq6sz0rG3bvu97HgMAyDIhhIxGI8YDVZXbnW6j0apWK9/8x78xp64F4c3tTTo9k3v+5XN9Bnwl/eHtVm+MHJ5hsskhw0RAwAlUmIgn4JiY+xPPvjExjyORd8C+7yOEJEn6bA4+/rzD0GcslGUZEwigwBhhDDCGAEJK6d27t/OFHISCsSAIvVQq6XtU0yWEDUKIoqiGrtmW32mPfvif/+KpZ15dXP52SEQgTwOck/zQGsGbtj72IJMSPoZc+JIMQMAFZSDCSDkm5gvOZwvoeA6OiXm8iDRtIp8DY4wQ+nQaFgIwiIQsS7JMMIYAcsZDVZWz2TTj1LJGlHmlcn5ubnps9TVdVlVFliXPc8djS5JUSVIxlsHYvnfjqD9IAfVMfay1x5RRjH1os+LAT3ApQwF2qYMwBTwUNPw11klMzGPGr8y7cSiqmJjHAgI+lYp+/jIYQqjrScZYGIau6x1LgQkhGMsAUM4BDQHFQlYUjJGqqoV8pdZqje2OqoeIIFUyaAgVFczNT935uHb2gvKVb7/0wbWPux3ftdSpwmlTL9dxNZBy1qGcLeuqqfkB5wSPPEflwtAB8PsaABpMAh8AAijhUEzoc3JCXSbEEbpVPul7o/5HRDpRz0dtZSbUWSIYERUHRekyJzU3jzKOmywdziN0q5O2e1S5TkgfzCOaBUXlM+L5yK1qpF72/s/bTCvAMGAuVHIJMuwC6Es56g5l8pCOjCL1x5NtzR9W2L4vmi428r2Tfi8n5LfgUQvXeFJE1fMnZ8vH58zHVpTHj1JKj0XAn/3COaeUfvbk8S/Hk7Tv+5quEoIBQEAQ2/Lb7W4un/n93/9HSwtLvY6bTGb+5b/851/92vN+2LVpXTbscqVSqU6nkhkAEOfg+EWKHMdQi4mZAM/zMIGEEMbYsWgQQ5RKpR52vmJiYv7LfGKE9ZmA4TNr5yAIjp84noD/ygoaS5/9whg7njs550CiAHCJKNlMIQxQo3m0v797dz375S9//Wdv/eD1N1//Enjq8pW14tT03u7gj/7oB1/+7d9O5/MuRQ5D6Fi8yCmEEID49Cwm5u+KaWj22Pr4w82DQsYeK4RkOKeQxZ6gY2IeAwj46wrCz9xSHp9Lf7Zx/sw6mn36bXPOAfzkoFQI4TjDkAJVBcNRP/QRQiAM/dt3rkqwPXKP/CZrNtIAiY+uHQY0V5m90BtZmTJkEHEBMEIQCkopEhyhh+RKMCbmMUTT1NFR76P19zLZpFR+Wk0ROwh919K02El6TMyjDvnshPmzCfjTDS4Af92a4/j3Y4eUAADOBUSfzNxCCFmB2bw2NVUOA7C1eajp8ukzi9WZdH80vvj0y8src7Oz82/9cv3a9aPq7MqlKy9utoRHOYWEASgBBAADgEd6zIyJibkfnusKwRljruvqBHmcQk40RY1PkmJiHn3I5ze+4K+ZYv3VpfHnZ+hjz5QQwuMzaULw8XycymbLU6kzZ5co5X4wGo0siLiqKQZkRMWWPdrZ2XUs9sqr/2Bq7lsHhyCZtZGkcQ6AQJQzzqmMMASCx+NGTMzfGQIBhYgCEXgu4IzTEGFVJZIbBg87azExMf8F/moCZp+7N4IQMsYRQscCJPDpDM05P1Ylfeoa+pOHj++MGQs6vf0gdCTVlvygP2h22vJuzaP+QFd4oVDqDxWLIah1tcxSwtMAkUQoiIwBQEIIhDAQNF64x8T83ZEV4nLKAl8wfvyRQgAojWffmJjHgE9svsXnOP7l+A74WH0kSRLG+Pixz2TB4K8rlzwv0HTFD0b9Yc1IwFI5rWkKxnh3y3FG+qAn+l1PklTXtTZ3bofcRkQKQyaEkCTlE9NzKDg9GVv2mJgvCK7tQAhTqVQ6ndZVTQjBORVxPOCYmMcBkk5m+/0OZb4AQNNAImm6ruu6TFUTQogwDD3PO370eHpOpzJBEIRhqCiKJOMgcDVdmp9fHAYbG/e25ucXZ6afbrb2feYYCdztNfLJhG2RUKRX1n5X18+VZgOoBuOBI5sJzKEEAfNcAJBEiM99qFKZJu+b0ci4tpFMqLuNeB5GyNIeuK+DSF1gpLD0/j/j+9ebEA/JZVKEvhBFXf9PnM0IJduk6UTpqqOeP7G4zpPpIAnWsa7hUDJkBJxxNqFaSLd5iMX92z1axzxZLidOJ0p/HxHn+FFDoMn0spPWJ4zST0ekzyP07oifkJ+Aib+X+/fbqH6Cn9BwXZPquckf/Ddnuh3rrTeuhp7e63gHO9bi4qozaiAJfnKi9bkwZwCAfr//aTAGhBDSNC2fz1er1WcWl15/42d7+9t+YANBut2gWWvquhoGlDLBQFBr/KxUdk09ARk8e+bVq7WQAZkLQjnggAmEJWwgKAHweHyQMTGPAowxx/WB4xKoyIIHjLo0dFlgyrGaICbmUYcUK9pTVy4gKP3JH78BkTQ9W+j29yUF9PsehIAQTAg5Fvgf70FTybQQQgBOyHGQ4HA0GtVqteWzl5999qmNrZvbm/XxAAOuEZmFoWUPBwvLxanZTKt76+r19en5OSOV07EJ1DM0xILJAEIIfUgYQipgJJ6AY2L+7iAJ+yHlHk1oCsAIYoAEJliJv6OYmEcfwij+yU9+DKD03IuLO1sNVZam0EwY8Fpt5Hme7/uU0uOtsCRJsixzzsMwhAgQQhDCnMPhcOi67u3Nj5ZOZReX85l07u7N/sFepzqbf/HLp04vl1PpnJFCN27tfv/715fntZdeeaacOfVv3+fOOGSMIgIwconMBOOe50tEe9h1EhPz+ACpAByI44gpjIsAYaArJneGDztnMTEx/wUIwrRUMff2d+aXs7pZOtrzJZj6xfvXjKTm+z5j7Njq6lh9BABwHIcxRiRMCIBIIIQgwGEY6il9dXX5a9+8wihB4APPHyu67YZHqcxUENjI0X7rO/9ocfrVznC3kCGBv5PRLnMrdBgFHAoMkZAFIoxRKT45i4n5O8OZrRIoJRIpQ1MI9+g4oBoET6hH3ZiYJwvyp3/8+tPPnqcBHg773/zW12WSefP1a0cNudOElNIw5MeG0AAASinnHEKkKIqsSABQ13VlGeuGijH2ace27a3N/fHYpnx84fK8kQAhHR7U2jzUb916+9rHncBNj5wdn5ZzqVVDQFd4kPicq56vMGhIiioR+2FXSEzM44SCAimhptRsMS1DU6ZMOL4fBh7AT6aRS0zMkwR58YVXfvH2W6NRTzcUXb3+wovPvfKNlZe+Ov9v/x/b+/v7R0dHQRAe+3mXJElRFM/1AQAIIc4B5xwhSVVVCKEbiBs3bq2v35EkRZIUz/MkCU9Vi+hUIZstGYf1G7c+qh0EZgYUq8ZMqeD2PyDALaazDFTa3VQYSILIAMcTcEzMBGDhYB6C0GNeoBi2LjFTADvkcQDtmJhHH5Kv9i89Xfr5T3vDPrv+UW1v5wez87lO96DdLgwGgyAIZVnSNO04FJLv+4qigL8eQMnzPMdxVi4ln77yQuCL9bsbrmeHgddpWc5Y7fXeqFQqhQqeWSwcHK4fHHZ+9pqzfQeztKwlULawgiTd9eTB2Ag4p2CIQRzIJSbm74o77oe9tjU49HWW4hjmchhmMGDxBBwT8+hD/ujfXYNQ6GqCyTSRQkvLMwghz5G6wzsQ6QgSxljgM8FlRZVkzfPCwLZdFcqKooQhdwKqGIlsIR2O91NyojQ9w5wxIB3dSIcB3N1uWf2RO3Cl4szU1KJ9Ae4ftEd25+7Bn5+DS0mhO3dFnxVHSolnHByE6hgK4/56NYwnjAsbwUnpdyN1kOD++edsMp1cdDzgqLiSkx05Rukao+pnUl1jJBF6x6jcR9ZPBILff+KJapdInSW8f3+LrIdJ23FCfAYAJBBRhEMCFIUbMnIIafLW7RAPxgyqSjlBcq4baKpth7aLpjVZpZQKAVVZYpyGgUMIwiLidnjCbEZN7zCyX92/3aP64Yn1tygm1NdGEaVjFlH64AhdPopql4jfUZTePap54f2Dc0SPP5N9L1HxsHHEdxell530e3/Q/eRBx2kmzZrPeGAYSjKtjMf2wcH+089c+Po3/sV/J378k7/8AEKcSGi27QsmgA+QRMfjUFEkQghEQNNlzqnjDiEyoMj/6Mc/WzuzoBuE8yQE0uJSoVDK2yMBhFQuzxJJ67avjYddiJTQVyS42LddCAVJA0OShq5CQ6iZyItdUcbE/A1UApmAoRAhZ1AwCKmCQoVwoGIhVCk0sfADb6iqKYB8nWAPOARwhABnEAlIGQUCQRDr7GNiHiGIpuQtaxD6EHDF99y93cOpqfJzz2kXzj/18Qc7jk0lmWKfElkPQ1+SJEKELMtCcE1T5uarEPJafd+yWt5RgiiWnOCFQs7Qs/tHzc6ws3I6d7S+Ebj6+t0GwtKg38xmk6pSkWARiWkfCC5nDEORhZBHasAkpgYgjAeImJhfRcUsYBIFWAgoQICFUIFtAnvoDkDomDJ3xiPKAh1h33MoJYoJZaJDpDAoAcGZwABgDGQO3IddlJiYmE8gqQxJpnOyTBJJ03Xt7e3x9/6X9+/cbCbNedNIAmEJ5JfKaRqo3a7r+1RTTYQAYz6EQlFIKq0hUup0YL+PVSPteOSg1p2bM6EM9mqHA7dhIr1Yzm9vNuyBWyrlcrkCC+W52Uq3JXNlxTGmPSphSjUMBCA2HSsRR39xkIaYLzJIhEjIBGCEhCICQh3EByBoUa8PAi+f0jSseZRJwAp8phMdeA0Nm5Ka4NgIOBdIpkKLOs+MiYl5KJB0noUBt8ZOu+2ykFA/0euOh+2WpLYV2bSdQSLNEIHO0NU0hQNXCAEAVBRlOBy+886HxZIxPVOpVqscNMcj39BTfas+Gn88PZdKp7L1w86Xn3n67PnFuYWjg/26a4nAdRjvyZq+ePrS0bAwHlUdV6gkVCQfIhRQqpCTueuNiXmS8GkAhKYgghAjdIQCK3BajDZyCSPwQLVS0TV5OBpbPodBQHQVjjuy56kKFVjYgHJk+kBmnLNYnRQT88hAlpanNzd2jmodawRSCdPQM4CZthX63lDwQJLh/GLF85x2s6+piuMygBkAyDASCiPDURcjrViolstFRWH1IwsIwHxaLuszlaKp52aKa5YVHh7VNU2US7ldu6sriplQoBgVykrXHiJ3AEFOyMRDNhVYk+R4pxsT8zcJBJQ4lACVghEKGmzYHQ3b3GuNURg4Y1PTV5fnEwnksXFGJmbaFNYQizHhSAAYiDAEkCGFMviE+sCPiXksIe1GGHiqImEXMUJAoWhK8qjR7qiKihHJF3LzC1OqKrNwZ3+nTylImApjzLZtTJCuJT2X3by+tbF+ODcLVNkLAiuhi+XZVQ2pnfqgWFB97t24XnNtSyLEGtjFfIF6Sqc2oqAJQjqVkntMG6KkCwXGXGGER4wQDzr4UEzMo4wgOggJDCwU9rh94Pe73mjoe8NeoxH6DqMimchgCYUhzZeyiUyKdzxfMM5dL0QgDADAAOuCM4Dubw0bExPz64d8/88/nKrmFClLaXtsW2s5Mrs4rZrOxm2q67rvW3t725cuX5ifn23WrEql1Oj0ABCeF6iqmsvlKaXW2KUh7La9TE76+je/Ohq6H763/sE7dxWNBkuj3/qHv7O93njv7ZvdYR+DwJbtftOHzOw6mxcv0ZW5qZ2h3+nxECoYU+hzgGP9YkzMrwJlTTAswoA5Q2Z3Q6frua4f+pXqrGtbkmwwgH03GI9sI+EDOMxo+ti3Xc4A81jIONYhCgTgAMQTcEzMowKZX5zSdKVW3185VdnZrW/trn/96698c+mVo/aPenZTokr94zHHO5evnDkdFmpH7VwRCwG7HS+TNYPQTSZN3cRHR4fFLH3p+e9+6ZmXbD+sN0a3N7d9V711L7hy9drq2nf26kIZ366mcPcgZEamMXZgiJR67tbWrUx6vZK7vGOfo3pe1mtBUELQRsAlAANuACEx4XPgImzctwCQ339rzCLOsmGEl9yJ9cERz4sIIzIY4eM6arkhJtVrRgUujoBEFJdHJDN5POb7E1XPUXo7OGGc3aj4x0DcXzcpQHj/dO6fCogKWxytXzwZnWvCbcl8LMR+4G4T4fuBNXQG8wsrz55bQgjduHHjnfffliQpDMPBeJTP5zkQo5F14+ZmveNJ2eXq+ZfKa6sBRNKEQsuJdZlRNRfZjhE62gnjDUfmM+q9EXpfHPViPKH9WsT3CyO++Mjw3Ceki438viJ1z1Fxx+/fXlHtziPGpajujyc96XzAVyroAXtV/yTUYC6XKxaLQej4gbOxsTEYDCozcO3U057Lbt2+quh+oaRhsjAYdup7rmkkU6k0IbLjDMYWg5Ankkq5fOEnP7n5/kd7X37l5bXTVza2Whtb+4qu/uinW5m7f4g0zdBmDpouhVxOFNoHu5Ln5xKwdTiqYXf63JqRM7msURdjQQVgAkAmABICAoAxxkhiJzP+x8Q8lnDf9ryBEnrUHQ+7h441wJwH9vDu3c2pqal8viwEHo1G7XZ/e3sfIZTJVGRZpYE0VakWFy9qxXkEDAnKAFgPuygxMTGfQPb2jmZnpxaXFpeW5+bmZ375yzcHg1Eikbj88txXX/l2v+sYPwhr9b39g91sujIzvdDY23Ydypjw3AGEQpZxSL1EUl3fPsRI3at1+4Pr5WrZ9VVEsO23k/ppDq1CWgvCsqOWqC76rm1m05o0lUhflFAhlx4XF7M7426vF2pQl9RQACgE5AIyziGkWAgYuT6Mecx40J5lnlQa9aPu0T3i1YB9SOgwnTIURbHGw8b+4XhkLy4uLswvAQCWFq1ut6vr+t7+kWkmM9lyKj+Vnp6xidR2Rl6oqFpc/zExjwpEVSXLsnZ29jCBT105b5pmq92sVCrtTv3atY/z2ZmzZ88rirK7ffBeY7Pf9Q29YFmO7we+7ydTKoCcMl9WVJwQipww3DTCpX4XCWHMLcwk0mxn3ZnT8XNXTjv03NXtykFfDcPO0ppqezNStpQsZKvpXS3Vs4Qv0yp2TEsgADFDEgM4FAByCgTHXEzq2nbSgT7q+UmPTGNiHgSKmZa0dOB1KIUpxUjmyghLfsjTRppSFoZUkjjGWFU1XTfK5fLCSomHiDIsiExVB5Ix5RpwZH/SM+WYmJgHBsnni/1+d1wb9QdthMRwOB6NaKvV0Yrk6tWPz6zhTCa3urqMMa4fXQVA1Ov1IKDHEZBkWcYYp1KpSqXiQ6t2WANsXCglDcPISxVJyTUaO1ze3tyyX3r+THkWSodOOnWmVHmKhjtQmaW6abne1v5VU15fPrucXc7u3azf6JeApCOS4FjCCHAaQgFhlIfTmMeNSRc6Mcfkq0uplGk31fqGR8Ne3+EIM8NMh8NmGIa+7/m+xzlPJBIQAsZor98ZD3wEVYcGA5+q5VNSWvHHITAyD7soMTExn0BGQ4tzUCyUQuoOBsNTp06Xy12IwNWrm7PTuWTKYNwbjltmEs0upGlA7t0Yjke2JEmEEENPeK4FYHCwXz994ana/vu6aacLnUF3c3DkA2rcvLHx9KtSXp9lIHScTUNJO04RCZkRyZcanYGheQg28Hbr2mD43vz8YmPXDqX/DVYA1EyICUQcQ0Q4kCChExoBndSONp4YYh4FHM8NbHswHFqObWAuIOBACAQhpKVybmFxZjQadbtdAGlI3Z3djeXVJaYGEjG4MyDhWEaYCElDydgRZUzMowPxfZ9IKAhCWVGmpqYuP3Xh448/tKxRmRQMtXz31uHB4U5vcDgzW15cmjW07NHO+44z5iJQFEOSJNsRmma4ju854bBnp81CKVvqHrWOdvdWFle+9bXnuvZbL33rSq6YtkZ9lR6Omttq4RUtd0ZFigNELpfPaAt7AT6s33KCJgrnZCVEEDCIuYBUcCQoAAQBDMCjZYUVT9gxv07s1mF971bY21SoU0jJy/MVTTUgkvKnS6lU6ty5c0KIRqMRhmGv1+t2u/X6EQuIBF0rGBEVCDr27VEmMefSeAqOiXlUIJ4XVHOV0bg3GLrtdnf97sbbb7997tyZb33tX7z/3rXv/dm7fjgsVzXXhu2m9fHBVhi6kgwloskysSyn2+kvLs2ravr69bcgB+5IeevHO5ub+9WKcfpUUSALN8vDceugtRGMWK/ezpnF5XOv3D5yWTetEhkBS6B6ruLldF3VV/noqZDIHEsBwiEAlFLIQygEgigObxrzRcYfNpz2UQL5aQMawE9LbKqSApAMrUG9fpTLZU6dOpVKJRhjnHPGWLO7Fzio0+gfNLY9HHS8Tqe/Pq3NgqgwdjExMb92YHlGFlyWZeIEg5dfWRoPgw9+2ZibeuFLX68sLk2/8+7r9zbu6LoaBFTXUqpiQO53O6PRIPA9HoZMUaSQupcunz9zMQGgkBVw9+6dW7daX375gq5l3v7F+2ZZMI/JIJlNnqrOvVKYeyHQK44gW3s5U2sRv9/Y+gCi7z/7QnfUNNHgd2+lvwmgxCECMIDAIRyQ0CDcDKVgooKdlG71pDipnXFkOlHxOyckSkcYpat+0ES1Y5Q+b9LnI3Wik+YnQn8cFQc6qr0EZbIsCyGCIMAYy7Lsed5wOBz88n8CfKhJwWypIEHF8wIs88G4ZXUdWSbJpCkAO3Vq9ey5U8mkWalUZC5mFlM7uxumVEIA3znY+r//x58tXvyvuvLM/fP/gPWOEzOh/vukiDSunLCfTJz+AyYqbnFkfN+ouOaT6pIfUr86qXqeVK8/6XsJp6rr+r7vGylAZF81rWwp7Fkf/Nmfhbl8qlBMr6ys7O3tdbsDmJNrR81Mmqcy+f6gUyxXEZQ6nZ6M5KPD+swiCKmXShvPPvv0+fOu6wa1o8b5C6uZqcr+Zi208LBH07nxFBG1Rr0zxrkM7LSvGsCfLpvWONNv9mSQq0zP1ZgahDhgMGQAII4gwBLBPMJdQkzMk8VnH/Dnv2QIIaBeNm2oMglCtzfsj8cuQ8HQ6todK5vNemHQbjevXr+e/FFCVeV0Onn5/IVCRc2kk6fmVE1Wpqamv/LlV+7VrXgDHBPz6EB0Q0KYAWwvLCfK0xLlSDXV2zdsyCq2PezebZfLOVmRTMP0fV8AbphkYals2+Nm45BRgBCGEHoBmJ17dnd3+9q1q5KEs7m0rutja1AoFLFICJpKmRkkbCJZGDcRJQVz9nD3zwk+1A2MQ4M6gQiymllotA6ZlBYsAUFSxgpUDIQpo4Iyb2JPNDFPBCclJ3uM+OyQA0IohIAQYowzaTWX1TzHbTRro4HPBJZ0WdL0ZEYqVipcMN1z2Vh4AfNCu9XtX712F2Anl00tTc2V8oXFc+cqqy97knF39HALFxMT81cQn3Wn53MQo1xBGww6TIxPra3OzcG9jYrjWBsb641GN5NJEiIzxkxTh1CUipXCq+Uf//inQoizZ8/eunWLMfv69Y8IIZlMxnGsMAzPnFlLJpOEkH/zb/7ct+WpwgLl43tbd5vWLVU/u3rqO3ZzXeAdSENTmdXKuiIjhBlQWhm17QWBEwIK0pATgZAQlApG4qV7zBeJ45XE8WSMMZZVOQidbq/VbDYEl2UtSWRJTyVGYTeTzx4dHQFENDOBEBJC+OEoU0xzSB3Xure922q1372x9dx3kvmlFx52sWJiYv4Kopkgk1MHg8AaAcdGYwuMOwMI1M3Nm5RyQlRN5YKTqalpz3Pu3NmEzGy3LMOUiqXU2umlb3zzlQ8+TPf73RvX72iaIUlSOp0tFvPJRLbVahwe7q+dKfY7rNfaUY1galatztNshgN2dXmO37x9vdEfXjxDZ+dOb+3vjd3BqZWyyKZ6A6XRBl3LCygGECJEJIWIiCuMmCebL9oO+HjXC/76BEwIafQGNOiPh72AMolgSqlljRQdmgl1ZrbS67cA1FwX+L6fSCQIlgPOZSVrA1nDfiZXqG93Dxo2KLoAJB5yCWNiYj6FlEtpgnXXtjybEaJaFt3f7CiyNnJtSZIIll3XT8/kDT05Hg91HQOu9Tp2o9GfX5i5fGUNYoeJ0cHRenW6MBiMbt0aCA5eeikhS4nAr49HgR8MVFUXaEhkVC6VTi+XcxltZ3PDZ+NqNZNO2jSsqdrM4sL0yIGCh7Yf+qHMAYRQQCC4ABxQIEjsiyPmi8Cv3AFzzo+PoK1QGvRdEQpNMRWiCQ4lDFOapiZQ0lQ49VMJlVOP+sLU1PFgaKZTng/CAKbzZmVuXi1eyS9f8ZH2iKn5YmK+0JBcLhsGTNOk4cAdDr1MNlEoGU8/c+n7P/hlEHAEZU3DkqRYlmOayX/4j37P6lIs0f4wSCb1IPBcF09PT8/Pzw8H4253qMj7O9v1O7e3dS1DKQ19srvTP3Wq+NyzS37gtGu9D4fr1ale0tTXN7fzOZAvTu/e2wfgZiF/ajzUDrfrTj5kAFOhc6hBCSDgc8oYDSUpDqP2ReQL6FDl+N73s60wAABjPLN60bvj+2NGoJCIrMuSogJDJivLM7mMUSml5ueWb92608fD6Ur5YHcHcw1xDDnK5XKzy6dm1bMtNNWlUTG2YmJiHgJkcbly48atkA+NFJ6eT549v2S7jcL04A/+4A/+w3/4I0NPzc4sWPYoDH1JBvV63e57HLjTs5n+oHvz5uDM2VNhCJ575oWdvTudztW5ublSYeGD92/cu7un6cpoNCAg0aiNMqlq2pzJJWaSBsqn4ekzszd3Bve2rs1Op3UjORpa9+5+wIK5xfkXbbsCUBqQNJcwEAGEFCFBJBQv3GO+UHy2Az7++9Kpi51urR+MEPNkLKmyIgK712hknz6dzyYuXTh76eKV0aCnyuTyxXODXjeR1Dgo7Nfq1enS7PxCxy229t0wlVTiq5yYmEcG8uJXn5lbnvnRX76xuVFbWp3e3u1fuHA5l536j3/xBkZcgD5WVBWOzIQ0Mzt1587NufnZhYXlX/7yFzKRVucvH2w0drf3g77ECL51rYEJymXzlalso97p9qimJjIFwkF3Y+eNmerayuIz2XzZTOPawA5a3kp2DbmWQ9uJfE4tnav1zo/TX2FSFgAAwAgAAMRx3EjEIYARcSijdGwY399zB2MR8Swfkl5tUr1y9B1nRLzbCXXDkXFYH3TgzSgi2jc6jun9geD+cZrFhPrmqH4SFec1ohuC6EjQnyAAABB89rY+WS2t+t3OUACruDp/tL+DAVMoRwznknk0hesHB3PVijMaHOyud5q7/+t//t/u3WuG40Y2N2frp27UONczGuJRR9BwwvZ94EFKIuPjRpxw8PvXZ2Qc3EnzeVLFekg2CghGGLFGZuf+z6MJddgPTfd8Qu+dNC71pJCQWfli8tvf/sZ/Hv/gg/dvtlvi1vW9XC437LmagfJFw0iIuVw+mZYFsKZnpepUIpECuZzmOqGqoWeefanZbB4eHPz5915zbJ7P5XyPj4YuBHIumyuXpyg4wETTDSXwR43ObYBHW7t9P7D2Rm7QGayuTCdSy10rQbRnMnMXBr4M4hV6TMzfAEKo67puJITrcMY4DYngqqreu3fv1KlTlFJZlhOJxOzsrGEYMzMzt2/fRlQtFHLFYl6WFFkWro9831VwfJUTE/OoQIYDS1NTFy5c/vjDrfqRk0kzxxLjYc/3w2xePn121tAAIqGi4HrjyHf7rc56MoWWlqc37u3/6Kc/7o26L7383MLyUw4P7tzaPtjreo5PsMGYYBSViuXD1i7GyurK6UZzr9m+q+husznaWK9ZaM6yvVQF4GTFCasyOyuRRcey5Ae8EX3crWRjvpgIwVTN1JNpjw0IBAoBgjLOIWMsn8/3er0wDAkhZ86cYYwdHR0BgFKpFBdYluVOp+c6BpY1gdBDcmgWExNzH8j/+//5Z+fPXfiN35gp5KempzvDwch1fQixYLLr90rFim54vd6ehEC/afe7fKqIagf7CKRWF09XK6FE0GhspTLms89dQlAZDW5BISql+fF4vH+w+fHVD2y/kUlnjeeyi4u4098F0J+qzG6vu50Dhwv13nVr2BlkK2fl0HAGQIEFAO2HXScxMZE8rAUcpZRIsp7IMruBIFAw9Bl1Q1our21vb//4xz9eWFiAEFqWlUgk1tbWAEaGbAiAFE2pWS6lGlIgQgKyk8n/o7aQfdTyExPzd4H0msr1sLa3/e/8wBKABmyoJyRdVzc2jlJJUqzoCLKdnfa4H0IOz6+dwsLZ32vdu7efySTKlfnesL2xdXD23Eq+kEun8qVSZdg/khW0VJ5moGc7PcGkTnv82k/fOn9x9szpi/lchXnFq/rw9NkcBMXAKxn6Yjp7jklJmzGiqpQ92Ak4/lBjHkcopVBTzUxx3Nmyxn3uWwQJIWC3211ZWWm320EQDIfDRCIRhuG7775bqkwTIBDBc1NzCBJFNkKBQuYqMD6Cjol5VCCJRNIa2/c2DtfOJM+dP3V4tN3pdA+OxtUFQwj71t03C3mytpYHlNUPWiwYpjPlYk7ZAps722NJHjBALBts7w6+9+evy5LmuZwLrmihaniK7tm+I0MDY7i5tZtMiwsXz/fazB0Ps9n8YWixkGjptVTpOQ/oLvORgT02OhmX5zExTxYQAIiwns4AiIbdDnTHpqaHGFarVYQQxlhRlLm5uWw2Swi5du0axKpvjzABmqbQLuMcCiEQAvERdEzMowPJFAKEJC0JCiVtOGrVa11GQTadZKGoTlczGb1UllQcDtvtdEpSET86aMzOLHznO6Vrt9ZrzTql6Muvfu3Slae7taBeP7AdS9FEf7QXAqwnveJUdmfDyeX16YW0bqKrH9/YuNvW1Vy1Oif7PABNI7mXL81ZLBkGWEZp1x5Jsn7fjJ6UjvMJ0InGPEQeVv8hhASMA6IgSYacmZqqq3KtPRiNRjdu3Hjttde2t7dPnz79e7/3ey+//DKEcO+gJQw1nTMrlcrVI4czACQAoYiydp40/4/ad/So5Scm5u8CmVkkkiRVw6os6Y3a0PdA4GECdF+wW7167YC/+tXFtZXiVL7sjtw3f/bB1g64e7exuFKcqmawQja2Gx9+9P5rP3+LjnQAWTKdgGTsh71yMr88NV8s5go5d3P7Y0lFEGvdrj0eO62ms3dwUEicglptjLaCqaNM6nkZLkKewkC3HnaNxMQ8gkiS5Po2Z4JIkpEw8rIchmG32w2CYGdnR1GUy5cvJ5PJN954w7KsnZ2dn/38vdlq7rkXLi9KCEKMsSQgZJxK8Q1MTMwjA7GGEOFAgGC7eXTu7HlKxfZm26cdhKhCkpgxQmQlqa6eepaIpAtSgXa9Vm/X+92ZhPryKxdn5lMHBwdrp7J3boNWq2sHRCMKQEq3D0LuJNOzF58pnjm/9uMffvj//dEdQ8+6rjY7NzU7O33rxusplDEt7N5+tz76wdmnXpxbeqXbU3uNP+laKYc+jxIvo3TSl+uCEQksBiLibvgBDygPWu8YpVeOYtIVfbTO+P662Mh4q5PGQz2puK1R+u+JG/6E9KARPOh+EgJbQZRAXA/AwOeuZyNK88WSqqf6Q69WH/0f/vf/8rXXXnv/g1/OLazdvrv11OkVW8g7Ryy91Zc1Q4Q2Z3Iy0AL1/u0Cwf3b90GfPE3O/fvtiel9T4iT8iswaXzryPKe0HcNTyiu9kOL63xCROmDJwX1ekPOUKU8qyra/v4RBHiqMuU6NJ1KajoJAq/XCfZ3hhvr+zQELzz3zdXlp6bK0+l0znFG+4frRgLMLxZst+P5w+pMXjckzx9DxH3f398//Pij6+1GOD11+isvfzuTydeOekBgGvKrV69SnO5aQdsaUsRdERzWd/vWdqZkX3quuHTGSJcdSR8KCESQp4HmBs2TKW5MzOMJYxwhgrHEKA8DLgSAEAOAJAlfuHBuerr6+hs/TSQ1w9CDwLOs0ZkzZ7773e/6vt9uNTKpVBB4kiQhHLHqiomJeRiQTmucMDOampIk1bZ8QzcURaYUjIaepDDHZod7lmPT5tFHzhBdufTVrc298dg+fXZW0Wi9XgsDIBHzaC/wg3AuO5VMad2u8NwAuIALsr/b7TWvHe7xfLY6MzvvOBwAMBgNB8NhqjgN8UhO4kwl6QOv3Tnc3XmnFOx0hGiPTY+NodGR1QoMiwHzERqED3bBFBPzSMMZgpggKEEgAUAgkIBgjEJMwHPPX7l58+YPf/ijlZWV+YXp2bmpcqXQbHV2W7+ECCQMwxGhJGHf91VZAvGd6GNFrNp4MohqR6KqpiLrQRDKkqpmTRri8dBJJNRUKp3K0naz47vAGRPf63QbP7/+YVsz+MhxR+N2xSzpar7e8e2hYndnsdzutMcIAQS1XnegKFqxMFevN62RvX/4WqlUYBSbac2xPScY5Uo6whBADqAHIU+aqcChKBgFA7s2uEDhAjTmoUR8MXB9nTNJkh54MOC4o8f8fXjQ/QcjmTHBGZJljRhJRQjq2jQUZkIFQCAEzp07wzk/c2ZteXkJIvqH//OfBki58vSz5WJ2c+wLTgCCjPNJT+6/aOEgY2J+nZDp6SlNVzlnsoJ83w+p4IIapqxpSqmcgHBEPY8LWZPl2n7txse1p79SLJYSfjhod0NdKxQKBvWoaSpWyA73u+Oxk0hKnAHfATICnq1nS6qZyBA53N87cGycShbZwLUsp1JM+QGjgVDlbLqcd/ub4ZiNw2D+QtVxT4+D1REHfhj4dIiBAQGO9RMxX2QIIdRxURgqiiKTFArCsedQSkejUavVOnZF6fu+aZrFYrHba2qG+dTlpyEUGISZZN69105PVe12C6sPfC0bc4LEC5ong8gdsGHKrjfQgpByu94caCpUddN2xr1+MLc8Pb+UH/YHve6hFBr5QjqTVgeD/pWnz9lur9dvE9LPFIr9Yfuo2fT9aUVKWsDxPWaa5nDgOVajWKgGobWwPIclv9Nr93u+oZc0tdDrNzLpfLevCKir5pV0csq+QQMrTEM5XQ14xx90SBjmEGaGGSIgIOeMPlgflbGMIebvw4PuPxBxACjjPmMBgFySkSRhhIXn0vX1e+12t93uzszM3Lhxa+306v5erVCZ2t3dTiUTCLKkqRiGRillUSEL/pb3fvHCQcbE/NogfjiwnD6Wx5ISFkrANBJhgCgjPJAYY4WiOTMv1tcd5lIzmUlnzI3tUb3Wc10HYcOhOKmbuWzpSO0N+n6uYBqJCheeaZqKIrVbFsRBOlPARAUoyOUrnYalKTPVqfnRuJ/ISSQhekOlZZ+1caoTHsxVp4uzc+P+oePJgRgznhFIBYAF1Ocexg/aSXQE8YAS8yhAmSfJCAZgNO75vFNIclWTFBXnssX1u1u97uhrr37TMIw/+qM/nJ39EGMYMLqxtXnh7GlrPKLI1jWlH/g4Dqr9uBGPP08GkTtgLnyEqRcMy5XspctrNARbm4fpdOJwx1pf36EAPP9SemlV6deTVt/r9FohZft7jWKhWi0t/OLNj9567R2ZJKwxURJwPO5n84pmKLmcWZ0u3r61U6tvnr74e5pGiExWlvNuf1zMrWWT883ajanTq+nqrNnRqJLreN4QTvnasg3nwcEFnzQ4DEIwDAIV8AAJCYPsJwEKY2K+kIRhYKgax3BsjWy/ndGTqiIpimRZTjqdNQyzXJp+7733VFWTZbVWO/Rc/5/+03/aONjZuHsnf6ZkWUjLlHxK46ucmJhHB6IazsLyTH/QdRznww8/9DwwPZ3DhBVyskz0D99y+jWqaYmx1ZuqFre3g9FIdz1na3fzn62dffalL7/2l7c6nZ7HB3ScKJUrnh20Gu3D/cHZc8vPv3Dm1u1rCPuAzxayGVfbyxd6HqRtZWEnoWF2BTAAzONsaGvP/wYA4EgAJDEACgAAJAMVAHD8hzSMKgBn998Z8yi5WsTKEfHJjtQYPBnd5+T60fv/HqUXxBMHrrz/IaUQEXriKP0fnPDEIjKdE4o/KiLiQ0e0I4qST0fkJ6ofRuVnUp2oqWRZMLLHPVNTMczKULVGbUPFlWJqcWklZN5fvv59COHCcjX0R57dy4hMpWKOvNmte87005m5SlDvD1OEWBH5jDLOetTiZD+s/DxqcW0nz8/9FWhRdxJIRMQLRxH9WUwaR/bB1ueD7icndTJBaIjzuarr8E7rUJZNmQjHIrquP//CUqc9eOoKSpi5vd0DqYdNIz0/BxpNzbbHrW77/Q9+aY1Eq2NJ2EwkTM/reQFTVMkwZYRkCFTfleyRxJhQZPXevc2dzXd8FxtJS6LBpYuXLfckqiEm5osBY0yCUAihaZqEDc5Dzrnneb7vLyws/NGf/Nn29na1WhWhVy6Xkwlj8073xz9503bkhdmzSQMOt0a2o3IVRAVaj4mJ+fVDVA0Hoe0HzngccB6EAehJtiwT39mTiHHuzDMQIEzg0uJqsVj0PK/X304kEgCPIKJGQqpMpSWSDKkdhDZCQNMQY9B2LNvpJZIklVYHvVFTqR/V9gNfXDp/KZk/X3eljuVDcn+fzw+a6BXlrzkjMU8UD3qHRCmVMWSM6bquKgnudRhjnuepqjocjlKpzNramqZpuVTyhRdeHPQ7H338x7bH08lcKSdpsqsRQ1YyQBlB//Ho6LH1b8wXAVKa0rqDHSyFlarc7QSyApIJjVLOAV1crhTLyasfbdy8eTuTLh4etFqtVrsHUqkkhFA3SDabUyRuj9BozMvZqZC6iaQahGP7qD12t7PCTRftjZsH/b6nG3I+UxKcE+ybBmm0GXrMwx6d1ADxwNOJr/yeFDDGYRhijBWiuA4XQjDGXMf/+KNrnht02j0AQOlS3rE9waGZSWTNfEJNYWgbCk2a2d0hF9DWQGyHFRPzoJh0PCeMMd/3VVVnFGpaqGkJVdFs271wYe7smUujAWWMVSoVWTIc26vX+1Oz84HPKWW+H3LhW06/0/VGY4eKDmOhkaokM6RAJVmBCAtVlWVZrtd2MYESoDtbW6cv64WV5XR6ehxGXbI9WCbdAcfWhjF/Fx70jg0hBKEIgoD6vi5zCCGEkBDiOK6qmaPRKAjCUqk0GAzefffdTDqpG1qt3RjCkUoMjLEsE8oCGUPIH4+dZbwDjvkiQK5/3JydLahSsn60bdsC5+Cg17ft4GAPl/I2AkY+V+FUa7d6IbVnZlMjtzMeUsrCwOeKohRLqVQqNR4PExl/MAiQZIVUBVwZdnnzsOe5oa4YEPqMQgiYqigQDcdWg4oZ8JivxE/qEj6WGcT8XcAYcx4yxsbjsWYwRZIQQqqqCgHv3dvc2zv4+rd/gxDy07/8AeIsk052G13btxPFxaHFdg5bDJjpVBrICvMedkliYmI+hYyGQCL6/NySNXYPD4/MhC7JWFbcG1f7iG+eOnVmNPQOD2qj8QAhcOrUyo31DVWTGcWjoT8aWbl8ulAoDUed0Wjge217zFzb9l3Zd9Gg5wGgebiumMrs7LwCEGPDMOwKtymb0GPxxHOSxEfQD5eTsn7/W2CMCSFGo1ES40RCPp6Ap6enG82urhvZbLZWq3meb5pJSZIGrc7Fl89WZ8599N763uGQZgII7cBysWQ+6HyeCPHCNOZxZNJ+S06tJYul1OUra6mM/POfD8wEz6sJyxZPnXlma2vng+HNZrM1OzvzO7/7m+1OHULOiBj15FZzWG9t62a9UqlcvHTGC/p/+h8/9q3Qs0N77AsuQSHLEjGMRDojjhrbvU4DhML1OgtJvVRFIXg4588xMY8pxze+AADf98NQkiQDQogw9n3/qaeeSuUKH330keM4KysrCCFKqd0bVioZWZM6A39Rz+GU5h30TEnzH3ZBYmJiPoM4jsMYOzpstpqD0JeFluV++nAznP7K0AfOznYrm812re6PXv+JhNIXz7+oGyEAwVdefXlra+cvvvcXlG4YZn711Px3f+c3/of/z7+vHbV1NQeBxhnSNCWVSgeSmkzLzdpdTRMzC1XfK6miCL2eI+kKJjJUhMCUIiYAhwBCQSL1W1E60fuvLHDkSiS8/+8T+uhDUfmJIDoub0R81gmvwEREAaJ0e1FEyYajd3hR+uAJ5S6RsufJ9HwcTtYuKCpOcKQ++/7lmlRPDNFkukkJ+8wPIUfLy6vh+J6WQKAFDw8GRA2/8rUvvfF/evuX73w4Pz8/PzeVzKuAeZe/9tKf/OkH+XJ/anZGx+a4Pc6q0gCoBNz/vVFXw4hPps+OSgdG6OwnBU3Yn6OcbwocVf8RcZEneuvJMel7Jw6eETH+iAnTiew/EeP5xO4JJmTScW/iept4nLw/RCGVD9/b2tpodzotywLFgnCdA8+lm7dTkGdlCXbaQ9FxEkk9m+WK7v7e7333zp17goG1U+cKudk33njr3/zfvr+ysjI/W27V3UxqllOl1Rzmc6V0OjsYDKZXp5hipjXFNLmip9pDzbNwMlXIG8kwpKHHGRMAAIwRRoxDER+ZxsT8TSilCEJJwqqpjxzc6/UopcmUqWna9vZ2Lpf7jd/4DUopwfzUqVMLs5X/13/3nxIJk0jCD0eqBiU5uTUaB35A5MdcfhAT8wRB+m3AqIGhGXgdRUKmken3DgAEw67uuH3LcnSDIJTyXM/1xom0UGRzYX7p9u279+5tplOFqanpu7f3drd6rXpjNHQzaV1XtXQKEUJ83/U8J/B86ruUBWEoJMYUiVB/4IwPPW8aEA1hDSAumA8YBUgokhQGk3pUeTyIvhv4NWck5rGEUQE4pyzUdZ0ZCWtcZ4xhDK2xTUWz2Wy7LhuNRjMzpUQiZehmuVDKlSWGMYAwmYQ+QSzwZSn1sMsRE/NFJNIXNELoqSsXF5cr+/uVvd3aeOSqqlqtljfvHo3tBlFAOpvH0PTckAb+9tb+eHC7Vt/TdLK0Ml2vH+0fXdeTnqEndSWdL2T3dhr7+wfpdIYJgzs0ZGG7uUHpkIbNgKLyzMUrawvpjDl2emE75UEWCCEQJlBgCDhCfPJzqliuEPNFACGZMXc06mUkyTBMy1EDaNm2FQR09866LKn37t1TFKVSrv78Z69fOLvqed7A7o2Zm8llbKuLkykBmCLJjE7m2vNxJ3Lh+2vOR8yD4XFvX9Lq7J1BuWSm8sryM++8fetP/tOPU2mlXMkXCkUkFYkcthrDqx/uYpCAEP7khx8ztlmrH3z7N77y/PPPj0d2p91FkOi6KWNSLk17juh292x7mM0mVU3d2dmiHWQaLJszymWtXDWWFhOZHCBEUnbQXs/Z67qeTxKSpEmSz6Hlc4gfjq/XB028A475+yBLmucOHXfU7tC8ziVJlmVFgFCSpG63W693X3rpJVmWDw/3IHcySW1/d8+iPiNQUcjB4d7C6TldVRqOI8uxK8qYmF83kTvgwRD0+u3BMLe0tJDL5VSV6Lo+GPbm5qZ10ygWsweJxrWPar3uGAF5PFSR3NM042Cv94Pv/XJne7/bJBBIrVoXQXvX7EmStjC30Gq1OAcLC0u2bR9sW4aqVsrVfFE73O82jn6kyMbq6to4fIqLnCTlA4o8d8BsICQDyYl4PoqJ+ZtIkuJDCIDo93uaUFRBZFlOJAwA0HA4DoKwWp3p9XqHh0dTpbSq6s364cr5C5W5uZCxo71GccZVZRU69IvmCzo+IYt5lCGVQnk8gM366OiwM+x7mXQxlZL9wPoP/+41WQbnzp2Zm6+eOrXc7zrtRsipQeGYM3Drxla37VJKLctKJhPZvGKoyb29AxqCqamK69ujsUhnLi4slZv79xBmqqoSrA86vW672+t0j7Ybldm0n5ZhckaRdeEzHloIyTJG/hPqyCIeCGL+PkCAg9AnEmAOlaSkArAd9BSVaKqh6+aXTl1av3tvOBxeuHBpZ/OWLKm9XsvUjVy23O2Ph902DQBCSFUJe7Q+i5iYvxfR4+rj0dHJoIu3d/YxBmfWntHUpKaaAASpVIL5Zr1ht47uzsw1q7PGyuo8Av297VGt2S0UCoEPOp2OrLBSlZw6nTUS+LlLv3lvfePq1euMsYqQypVkIs14vVMoK6k0VnWWSCqrK2vSqeTW3XuaqpTTcw2QGjoIYiVtZtSE7jE0EgyAJ/MIOibm74MQwPM8CIWiSKlUSqbesM8ppZqm/f7v//4f/efv3bmzlUql+n28tLTU7/cr5SKEsHHUDkKQMHO5bOnQsRkPQYSMKiYm5tcPcR3Gfe2t1+o79/6zF/RTaVlSeK8HKiXFHdmepe3dhm5XGdeZppW+9dWXP7hxbf9gy7KdqVk5kSLD0bhRsxDQzi7f/YM/+PrKcv7P/uQHadMs56byyWq39p5Kx3kzLfz+zlYdQtNU84trxTNrK8i5kwN7Geu9btuDvoL0RZZaceWC7EbJJO4/MUftdKNUt3hSnXEE0TvsyYxcMJ5MgBz93vv/ziKMyiNPDk5so37/F0fnP0J/GSnQvn89owlPRCLrIeK1PDKdiPJGNu9k+aR0DAGanjo1OrrlDNuyGjijNgCMyGHCTEGA5xfLtm0HPl1eWl2YT2LpN19746OeU587fXahknbbt6qFc9d7LCVP5gudoyidekQ6908GiKgwxBO2V3T93z/ebfROKKq/Rei5H3B82UnTnzRecvROMSr+9/39JZzUSR6PaJeo/Ee1C5swnSii0p90fI5ul4g7YMFBIpHyg5EQIpVKCeFYljUzM5WtVgNPaddDRU52uvWtnY3p6Zwf2C+8uJK+Y+0dDDUFJbRMtzmq99pXrpxdv3sTQ3R40BWcqbJ6eNCxxx8MukIFghB5aWW10x/84u2rmjS6fPGC43l+q2qpGMgjNX/P6W/17DKn/ySVWHWxPVGBY2K+CGi6gTEOQh8h6IfBMLCIJCmyKsvy0dERACCVSmmaljJzyWTy4sWLd9Z/UC7lz1bPN0aWrqvz87Ov3T1KmgsgiJ1Bx8Q8KhDf92WAESIYS8mkyjjq9qxOpztohhDKREKMe0QCM7OZQiH3wQfvF6b6qjJYmEc08DAThGpZk3/z1ReHgw0kQlWB0zPF8ZDfvLG3cbeuGWk1KXr2ePegNrQdCiBHYmt/d3t369yZ37TGM6F2FkomB2PHPiDBB2llxtVOPew6eaKI756PedzrwbKswHMhC4uFHPSB1R1ziMbjca1Ws2xlMBgMxh3bts+fuey6ruM4RIK6ios5o20NHXesm1oqwVhjTEDUTvH+PO719qQSt8vJ8rDCyxJMkO/7hkmCIDg67CfTSiqVHY8Hw2Z/0GOuDTU14fkWQka5NHP+7LN++N7UVFrWSb/r7dxrtuu2LIM3f/qLb3z7IkQkm4Nnz5pHRwM3wLWjoR9i2cwnc+VGV9ih/PSXvmOayd2N7dD3+7oYjvL++FldflGIRSK/gZGA/BoAJzMBxx30ySC6HR9O+z7ofvW3He1S3x51NB1ALkJAdCM58izDMK5dXy+XyxwGmqYtLCx8/PHHxQJud7u6Jt25+eGIomy6cnB0kEpN0/0hkXMPNP8PmodV/zEny8SuH5/QdiHJlGrbFBPoOI5lW2PLmp0tlUsLnb0WQbBSKjDGIBSjofXWG+8vLpwSvLa4RhbX5OWVUv1gCwJQrRQPd3s/e+3DVCZLGVTN9M5+3fKD3Ezx5o07EJ87VXgFyArrD9TEIgVAkNTC7EwHnbXVnEdlihVFW1OQibhD4eMdo/AR5HGxEn/QPAn1wKg96CghlDWFaAkNAKtXJ4R0u92d/dvf/s2vE0Lu3LnTae5vbqbvbW6eml0Y91parqooysb2tlZNJTQlnNDR3JNQb08iT+qE9LB4aDtgRWMBpZQFiYQxNVU+Ojo62OtVq5osGRgSxsT+/i7EIpfXxqPx1taWpngjhw4t8NKXp4ql0qmz47WVMwcHR6029wJxUOtZbvug0Vk5vXbu3OX2mA9bZ/rWaq6yYKY9O1Ap9X2QGXllW3uaq46ER5x3AgYVvAiFQk+uV8Xh+Z4MHpcd8EnNR5Hpcw54KHwvIFBLmFiVhOdjjEejka7rhJBMJmPb9tHRkSajYrFo2Tf2dvbPrV1Mz5y6tb3huOHSjEp4eH/TmseHh1X/MQ+XJ7VdCCYBkUIICSFE1xIY6cP+YNttp42E44wkSZ1fLNpux3ZcVYPJlJxNzTdaW++9LUJ/f3qmsna2YpqA1fr3NsJsTrOsxNAhYZA2k8/1x+m+lauunGNq3odZoQKuyxiESqD52IA4wCDEDACuCqaGQA4xg4SB8Mms6JiYvw+GYfQxxICyUAiEGQSA8Ww2SylFCH3jG9+4detWt9s9e/bsu2//DCGkyAanPJ/JaoY5HFiylkwkUixoTngFHPOI8rifTDypE+rE8YA1A0GkqEqydtTe2W4EPiiXKmHIvKBvJg0ghJmUszhrJjQglF+8udHrg3SqqIjw2kejTpedOV/WU/D8lTmXSvnckmGsWE7SY8r5Sxd3GltEOsjNmJlCwqXu3uFh2LACfxy64fL8qSQuM5ehgMhIB0R2ROCzkAFfBfqDrJ+YmMcSy7Ko7yUMPZsx0qVSbzjoj+0ED5eXlxPJ+Z+/+d7djTsQwlK+eubMmVqt5gXs+UuX6od1qzZKZwqqlrDGrq5pwRfLFXRMzCMNsbs49NOjEAOWU5U+QN7YGet6MQx7CPV0HVx4emZ55dSZtXO+DVKJ0Y9/5gAJCm4LSv2R8ou/3JpfTJ06VUom+7Vm42uvzs3Nzl2/dmfj6n8v+OCrq/i3vyU8fEDh/B/9+7u//PkPM1mYLq/m5XNb917Pps4QnPOQo2qeKiso0CjXgbh/yHAUFVg1kggdIZ9sCxD51kgn4FFH3xOGgYuIt4oihLqTrnyjVmqcT6afm7xdTioc3mQOJaLjMd+fSfV/ANzffIHzYMJ07g9mvlnKKOrT9Xu3SoWGaTVs2++6PYmoU1NJTZcWFqv9fv/waPel559dWizkzdTNu/TdzcPC6tTF8nxKkgwScAKjBLlRrR5db5O1I8Yn1U+iVhCTttfJ8Kjt5CbV0UbF/YURRyVRevcoPS6ZMJ53FCelwz6pk4NJ8xPpC7pUSbg22NltHx4OU1mwsDwnuLS3Vy/mjMtXljXdObVWfOWrLxhaWgTKv/7X/1oy/j2GtFYP93d6UB5nSzqU4QdXb0PV9D3p3XfeXN/YXb+7YY0aK0tFWZEPPtzOnlo79OqtsOVqY5X3CwFsXv/DfVvJXdKnZhMuQ3YYOqGgCEM8+XcaE/MFACEU0oBgqChSfzQcdPsQo2w2G4Zht98JQ0YIWVlZ8R3ouv7TTz997+atH/7k519/9Sstr7+xfvcffusbckIWXhfg+IQpJuZRgRzVtgu5udm5KqW8PxwfHbYNw9B0RYjA9exESmDCiuUMAbozBGOr98yVRLPd1gzdMLjnIC7I9OyUQOW3X79JBTl8903DTIXUTSZJvjSV0OF7H/7omwvzBiydnnmadvzW3mtWd6vW/iC9/DW39fMmr3F5nhjzkp7mSATcITAOGP4wedRW9CfFwyrXSb3Xsqx+t1NNJMqlgght26eEYRCGnU7v9t1aGIa379y1bfvF579qmmYYspHnXr7ylCdCDMLpSn7ca81MZedy+s3BSeX/yewnMTG/Tojj8nanYSbKs7PTcrPd6nYYY6VKEXG6s7OparmjmvfGGz8/u3Z5tnLqzTfevf7RBwBJyWQxl1Ea4Xg4sDjCC8vL9X2bCXTYaI7sMQCcYDLoDQIHl88nZla1FZIpKYbS2/rhXdELLS0jec33hnDLVMal2SklVRgDgwYuFBoAj7ud5qPFpBPAY2LD8YVD003PGo4DnzDf8xwk6zKUqduzLKfZbEmSpmma7/u5bMF1vTff/EWj004kVjfv3UZJJCG0tXn36S8/izZ2AEg+7KLEPAQmjZv7RdPpPqz8k69/4/LGxtbh0Y6umfPLxelFczTuu36NcKQqgHOwvXVYq9Vq+70Xn2OUOYOOhCWt13J29484AkhC9XrdD0PDgJSJaqXg79Udx/MtuLfZqVbKTGu8885rF845U/OV1Uvau9f1Wh2szM6lhX3mysKp8+cCVlnf7zvDDiSKqWVYhO/ZmF8Pj/uHFMXjvgOWJCl03f6gZyoyUpV0ISEsf9AZJZPJ0dAaOd3z5y7Ozs7aI/b+e79UXjy7sbeXVbFKxPbBTjUnJdPJe5vrPJz444p3wDExDw4iKXzt7FSugpvNPkBBuTg1LWWGY+F05Ew20e20OONzM6vVqXmIxPMvXLaH5ltvf7C9vhVycOmpU7LGbWfoWA1NBr32yPVVwbgqmRLRGRWGlrw4vXR01xkOetm52T56urRGk7l3X30xb7cO5meyuux2D++EY72cSklmybJAK9ZJxMT8DTzPY9Sj/ljWc1oqg4k2chpCCCBQvV4HRCmXp4SAd+/ebTabuvacoii12uHUfHlubq5aOdWr1W9v7OYWr4D6wy5JzMMg2i/ChEFKIrbMsd+F//8gb71+8+z5memZiqyKo6PBcNycmZmZnjtjt6HvBwe7ewRjx0KF/KyqqpjwwnzK/nkPqf655bkrzy4EYbfZdEMv1ExNoKDbQ5gUx6PAGQ2ypWS5qmIi7e402jdu5lZy5aVXKgv/gGYrAdkplJGkIFniSwv63LJGEnanu7N+Q7SlZ++b0cdF3/aoMfkO7Mk8sp78KP5kCnZiO28IDV0l3ghBwYTwAwoQXl5eHo+tdDq7uLqGELp9+zZjPJ8vSpJcLhc3r15dXpu+8Pzzewd0q9ZdffoKJerJ5f/J7CcxX0we2hE04XM7G6PBeJTJ6dm02uqMdzZ7tgU7tYbgJJ0qJs3kzetbL780yOe0jY07PccKcUdNiL61e+1GPZWEqaQJNXxQ25GVVDaXUOXqvfWdRi148cXcV796cSDryf3mjTe+1wuuCqVTnPmOVLhwdwiU3Z9XR/Iz6dLyUiLgg/rgGg94ITm74z6UeoiJeaQZDocEomTCyOVyVGfNrsO8MDuTNQzjmWeeUc3k9Vsf2LY9PbW461jJZPKDWx+XS4VMJr2zszMKikRLtMdOJqU97HLExMT8FURJWxcvXrac9vxSynIPPdrY3bD7zRAyPj2bMEw0Go08n7/11p0f/PDNw9q9f/IH/xhBIsnhP/1n/+L6x1d/9tOr3/rWxfFodLSnAOS2u3sY7RXyU3PV1Mcf7freT1eXzIsLlVef/2/rLf7Dn7x7/Wdvr556cWn58pj8V3d2v1+d21E59EYQKibt6dyaNqFk+e1ktkC5YftdSbWZS4RXRlrwiSgXHq+lj+VKnEUFXI3Q0UYrHiOejkwnivvnh/MJnfBGxYuNXKhNZmQRucOL0PlFgSJ0pdG6w8mej1yZTtguJ7UBmziucES7QB6ZzudfASE8VhyG1C4tP1/f/Nhrty6tVEfWZntwdNtX/7f/bL5cWfrDv/jRMOAjNzQs+8zplcAbpJPZ5cvnrn68tXPQP3Xh2aX5JV3NwHDAqUIIwUQGAFDOmYAAAIgIFvfX//HI/nb/foIi9O5wQj2oEPdPn0cedT7gIA0oIt5z1D+YVPcf9d5JdauRcb7v/71gdH89faT+OyKu7UnpYqOIqmc06ZF4VPpR5Zp04MAROvuIdEit1pLka1/92vOqzpotUa0s24Na/WiowtSdW7u2C8oluViYvnHtXn/YfP5LlwAML1w8ff3axzt7t80k1gxw9doHBEmuxy9cWllghuuG1cpKt+3cvXu31doHzHzqmfzamSnJOKpUrUKpWCphBA49v3P71h2ra11cWV5ZWl45u6KkQW/QsWjrqE49x7WZ5YdM52kJ6Joh2dwD4LPZ96/KNWH1xMQ8lqiKjIWnyYpvB412y/d90zQlSYIQ1ZuNVDLpcLtQzM3kZxp76/PzT1fnV//jH3+PUnN2flGWZdNQVOinJfV4YBJCPKnWdjExjxEklUpsb7cWl7crU4VyccXQkxgkB8OPqAWnpmdL5Vyr1RnbgeNRVUvfvLWz27j2rW9//czZlb39e4Vs4fLluU57eHQwgAQMrA3DlE+fW52uTP/izatMjBaX15r11tVr72ZLUDOl6ekBD0A+u58yRb9/UC6lUwmz2x+3f/nh9kFzfu3c/NLaZX0sBcZWPWAsUPWUIpV54HusBSJWajExXwRCa4AwzWYz47DfGwwcz0toEoD8qNY42K/t7u5KJvJo2Gg0ioVyoVhGCKUTZqayBnD6sNGRZJ6bS1WTCCH01+Zg8at77piHwqMm+4k+eYrXbScJSSemOd+1xn65NLe8dHp7e2N+qTB01VvvUcseVFAOY0gI8Pzx0tKSYWrr2x/95C9/ybmdSuvmTKpazsmkWTu4+tKXpwqlZK/fHI0PlIXF7/7OK8vLU4dHu19+9fJo2MbYXzs1l9TpL3/5Xr+zJ6MqlIalMs8aeRHQ3cPOxlZje8dYOo1efk7MJ04RkNgZyb1QjIMmBKGmhiBEn/Oi9/m/xGPHo8ikusPHhYcVtow6A993p4oJnkh26+0wDLmCBQ9rrW5/NMRA9Nut7e3tM8sX5qYufHD1xmwxu7Q43xz5g3EPy0hQVwWhFNgYJx5EcWJiHgqPewcm7WYgkDbshz/76dvv/PJDy2mdv1y6dGXeHfi3bu289vrHmQz47d/+zvXroNM/cvykqZY9mxWLJU1B1z7eEWxLIloykVYVUcwndI3eub29ce/mSy9MnTm90Gxsy+rwzMw8D4XVDSWgYO4KPPD8hmHooS22d488B4/6SJGmstnpavlU2L6Wy4euMu7wkgcMiEMqCGNZBIJPz58hEAAAFJ8/x3xxMBW8V6ubUijCEGFJ1QwAmGCh5wcbG1tTM7PD/aZpqKfWVg8Pa7WjcSOX9oTSGYP6wC+Wq75Pj46OqoXTGGMhBBdACAEgjLe/jwiT3vU+6GhI8Q741wPpdnpMjCtTuZs37ykaePHl0wLQMBAzi0UjaZhGRlEUzVR8avs06BzWZJhEGLrW0ExImXQyk9fMhKIquHZ0dTjsl8rZcqlaO2z88R//cSqZIRJkwoFC3Fvf277XLhXSkpTGIKDckSDIFxTBfE+XJYVT1gVybezkUJZm8qNQqVkulTyt7Y69IENQxpMpAMeb4M/NuwI+/nuqJ5MnVRd4UgPfpOkoInCHg5GGZQmlsznM1HH70HNcI5Xe2d3vD0aXnlp54dlnrBG/t7G1cqrc7o26I6+6fLbW3vOcYb5aPWgPFh2AEOKcCy6OJ+C/emk8rsY8hjzuYRlRZTphJvSd7YNOB2Sy8vRMsddxRz3txRdedmx/d6cOgWpboaFnSsVZwLVud9DtDFrNPka6pprN1iEkw2/95lMXz75oKIXxICRQrxRnTD0x6PcP9w9G7eBgt+m7wLKYbpbPX3jVME+5XonbOgjD4Wjs+K6RUfJTyEiDwMObXXMYTCUM89Rc/0zpXsp9F3feMp23AOAAUACPDaE5AA/c7jEm5tHBd0YEMgkTSqkia4lEAmOsarJupCRJCgKvOlVOpxLr63ds2zYTmbmlU4PxyB72ivnEwvx0Kl/oeXC96Xx2B3wMhPBxP8SLeRDACXnY+X1cIWO7XipXNjb2l1YSFy4ubGzee++d+sXzK677frsz3lhvrK8fqBocDDxVNgTXkimGkVw/Gt28seUumfkSlTX3oP7xwtzTzWbzqFaXcLJcnIHCti1XVbVbV3eqM6BUnNrbbxwcNc6cO9vpKOsbfkpG5XmtMsUEW8BE81hfQllE54+ssXsVo3D7/FnnS5dyGgc/ee39zfW/SH/9PwABAeAA8M9JfdDfEjAwJuaJgQeeaRqGqTebwwGmxESqIiXTlaOjI0TwN7/xDc9zrl+/ms1kBUSmaRLVsCynXjt4+dVvZqfmfvjaO90x+1JlCR7FY2VMzKMCLK0CFkoJM50vyfMrimaI/d2ePZT+63/13dd+/ME7v7g7Gga5gr60PIUJ3N3ZD0aarIWSEkgYyUQxDVyskGJF3mu152enTq8uarJCiAqgFjJSqky/8eM3evbdr33n5Vx+7X/+H35w7+bmbGUm9ODs+ZVETpY1p9/cK2hzOjm3vuszI1GYP7N17XU4vltNhasLlWe/9OrIN/7Tn/+0Wfk/AoAEwEAQAQg//gsEMCI+6KN2BDGxznXCdB4WnE2m652UyfWC9w/mERXfdGI98QkdNUeBAeScH5soH2srGWOMseHdn4y6vgjdtZVsPiWv377jj9unThefms22u4jK6Tffe3s0Gj1z4Slht2XSN6bPXfvw7jPPPOOzUX9gE2W63bO//s1XOmP1RodbUkZFFDCfEyUImYoC9qipDCbU0Ua1+8TpR/SHiTd5E6Yf9XyUvjZKlzzxeyN40JvaScfDk8pPVH1G6Z6jnscT3tlExkuers50O854bDMwLFQKhpkQHA8G1u1bm/VaVwicTidLpdxUtSzLRAixu9kQnClSMpVMhIFFgZVIZReXp577yjd2tzd73bGEbQjQ/OLqTGXG8Wh5WlZGFWugSiCZSax47sbm1nq5WDagu3Pr6tMvnldzaafbGPnju5ut6uoLdmvkjm5it93ww6NG/14jkShdGqGzn1wAf77UkMd2WDFPJH/zWM/UE0mtsLV+w/OtXp81a0dpU9/ZPvpXv/O1m3c7r/3iqqIovu/LkhRgZJqmJtGlxdlWp797tKVqqcUFfaqiu04HwioA4FfPjSK8qcTExDxQiOcyziCl3LGD8ZAaBg886Dr0Zz99d9ALgTAAQI1GjYmBaeqjkeUFluAwITJBSC2nm8mJ0nRycWkWkCyGeiZTKhczzdaRACwMg+vXrx/u7PiBuHXjg37/ljV2ZFlWiWqPiDU4KhcNhShPP/Mde9h8/c0fJlLUGXod964Kx6lCmoXyQRP4vWy1eEabnvLCY19PCEAMAIQAAgA//ct9eNR2il80HrnoQxN6zDmpE4vJd073EeZCCGkoZAIkwnv9+hi4RMKJRMp3GRfA9/18Pue13Wefuby3t7tYzczNT82vzr/7/v719SbR8qqZtd2gWs5kDeE5AmEOofj8HPwE3OGdmM/zE2vfSdN/7Jvgseah+YI+2G9IxIAAcwZrR91er+86Agjc7/qMSoamIywsZ9Dp+I5j2Xaoqgnf991wzD0XKSJfIUKIDz+6e3v9rdp+c2159dWvvlgqVmWd9AfdnZ2dww1rd6/thWB17Uq5Uhn0WDCWAi/Pzczc+ZX2CLet05XCarqwM0+10PtSrTFIGFOKkRmMONeIMM+6eKbvahI+9oR1vA/+rLIiL4BPqkIfOaf8MU80n599j/vM8Z+mboReuLAwc3T4zsDqFVLTnhMQrLYHvd5wcLi/rZiKCP1cJjEYjxSzujxfeOPNW6qqz86tDi2/1x0WUthQdORxiDhEHEIBhPjUhibeAcf8WvmijYdR5SWalsBICqkPEXGdcDQCBMOkWUCA9nuu6/qGKRcK+VxBhxDWa23O0ow2KbByWVCZkmdmpi2Lrt/dnFta9S3Qadt3bu0urRR539/ZP+p0BkuL53S9s384lHAWQ5mFcjZTWr7wwih7enekeV6y97E5Wxy66MzYH6fMRV/6GmPQGQHHo1BT9dQ8lg1CORTSZ0UBx/8BASCAEbbQ8Q744fKwFkAnFUbt4e6Af+UfQghD34EAmYaKoKBhiAEMQkoAGFvO7u4uhGJ3Z73dbl8+/2yllLUdzx6Ns+lkMj/tAsX1wmw2DTjTFRkTgI5nX/DZNI/gr3p4ffx40DvgyftDvAN+nHhoO2AhhOdbruelM3IikfI8R3DMOYcQcs4ZD31fQMw8VyZY4VR2nFDSULGqlacUjGCvHSiKUZmaZtzp9/v1/cAaWsXSK1Nz+cA/DH1yb+PG6dOXfT8z7qsSTFtD2ZT9hVX9evjV3phbrppQtI8333MsOZs57QBp4dI/t8e9wB8rgnLEOVYsywIAAqgB8LmDxP9SdT1qO+CYmEk53g0f9+Tt3TvlbNkeOTJSs8k8pTxpmJSO6u3O3Xvrzz37YrO1DVgQBn51ZnrnYBNxu3bkaGltr163PJbQclvt0dxcCulZhAWEHHD+2QEShBhEBD+IiXkQPO763ZOCKIqkG5Kqi0IhWyjmwjAUHAkhGrUjRZEkogMYjkZDxkJdywSeBHBQncvMzkue7ezsjAT1Vk/B5bW0kUgd7vQkElhjnzE4XV24em17Z+sjgxj7+4cHh+Nk4jwCRv1wGLg9L+gH1q6mz3X9IJFIjkJj6MwtnXt2aIMx5UwzoaRIGCEMKGP0eE8gCAD803mXf+7Px+P0LO5wjyYPzadu1POfemn+lX2w43T6CEkYaJKaSqSYA+zRAACLchYE3kcffXDh3Nm5men5+dNbWxt7R7eL2S/XGu2CUHjQo46vJrMMmdv7nfLZRQgFhAKiTwIOQYCBEFHRjWL+dh70DjgeH349PCzPYmQw6CVTRhj6nW7DcUcQYtNISpIchr4fMM4hQseKCBkImVHfE21JyQcBOzjsNw5BNp1mAvphO4HNSqVUzqxt3F3/yY9/LhC1xl46VfT7euBDyvsDa4uLgHPeagz/7X//h4lTrUz15dL8VzwWmulMNvf1/aZgGFJe0/UED8DQ9iViaHoSMOi4niF9ZvMcC39jnmTua4RFJNFs1Zdn5wRHiURGS+rv7WyVCpKmGQDBXrcd0sorX/3yD7//+s7Bjm4C1ciGdEeVcdrE3Va3VMwl05W333+zfPZZiMSvmKRBCB93D2UxMY8jRJEFhgIyFQTaUXNomrqrDvoDK5M2AXAlGWSzGcvCGONKNZ3N+3fX+819dPtqqzqdXTufqDcOWp0ckkpX39nUdXX9zvsvvfh1WWE/+dmbmmqM+oOQQjSgiVSSM9sLNqHSR9hJzxhJrV9Im6EwbAAlA0DBoSAEKSELGOcAYVUpYiixwIGUKVRx8VDRVIFBEAaccxXLspA5FUGEvm3S+JRROrDPrsd+ZUcSGS7zU0XHZ8OoEEIIAeXjxRQSQgCBhDiOSANwlJ4vgpPSDZ/Uig+TiOej4jRHEPXeyHaM1FNG6FkjszNZ/5n4zvjTgLqf/cPjv1B4f90qhohShiDQNSX0fAi4pOJarSH3nPnzT9mCO31bGuPAG6kp1UR94DN76D7z/JeMtHlzfdsPSULNO8OWikHCSGzc254qKP/1P/5dFxT+6Oc37NQ8UHlGSdlDhZFQkhnyXcElD2OMJ2uvKAS/fzqR8XQj+9tk6+zJ7cii0j8ZXXu0TjdCj44i9McRul4RYfsS9d7I+jkh3fDJjbeTxRs+KRuOiU/CJixvlBEKMbScLMmeMyQEJZOmomgI4kxS9/0+ITJjzPd9hIjnubVaTQhBJBCGoa7ro6FPKcAw3W3TTuuwmEpomVwy4X/4wXXdZAsraUqDkeUF/jCkkiwTw0glzbyupWy3PRqOz64keeBhnyblpDvyKKOyjDAKDSMMqaAcCZkCrHBEECYKAaAPOQ2Po5gfDxaccyEeuO3C5xv+rzdSVAN/9rv4zNUuhEAIDgUUgkGAhBAQCCBQpGlQzJPDZwPNZ46XAQAARQ40EGMEBUAIQSggEEIIwHihOmc5npbU55bnQAhb7TBVnl4qV4ej3srKUqU8VW8fttvdTLKcSydu3jxkQTAaDRPpHDHJZq3NMEESKWdTCAgAj29/EQQYQAAhBDD2qR4T8xAgrj+QlUwQOpQ7mqZquuHYVAjseWEmowEALMsJQ991QyFEuVxOpBM7O7sES6aZCDzEOff9QFXVrc0D23Yxkkfu2KfjqQC43nh6Rr553Ukmi7lMFQjFd2EimSsU0xwMD2o3B4GRmJnLz19QZZmGDODA5SM8KgoAFBUz6tmWxSGDUEDETCPtBzQMOCSYYAI4pJxBIU5KQRG98vprv/+KROQ+6fyNFcEnOx7BADheL3AAIAAIQA4Biu+Gn2x+pX3/qv9EdFtMIIIIAC4hKAgCABAEAWTzqxc+WL8jySBTNpr79cZhLZ3CTV3+8tlpxgxEzPHI29k+NNZyuVKqUEx67rharZYXTu3Xt965sVWoKKlUyjAIEQESFAHAABAQCIgRQiBeCsb8eollSMeQ0jTLZTQ/UAYDX5JwNmcCOHAdzzQNjCXGwsCnIaUAAIQIIUTSAMZAVkihkHc9ezDoIUL90DVTYOx0FFmami4UK4XKDNndHeqmVCiZrVYr9OXlxYuSJFM+SqWSSyunD9o9Mpqnmk4FgdiEXPahF6JAkgZBsGuqUo4klLSdTY5kGFJP2/ILnPmUCggkCLAQDAgB0a9v2Phs6Pz0L1Hxbv/aEdBnB9eYCwAQgMcj3SemNr+G++zHpaM/avk8KbnR5xU+QnxyKCKEQBHOpwiCAiIMoSxBIAhBEEFBMEzkp5S9XRZa/rATOiNVIpKqW0F44eKaZW3v7PQz6VKpaFHKQ+qfO7+myKRUTg7Ho+bAsaCmc5zPppMmkQSVAYWCCwg5OI7MADFE4SNmBf2494cHzaOWn0eNk6qfB13P5F/9736n18Qi3Lx3txb6Yjiwu91uGPLp6uxoNBICSJIEIUQq4JzX602fj1RVliQCYACgn0iLUjl3VGtcOJ0vlvLDvgeEppvAMGGpnG3WXFVnC0tTvXb4zrtvra4uv/r1580k3Ni4reqlci4TKFCwDoE4DAM3CA0TFBOtO5v/iXIpkXtOA6Fk3VIQzqMrNYn7BIWUcwEAA5wBAAHGkZ6wJiWqojmPulOJ8rj0yb3vp48hCCFCECN0fAEsOBTi+GIYAABExFYo3gE/GXy+m3yuz0AUIb3FkAEICMJEwghgiSAhBEHQDoLyVJWODtuNmme5mWzRSJqCdyGElmX1+/10LruyskJ9JoRfLBYvXrxw6177rR+9SVKp1TNne11u2+N0UtcQJVBgKIDAAiIBIQIiKjMxMQ+IL9oCInIHnEqrt6/v1WoNxw4ADCSZA0F0Vbct1/d9VVWF4EEQYIwJIbKsvvzSZULU/b0DzrkXDKGgpUoyXyJTRXVlZWFvp9Wsj2r1w/7Yz+eLi0vzXtDQlHSlbGhqulDMHtRu7Ly94br20+cLU1OZRB6HAkDGqYQYkpPFtDEYjsPNGb1cNuybN+5eX/++YOrytEIungMMykgJBaYcAIAQYr8G683PhJh/RyOs44DnnxheQYgQwhhDCAlGx/+Kc84Z4FwIKAR/4CNffMT90Llv/0EwYmEHBEIIIo4hgwgQDBljXITDXjeXyY55v7nXD91AJSngCELHe7v1ZqPlB+7O7roQMKlnZILarX4ylZ6flqq5ZKgrhq4Mhx7CnPpjBaVVxBCCAkEOEAAcCRFfAD92RH7Xv+Z8POk88B3wUX2z2dk20u58kgDIpqbSnaZeO/BGo9GxHS9jXFE0hIDg0DRNP7Bd1x8Ox+ORG4Q+E7R2OJyZyw+6zt3gYHvryHMFIkI1IKU0lzbPXZybrpze3e5sbe20+7XhqDu2Gwkze+Z0Nle1lfSG47bdTg/gVCoxn0jmB4O9vM4Xp9PpTGtrZ0uSwrEXHPV+obdfltUskmUIoeCfVA2HHEaYt56UByX4OY5jqR7jecH9K5Sgz0/AGGOMMUJIxp/MvowhJgQTjAsgoOCxBxwAwKO3UDg5D1ns004EPus/AAASabvgQwgxBIJRxihDggae79p81McqCrngRJZUmUgKQcDU5Fazf3hYM5O5rb39bre/ML22tjo/HllXb91gLl6eKRwO+0fbd2VzPpNMeG5NxZxAgRH4JJTn8Um4YI+anv6krP1Piketfz7uPOj2fVzai4SsOzUrzS8WdYMI4C0vXrx73fnBn9/s90LOuev4skLm5+c5p1tbW/Vac6+xvbI0peupYT/Q1ZxhVpq1Zq9je2Nrfj4vhOzavqQKTTUQQrIsecxxvO7G1tW9vfoLL52tTE+H1PFd/ssP2uTOjcJM1jScsD/UWcVP5dodMXTxXmNB2kyZqX0hxJW1bzcOuzt7HwbdTiqraHIaAQi4gBh+4ifoAVfQZ4Mm+pRPx9CoCZgIIY6N7D8/AWMkEBKMQQCYEEKIYz8I8ez7ReFX1nAkynyBCQS4EJBzzhmlkAdB4Hkeon630/bsIcSyRCQAMWcehKHrBEdH9SvV2VTabLXrrmcnk2lGYbPV2bi+USrkhWfVD0fF2UxPsG5rB7+wSuAneRDgr65CYmJifv2QIKBAEM8LOt2jp59bdsP9udVcYbo36md92kAI2WPkeZ5iDAMaJvQZwbcNg5cryHPFqItcjmUVPfOliqHL3bZ19aMdawRUFe8f+M+/kCGkMxhsVSupyhTLpIsLMzMY6uGi/PrrbzdrrqrXploGB3YunXn5S1cUSb59/e7A/538NLNE72hPcv1TanINLBfSFZ9MLTDBbSEEDxBRJSAJKgvGgTpZHFAkyCeHxwhyCOCnRjJyYAkhmIAIYUQwgJhzHnIhM0uSJFVRZRkjhBhjQRBQSlXxyRQLIAQYIfLpRCshFnJKuWAcQSQDQCBEALCQAgDwsfgDAw4FQ4JzDjkDAHEgAEBcQA4BEFBAcFK6zEn1did15CL4yaQTuZKF99dTwgnjrUIYoRueMC6sBHXOqeAMIYARxxBwTjkLOYIYYUKwJEmEkOMJGACgAE8IyIUQAlIumOBCQA4AJQWMKA+9QBCPayog1G9ZrWZ796PS9FIiqXYDNl1O769vyVTkKhlXSFuNgb5+uFqpTCUkvTJds2s3P/zoO7/925lTlwLfR2MBBwM74epa4pmnnv1f3txde0YGnaEGzoUq9rAjS7rNehI07l8PEUSeBJAou8IIlQGP0MVOuCyIaveT0oOeVDoI3z8dHvm9TKaLBTBi3IjU+0b8jCY7WTyp+oxi0vQnHccmHW8njR8ceQe8unwJLCZu39za2tpp1IczM1XLCg0jObIPNU0xDMPzvFZnJwu0ajXV7/SyhezmRsMwcaEs1et7MMDT2YI71v7Bd1/d3jo83G2kE3BxcXFvf1PCKJfOGNop30WakpmbKa2uLguOEOZ372nNpqDMz2ZnjER+f2f752/84ML5K5efWf7oaEeRS56dC6S0nErBVJ7hip7LhV5PwgQSAhBmVITUIxDKKrr/PvRvB3IAAATHNtTH0mIgESBJKsaYcR4ENGQhAtiQSCGjH99/YwwBEJwDKiPGMCaJIAhcPwh8yjmFjMgYE4IZ5BxQwagQn9i5Cs4ZACHln2w7BBACcgEFQABChAQA6FML2U/kmEKIeG/8eIGwOLZ4RphjhCQsAMSAI84pQhBjgCFHgh7byAshGGIAIMa5EJB9OgEzIRhmIQsBpQwCxhGlgFIKACC6kGTYbvYWlk6ndLlYABs335ub1SQJK4riOI6uFaZnchvt7s31Lce2h+17hf8fe3/6JFmW3Qdi55x73+K7h3vse+6ZlVWZtXb1hl5QAEFgQArgDI0ccYacMZNEmb5J+gP0QZ/mi8z4RSYNpZkxG5Kj0VAzGAIDgugGuoHu2rpryarKyj0zMmNffF/fcu85+vA8Ijyr0gsdYCSqsjt+Fubh4fH8vvvuu++ee7bfWXjt5kojxTQ7l3PKcunS5bX7W+JmGX0kFmEEJhQlgFZ/xSzQJzjBrwR00FPnz55bmn9hdnZ2Y/vWnVtrld3Acdznrkw+uLsbRvDt7151PHPr5opYNT3nImKnBzs7ldK4d+45r93kSqUWBd6/+G/+1dWrV3/3d96YnZ2NougP/3BrojR2dvn8z977sDyWPbV8UcR+8MF7LGZsrHjm3JTrx5Xqbr3e7AeklJPJOhbq7f6D5TNbUbe6G047agpUph9gX7rKT7vSj0ISlSbfUZqZDVtjGYH8I10woihAAGYQBN5nbOKUi5mMk0qloihqtcIwDD3PS6e95ZK7b39OuKuIWYso8L2gj52udLscxiKAmgRBYhQWITEgSEAIbK1Yay3zgf9vvyeIiBq1CCIIMyQO4V8Ok+BTj3IctXMfuXN52pzPFpGBLJIojY6DWruKCE1/3/IMIpYTCItoERYRZmEWTjRgkZhjhBitsQiGSaHEcayU8srZdC7davZblV7gBQxeoTSWyat2s57LZiYmpjK5PIvp98KgF9oonshyrdqq93U37D13bmzu/HIX1KMtmTs1JpARitgCgNEAyoBiHZ8I4C/E057Po9s/2Yl/EY4rXfBpn3cUtO/l7ty5P16aPX/+gpWO48rMNPtucXO9FvRNs9GZmnMuXrpoYnnnrU+8FLBxXJ3ud3SYdk+dnW81gp9vra7u1Rxsl4tjFy+dnZ0p1Gq15aXpi+fOK9EXLlzu97utZoslrtb24jgiZdMZ98JzE5fw9M5m9fbtuxnfM0VvfW2n3+0s8JJp381hs1zW4JTYCSm77eXX2u2zu7Wo0u6HAZCrEm1DWI3auY9OE2IAQBIHAFAIbPJnxsWsh1kfjCbXUuxq33eyGT2eCYmISJRK/MGDbKJmHKYVZh2n51MYQhiziVHEEKKgEWRB0oSAYq2NY2ORAA7Kr+LAdg2gFIpg0isBsCOynk7wFQeLYbEAVgQAhch1Pe0oSicTDREgCcEDa4VZQlAimATTE4gIMAMhihVjjQZhYQBiZmOM53muN9PpxM9fPG+4LahWV9ZOn73kp0ynWSuXxy5dvsxx471rH2Ku8MILV+9/9GEOxvYMqXzWCTPZbBZZdmo7fYxAzzKmSUMy7QiBrJA48ZGpH5+NKNxftXSXo+JZF2BfNRz1uvSf/NsfLsyfnvj6TKk0nkplXI97vVqntzszn3/1axeMAccz6Yz6vd//D0D8d3/2NrMJesB2jMAJg11mQ6Qsx8VCrl5rra+vz81NF4vF06dPI+h7d1c/+PQ913WXlhcvXDg3PlG8efPGxsZWNpudWyoszJ37GB5e/2g1hszeto1M3X+u2NtZCIL22MRYsax6vQcWopTq2t6ek/0nYej04mzbirUCQJ7KuOQF0j/aACW1JVAUgiZRhJoAEXI+pFTsIqY8yGkfwfVc7Ts654BSqBQpRQfLqIj0olgTOR66SkcuxBGEEVvLHQDUgJYYkRQJkAEW2Y92FkgkL+JBVI6IDDKDEwn9Wab8ZxPPigZ8XDFI1loRRhBmsVYSRRcUpVx9YPkQEWv3lWDjiCAxWyvAAmyJ0IqAHTggEBNKLBGRdDpNePr6x2+WU7R8pnh/dfPRxup44RKKOr3sbVYlnc3V1rfXN/dmz5WW5peivcrGne7p751prK8W9FS10bm3sVI8fWV81iR+aKUUxAAAlMy/X9LV8BjxZUXtnmjAX4zjy1Y4nvMeFRol8/zlVzKp0rUPbq6sbC2dmrLWbu9sfP317+xOdhcXzmRyOp/Pzs/Ov/LqCxsbaxNT+W4LVx9Wd7YbY7Ebm06/b+cXZ5dPz0dx9979rdW1P/Z9//bt+4X8+Knl89/73m90u+1KZffdd9/N5vxSuViv21ptV/vO4vy5ycnJQmGM2Cnki/VGtPJgs9X7uXBxUsb2etVKbS3oVzmCRqU9cekPVOqSk30146f6IDaOQIgtHVkDBkEETehq8LXjOKIJNUHBN5qsS5HvOilHO4q0QoXiojdYQAWE2drEnMyaiC2LIIG4ishD7aCItn1LrlIoVhxGZSwqGIS/Plab4UAPHnrA8KQozTMLYQRQIgDEJoaYjFKKQIEDsO9uSO67tZaI0OJBelKyG0tWjOQwUmQTOmjgRACncpOT02vVva2pKXvn3s1CeVY7mVQq9Y3XLt5b621tbYWdYGp2gdDttYO5qWnuSD7jTpbcTrW9tt4pz7/Q7AZT48rhUGPgKERQFhCIGESNjJwaidEa8FdrBj8r6Si/ajjZ8yXQUT/707+4vrn5pzs7G+fOL188P4N59913Pnz+cq/V3VzftKWxmUa9E/RNr1+PQvXNb34zl83/7GcffPTRR9ms3+naIOh4qSgyUqn2Ot2o3W5mMpl2B5jDiV5Y3Q1Pnzl35vSl9z94s1JbzxcnFpZKxTLdvPWokL91av7K8y+c+/C9a1GM5Yn0xvqKm29PjL+ELhrIFiau5mLTrHS8Xmfl1rWp+VLRZ/I0SkQOo4k4MkcPHhFCUApdR/kuplx0HdSEOY8UiqMp5UDKQU+JJgaASDyWgUJjbaL9oggJKgAQsYACwEgJtxF5CpWntVIxY8wkQKSM1lpokJ4kzCICSSwWogjtq78AgyX5ZNP77AHRAQAEJRKLgIkhVoxiY88g4gHxJO/DWhBBy2ytGMuGLXOSoKaFeT+AD5I547rudnV7dnY63Nx9cHsdOJPPT9ZaDY+3PPey4+jdak8BTEzN9qxEkRlLZS8+l1OqpaJ+t96vdOTiqRfe/+jdF7Jlz+sqyrjKIwAjShTGxEpZsCdO4C8TR9WAn3ad2lGtn2xoEhxX1Ld+580biOi6msXWqjeiyHz3+69cvvTKT3/yZjqL7394/9F9uXRp8ff+3m+Wx4vdtvmv/t//9YVLy+MTuel5VatWzp47+73vLfX7/RvXb25v705NTRibarUlky1ba9/74OOfv3trdm78tddfKBTGHD9EiveqW41mNZWa+tGf/4X5pp6ZK13/JLbQnJ2fZ8h4wcRsYVo0dwPOl5eMjvfg3di7s1xayo3PoJNq96O+dL2UVZ5WQGZUeP0XDx+JUuho5Trou0oTpj0hApfAU+CQVShKRIH02bHWWivGWBHZzwdGGxkhJNIizMBgjWXDzI7KDbQaJraIzEREZJVSifQevhmJMrwvgE9U4WcYCBpREEkEQWJmtAYtSmTixP4B+9J0YIE2KILGWmslHhbA5HFCk5bUQRIREaWUOGF+LGN6k+vr91648s17a5U4bMyV8dHqShzHuVzOdDmMOulUplAoYKe+fDmHmeKP376WS02AI1v1RhCQbbtOKtAYEWoUElACYJGNPhHAJzjBlwAtUUyejhizpclmq3r/QaPT+Hkh6zcbWJpyOlX52tfKv/79356fvPLHP3+r3WmWy7Zd39h6SHPz42+8Ubxy9exYfkm78pMp71/8N3+6vRFMTI5NL3i19k5lve3occ+TtfXaw4dv2ijK5sxr35x77srC1KTfrz9f8tp/8j//hefTzFxeabx7e6uYPz//3P+u2rKZbLfW+kBUL5f/2vjsy710x4/rUXgf+jO5zCUCv9sLegBpJ4M4KhHpyVa1PoQekBYEMVrIF5UF5SFlJEJGAiJUgsoAMREiCgcIQshaDRpEZETMua611lgRISuKybVijUjkpTiMOTbMHMc2iowI+b7b6Cf5ykKERAr290q98LE8ZoWYJKRZ4sTWjYgJmSUzW2s1Hi3q+7jyiY+Op1tnYhQDyyhqFhrRHx5VVpKfnB88qt4qcWfwhlCpQdYvKsUIsZUwNP2YQ4OxaAMIgBIl/Rm6OwiAEFmjXRdcJwxiBuNjLP1qfe/heGlWtNoIozbL9dsfXXzlG1k9TfUHN+5WuvWNarV669athYUFEcnS2VKpVFnV40vtS6fyDo5NZiiM3p65PKMLc6mdd89enAu81gav+NnnupV6Ia16oafVqAF98gbXjiKiGZWHOgpHrKcy8r7bERqJevLGYtRpn7Zp9Mj1uUfUqx7dzVHBESOiO3EET8ARzXBHHbcvq37wKByXz/io7WhPTViJBUIb1dN+WCwrwH6r3S2NZ1qt3e9992vLp85+8N6tP9n+8PbtFcc16VSKyALGxkbraw1jeH7WLCwV/ZS6eGnx0aNWtbazfP7sUmkBZU8426x0MtmiAq/ba2u3z1YB+NlMeW6y9PVvvJTLpz788EPL8amlhTi2tWplbml7dsm5fuOH3cptt4unl38j3MosFX/f2flve71K19wAzjipsxldNtiPsTuywPUIaHIQE7MxsBWwDFYJDTtlB27aRPgBW0iMziDJOCb5SBYZEUgJWyFCEBYBhSLgWDaBsaGFyIBlSuop0j5DJTzOL32gG332hkkygxABUQgBCU4o87+6SDjA4cCvu4/YirFsrbAFZmYBkP17+yQQkbAMzxBrbavVcvzcbrvVbjZLxazyU+3abjtqTFK33VY7Ozvj4+MXL16s1+uImE6ny+Xy3ZXrAV3pdVDr6vbWw2xxPpUvbmzemYrCdqfveBnUKgpCa2NmVK4D9mgF2E9wghP8+0Pn8m4YgyUKuz0/rUoFP+Oz6/KZU6e3d1Nfe+3X7t+r/OEf/KTbYUY4dTo/Pz/tpBr5Qjw/P2mhur5abTdua3+KxTtzbq7RCtbWGiJmZnYGRG9uNsOYUw4ZQWGlKAXop7zxufnM5kZ1anKuVM5Mz0wobT3Pa7W396pr6xs/zOfOzZXn/BeyP/zxH45Nhfmxb6ecb+zdY6K2g3tgGwwClLFoYmjpEQJ45I4DPQJGtmItMKEQCpAVooGsgyRoeZ9L8mDnhY9DkAVEkuzeRHshABZrVGihF9nAsGEdMYhSCpRWzMk3hJO4m0EpOFTDwVmwL4yFk3AxQkAQBEAQoKOqFyf4mwKSxoONFBILWgYBCWLLFiILkbXWIgOzEIsdlT9HRNbw8J/GmGq1Ggf9Qnky5bto+xP5MYNRtbGrx1Qqlep2u6dOncpkMnt7excvXpyZmdnd3ZXeXqFt6/UgVzRB2Kg9dLy2X4eW7/tb9TaMFREwiiJXH23/eni9X7Egmq9af54VPCvj9qz0cxRGyqNMads2QHM56me162j20pnW+DRcuLjsp7311eoP/93P9rZ5enrcSfeWTk2/8vLzrFcrlcr05Fi3L7Vqp9GsRLH/wtVvvXC5WChO/+hHP97Y2JxdnJyanvjpmx9rO9EM+mGvbUwcRrL2qDIxlclm0zZKvf/+tXfffVcpnJqarFYra6ubYR/2NrY641c2H4WtoHlmcWKs2Gi13wzi3a2u649N+oXTkCv3CWPbsWhBp448EELEDCQk5CBpha4iR+OwpfZAFgIAsIUDIl/EfcGZOG5ZEGTASUlgWSEZA7HhMLKhEQvWkEZRIKQG5NWD9geKLWHChi9DGBzAiJCQXQ/8wUm0rNBJEMQXYeSD+vSH5+DeJc7+RIvtszBzbMUw2sTLmxjDRxRjICK731RiIDHGdDqd5eny0qmldQjaG9t5jyrtWm394cWxpXq9vre3d+3ataWlpUuXLs3MzPz0pz/d2Nh48dJMrlm/fuP62bPThUK5Uq3FXu7CS8/X1ra2G918nq0F0pxJpyyHURR5I0y1JzheHFWQPOuC51nBUYOqjgv6u29c/uTa6sqdvbAlWTfdqoub4nyYunPnzrVrt7Y3grVHYWlsQljFEQf96OHqjbll0E6MZFIph4jr9fbe3l6j9j5JASn3+uvf+ODae/Va7+zZGUBotjrGgAInlU4px1TrnZWHu5lMJp/Nl8vF85cmje0qFTbrkQgrpdOen01Dcby9e+9+vnihv/nNsfKMdXeqhQuFwjmVf1688cCYCOsAvoN5ge6RBk4xIIAG9BR4rkr7OuWio4QUDsdGHbwicGJ2Tn4O8kZim4RKffYrcRxbm4RrIeFh6rBDhAhAygpIwsgBiDLah4GJERKHBXNyy/6at/oETxOGGQ62QcnMYQYAFmRGEbCcWFP258xoW8bBlEDEhC3LcRwlfP369a21Fae3U07j+t5ep75HsqC1DoLg1q1bExMTV69e3djYeP/990+fPt3t6F5Uv3n3g3730qVz56ZnMhPL07Oz5x89rHYiyqKHyoowEdhRlTW/EF/iRueJOGo07wkSPCsC/lnp5yiM1IB/+7f+3lj+7bTzbnWyMTHuC0rQcR7chPyLnu8VxsfzjtKNBmxv70oc3/j0oe/lXnzt1ZQ3biKHHOs4qVql/eBubWKi8Mm1j3K5xX/8n/zvrfV+9v7bpeLMG7/+rf/uv30TBQuFVKGQUxQBdqt7nU9vPJifKX3vjZe87Km9yka5NDMzdebaBzd//OOfxrJ9/dMPlbaFklhp3Lu9efG5b4lewgUdOwstnOZIDHaUtoiAoo9KHKWINYCj0XMx41HGx5QLDtpErO7LuUR9AQBIVNfhUkgHTYmQsDAjA1lha8WwNUEgbByNhIrBQSsRxyiiEImAABXSvkAVAGGgzyivA21b4YHwTsgbkn/xSRrAVxL7ZmMcuhECAAwEMCgRDUgg9ouXkiRLWPaDn62NEHF8fHx+Ybb5qFKanou3W9XKXtbV5TNLAFAsFh3Heemll06dOrWystLr9b797W8rpaKuyeR9Y6OVB2sFP/f6ty8uXzx9d3W3ZbX4OZ3KaC8I+xIFASI7rgsnFGxfSTzrgudZx1PXgMNAXrr6/LmlMbYBgn7vvTsP1zoPHu5peijIxWKhWt0LY5tO+0Kq36ufPX355Stv/OztO29/+H62GESBjvpU38mfPT1ZGuu//fbKqcX3dnZbH76/XSw+fONv/dqZs+uNetPGptWpO44UC063F65/uJv1nY+v3f/0xrWgH3//e5dfu/Ja+5Rz69a9hdN518z82z98d24Zf+vvLcWmsLO+aaPL6dw0oRubkGMmRVrnACi2naMOnKdJg/gu+B6lUuh74CirIP5MVZyDaCyNMKT+HgppYS0Ji68VC2CsWAuxFRP2iG3KIXS8yJKExlrDlkE7iEAERDSgA06Ahxmfw91OeTpZiK21cczWJr2C8OkGFz/zGK2ZPd0NynDY1PCHsVBS8wOREBhRIwsgj+qNtdbTKhHeRGRCo5SamZm5v/IIvdL05NRa5W63052YKM/MTI+NFyqVSrFYvHLlSrvdfuedd6anp19++eW33nrLRMEr6rVcbspFpzyRTvlFMbrd3jIq5WbGhBxCox3iMNbuXyew4Msa51F41olBTvDFeNr5x1/WfdHrm/deuXr58vlFjOOtrZ2PP35QKqe6UWpnq+VnCBF399YQS0qnqrWen8rcuvlo5V793TdX/pd/8+n5yzA+PtluKDFiLf79v/8PH9z/5//uT/48kxl3FFZ229c/uf21b3ztzs07Kw8ednvtifHCqTNnFAWfXP9wa6MVBc7KXRv2Uv/T5p23flRJ5zvl8flmc+3q5czcYqHV6v7//vu/+I2/kznzAlW2mrR3xnEDdPoGEGxB2VSMfcNNjdkjXbCjSZO4jngOOi5pJVoZsDZJm9m/Cwe0GEBAn1d/RQRAiRhhYraWxTIaY61FG/cRla8dcjQpjEysYzBsgTUOyAVhX7gDsDDyZ+598qfna0QUEWMEkCC2gy/+dco/neDpA5U8HgItgyIbwIiAlBCiATAiAI4MaGdmRIJ9FzIzE1GpVLp//cOJC/PZfNFP5VTsra+vh3Fw5dJv1pq1V155pVKp/OEf/qGI9Pv9bDbred729l1HFcYK8wvz7pUXz7Yb0ry5qhyj/Qntp8IoZmbP89AKIsRxfOIDPsEJ/uaBP7//z/aqq9b052aXV+/v/fjP/9JycObMzLsf3N1Yq2+sdusVscZ1HKUdJGUWZss21q1Wy/HiyDbKE1Qul1vNcGFpbHqmdPPm3XZD2ShXHk+/9q0pQw+iwM1np/7ix59Ud+1LL33LAj54cK/TayrhqamZKOS1tTWWaHpmbGauWBzLLJVTNnM6TM3vbabrj2wh3x9fnBb14rq+9MQL0IQAwAgIJEhWJMkE9aQdG7CoHe0SkRJJO5T1nUm17nlOPuPl0n7aVS6BAgMsdhAZk4RDI+I+a/SIHXQzdKzlOLZRLGEExmJCkrXRNtr1HcczVrq9sNcLQmNByM0EDAToCCgDKrZgLFoGBkUgCEwgLomrlaNJIUxnFAAIUmRMHFtjhUEQVUShMRzFNmJgUQyKRSXtHIT/DG5tYsE+Jlqt49ppHld+nvCT9bZRebowQucclVc6CqMk51HbGdUfZQUUWQciGyPbNEHl0aOFyfG3fvIXprtx5VzWdfmDD1fXHtS02fjH/+jF3/87//Cf/z//5Q9+8APHiV3ttKp2YmLq7/7eG2/97N2LF8qbD6ovv/TdpulL9lx+5rVPH3x66vzErBSzXn4Fopu92M0sQwws4dGyy0ffl5H3d8T1jsrDPq55Mgqj7uNITWtUeu0xKdhHzjc9pnl71HEe2f4x5cuO6s+Xtf487Xb0j/78Lcczvgf9HtT3WnEcVetbm1u3e3EKUNIZP+xL2AetlZ9SjuttbmwjOOMTpZm5iUyhNDufe+XVl30vc/Pmzd29jbn58Ydh487D9UoVmXaeu1rWqb12L/Ay/fJEvt1pPnhQWVvd047veXVHZ5LKQul0ujiWJ6KdnZ2oWwqC28WynV/4renCc9v1e1u7Oz7VYO7JF3Bg+hMRAYuCCGJFSKcRmQQEAdiSWAe1p3UmnXId5Won0S+ZBVgELII6SAM+iLTC0dNKE6MIK3AEABInMAhiziqlGCgmEatj8DENLiBmsgSkBLQVCg2EkQ0jjlksWxRGAg3iKHI1uA4RkVYGEa2Ip5GScrNCQCBxrBR52hVSLCqKuReY0EassjBkOT+WyXGCLwNJTUqNyRIrNo7DOAoIvWJ2YnNj03HiS+demMwHd67/EDiVTfnlwtj5sxf8lCjl1faidrv71rsfvPbay9/59uUP3rlx/ZNPW6b70rfOtWq7lb3tCxfmxTT8lFY98ikrlkFEowY5yQM+wQn+pqH/X//lf/9bf/s7ly+funH97s/eeae61379GxeuvPD6/bVGpyn3blfioG5NQCQCJoxix/estV5G1Vp7nbiTH4exiWw2mzNw1mCnUgnTeXXh8kIU0NbWTqe3eeEFW8wXZqbnqruyt7fT68W+W4hiyIwVO50+IqZSmXQ6cYuC56VuPFhpb0Zj2Rp84+r4uTdwzKeOLjq5Uc5eRth39AgIJMuWBjDkATCKgFiQWKNJOZB1nLF8WiFpBRoBhS2zYUPAjtaPyd39N6N8WoqYUJBEIRCJZhRBK1DWACBs4xCNg5z1UWutlVPIgQhaoZgxiGw3kCDkOGaLLgAmfkGFohU7ZIlYowVCjWgZSIFjCQgRUZMSJCKF5LJAn8Bh6YutP+4bPvBHHhex9LMi1EdumUYG7X61rksQeBANoFCMGBv3O90OXTr/XNzefnDjoTWtU0ulyVI5qN13ML2zvl3Z2ivnS5kxzxhaXj6lHPfh+u2FyYnxUml6Zv72re3Joj+W9e5sbk+Xc7ZnQl4t5H3dz/qUD61otISuPRHAAHD0+XNcnsMj+yCf7uEnGOCpB2Gl/bG3fnrt7TffTaVpaXHy3NmF+cWJWn33tde+HgU6m16Lw9vW7PZ6PSICFBvHcRwbE27v7mkXMpnWvdvb9can73/ws1dfu1woZmrVro1xY61mYqde7XUaPDkZZwvFRq29vrZn2MkWCmEI9VqXCJaXF5dPzVWq22urK8unFr75rdfPnd9u7uZ295x6YLHZcAspdEoROH9F2gMKcpLbYxM/XGiYiBQyCWswGccWU1LKQjblAQCyTerMCDMCMAwSjHBQpRcOfHmjzusqawUVkSZxBNkO6silWFjYWg61NS4iouMqx3GyrmHB2EJsuI+SQgi1MgxCblLz1VpOqsMiMDADAqGiQdIxWBIihYiuk2Zma0UkZkDS4vkqq71G51D3/Xw00L8/vmrBI8eVT3nUqzoqA+DRG0pYwQmRCZTEcdBvthvh4nx5rxW7rg6s3VhfmZ2E8YkC2/jh3Qeucq2nHq6sBDEuLo9NzsxNzi0Vc1kTs3Kzp89fyuaFJIDYLi/Pxj0DXmusaNw9kUhbDlCFhq3yj2ZSO6758GW189WazV8evqzn+rie368ajtpPXS7NVqs7juNMT02cWp4No6q11tHOH//xH4+XFjc3gl6vJyJa64mJcr7gb21tAdrF5QUvrVdXV+/carrOrU6ncfr88uTUouPgo4eNnd3dXp9T3kTc0duPzObD1uxCJl8oAfd73Zaj4+LYGGepWt0Lwp7jONlstteNH9zfGC9v/Pr3Xu6ffm1lL7dZIVRezksHznSXnRHpvgCkRAal3QitQtIERGKD0HGVUqjQeo4UM6qU1aUMupQkhCQliRJJq79gzEZpfgpJITCIJrQirIUZWBgsCwJb8bUyAgiaFCpltYRWQARZxEUkDa4iK07IYK0oEINk7YAEUwhFxAoLEwOYfXZ+IiSlmMUOqjKRQkANWjnQObz9wxG5Jxrw4PNRX/iqXReJIIAIiiaJrYn6nWYnat4JetJupn1FSOvrN5rVXVfqlov37j9yvHS2mL63drfTj1qd9pznXX7u7Ls/+P927PN3V/q1ajfX7YK0lLsURr3KbiNVaIa9rqICsFFKpXzfRMp+xSwBXxZONOATDOOpa8BRGO/tNjxXzcyWtXYbzX69xgrVxsb23nZ469Ptve0YwUfERqPVD7qtbvvCxVN/5/d/t1gY+5f/4l//6b/78Tvv3Dh1ev7evd1W2/5n//k/On2me/3jP+sFUbfbymXGrTQRXc/NA3spb5JUwXMdwtQbv/n6g5V729sb6xurrusW8lNhYNYeNhvd04G+ajKTjgSm51drpud5PSc9ivKKAQgVCitihegpdBQpha7tea7nOAoBfU2ljCqkMe0IsRkwTQ4x9yb+YIBkOZbBnyKHn39+4PaDoq0IARgRBCYRYYuoWCsHkEWxYBIaFduYQYxFZhQgAIUohBj0QxGJmS2DgGIEUAoR+yYkIhBkkNgm5EmWEEIwwIKIjtKKCFisAMcmKYd3ogEf9fgjk84f+R9PxijTNyMDKABCQBTkOAq7zXYv1HF/PJVR5BO5/TDY3F7xuZN7fbbSjX72wUff+Na3J2emH7z780JxZnoi32nu3rlzd+LcqR6mM+NFVzY31itucSJoEJIXhM7qakelXFGh43ra8ZLqiEe7gK8YTjTgX2581daf44Le2d1utw1kpdMOAND30sK4tVMtFsa7balWo04HinmXiKyBbicMgmB17dHP33vzygsv1hsVQHA9eeW1i+1WfO3aB//D/+eHDx48SKfK09O8tdGyHAP10+mCtfHOdjOMo0whjWSAujdufuT5juPi7u42iA76kk6NFfPzq70zvSDNniY/HdhsZFm7lPUt90ZRhSkERkAichV5mlxHacK80l7KIYcExCXKp9F3RKSPIsCYRBHKPgmGICWMkokAHuYzGukDZkcQAFghiBjFAALMVoBACBCTusMiwlaMCIowkhAJarYSA8RGYhv1Y7CCVsQyWgBABaCB0IljBCUIVtDEHLMVIETbMjEhuEp7LjmKCIAtMx9yJ8Gzo63+KmN0XuPgjUJEAbEm7vdA2oszyylywqA9VpzO5yfj3oOw0Uk5eUqFqzu7p2u1Ymns6ouXJ8dn47C++eiOkO9my2OZaTRKer1q427QelRUc6+8/KpZx0cr/fJLKXKDEFTcCWMb+37mWPp/VPyyLqxHxZelAR/X+B85Cv0Zue9HzT8+sgl6d7eVTqtioVSp1D7+6LrlxtTUVNA31U7LUYWUjzatmanZbLJk0xk9t7CwW1l7/9q7i8vzl54/NTU79uDhp43u2ifXmo1G/OZPP7IcX7169f7ddUEmjZ5O9Xr9XlCxhpUrnV4znTNnlpfv3bg/MzPluDQ/Pzs1udRt272dXhSoip7kiHxoisst7Rsnk3dqTrzDo8KgARhAIyICkSiFmtDVNJl2Xd8BR1mLpGzaBYVGbAygAIVEGCgZRUFKfK77Wi/8IgJYABBQkFCYhBg48SkjqKQZQRQGthKzWCPkEJEG1IQagY0x/TiKI2soxcwxo2GMBZIqTUCYsQ4iWhBrODISGQBgQegJoECobGhjz9EuIYL6PD3WoRJ8IosB4KtHnTgSyAxAggAEAMxsbCxRH8Td3W6o0CzNz7lpr90w1TDqtnmnWp9fPvNofc1Lh3//P/y9h/c3/7t/9V/n82CbiNpXKr/+cLPk2cWlU7pwbunlFxwFWz3a2ayWX1Fe2hKmJESXQnuSX36CE/yNQ6OBr393eXrBtjrN5y/POur5d9/+ZKw4s7F1e/ZUKZN6BCY+s5xVMnb71gPouRP5/JXLr1+8eC7j6atXL2yuVx+ubLz14/XlmecyeqJarUf9cPV2p9/ShdRU2AuNo9BDQaP8lKczYVhXNliYGP/1/9Ov2agzNzl77b2NtY3cmZd/223oB1uVQjQDWegBYIR5aCK0ICKGGaVyAhbEKDEIVoPVJABspC+CiOigZLUq+jKWhowDKWUQYwJERzQCMaIAgWcUAIAMlz+wFgD6iIiYBD0NeDeEEFFxiIhICTM+IAoiIklsooEXeR9KKQWqG1oYFFQCBrFCCIq0kCUwBALMBi26Fkk0K+05oQhaRmswMhQbNjEbhjjtMAuzWASLJCTMICyMGRHLkRVkNIYcchVolIzvGWuN4ZgtMwyymFEhH0906ygBNqpO5ygcVx1QGFkn9cntH1e+6SiM2veO7P+IohoomZTjOI7TaTXH8v76g2YfM8unzszPlO+bDrtzm2pi984axop1yNqUMsHmg59PTU299sLLjZ2NjdXNVGoCHXHilWwvCLhaa/RXG8GpLH/zctbJdN+7692wxXOXx9NhzTZV1489h+q9qKi8YxmHkRhxvUfFsWneI4hHUEbVx30yRlWWpBFk30xCACIWJTlX4gtj3Od4/wwjvee6w2zwBy6zmEdpZk/ZWT2irvbRb8uXowEf9XEfTZkzkkrniZ+qUVzQ3/2N2UuXJxaXJ+v1xanxxXPnLp09cy6Imucvnb5/5342DxcuzC8tLDqOt3g6Hwbx+Sunrl//+PqNRnGs3Kj32x0G0VHIldoKIo6VM5OTs6XS+O5OxVq7u1vxs3prZ8Naa23QjTuZjJ5fmipNlDDSrUrQb2yvrreavfy4zeYmZi/NXolMctmPeTER0ZhQoSAYInFQHEVaCSFGFtkCD6XxHg6DIKAoIYtJPT9kEByYnXHAxXwwkMIIyCxExCwEgsKIqBKFmBEV7BM4AzAaO1jrD8owJEDSycPCgIbFcmKEFgchqTFoCUUQhdABtADEwCBIQAoJgBAIEMUm3+SD0kwEwAAIxhAwgXW19j2ddpVWoACr8eGEeFbMOyd4Ipg5iiJETLhKC4VCOp2u7lVmJqfaYX9+ZiYF1NnlyeIFJmw1msunzn7zW99N5fSNew8Z01deeKnWWJ9YmmRPe6TPnp3fWulDGDL7IlkynazvKoUM5HppRCUmymj1lbMEPOMQeTIhDIMSAQBShCAIOGAqFVIH30x+J8+wsfK4AB78/DUk3gm+gtD/yT/5u9m80+02U2lnaWGJJazWN/JF5/yFM7X63q9999XTp5dXHtyr1x9devH8pfMX1ncrYTxbqdS0EgC+f/9upyWek+p2K5OTkyK9dnvH84QoLBbzcezduv9oYX764qVzjx6u3751P52enJo+3el6b/3BWwAwP39e+6fnpl9y8vP1fkacAuIg4/czMlhxiAgOsUvgaPQ1Opochd2YrWXLjCAKQWGSEWwH+xAZpPEYECWASGwHVWuGp/Vjk5slsWYn0ViOSng5WACICBEQGREjc/gIJFFdSREkRm1BhIkFLJAIsaAIhhADWEEUVhbFEjIoS2KNFiQBsUhMBAigBa3EHIOQiLCgEAkwgEIATywiaqVSjvI95WqtEQA5KZszGLG/QR/w0xb2v4KbiWQuKSJmjuN4fHw8k0nf/fDDb33n9cnxQhy019ceuRDNjZenF6d2Ht1fXjq3cPq5h1uPVrY6MxMTM3NLqRQ0gx036yqEnokmxwtZ9iPO7e2BDRtj+UnHMRGL46XIkoRR2vdM/GyM85c1344rrkJACQoKWRRCVIgCjKIOjGn4uI5mrE20MNnvXtLDUfzdT/95Oba476MdfWzX9XTXxiP7gN99624Qby+eys4tjG/uXreGkOzOTp2tXt/Ych1kifNjfhBBZOrtYOfU8tLi/NzG5k6xMF1vBO12/9HKtmH7wnNXr169+vDh6vXr13d214N+1GpX791bZRhnk5HI50Bl/bF8Zo7t1Noab7am0l7K7c6ksvMpfz7mFFulwWPsDl/JwfW4mhWIVuBo8B30XXIUaEWIElsyjMCiSRARBpZbSujvBIUEFBKjkAxMkZ8XwER6UHY3QcJMiRAnQVooRITEAxM0Shirg76JiLViLTJLLGbADYIakAC0oAKEmGMRsQKcSGsmwyAiEaMAipBljBktiBHhxN8LAkhAgkKEBApEME2IiIrA1UoBWmtjNmKsiHOwRiAi7HPPPe0H8iTg63iBA4I29jyXSOI4LufzriZE1Wk2Ziay9x9thWF/6cxiq3YjiMJf//733/9oc6fWrXW4MLmovXwY2oly+eM3P/juaxHYZq/WGS/PpnR5o22qwtJrFiaWfO7bOFRauaBFWFlrvqA+4i8jjpyuNrqhJ38+UgMmAFaEIMKY2L5QYFBWHD5f1YN00qvPnmaEqfwEX4yvWvCgfuetD3/rd74R9Brvvv3J1OSMiDD0l0/N3b3TZavuPlrZ2dk5f24plS60O1Gl2nrv3T/b3d1rd4IXrrySz5WuvHD+ytWLH3/8ca+3ububQeyn0ybod4vF1Pz8hDHVh4/0yr0V021pJTOTY41G88atzWJp4cXv/1NNbr8X97pxK/I4itNuKpNya/vRzp8RwL5LiKhIPAVaoybRSimFaVExWWPRCusBjb1lhggFBZFEWyIQVkJJfqXgwAQtsP8jAKjgsfPub5QEzAEzpSVKKvwKIgbxYRUjEbAWmJEZEx8zA4KgIDAICAtCJMAMliVmaw1bAcskIoJaxAqQCMZWLKO1lgUHzgqh/Xzegz9NQtHFIJFhETE25tiwqORC9g3xf0Oa44kGfLwgImutUkprTWijKFIqBSALZ87EYW9n/UGn0Y77vb1Krb61E10Yv/DSlTfffbC+smIdSqVSQS/Y2QmgTPPlqbSJ47jj2K7lsUYsO10TZfJO1Cu5yo2FbKgoUpBioshYVM/GOD8r82FEKMLARIcigIzCCCDAKPCYD2BoUzsqRmH0OJxowF+ML0kDHpXO+vf+o9+K4uDO7c7Dld5P6h9Mz6a/95uXXD/+5je//8Yb3//w2vs/+JM/vnnrYafVcBzFr2T+1hu/ubax8z/+j//m3/xPP1xcnr18+dILL75w6eKZax/85drabdfxMxmp1TrjE6nXX3/+woX5/9s/+zNUPaXTjsulcqEZdCu1egSTc4XzxfxkJuYoCF0PkSWOgkZ1C9Nq+EoO3cCKFCIhS+IzAbHCYMEjRgCFYIUUoCYrItYyCyKCErTIikAZRGQCZOTPeG2TP3mI3H84DiIABGBEJEIk3hfGg/Kpsl//IIl8BlBESgQNg7VgLBtrmdGKsAOW0VqJjDUWrJWkboRSjIgsnPBJG4YBoQcCyL7fVxAxcQNLYkJHRCWKCEXAWLKyX3EWBoN2opc+o0gEsOM4IoKEcRzHcey5emppMajevXf7eiY/AZZv37ybV32f3NgYkHhmvKTSutHsYCo1OZbT1P3aS1dPzUwKRGu1+yurD8pTy+lUqdmquY7LYrQEeSeVglDZEJUXxuL8ainAI3FcJuhRglMBJxowCqMCEiBEAHDw0Bc2/BpYe2B2PuiJiKB+ctDcyYP/N4Nj04AfrNytVho/e+deHEImXVx/GD26FywtLa+sfXLlyosvv3K5UdupVRsr91d2t3ZvXH/0ytXzX3/9pUql9of/8w9b9d7bb31w7cNP5xbnnr94fmczSHmpQLuu6kd9d2+nn06Pzc/Px71O2lfN+lpUzJfHx8vuZVGL7U7kuYiU1bkCY78ftMh1AiOpx2OvDl4Ni0UgFBEGjWBZRKzCNBpAQlQKCSWRPWyttaKQhPddoklcsAKwI0zQlj8rmJM+ROIMNFACPCiUhOjBQVlfSaxGiAk1h7bAxnJsIDTWxGCsMLOxLjPEFgyTNcCCFhAE3X0+LgvMgsxsky4YGEhfSCQxAVgAQsbkHyRIhAxkGWyykz4cNATAA6aRY5kox4WjLmRH7f+zbhJPTNBa6yjou55i5iAICqkCZFLBbtjuVHPZ/JnlM4xOc+PDbrXx3ofvG9svOLZa2WhUa7nMbN/l2DYnTk9lS+l8upC+v2krDY8kbcNGq5saL3X7/Sx3pvP5Wp+3en100qI8gPDLvvRfCE/bhDiSCGv0P574cRJb9YTPbYyIhKAUKQQniR1F8ZUeXpQOypphLAeRz7BvbxOBeISAt/bZnv+jcHz3/ViaOTboG9dX8/n0t759pZCf/vja/ZUHq59+VPv04z9LzzT2qmtXnn9xcrZULpdRVKsZPHq486Mf/zGATE2UT58+fffueq8ft3XUrK/8+R9d01qfOnWq143ZjK/c7t649oepVIq9aYyd8swsmLhZjxpB94WXz15+8ffuGRbLQRAQuDGH/TAs5POel8KolfTsMxpwaJlAFIooAGsBARAVC6BFAkWUBDqTDFisGAb+XkVgGBRyEgwtg3k8/CMAmIRQwedkcyCDR2RQnZAGXdIaLIu1nDwqRKQUEVIUWwaxLDGLZbAMRkQAAoNshRmNBcMoSCCEqFjiRHoKoAUQHGjobO2Q9BUAK4IA7GrHCougEUBGK2AtGAYXEwP04a090YOfRSQCGBGjKGLHExFjjNZ6ZWONm41SqbC1ueEWsy+/8nWu3i1lcqvr99IpN+w3Htz8MDK2mw7W1h6RG+fHsNLKOm6xND52WvI2iNu7a/O5ySiXawWRYDCWcTKxSByhkwE3DebZEMDPCkYLjFgBEYBL6CjSjnJIIUpK44HoZWbmwZ+4nxh5IICTBadpRiZGPaUrOsHTgO62ar7P33/jt8jRVnVWq/cf7e5Zo5ufxLc/fOdv/+3x7c3mW2+9Mz1TJCr0Av3WW9GbP/uXV16aw3Q0MSdBW1157rkXLl/8L/7ZH6dSXrXbqlR28/n8+avn33/vg1qvOZUqqXzm09W1lOPn02NBXz6488Bd3srMvmhQxOWIAvI9z8l2+jspTxMVkp7tz6PBbwcQABkwZjSCODDMYN/xgS2gVRhrJdpBzyGlUr6Jky8m8dBm4HIQhwAEGVEELYMVTuooBKIPBmXYBBSJ+8SBazmWmRPLM5EiIE2ahLpd2Ldp875lWgChH+5HbIFQQgGCFsD2zOcfGERAu58XeOgrQQCAMLEzDz60gKA0KFBsk9Cv/XgNBAUAKNYeLQ91ZB7hEfFlBTsc1YR41OOPyxQ5CmFEuWyKIWSFvpgZ2zK79abTj1q5lydPbXx4+/T4xLaylaC21dzM5xbu//yRq8YX5s84/szW6kOnVVlcmvqP/sFv/+mfvfO+9q5emVlZN41Gr+Drve6u5+swuiCPbsXZ3Z32mLiZVG5sp9GdKkhnxMIto5yZx4Qvy0IzKt9XkJ9ogRtVFzwJ1xxs0YkOVNWs7ic2MaVQEWgEIkKAuGeISCtSOnQItUosc+iB/xn782Cm6X25CxxbsQzWWhHI2Y4VZCHDOrZkWLEoKygjfPlHzdcfjafrix09H76c/o/qz6ingo5oKdHf+tZvbGyu/+Qv3l8+c3p66hTJz/uBHZ+YGstnd/e2fvjDH9pYM0d7e3vWWs/NVCvdSy8sFnKTD+7fatfDtFeqNeT2nUpp3BVhIsoXPKTg7Pmp56/+3YcPH37ydtcCdVpc6zbsRGZh7oXymZcL2cmUyu5UtxTJ5GQxjOMg1ErPhD0L/oiC6k9Csh8EEGARBEQgCzEhiFgeEbyQZAgLMQgzGMF9hXIw0WEoE09EolECDGEgYQGQhUiUMBGYfd/wZ63cBySROHjdP93TXeBO8GxBax3H3SDqWgvWSr/fD3sdp98vlYv312+PT05MLy5tr9Qe3f60mM52umZ6aunf/tFP1TfTzz13MY77bJ2/+3f+wxufftBqtUqlkjEmCk06m1NobBwjQLe2OT2WB20++HRl6vKij1wq5gOInn7wzrOB0abpUaZmgoPUiSFbsRFRAoKCqFDAKNAMiIJKI1GyhRZCIKDEmEeQ3ILH04DBMAMM9uwugmFQmpjBF58ZDCMYEEAGYDYk6uQ+PlvQP/jBu7lcbmv3dvrd25efv8LGS3lOvxukUpLN5uLIuq4qjmXC0BTyORHhGNt1u7ZS73VIO6V6EyqV7ekpPTs3Gcd2Y30HQCHaTrdenpy0UA36cSSaUHt+xnX88dJYOu3sbT8sxvWVT95LefG0Pt/v9ft9b2bhFa1zv6Ah7EARsTyQZwQAFhFBUCyN3LczAyMCCAvaxOcqSkRiow7aHN6KhiOIpOJEt93fximFREAE8Dlf8v6fSZTLQQz2IEtopMI5QtEarYEdbeEY2cpTzoM8wV+JxKORy2Uw7nU6nbDXyRmD0thu7fnlHKRypUJw48YtL+cQeo1aCOI0Go3SuHv23OnzZ1967+cfWwmioN/rtCzDxNTUrbuPXNsjgu3NzVOvnpkvzbR33Eern85dJug3WI83IcrAU2bC+ophtKY1HEsxxEOgRkapHRw5LIBjA3bAu8SCpJAEEh+WLyhMwJiEdSAgIIpSTybSYWP3vUnEgCgiQiKC4jGDsclnlkWYhcEAOP9e4/LLjuOyqB3XNkevb9Sz2bjVildasYkfBB2bz2fEmm63p8jPFdNnzy/Ekbnx6Uo2m2+29nwv3Wi0PZezubHIULPdCkLJjxfL2dm58sz61ruR7aZ956MblQhT6eKi6Hu1WjWdL6VSXqO/u7b1SU6M8cfDLtfX3w+hU/EXK7VmLSxktNa5i5Ab++Iey35s0cBEvG97VYiJPVgxEX02n/0AlIhDQEEQAcOJKoxhjPs70AMBiQAQ2xECifBAuCIiysAApXjYjjQIhILkSRv0//B1+M3nz/DF4/AVwXFN6KeNZ6WfxhhHgVIqlUoF7Zoxplgszs3Nra8/yuRK641OoROOlXJZJ9xaf5Ap/HqrGZ45fTGbzbbajTfe+PU/+9OfP3y4Zmy3WLLGmL29vYhTm1u72rSXFubPL50pL05Y0TcbBrwZV6sU2GpkvPEstkbsNH9p08y+6Pkalr4DE/SI9STxNB0sR7KfxcsWEEELspBWqI1QUt0MMXGAWRErqEC0ICIZZQ7PODQslES3ACZLBTIysACCEAzsZ4KJzyrx0cmTBfBXLRhzFJ6Vfo7CUfuv//P/zT/6oz/8t4DFVErYqk6rr4iXlucDVo2qabXaZ87Ozc3NrT6sNuptw5GJ7ORkYWZmqturb21vp4uzi9NXZmaff+dn73//exdLM3mVakdx55M7HzfCqFhK6eJyIWXnF5Yh7m+u3GzUd62jUqX2zQe3cwrzrqnc/6gVxGMzL5dzKZ0d2/oFrm1YGzMJsZsgIxIix2IJCdHSCE7OROVExQgiYBkYRBgjOWx5WBW2Q77hx7DfvAyM38gWENHwoQn9Ma1xn1M0obw5IL6RkQQIRzDFfwFGa8DH4xM9wfGCiJg5jEPlhN1m0/f92dlSsVis7zW9dHEv3vIyhd2th2OTpW7tAWGvWq12WvHsfPl73/v622+/bQzMz89Xa5u727fy2Uy10eyBdtOZnXsrwtGv/cZvYbpwf6e6U+ucO7XcaDfS6bKtoowI2f0lxl9pav6MBjzq+MS3OvzfgQAGRYIxiGIEAMugCAAGBi8CIGQi0AYchUTU3SceOIh3Tn4pTQCQcHYYAWOT0BOMY7KChm1sIWYxDALAhMe0bPzS4iunAT/30kIn+Bpw+mdvfVSvNgrFTCGvTdyM2bhuptWuxKazsDiZz+cb9T1Q7Dg+W2rWuvVGo9uJLpw7vXT+9WzxQu0ntUp/bvn5Vx3tWg4Wtle0Ez94eLu46J4qT84tLjy48X50f13btgQNFSpPb14891zJ9x49+FR7ZvnMWLHIjWAXnMlfZCAO5AEDogzSckSAkdAkaUMjfDYsiEpAEJUVYBARsvs8NMPe38FpR5LIHzyZh19Mwq8/fwwMxU19RgM+ah3Wr5ogPK6gp1E4rut92sFZxwXXdcXq2BIRRVGUy+U8z7t9+/ap+ecau6sXlxdnpufe/Nn7504tzC7Xg27L9WRyauw3fuPXP/zoJ5VKVVNhemrSSrPdEAAuFMvjkxcebVaamTSyrdf2HM51ey3HVX4mvdNYL08vS82Pui0XRlXcfrr46mvA8At0cnhWDGIwUQsiCQhIwi1vWAiQARMjMpIoQoclZlA4WID2T5TY1QAAUk4iztEKMIuxGDMwi4msILGAEYhFGJARn/WizvDsa8BHhf7BX/yrF5//ZtqZeefNd1jCmamxUsnr9PaWZ0+v3G0xw1518+79G91uf6xYbvWaxNlmJahuNMgxhYn5ufnLqcyymzr7O//rc67rZgoFZuNrfW7hDLNpyHg5kylNzWol69W3tyrNuWK7TOFEKU0u9oNGoMdD9Jx0Nj9eZB2AagM8WQAPY3i6W8Gk0AQLAChhIUlqJDz5u2gRUQRJUESQgVgEQCFZAICDWoT7bwhHVP/Yb//A+pR0bHTUKB36fR93A4/o6IhmTvCl4mkvECKS2J8dxwnDMJ/PZzKp9+/cPbX0HEatmemJdr2Bqcns9BUvDn2VHSv7r7/63Xfeeafe3A2DOOBWUMzOL46l6DQhpnP5VGmiH5rLl1+Yn8xrhQ9W643e3tzkJIoxGthLZzIlrbo4Kq3lV2xB/LzQHWi0I6KInzgfRATJgSQ6FEVYGBiAUUAIUNAIIoNCZkEtQATGaniSIA9cAADBpLoaxVaYgUE4RgFkRAYxQJzEYcEoe92vnGA7LhxVAz6yCbpSW/Uyr2syL79yeWZqgSBeXCzNz5dVZvL/+n/5f+xW1hyHNjbWWq3WxfMvVxqdOx/1SvlCbMFylMtMjY+fZncaqDxzplip7EaOdLs9T3lsQZGzeOFFG3XS45Mi/VQpN7UwNpWLyuNmeZGy9RdvXd9quhBFc1o5e5WUdPuoFYz/FT3+vArCAEm4AwuikH0skvlzAySQkGQBEQsCgGEAEKX2H7B90btvK36yTUfzIPrxwNM72Pk+Xubs8H7wEyK84MAm9fl+PvnjE/ySIwxD32UB6ff7rVZrJp2en58be/hor7LpS4/7tZu37s+ffrU4fWH70d1yfvYf/5N/8F/9838N4o6V09bKrZs3jO2+9vVzu9amUqlev1/f3DTWlscn46izs7kVu9MEsrw4Xe8ElEs1uqGJkbxfUvqGf2880e01jGHf8MExiGhQkST12BgSavfBPzWKZREUAmJgTFzDxioYyj462KNbazDxlwECoBVIgkZRdFLI0IIYEEFgEUYcJYBP8NWE/vAvwQkeCTx6tHp9fj77n/7Hv/fq1csr99Y//fiDV15dZG5ce7t64Xy5ub1lpz79X3379f+yXZkozafc4q3b9+7tqvNm6dzl12+tNPxWy3V9E4Pn5kCAEETA8zztS9A3lnMvvPaPF+ZfvP3zfxHuXnvZnTl9ZjymJWfsG9nZV3e7puF642PjQTsatYM4XCE+a4uGQdotQMLB/FfILnUQpCCJGpvUARP+rC/2i5sx+1TQQ4ceJjINde9zzy0+1vqo/MLRe9lRO4sRH/9V0Z6fAfOTNxyj6uyOwhenbTzpvCN89qOjT4/UzigctZ/WPl0nG6aVjp0+BppbS2nJZsd/vrZ95uxLvtlw3NTN7U0cWzh3/nynvtGu3UxlyzFOFou+1rrbbY+XxyYnigTOzrpZPn0pNz7Z3FofV94bLy31e+rexvbEtCN5vLNichOdyQLZbXTL1Vamt+5kSvGoHo3S/J58X0aWTx3RzshYBBmZx/DET0fOK4yS1hCVgoNaKmQghMdNzYOgTiuKSCNoEkWgQZAtIFs3l0hHHgIA8Kh+mnDg1dq/IEANACixIACSABhQhiGMAACG6s4+tkDEqIZbGfiyEGyyoRcAQA370l0AR9TJliOK5qftajmyRo5Pfu6Ommc/ajWRUfW5R6yHo3G0bBStCf7iz3+WycBYSe9s7H7w/rsZj9ZXd7YeboF1y/n05nb71o1H2smGPPYHf/QzJXMb62vf/95LRue2W1100w9WV8fGlvrceOIJms2OUuz6TjqXzftnuff66qeVd69VXnl5fmpm0SksxV66oJQlEBE35cQnVT5O8CsMZhP0TezYTNqLiIKgpxSWy+X62krax1za6UnQr2106ntRGHTDaLO5Xihme93guecu1qqtb37z20rpeq05PzMzVS42G5Xx8pjY6FGn6mrIeHqjXZ0slQgo7HbKee0XlFRD1y0/K1SUR4WgUogIihAxIVZnYWZWgIgCg1fYl3FaKUQhSmqPiogAIYkaiNsB8bs8bfl02P8jph2e4NmC/qf/h9/tteJPrt1st6ozcxNBt/fuu+8TehI3ZqZPsTgxu9c+fhAbqvdke7ebznZsnK1348uvfa/YajdCGMu7MpqmZGp82oJjGI2JKJ2fWLy6u7t7f/POTMVfPHvayc/F1vd9LxYTx6HvevHInfgJ/iYwemf6bKSjPG1f11P3pbEAAAqINWG/5zrWcTQBVis19sO4U+3ENTZOv9eLwn67H9+7dx/ANJq13q3+1uZeoVBamD/Vbvczvuc7jhKbSzktFQbdmu+wgrC5tz67cFaL0+s2F8t5LxXYIPL8FGI04oJHfHzk6NCj+VpwtJdt5BmeeHQSDJUk22LiSxUAVsqBx8VbckEaB5TvB1qnADEOLCufl76jg/VG9ee4ghCPpmkddb/wlXuOnhEf9pF9wG569aWXXisX45X77pkzp4j0rbvru9t7c/NTpybOLuS90jzWe39x69adR2urKc9Dy2HMW9XumfLCzJRXbbT9TLbf7+KIPP5eL2I0EbMxsaScsbnnX0lP1fa2K6sfjPVznq/61qKPLBRZo5lGGwlOcJw4STf6akKhZNOpPgTdTq26t1cup8RJ72xvpdJ+1GtEvYYHKWhtcS/0NZKX3thcmxifOn/+7Afvf+J5XqPeeunFybNnLuxt3a3OjHU7jaDT3NnZbNUr2UK62dxLa98F2Fnflu7m8qTJueMpRaF55unYviCtCFk4YZ0SQERHIyKJokSSDjtuAUCBhX3hJiLmINtCBgJ4uOWDrN8nnvhYruuoz+PI/vySPtZHTisasXE5KjHRcUG/9c7Htz9dW5o5dfm5ZSKZX14+//yrP/zzn/f4agueB8/NZP38RGei7nVbe0HURnA7gRqfO9exLrv+zNJkfbeR0hk7IlhJaZcQAEQpsgyBcd3CckFNxJ2wGWfToZDnsAhbIdSRNXgigL9UnGjAX2771kZae5pUYONqdU/Ed2kiCoK8xk4UOUoX8/lOt9uu7rluEBvZ3NiOIzl//mK/348jGRsb9zyVSrsP7m3NL00bY1qt1sbGWqvVKE/ld9Z3ndJcs1HZ3q6ksLtXqY3NR8VCuRNaGSlIRnz8jGjATsKUJxZRFIKrSGutFcU8qAjOfCCAAQBkIPOEmXlA2wMiAvup0gfcO8nrqHE76oL+tNPtjiqAv3LP0TOuAY+6vzroTv7kw93tBfPay5e6YaNtnMsvnjl/5Zv3dv5W0+atKA5M7L78wtdeMUH1L3/0J4x09sqr5bmzTjrfY+52u57nEY/M/45FACSOY+04iBTHVrQS7c2cfjniPnqOl/ZiJgYiApbg2Di3T3CCZxBsbGAC9jjtuSYOG7V+eWws5/mVta2g3ZguZ8oT0632ZqtRKZU8RiJMNRu93Z3q9PTs6urqmTPLtfrOg5W7OgrCmB03HVgbhHGr3+30e2EcbN+/P382N7cwXfBLe7WHmc2mm53REsa/nC5g8CkJ80KFohU6DrgOKCWJAD6oZob7iK2ySZ1RRB7U5QYAdZDg/5kUYT6iKfioeNom7l81HDUo9alrwFamSyW31e5t7QTlyYXtzVQ3jvJjL6rsRB8c7eat0MLl75XHsiZsTe5Sxmu98rXfVJkxrXyXgnq9Oj05F7bjURtT0ahRhWEIxiqNkYkYLILVuQngFkDPSEiURkRrAbQ+EcB/Mzj6xHq6JrXj0gyO64H5skzxWpHExkZWiThKZ9Mqk01xx0rYExEnk/cK40I1x/EKhUIq5dVrPcfRrlM9f/7suXPnmM2dO7d3drfOzs3HjKGVIBYnla40mvDoYTbnWYMTU6XJ+UUIux8/fJitsF/QjA2A9JH6+VXTgEf1J62AFGlUSotWoImJmBAMJbW3mZGZOZG+RBSgawSNJWFOSnUzEAABR8lZDgTwfn7wyAs+FhzVp3tUAfNl4bg04Gd9w0F37t2NbRQZW6vHDs0V8193+Fs2+Ha6EDrpXiC1kMLCwkJHp7g4/a2/8x9/7Xu/ky3P5cemGo0G23hqcrxZr7ruk2v2AUAYR+RoR7uO0p5WDlmlIqXCdj9iopCjTq8Vx6G1EkXxiQPyBL/i8DzP931m7vd7StHU1NRYvtBqtRwNItKPpNGN6t1eEBlmbjeawk4cwfb2TqVSuXr1hU9vfHzn7nVE2+3HnX7U7Pb6Yah9v95orayu6pT34ksvLy4vGbC1ervZBMct+alMJ6h+2df9tOA7lNGU9Z287+V8lXLJI9YQewo8BS6Jg+ySHPxoh1yltRqAUBPpzxDL4y+A4+r/027/BF8u9GR28dLZ1yfHTxnb7Zne5q137t74k7Hchelv/a7o1OypCxFg2Gm4mmyntzBeqvbOxQAxx37aA4aox76XjmxvVD5WWsD2epqAwQaxBeUyA4CjnbY1QJABDTFbQOu5CuzIvM+RifDHNRIjMCqv9Kj5Z0eFHcGNT+rJ4yAjyi+OxOgt9JM/HjH+fMSd9eilY5Rm/NWqR3tsmvqIdLt03K/E7lhxvFt7mMp5+an5bHaiNB1S+YX2zWvPXX5diqf27tSzC7GfClzH6fbqQdR74ze+c/rc8o/e/EsvU5pauAqiTNadHctuWV7f6p4/c/7VX4Mf//TnH//0o3/wD3Pn/Pl7q/rNR6Z/7kWVaU4Gm354llJHSz8QeXLUNCp3eEAOhoVYhtXHg2MM8BOFikKV5NoO+1wBgEjB4KkXBEaBJDO4J3lCUcgKQgVxypVsyvU9VaYaAIGQCIggW0rKeMcQEKKLgI4a7pW2bUtoEYyFGHVsrRVgQUgddE+G56phJSIJVzMDWkkY7kiP4KLnEYnSI/XWEdOKRoTKjDreGXG8GbGCjlhmRmLUeigyYiEb4bQ8cgzKiH7yqMNHDJAzQu4cF6/AqM+1n7aRrTx4VL91533H709OlsBVW7Xa+/96+8ylq1PThWxpTmtXQHd7YbUVwQnVyglO8NTgZ9JZ4xNBpVIplUpBHK3fujU5Xqw1uvl83nXdu6sPTy0upQI1TrV+p2usfONb31lYPL+zU9/eaU1MTE/PZW/evLWztalJGWOmp+etiTIp37JBUq6e3mpGscMp1S2XzrTae3bSU27zuEzQYh/3lcJAstqEckMS8rj9gwUE5cAF+3g7BhEJDznUk2MsEgAnNBQEieAkBMhAoAkVGYesg+w7ktLWRVDaBwAUFBFmQAAFSkQIB3vBocoHgohASgvGFgFBLDKCWETGUZmWDhEAWAVsgROiSSZGGCl3vmIYTZxygr8J6Pv37z1a2Sb0Y9u4vLzw9W+8uLvdffetm7wXVlY6dz7wivPPlecv58dPdQOJ0XGgd6QTjN4RHEf3nz6+LGvPcWlmRz/xkT4eveU+wV8LzVbbegpJddutF89fqDS7qxs3Ty/MNACy+WwchxsbW2cvXIy29xxR1prnX7x6+swFRp9IHCcMYz07P3X2It67US+Vx9pG9cDLpLWv6dKF8/MZwzC51kaROKM6S+PF3fVKD5TjtWJzPAI4SdfBfcF5INgI1bDysc+4joKEiIlSOayJoo200lorADDGMDMIIBKzoAzycRmRiAgVEuWh6yjtanQ0eQq1EleDVpBwMiMishAJI6ASEXHxMINo6A0gusyiLKIRAGE5ULRHqJAKRQQFRYERGbA9PzPyF0YZmI4qmOWYCJSOax07YlD/F7TzlIOwxstzu9tN33McNXb/TrXdfL/f5bVHtYVpqtQ+ff8va+7Yuctf/93nXss5To68lIRHE8An+OXG09+gPBsboCO3PyofER3PcZBDhZLLF9erLQDo91rAJoqinc0tR2HQ72+tral8f3Hh9edeMFtbe7FRpbEpouzuXj1XbJQnSvkXLmutI2Pf/+j93/+t7/hKXnrxitvdq/f6USbfblSzmvJuWHVto9fK6ExzRN3rURhlcjwobDi4wAHLlCj9GNfxAfQQDeSwLTrnK8fRjuOISBjaKLLMjIKAriT8swQICpQQIRFqAE2itXIcVJoUoqDEzMyEKIpQoyISTYxsEVA/1v0DYSwiSWVdZhaL4CAIskXhEaZaZCsIwGBBkCHJOUah0a6TpxttOzp47clQT70YzDOiaR0Tjnof9dmzp7udWzYmBL+2123Va+lUoTy2qGB7biLHrux1Vtu7t6V/VXuAoo66szvRgI/3vE89YfxEA/5Sob00AIT9tiKst1oRw/nzF8FEtVotwz1hNbP0/M7O9tb2xkK6cObU6Wv3axurG7nsOIFohYvz8ynX67Talxbn4iC8cevOjdu3f/+Nb8xNj6+37Mqj1fx0f2zhG5XKzny+EIR7xUJkerVUutQ8Yj9H+rQ0Dnt/D33AEssQhsKJRESSCihJXW1CQsSiy54HrosiEDkURcQMiBgjiYixbFgMWxZmsMAQAsQgUcRayLVJuyBCGgNF6CjyNHsKXRKlUSF+3gc/2ASAIQAliMIawAArQASwIzS85OwgifQFEUZBFgPkH3FEvxzgSI7uI7ZzxHSpo7ZzVDwzGnA/rFnuRAYdnc3lco7jGWP7QTPs1c6em8qVSrLdK3q9stvtQ63VroP3V5UrOsGvEp51DfioaVFHbeeo6IcRWUthP5dOtdrdVDpfzPr1h58IG9dRGqFUKD7a2OQ4ch0VBD0wpphNTU6PRZExMY5P5qw13U7XQbdcHlOud+7cOeH44pml63/283qzpUpqwrYlCHC81Op1S343TdQUOvp9HDVuA2qKz5TWVhwOS19KjMeIhCwgg1AXAUIiIAQsOLGr0dWglBJPMXswuClkmSNrg1giYwNjo9gyQyBKLIeW0ShCQVRJ4fqMYzWhrxkFFaJDgAQILEPzarj6GVoLLCCgES2iS4giTAgygmiIUETYoiEWYQUgwCQjSgc8fRzZdTUq7/O4eDJGRUOdAAAAdL3WKRTGEPxuJ+p1gyhuWhvl8qnC2JK4bhD2bNhobt269uYf7LUR3ezlN/7pkU7wy6oBn2RMnWAYR1/4RjwXjutp5Xhu4LtBGLulcq1Wqe3tzE5NQq/OzK1Ws1QoNj3P85zVhw/2NtZsHNT3HjJIp93Y23ngeOlcrqCRi8Xi4uKSV+v6Wk2WCp6jxycnXMcJ6itZv2dT04HV5fbOuVPZj9o9gPxxDMMgCCuJn0pEbDIyPtp92ikkIiLSWhOR2i8xlDxQRKSUQsSi29ZaHMWO4yTtAAAiEBsBNEIxY2hUP+YotjFz3XpxbOPIWGsAEBgBCQRjQ6DQEBhODOCAzIBsxYVDNX3ocWaDQCRCQI4iRFIKrCDJk6PEiRwrwgq0cGyFWSyzCEajw3Cf+PGXZWmjEfPwqHJzZPUwfrbXyacdi6NreyYIYhPHbDGdzgLGnV5VOxKDXtvYTbkeGOzUtz6t1LvWf/HVbx2p9ROc4ARHApEGEMtxt9uOhfKpzN7aStpPjY9nN+9sdfrt3tbW4unTm56XTaUbjUZtd680WahVN4O4V2s019d2Z2dPj+Xy2bTfarUM88OHD/GFebEmm81266lUKterrxRyGXGBoRg17WIp/0m7BTB9LP23NsYkNooUERANxHDO9Q4cwImU1Um2rZjhdKPkX0SUR0WEikQjK0IiTCQ1QR9JAzlCTgQUM0YGDFsdOf0wCvoYxSJCgjrxycZmUKweAESsCLNYRDkwKX+mvgICE4AgEZEWFEQCpWRkWJXSWkQMAzMoZQ0Ds7AIBMcynH8D+GoFT/2qQVveSKe8+TMXtzYa1UojX/DTrlLCccs6Kg1CjKZW20hn/JlCLmM+svWfF8fPdG2mDw65BMAOpqKezYgDGAmFAJYHsYoOiD6uRN3ReWYj8mKPqKEeV17vcTE9jcr3/YKKlkdqfxRQRrQ/4vkaGcRxRMiIZo6ahzcaI4JoRoZ7Hk9+88jmR3wh4wsHpl9trt26Pjs/trcWzEwUe5Fz7a0/Gp+bHCsXzp4thd12das2/tvfMVp2d9ZFQ6F86tMPrvX76LhjS/PTz5+Ze/utn4C23Oukwbm5Zh/VbrrBWp568eb6uikXLlyNN3d19c17jbVHLz03n0/d3wuYiNEVVACgUDQaJaLwMUEFB3VzI6UAiUgRaATAQYIrKdaEngO+y1nXplztOaIIFYcHQc7DwVahOaTfQcRE+hJRTitEJEJETu5RcphDqUQSiwSK2RcREkEx5OQ9NspYa4dDujQc+pv3NXINgNrS/kUd1BQHEYlgUFWGAAhZIwMYAEhL/MT+M3cR0ZJYlshAP8LQSGwo57AVtAxGxAgxEAsyojvi+cUj5sU6ihKOa7CcpESTAJIIuY93bwCFDiJqJEWACISShMsRDh49BmJAYbTCIhLi4YZj4CwgQsSUDQmQCBQKAQJwQtLpaVf2jRnJSCYd2AXvoDMyXE2Z9Gci8pLDcmyJgAhIIQCzRNbGIsJQBAAWsQQsYjCpagUO66TzSWa0ACXkoBqPWlZv1Lp91GZGLQRPXsf0d7/z3XYr6HdFO1gcyyqF3b7Vkc5m41ptz/d930tPjBWN4WaldTe4Z5rvv/hqfmymkPa8GCIGZgwNWKtBwDKzgCVRijytUoRuELeOeAUnOMGvLqIo0kCIGMdxt9v1s2Ptdru2t6e1tkb6/QCEVldXE7YsAKx3AqfVI6eZVhjG4alTy6+89o0f/fAHF5aLCKper549e6ZS2Z7S6Vq9kUuVepqdtgqbW45OZQpj45OFh6ubmVLZ09OxsIWYRYhIE2sUJXLATzAIUYLBq69BERKJQlIoSTIuALvkKQRHgafB0+A74ihQKIpkP5c3yfaBQXpSIkj2kSy+iKJQEAGBCWmwOOJnd5PDwimlkRmZlLVwEORFRAj2iYLTwGfLCyavbEcEWzEOtwP7SzMpJUlZYSVW0FFiiUBhIED7ucMog4RoBXhclJCH0W1EAKKIFCCS+ARDIwzMg58Yk3IURAoJhAASUhDLCgAYSBAgybkCEEG1vxFHTHLFBr55z7GIqJJPhUFABJFFESYTQ+RgZyMAQPYwIgABEkmuiIBkePAPJkYGFRGQgkQhYnESslALDECWxQBYgcTLLvuGckQBYUECADr8+BmAfueda0o5JgZH+9Nzk1EUhXFERHFQz6WpNJbb2NhyqDw1OZ3JzHY6PcxkJrOptKM6JmSOhRjQRSJ2RASEScQRIbYqtkI4iqv8BCf4hXB8pq1R7TztdKOjQSnlu17HmCAI4tjNah30gyAIJicmYsQwwijianVvZnZCKRVFUb0f7dy4+bu/szw/O/HcxTOLS6cePFqNldvvchRzs1V/6bXFH/7gx+NTZyqVRlthcW6su74+ma9/49VXlFLbaw/efv/nf/e338iThEZCawRYK+1o0iAkxjmkUDpM0gUAXwkREAgpq5EIBUBIwNUOIWgCB1mRddASMpJoOkjzPfhBANADL/ChEpzIZhIaFpmHohcZceC2TX6SfOOsQmYUocRicqCxDZvghudSPyHTekz9BREZRe5sYhpu5KApBGJkQbAALMga2SIiYsSCDAIkyCgKBoo8HjEN6YstZ7h/pYpAIyFJWsVENCSAJfnpoUFEhcnmBhBYREjAhMT78QhyuCMB2k+jGoSmAylUiOg5ifBlRAKBJIYdkFWyndq3IyY+BWb29zc6B5eDhIjIyjyuAUvS56IDiQkE6cA9TywmZrYiViBiMEZpC0ZAEGO0ICggPNjosACRHNtjffT1Z5QGPCJrIIwonfYYoshG9VY96MdWlDGUSXtnz5792tde/elPf7qxud4PKkvLpaXlWXeScs56e69i3UKuNB6BH8TKhVQQtxURoqMIUUCssA1i7jveCJPLUxbMx7dwP932v3r9/JJ2TCNjVp7tII6jotfruWldq9UAIJ/P+76/W20ycxjG6KYz6eLOdqVer2cortUrUd866aIARWH4za+96jjOH/3JD7drrWxxvN2Ne0HYD4IwDHYqm8/xKUHnxo17z5VeWp6bev78QkaFLZMKKZUvTbhoiykKY9OPrYB2XXAd0QBiQTuHTJBDyh9mdJgYizUCoUFMlCpwUQBAoUUQhZaQCQWAHRefqAG7hAA4FAYlCaWDtY8prDBIV4J9n6XsNzKQzVmywwt6EraFCIrUsIJ7eIBONG/cl8EDiTYqzzIYEhXDc1IAFKIgIyCjWCSrABiIAFgUQiKpLDAk+t9ToJ4aGNJBQESQBGloiAc/BKBEEGC/4joBWwAAtCTEaJLjBiHcKLRPeZgotgSAIoSYMJQBgkrENgKhCCJwjEgIlMhgBLbWEkqKBsZn2N8rJHnbqA92P49rwA4jyrDfQUQEMBLLDIaJDMZkERTZhEkNmASACMCCRSFJvviM+KQ1M4kgkQ6CKOi3PS9dKBRNzMDmzu0HhUIuNr3YNtq9usX84pnn5s72Wu07vUdB2j9Vznq1bmz75OlMVyExEilMxoYMOiJimU/q+57gr49fNQ3Y87xMJiMiZ86cuXTptMkU415UlKi+uTk9Pj+/fPnW7fuOq9qNvTDsp7SzvrHhESjtBlH04OHDSrU+OTXnpLO5vBNFJmZZXV8TVL2gPz4x+fF7D7TruzYcy2gN1nPU1l7l1PxiGJnxAvQ19DUKgOuC66AGIMb9x1cOdFNEBJCstoiskIhAExIKACALSoCSKE2iQJAsAQKKqxV8zg6MiA5+NhgqWZGNDEnfgdBLfJ4An1NDAcChQx/qsJhX+4L7M9ZmJNoX3gcyOPnuk+/LAdf6vtt40A5bTlZ8jWCRFFoNBARakRChFUkkswiiwIGp/hfGSM140JvBdSGABUGRHqrh4PMDE7QWFAKFhCiASZeJAByMEjYsBmJEZBZCJZLUZRcRBAQBSlztzMyBIGpSolARJJZnFLS2T0IKFMFAACflHHPuwCINkKi2ohQgitb2cyZoREQXTbJR2b/pA94zAgYkAtZAFkExC4MFVBrVIEubUNCiIFhBkFGxLEfE09eA48DnlNI+IvrpjOt47U6n3+/PjOluv93sNB0ftSdLp8uLZ4pnL05cvoLbW93G7v167WFDVjtBiWi5MHbB8wrMYJkNM4MFxagMEGB4PGlIXzVN6ItNQyc4wV8P1tp2u729vT2bcur1eqfVV0opz5sYnyyXp7KZsTjmyckJycHExHi/VdeIX/vaa5evXn37zZ/2+/0XX30Vyd2r1nP5dGRMOpMXdE+dvhDGMjExXigVJsvF9Ts3d3d3z44vaDcVdpqZ09OtKCy51iNIaRJExwFNokEUSIwHGvChFREAfERSoBGIgJAJEJCJBhzOiIl/d9/giOgpgsd16OQNHT5Hg6Ch/VVZwdBTltgzEdEO1WZI7NjJezXk6x1uXxEOWZjhQOgSHgrRYUlgRyyghvdFgsBhHwEMMwIyCQs6yEyKFQCgh8owADKwCKASscyCowX8qOCd0ZCh7xzsLCwDixAN7teBCdpFJCFCVKAGLnZQAJxRkjhVORljQMssMtjoiBxwTHKypQG2iohANCqNShEqFESMBYkw8d8nw86MAMqhw2mDCIhCxIjoqAMLM+zfSgAQKyjCA5sEA8iAMYVFsSDbfYFNloAEQCsEABK0AiiMgJy4l58VDbg0ni8WSlGoet12qTSLKLuVvbFyXqc6cxMTz109nyvo6zf0C1fOTk6P5cuFzbVrwFkJ7qzfeai8ks4s+PkLPXvD5L6F5ApmlEqD0gwUsWLgkXUKnzKetmn3qOcdJZiftiB/1k3QT/8EXy0N2Pd9G1ql1MzMzNrGnSY4l85ebDUrnuchOLu7NRNzFPdOzU4Ui8X67tbVS2e//vprd1dWG307NjbV7AaXLyzWdrciS6lMaWJ8pjw26+hiEO4Vx/ILyzMYdpaXl71MYWNjq9p5dGF55vTp0yv3b09jrDV4WlkEIuugaLCE4A7mj3xmQiauwEQDVggEDEAI4HgDiSuU1DZIBCFrQ4gIMijPMFjNARjjYU2XiAYyOBk9PDj3vr9xEAc2+NJ+hjAQPlbU6HD8k87sB+UeXgXjgVk7+Un+1CMoJF2d7A9EBBgPZTAqhYhCYJEQwQqJoAJylKOYEZEN04DIGuGLCJNHuepGrA/7vurkAg98wB6aYRvDvgLMjlZEogicJNELQaEAoBbiRIQBMQhbsIAiEiCJDIT38K1POY5CUpo0oaMUERAKIrrKg8c3WMnxHoQwiKMeiNjEieA6j9kkDsICeqxEhC1YyyBgrSCiMBqjGcQKsoCAoBJUQsKIjiCQIAlYALRACCIwIpbuKwfd6baKhQkEpcgvl6aDsBvH0dRU+Xu//o0//dM//vFbP3j5lctO2gXH+dM///NGo/5b3565dPZKPm3Tbh1113Ojbndvc/MtyKOfHssW5zP5Bccts/JZrOUvixDmBCd4JhFFERoZGxs7c2bh3oNP2lHg+/7DWm3MM57rh9Ytlyc+/uTWxVPni2P58fHJ3/rNxT/5sx/E4OTGJta3K83qzlguncv4UdwvjuV7oVY6FUd9JJ3LZebmp4J2bWJ6KZsf89PFnb1bU/MLzOzmy0oMkSIQIQGwCkQhawRSA1MkPJ6JhOgeSF8FiEQoDAi+6wgCIvIg5nVgYkb75GhkoP2ld1/YJim/OBQMNSxBDxm2Hm9niKzjcUFLiady4Co+4D/Bg+jcxwOxRhFTKEw0+KTaBCYRP5KUR6T9TivlMAorUKBFGYDB7oRAJZJbhEYI+KPut+WAzhNQKdIKHVJIkuE+7gegiYigWLCCgg4TkaNIKdD7MXGE4lgEIEEUJGEwmi2DCAAl5SATAc4H4+m7LhEpJKVQ70tfElBDVfKGb43mHiISDWTwgdB1BkFwj5mgAUBrjy0AJiZ7RBCxgAo51laEB3dI9r3biEKS8H8CKkEg5MfrRX7FoVGdunlv9/Tp5cLktJueyZf84vq6N5b9+M2d9g6Q37h395O55bl7DzZ2dv1atfzv/uxBqz8+PT0r2VqtGmLHTs9AcTa+fe3/juny8vPfnJp5RbyFZpRDd7IfYdShcqnp0o4NAKHYCKkVp73CohN1hFKWnBiMxSZAoEAp8MyIB8COEOVflqY7CqP6c1z9fNoaM3xJJHqj9dNReclP7qeMOP6o1VpG5+8ebXxG+fxG3S/HHY9rH6S9RidzZSuavHpm7vZ77wS218Li9c2tTHE6PbXkrTWmF1+7dv2j/+w//Y3/8//xv6jtbV6+fHl7e6XdbLpa37z+4euvvw79xuzEVL9ThUBF7dBx2/PjC5tpNf/cr28+ur+3s/7K15evP/Db/Wghas1JHevd/Nz5NuUiALKhCVrk6ki5YTyISkIchNwCJHLMgrAIICgiQAWaHEQAihOrssYDrQYBQKVgyFAqvP+GwAUBkUEZpYNhU+pQjoqIUoklGZkfW6/3s1gTv18ysI/d6GEGyeFnB9XgOoblLwBC/OQ6xy4xAAiK7OfPACTdDoiUEIIQgzWONYaNMHesoDAyKx7OZW/ECAAsIIIWhAVFkAFIeQdT4uCqAcBoACGbBGgLCkJyvKNcEVEoGlgjeIgahQgRXEWgCbRil0ARKAQU9MgiMiISPT6BHQOPi8wEUdx54jgIS1LK97FdFEDKiR+7L/uvxniPbbwGFhGITIxJzQolBIhiAUDEorUkImITawciiBIAcB3LIiJoGQ2DiBrouBoZQZgMgBVWzFZQBEbVLOBRRURGLA+j0tJG8UaMXuaffLxWVJmdTvXalVQK7927ZmIcL86t3K50N2+CE3ztG5cm5rLVvT1AUZjud7o2m7t7e2tvp13Za/Z7RkTGp9zJUi6d68/Ma8GPOW4UCqc7Fdza1UsLLxbGJtYf/aRnNqbLU9ns+PRkugveXv1axUxrXUBdJqVZIhPZOAIxsZ/7sozWJzjBlw8UNjZClEcrD+bmZjSB7zqtdjhenF/f3splC0p6vo73Nldny2nTjxcWFk6fPh3HsdZ6ZmYmiqLp6emNjY3f+f7rU9OTN+9s5HKkHO722plsen5+ptGo9/v99FiqUq0bY1KZbL3ZCqq1uVMzsQlCdEG7AICoQBxrBr5JRBQZvMJgeR2s44kwEgFmTmR0cuR+/Oz+n0PBUMcyUE+wKu9/PvyGH8+eGpbBn+/PoZ79OSQ7j884jCVxm+7vThI7c6KVamIRYWBBETpsOaeUiAhQQo3JgCwgIrEd7sbhK4AVYARgRBK0IgygAAgUAqsk9EhERFhQrBBJYplXSKTYISBQgKwBDiz2j43bkMh8zIrgPHnY7T7V6FBEHiCiSjZmAyPzwb9EEAQEkwi05KrkoAPIyT8SGm4WABIigUEOuAADJVcP2k0bYRFgi2BFbLIXEcMoAixgQZiRE2f2cdE/PX3o2fFxY2B7u1bMxWLa9W7rzJlvLiws3LX1RnMnjr1e2203nOWlU9Pl3ObDt8U4aw/bnZL1vCz4tturWe5pN/17f+/bq+t3WapnF6b63U9PlXJT6LkcRGEhbv10Z+NO9X62VJqdWpwWP1PfbHSyv61d66Zcnc5r7WjfIddB9iJ5Mofbs6Lpfln4qvXn+HC0qMJRxx+bheApA4F77Zaw3dvdXl4611y9C2w0yEx5YnXlrkS1sBmkde/R/eunxs/fv/MgDMO9vb1yuew4TiaTUUp5njczM7O0POe6br1eVbreDxpB0PN9f2Fx5tOf3Ai6zVwmvbu7m87kpmZm49ae9lOepwLTD5g0FcQCWsXaDWOrEODxqGNEBAGgRGWRQwEsjAisDlfbwU/yJwMMiBoGFyqDCOQj35fPC1HEQ4v1vvQaNGsOXYw4cEQmqz+bzzRy0NQTT0p0WE5x+HgxBpEk2XrsizES0No87uPERCb5qIQhIQuxDFZYGC1AL3qs2wdvkguzIMLIaiCtGUExIyGhaCRMDBIWBFlrIAKHwNWgFTkkikQh6sFVHFbdSM6g9uPCkgipg/eOerIlyaqEYWo4FA4BwBkKl9t/k9ySz5ahTN5YeSyyjzmxQ0jkEDMwEzOwkEjC7yURaAvMAkYgFrGCxrIIxMKQRF2BsgIyCDM4uk1/BJ72uqp3H3aDiJWTqld2U/mYdO2HP/of5mafz2m33u5/cv1BLpeKTeTpqWxGNWv9ctbpB8b32ff8MGh3O2Zvt+V4Nk13Jsr5dlNBmMkqZ72y/fOffzg5Ppk///JzL59STvAXP/io03p45sL5l1//1tWL31sJLzPkI8xGBmLbB4yJRKM8O9b7EzxLOOqDNPLop+xK0Ai9dhuCfiqXy3juVqfd67QJobmzGzarUQ6b/X5G+e1qpZB76eH9tYmJiX6/n8lk+v1+pVLZ29vL5XLPP/98tbZrxVQqlVb3052dnemJbL8XOC6l0h7ETr1eb/aFctOVat102xiEygXDcRhHrCJtAS0oi9Yo5fzVpnsRYRbCxDhLwxqwyED4faac38FyTEML5S9yjz4vffffPEbAdPCG+ZAVC4YMp59RfP/KPiilhls+aJ+IAHBI7098q+SoQwKKYdOu2v+uZbCSlIhgEVFwmOY03CXNDABJnUMGTPRkBgGLCg8EKsO+p1YrUUiOEkeTp0Ar1MSEoEQN24cP+u8eKrIypNQK05MFMNHwAj00bqA/M6QHgvYzgza4L6KSr1tBEbH7seVBPDArJMWsBpxdQC0bs0iSCmwsM1Piq2Y8DAfnQTVqEgAaaYT+akGLBVe5fspd2344Dt7ps+eU6sRGb9VqpdLsWCnt+9TptFbuP/S9TDFbMLaezviu64YBN+sRYJZjv9NwOsXYdZDZ7wWUyeYhFbWMrqzuBls/ufLChXo9QreQKqDy/Cgyld26P2mstcISCw6oYhBRK4iOxon6ZeHL6s8ojeGrNj7Hh18tDZjEsgmCbnNherFe2/Md6pmw22lsra/kU07Bo9Zuzc8UbNB1lL6/tXVrZWdhYaHdbrfb7X6/n8vl3njjDUS8ceP6+Phit9vf3L3b6/UunH1tfW3Xdc3W+pqYuNfr5adwurRw/9E6hG3u1M9eGGcNsbU2Mq4IGaMdASR1wIj0eHQrESVBMpCMrUiiAcf2cDUfCq4S+hzX8aCpoWhe2Q8s+gXH6vF7um/g3GfVODDkDvYCLASJlzT587Egrye+/3yHDxXTfStustWQ/f4MDNAArhqcHQ5tv4iIFEeJrdoQs6Dat+Er77Fgt4ML9BMvNWLiLbYiDAiAJj7UWW0SiMTAzJ4SUuIo8hQ4jrgkOjE7Jw6CA8vwPoZ9mcPXPoqDfUQMGRyY0PfHf1+13Tc8J4FcBzcotpz8lwEMg2GwVgxLn0ySbyyc+DssAgFIly1IwlbNlsmCCIMgCVsAQVA8yG5Wo7ytfz08dQ0YVEspR6eyz7/wgpfJTk6em52Z+vTTrWr//fmFqX5/p9tv5Qteba+2U60U8xPFYn6slNMaO+2w32MiXatEvV6QwuLmxqPSTLq/2ak1g2qF65Gz8qBZyvAPV37U6XRy6dJ4OTM93popNzvNG0YmBCdQz2nOWsHIsIkxhNh1nxnz/QmeIXxZGvCRN0xswMTddjMK+u1Wezyb7nvu7m63Dzg5VSgX8p1GvlXvGsMM0gl7tVrt9OnT2Wz2448/RsTvfOc7Sqn3339/Mm/ZFqJQjAl8Xzs6ffvWw+npNFvrEPZ6vf7OTnbqzF6jk3PIxryzXU9Nl4hcY0UrSmyaju9o6X/GgTp4JSIBxIGpOdFmRMTwiGjnQ1/pQVMCABp4+GAZ7YV94sAeSsSDXgjI4Vovkjgik3AeSHYJCADO50xtX3zez+jWB38i4oHIP7CrA4CjDgkoDlRwRAQTswgiaRSbcEsBAJC3T42Z9GX/upKYXmQQm8SgyWAjE4oICgAl5CQsKARWlKNFEzgKtAIHWRMoEoIBQ/PBsCc5tgBiYCh8eWhIYvNkRUg7T9goABzqTckV7++HBAbaNojgkAAGEWRBBoxYYgsxQ2SQGdpwKKcT9pcBLwcOgsUAQSkFCQUXkjUJFSUrRN6n33429toAAKARvSDudWrdTHmcZbzbL1558bXSVO+9H7UvXV66efMnnerqmenT+Szdu7NhTWdzw/R6QRz3TYztVpDL5UB0Lpu9d2/3u2+8funywur2g4INPvrgk0YNl+fnahsNP53PTRZnZ2c9t4cYSNRzbXZtZ1U5rNwseGnt+MpxAR0QbeL+lz0mvxCe9s7oWdHYTnC8YBt32q1us9VpN4H9frfvajVZLkXdZrMlrkOF3NjWaj2VyaVy2UwhW6/X33777a9//eu5XM73faXUO++8s7Ozs/jymSiUVjOYnJ9Ip9PtVrjxaG18/Fy/30XX1VqvrG2Mn+rOzi0sTJYw6t5/8PG50mnyfWB0HAcxRmTPU8ocbjkOHIQAAJQYI3mw1uIgCJktwJMoJ2UQvZy0cPj0WBninBz6xy/yfA2LgSQP6PP/HX7PQ5sAhTxsjx1+feK5rB32eR8KY6TDqko8+DxpnwBgfw+QKKuAAEhAgAJIqDQAAyYRQ3qIEWz4jRUASIoekAXmhKcCgckCEIu1gAIJWzMpIEehQlAkmkQTEjKC3S9nMdimSBIWBiIgFtQTLzkaoQFb81lqz+RNuH84Pq4jqyR6HGSQPLTvPQZWgCiCSfkHI2KELYBhRw6HkVBUMtE8sgBoBYSQJSHeBBZ2EgJNIEZOYhMYLAAd1+o5ah4e1/qst7d4en5cUbCysqVdlSulevanTgo63Xhp8YzjNu49aE1P5RoOZNLEBsZLcyxhtbITRRz0rdY6nfVKpXy70f3gvU81ZbpdT8QtOuOzp9J7e3sT82fyBe/Ro5WHm435uQK37PVPW+1qvPD9M6AmhWaMFMSIoVCwDwA4vCM7wQl+xYBsG41aGPVtHGVzxd279zMULS0v7q6t1Op7bOzi3NleN8oXCkBoULLZbKVS2dra+s3f/M04jn/0ox/t7u6WSqVcdqzTVo16+7kXlwuFwtq9Rq3adnTqwYMHZ5aWTp8+3ZXt6enppbPnw05jt1Ld2aksR6AyDoIohwg0aiYX1ZDQGpaOjOpQHA8tRkaSaCs8/MEkdeZQ0x02NSer7YGOeDgOR9GDASDh1NpX7OAwuufw0CEtGcBVQ9rz5wKIPo+DKnswJIYH3zkM+zpQ+0DBPtf0QPoM4nqVUoIAQkCKARRSIoDVfvDpZ5TLJGmIQSwwCjAgE4iIBrESgyAwAhJRchJRCKRgP0MXUJhAEg/148M2YBIx/GRfuOUnWyKZD7XbA70fAEI5mCeHNxcRSQ6j5YdHm0iDoAUBRCFhK4wokqQJJUNHIIREgoSIBH0RpiRonJl5oEMnpn4eZKOhFU7y/p4VAgo9da41Xs48fFDzda5b+Tht1zZ24nTGjfr6T/94NVe0Swv53FjUCta+8x+U8/l8dXv67p179V6sFFy4eiGO+xPTpXYoFObvPnq0sbG1eGY+klA8xdrZM51L5cturp4d22zudNbu6AuXv774ym9vtVPx2GsiwswiEQhpMygnie4Ik92IfMqRvoojaqhHJ0456jdG5Y2Nirp8uvWJnxmMqKM5ykiMo+7LsRksju2+DNtdD4rSx61H29u7Z+ZOnT199vq99arOrjf6xX5XnKmv/9prf/5Hf7BR6c6cnoGoVW8Fa62CTzO91n3hrQvn0n/8v7x5/96j8Ynp7WqzWa1ZhbXOg/trxe+cu/TRn//MdTJVO+GWiq/+/v/2Zz/7+NQp74XZKIzuZCdPPVh3ll7/O7HpFWBX67wNIIVo+v3I0T74AImvERElsZgiiTLRoTwmBKDkCY3iSJCEkwQbFEkWVtHGGV6CD0yyWoUH40B0mAyTIU5aPrDxJuokK2cwegIocuCANUP5u4nkT54gHcUAIJhUvoVES0LELscwKLikBicFBQAOBwxiOKlzS4wIihARLCbJqUnAUDImAICcGdzQfVotTDgegQekX4/nQXn6QIM0MCRuLVkYZHzRYI4JAYCrNYOwgFiMREwSuiVc289HTiY2AREiEUZiiUGQmJGBHVQWCJAJ9Wc01+S1YYal6SH0IOobRUQ4GWkQgRgtfG6XICIZlaQUJVbiwRsBsFoftD/8pgmugBixliW2EjGzsAX2rIIBq6hF5GTXgoDhAaciAik4CBELD8jKk/YHGy+L+OQgMvX/Z+9PgyxLsvNA7Bx3v/vbl9iXzMiI3DNr76pe0QCa3YQIEARJjSgazcTRUDNmomQy0/zXf/2T2ZjJhiNSMpmGoxkNKXG4NBpAA+hu9FrVVVlVua8RGXvE27e7uvvRj/teZGRV3iYDzEItnZ+VRb24eeMufu/z4+ec73wnKyWUqdGdtT3L7mTsngExN7vcanQ5NxIZOq4g9FfOzCNTucICFzpKulubh92uOH3mEufQ7ww21h/HsZyemkoSmcTKD+Ld3UPGYDrvil781pffqM5U37l2zbRcy3STGN9595fnXi6Xa55rwqgTD4MOqdKp+a9tJs0Jwy19S4kBBwAFJ22k/AIv8PnDcRcw/fWIpmtZ1pkzq9NTsxu7TdOczi/NPr53/cqVCwZLuJ2z8/XF1XN5I6hUKpWC9/PN+6+99fUvf+3L/9f/278sV+YuXH252w8cYRmGmcjYNNzFhdMPHzxeXT2bc0qFQuns6rlcrpDP5aLmbr87KM6V/dFw1Do8vbRqYiiATINrmbq3qEjptAxEpzaYEDH9ldMT3u8RASq1Z0+a2wFMvBlQaRDyWIYwtaiMBE2cMMZg3CoHMYGnJBWPeZwK0rradKseX0Fm31PkMA6UIwCkzesBgNAEhDSYOzmYBgChGTEc6zIC00BKEgGaICb3IgD1ZDmCUgI8MUV4lL594hummMz7x+p9nwwdIDBGqQ0HwOM2QhFpIkmgCKXWUmOiSI+Jv3g0ymmIgYhihuLJnzNAYAiMmERIry1dzRw59Eodt8cwyWQDcSCdXg9L+0ikNPaPW/H0QwzGuAx6Ug+dXlosj0IkeNxjTnRChIq0kqQ0jdefAJDmzif2O32lCP4yHtLnAmLQl4cHHdM0EWVtqrJ/sM2M4tz8VLWWu3bt/e3tXcHNsFy4eHax0dxvtdRgMCLNPa/QanaajZ4m6Y/IsvnaUuE3z7311W+8df/R+mAwgGHs5ejShcvX+75hFAvesuliAze7o92NvZ/M5QqcLwIAjPl7igiJFBDDFzocL/BrgI9Y3yPPb/3Bg4X5RWZaH9647li246ABsliuGJwbpihMLQ6UyfP1c6vV+bkZ4933zlw6c/GlL793vbF9yHjOmD29VAp1FGqghKF54cKV2ZmlR5u7M1OLea+0s7N39uz5XrMtCF03T8RJwaDbmi8V6pV83G0KkMIUETCDkHFDEyiS41Z7gOPWdjpdLosnHvAxJ48xRghapVOwPprxU8nAI8IWImgiRIxBHHn/iJR2y2EMGemPxaWPeM6KAZBGlWpdACMildHMQEHqMQMo0KluFoGepH5T5rBSoFU6CwFDc6xfzVABaa2V1lpriyOkni1oxgzGx8RmiOPjD/ToOsf88I8FePlE2OQ4AIAhEdDRegXGDi5KQg0sUTrROpYoNcVaU9qCeHzaiVnVRKR9IIEgNBqEJiORdkAaJ4/pOAcqHRZFTzza49DjzSllGlKbD8AUPbtcKtTG8XE4Go1J7hwmP8fbEy0JmNZaEci0YwQhETDxbBIAZdGvP2M4aeRVbG3uAJGmZGmh9vrrl+4/1P3hTjmi3cYht3rzi6VKaf72rUe/+Pn7zWZDqQRNEfix5xYty7MthwvW6TSikB5vbk/PzY9G0eFBK/KjIB7GcWJbfPF0eX6hVqmsFsxctZy/s/Fep78JB3fs+jRjjDEOwNK1JABHRJ0ZcjzZDZ90ID5ZStXJz3DS63+BzyayUgB4jO9DRGyCTvtw9ewaA7j94Y1XXnktSaLRaKSZQFKOVyzWZzkUArD2Gp0zCxVDh9/4za98eH1r4/Hg7KVvdIe7w0Stnb0QDkH3rxWLZa88vbvTcJ1iFCnbVHt7e19+8zd//uG2zfH00inL5o1mb2N979ypUzlLtFUMpARHhYwzjgxizqRM+7XjWHr3KPQKYxcn9XWOPJ600jW1vgBskm5EpXHiA9HEVCMASM21RilJawIgzkEIZAxRp7qJjLGneNGcjVvlKM1Io9aYsruyuhhFSsDE61UTP1SPRYlBKdKKKaWUStOKxBincQw1ddxTjQhkMk6vgjFgXHPO04WCOclxHremkPqeAE+ywgAT53hMQko50UfaIEKnZC4cl8BqSEUvQ0JFOlY6kRBrLRVKjRpIHSXUAQAxXcOk98ARDE5SacVxzIImip7S8sWj6WiyBPxo9l2BTinWqR88doVJJ/qI3f2E8g0A0dPt/47GIUnU0TgcnwMFaA06TQMTMEBOSDR+muMrmxwq/TXLAGd+vzL2fz54XscXX/7K63E0un33fW5EXh5+7/e/devG+0kSEuuvnqk3DyPL0CoZJtHw1NIcIl15/Us//9nb64+2w0DFjnJdO461aYrt3aH86Y2HDxsalExwdmp27fyZzc2NIGyjUWKGbA2iWA5OLS159d+yi99uioAzwRjTmmRCSsVpUoxbGRpoL/ACvwZwDOE4jtYgTCuJguGgk8Sq0WyfXa71+/3eIFh5+XUO0Y0bP/ry5fmXLp79i7ff/9mPf/43fv8fbh8eNDp9gvj04hlS4HrW6ZVT73xw970bD9bOX2HcUImcna3raBj2m65V8jxPMc1dD0Q773pJEmkppZSolCQhMc0HGYxiIEDGxtYXCBQgI6meGJvjTk+qVjlJHI7Th0SknsQ/AVIbrFIeMleKlGIpl4MDU4Ccp2YXj6zU0fgITJ05JjVKhVKTJk6U2c1vlIZAU+tLQAgKCCZlNlrD2Iprnjp5PM3RkiJSABoZMCBEZAkA6DQCzzlyTowBY6TYk7aJRwYYEcVTNKAnZUWkJrl/AsSUrUuIkDZpSBcBWrFJDyIWEkgNiaJEQqwhUaQp9Veesvd6fBeYkNbI0uQtaFSMBBAi+skTzgEeU53kqOBpc5J+nvRAQhpngsf+a6I+urBIf/rH7ODROgMmGv4fN1ceBwCugIA4ABICA0YCpDp+kPHH8Rh9HnBiD/j3//Zv7e5shnK70z5499qPL135B6+//vrOzs6N67+UTiCT5Oql08uLS73eoN8f9vv9cjlvWkLppFav25ZDRNjHOI4r5VnHrt27uyelNEwzDjnTVqU4ZRvNeoW57rC339CRnluaM0rqoH8ryS+QIIMZiAwZMWKQMo+eE+378+IB/woP6bmc9aTj9gJ/NTj+XCbhUE1EnJHr5nYODrkwBMNwMJQIZ85d3DvYc7luNQ4Wgj5TYTwcVAoe6Mr++uarV9fmZuxBAP0BLxfyQkd515qv1FfXTv2r734/juNWq1WpVVvtzoWLq44hV5empDSHgT/wZXFpNjbdR7v7c04pTlQidRwmkTKAgUaKTNSSIyPQgAjICNOO7hqMoykZ8ckHAAGakBGlnWhTRxMBUOpJE4On2bB6HAfGcaUqMSKmNbI0EJxajWNBMdSgAJQGpTFWLFGoCDShzvi6hDJNIBIRqbSeB0ARJRKO2LakJ7RbAAOAQGPKemJkIAACQ2SGgCPuFQdiSAw1HtW/HpXYjj8IelLmBBMXc/ylpmM2ZeKYEoxjzml8mCZDlyAkiqTGWFKiQVHaNxDEWAXlKIgCRAjIOTIxWS7hJATBPva+HX3Aj81LaXpYT2xruoo6GitJT5OeJodNDedHNgKA1k+d7ujDWCErfasmemgEcCzT/LRaGc+aD5/P/PlJ25csiBu3f2qb/FvfeSsORkrGzWZzc333+oc32o2QqGvZwrXv5fP5mzdvb2+1a7V8Lm9VawXPs13X9P1gOBwmScI5So3Fcn04UPt7h1qa924ePH54ODNb//Lri9W8u7KyeH7xTGOn1RoMHq1/7+EBlc/9H23bdhzPNGzOmWkKQ1hCiN5o9KkMxBcVL8bn00XWF5ueVn2iCS8m59rCNKNE16dnDZOHwSBfnfra17/x3X/5f2cm2oKNWvsoR3kbo1F/49H6QqlWW5hOgo0L58qC1fK250BSz1tnVpdMi3uec+HCnLBysYwsS0g9MtEpeXy/OUxAt0IV+lI7eatgtzsDGyHWEISx1JZCSEBKtPIJAiCyceB0nC1CjU8arac/x4QghJRbk9q8lD1LYw2jiemZpDkJEWMtAYAwLTZBzRAYEAN5JKU1iXWnxlsrrgiVxlhjrFisUWlUBFmpq0SPWceaSJFWE8GQcZkNscnKmFFqw1mSCmYJJjjTghFngEgWS+tW0zvQiIRMI6JWk9ArPfWs05b2R77mpB4LYMJG1kcthYkAINQ0MZc4MUJp0FVLIpmqVRBoYIAcEDU9dcbUqwUA1zQQUSAKpjmQQI2EAGAI8ZQhPLKUk1TI0ZWML4+PSWEp33x8YZT2GjoeUR//qmFc9/zk55iWzI66LxxxBcYxEgRINa3G9bsEmhEb08FgvKqYrDCOZdOP4/M+vYkLl5YO9nc0jQ4ajyvF+rvvXgsGcqq++PjOJhfaQGP9wdaX3nztlZdeLuQeFQvV/YNtzrFcydeq9e2t/dFoEMcxkWI8uXXrVj5XK+Trg64vWEkQBj3+4NZmoDen5wary2vDTnPrw61esnx65ssqn7csyzRtAJCJjuMgxJAzAzJEwF/gBb5ImOTeECfCvOmM7Njmo0ePNPFz5y7cfe/Hu9vbl2fm41giE71e2zIwb3OuDDMRnXZrOOrrIPnB9//Nd/7uXz9o3I/8oLOzn7R2h1X727/5d3YOGrNzU1ZuxsmX3//w/XNnT8WxXyvXmt1eGPQKtakkGt3Z2OKK3rxwdv3hY8NhCkUUq0RrYhSqmAzHjuEo9IoIabwKgGljrHhFky5JE49WE8JYJnA8pTMAUBMr+JQTfCTEwRAQkI0/EJImdlSCAmPzAEQgNSqCRLFYQ6wwUiwhJI0qy4NBBMA0/qwIVXoowHG7H3xScgoIRGBSSAyZYAbnnDHBNIJCIMEodb9Tywqk0wWFBufoaR63YXQk40TAEBmOtSgZTZriakzb3afPPZxoWaclUwCQ2j/OQWkmlZZaK+CU1tYCI62PBnJs3hljjFkCEIEzEMAYak6IhIDaYsebIqQXQABA/Eid+gkAABifRAVofLtjc/uEpH2MWgUiHUmcNL2aeKZ6TAg4VpH15IEyIk3pYgK0Tg2yGHMIjr4g6QeZ8XzFX0Hs8pOE+MU7d6WM8zlRri2aHGdmq6qqTi+fPjjcrdemDw4OOOf3Ht1zXXP1wsJg0Hv77bcPD7pRCIL1STND5HKeJWXsMEVJ/7WXLz18+DgK+qGPVq7S7/f3Tbd9dzQyb37zG4VSeX5lrXyalXNTetffHwZm0V0bBZbNzUT2w9EBks+sJPGtuboXD96xRVgsf+lBo+bbdUP0Mm7hZOy4LI8k6zHyjAVBVv1xNoXsZHVjJ+1fm42s8Xk+9dOZZ82oY1ZZjZ1PiKzrzA4lPZ9xOGmoimeEzkJiOdPRgUxAS64sh3sErcePk4EybTE1Vb/34YfxcHhmeR6j4Y++/29yenB48KBWLi/UrA8+uFMyqU+FaxvR/Lnaa4vffPxgqBU6UrT6O/bimeUL57//w58hL3W6yai5Pj3Tmalyv7lrDPLhS2tT+dKB2b195wZLnDVWhAK7s/kzl58LN3/ylVOvfNi316Wj0Q3iHmdmK4lSO2QysJBMnuorEaALqBkRoEaSCBqAGOi+aYxndn001ysAiHWCyAEZAGpCrZhSmogcPmYkMcY48LQQCREVH4vp67GRSXlgIKNYEUqtYg2R5jGxmJgGIGWlwsMT9f40K6zN5MjYozjWNj5Wzy531DoNnlOSFtYyI32TQ5QAwJGlNTEIxAEBtclDOOI8wxO5C0sIeJrfnr5RvWTs4Y2lJCaxd3WUY0ZKC2FTgxVLVICAjAuWcsk0IBClgYmn5i3SoLSv/TQEzZGJ1OATwlG5FMDY5U2jGURDbX909ZCazokww9HSMMXgmBDHcR6WLeSxkrRjF/UkOf8kMQwAUVpDlUbRx0wyAIBIHf/7cXQFYBIG+RjU0fbx2Y+8/Ix5hp49n2fPe88+b6ZOwwn7hYuf//gv8nnn1Vcv28KJAt9zLF8FH7x/bel0wXNFmKBhiOmp6UHfv3t7q9PpMcfo94fNRjDsJ65TFEIYhlEo5IatVq6YY1ytrE7v7+9KRQN/p1AolGpzPnWvvd18eOPHNbtUK5ROnZ9H7/DmtYdhaFenL9ZmVoko5+kouP2Ld/50qmKVC+d6/mmDNdB7rN3HNe+1nv+GL6wT3dgLvMBnGYiolQTUbFwdiwAgo/j2rWurl16JQnd6qrw/2tt8tL505uxBp1+AwYULF5rN5vvvv28YxtraCiL2+/0cSd8PdncO6/XpW7dunTlz+vz5C3/43T/5ja9cGAW+VMny4kIUD5vN5qXVi9VC7fbNR5FPO4eHCUXDYSdCf6Z+4aCl721fW8v5/TC0PYd6sR9K4sqxhYoT1EwBSdCMAWrUoPl4QkQA4kgIjI8DzExJPF5zcjRNHyVBiY7MEmoNOo1vptRm0IwA9bih4TOHTRHq1OKmNKNUw4QA0kKktMYGU20kfZRr/DhUxoTLNSJiSsdlLNVdIkQMdYIEiMSRcCyCnaZ7nyR3j8d4Q/WkV26aoE5/lerI/0sjH0dKlgrx6awnESLK4xFZmsQVsheCUjENyCEtBkNkwEgDYPRUve9R5pgi0Mc3Hv3Ep/UYjjIQLKNrU5aheoFfDXFxbZlIXb/2ThzCKy+vTNWmGwf7JGl+LV8u591Crd3qCTNCxH4vRl0oFs0rl1/b3Wlde/fWwf664+RN0wSAMIxLVTuWvdNnZnZ28yqxh4NoYWHp1PL/7MH2RvvhnW4rilH32l3IO3Munpk1m82my+7XTXXt+ttTNW46narz9vCB5S3e3+54Nisc6L5TCBfPJ7MF86H60nO54efl4WUd57MXEMm6oozr/5zQ909+/JNuP+nxTwbOQCklkBmchXHIwUTSI3+YxIPW4aZho8l1MGxN1YqXLpyxdw43rr/NF6r1ev3BbqfZbL51da1Wqymldndas7PT8wv4+PHGqdOzv/Xb3/jFz9/d2jz0XzrVH5JKkCM7PDzsdHq2l0tAvP/+e+fPvmTaxVze7QcPHz6+p0tz+0l+ulpEnrx/b0vMVwBcYiYwDP0AtKEQBIEm0JoSBgYCgDYkISMGhAw5EgOGDBkAEitvZgABAABJREFUJXDcMXqSo+RpHRNMEsNp0BQk8XGoWSMblzgRIoisCARwnVbjpjJbmjDN5uLYHuiJLCE9Ieo+8zgZUouoj/40XQqMn5fWHBAZaSA+Mbx4VH5zPMSaeuofy1mmR9LHWMRPIzyq5sJJTdc4lp1eS6quRUCARCQzAmRJwhGRa5QMGCAf14zBYBxQ+EgbZoyfGOMnPwGQ0xMhlHS9NP7/03Tzo0VDVrwuyyxnCqdk4KTfu5PPA58ORM42lCZBML9U+va3vuX7wYO7Dzgz9vf3iyVv7ezS5uZWu9GPYh2GQ46F0WhULpenp5aSiN28cU8pTJKk14sdD5ZPV0+vVstVvrBcGPZYpVKZnpq2zPpXvnq5NHf+Jz/9QS8YrF18ffnKK71Eu+qWDHrl6fjMktzfadZrttbDN19Z2zMcq2oMJXUbye5mJ1HD3f696SWXn34+BvgFXuCzAIYESiEa4xob1KTUsD8oFsz+oHnaXu23D+IkeOXyBSDdabVc1202m9VqtV6vD4fDOI455/l8/vH6PUScX6jV6qXvfOc7f/LHf95ujbRCRF7Mu3ESHOzsqCicqk8PRvH+3sNRa/fN2m/eawTtANCqgNEslN1y5epCnXV371+/f3vZCc264GQkBImfcDQ5oEbiSBKQMwiRGDDOEo6Yphs5MsY1T8sIxy7nR6c5JD3ZSAApsTY1j+woi6zVUbEJATxV/nv0mZAREGhARpzQQABUSEioAEAjpHlFjQAKCTMtMGWEECcu6eQqJhZEcD5J6jJAYgiIyJGCY+zf40ielkI82kGMm1LgR36KySDAk9MDACg9DjsTaUKmiWAs0fVshKkBZsAY45gSujiCDkkcXcZxDzh58qSequs16amypSN85M+P/ZoRks0c/4wb+Jw40pkG/qRlSL1WYzDslcvemTNner1eo9EGYUjNeofJteGj5VMzcRIG4YgQnJwC7bfb/h/+4R/WqvOCedVqtdMZaK1t2yzm2KWriy+/enp9457jGpvrDccyNjd36zPv11Z+e+nM+b1O0m63jelXoPp1HdmymzTaB9w+LNRlpW6urq5ce++GVuWpszWv8GU0lh6s/5LcW7nclJG7CLkzz2HMxuPzwgP+Vds/Lx5wZi7/OXnAJz/+s/ErcsYImoFG0ByJASRJNBr2W93O0sqFKAm3d3dsLoRhPd7c6faGK9PT/f31Xq/nVBeWlpYsy3r06NFwOGSM3b9/nwv5v/vf/2//yT/5J/v7jdFQ1ut1wzAEs6Nhq93tnDm/Mj2/sLs/XN9qmLo9TIaREhoqtmNP1fuLC0VeclBCP3Z8Khu85JlO15eAhifMOFXR0ECIDPQ4zgsgGCCSYMA1Mq4FMI6AjMwMtipoPO4mTWjVOOk3/NFIZppxPJr0j8BxwrsmZKAZoME0ESqQAKBgTMjSaQ9dAJVF6sx8LnhslycXow2DI41FGZFpxjiSApBjJSk4nisFAJikzI58zfHR9bit3tGtPVlbfOySiEilhhOJAFMeWfpr1nsbacZSOelxu4xxDXUCGeVDxxWmjh+STbRIYLxkSpdE+lhg4anxERkRhf+Acf4PwRfWAxZClKtV2zHb3e6D9cetzqDVHXlevl459+H197Y3O4tL1ULRy+XJ98MoDF86+9LG+m4QBKB1HMdCCACQUiaqH8Wjg4ODne191yl5bgJabG5ukaPsx7n6/F/77d/6251us9HrdEc9r1q2q6fc8oPN3ff3G++vrNQunrtqmdNRbHR8QQ5HGDR7O4qcxeVvmeWrvilG8b/3Xl7gBT4/UJJzDpJIaUMwwSCIwtFoUK7NfP23/9rdB4+Bu+Vqdfeg3+yF03NnXLN3a3tbCDGTq0dRNBgMlFJ3797Nk1+rVd58863v/rs/TmIKglAp6vZaQpitRuvu7ZtMiItXzylFsaJcefrxnfcOWofLZy8P9cz6nXeFBg9Gkb8NotrzpVuaB5m4LDEwQcYdAODH+gkdm0w1EQOUOpUwSknIhBoVfNTDG0OySStbjQhAlFKTzCflTE/NjOpY96QjK4xjpWmUWhOBYkwJTcQUkcRUPQqVZkqT1Cw1imFGeVJWtx913Bw+uSSUiiQAQ80BJdMcx/LSR5qOdKzlLQAcSTrh07dm4FP9ko9unPBZfXYRgcYqjDQu9aH012zt67TBH/LJhaSqWeODHKUGnuVpPnU98NHrmdCSP2p60w+ann09WaF+yjSEX1DR5wwIJ5ePknB9c68/hMXlliLR6vtucdofIupc5Eda5h2rGsVDxHacBDs7O0kiSeOgN1KSeV4+CIIoCkTJCX268eHDONaFnF2p1LqdoWXrne292kzAKXGNvl3tTZVD5rb6UfTene/5/na/v2uxjqGnR73u0kJNavOwoeuz+6H88MzcQWvHPNy8XmCOLFQApz/tsXoKn7QHfFK27fPCJ+2hvkAK0lJwoUFppYUlECEOoySMaqVauxfGZJy7+MpcOddtNgPdXli9pBrvSCnL5XKhUOh0OgBgGAZjTMaj3/ubf+dnP33n5s3bL730km3lGPMbjT2toNvttpuNq1evMoLHm5v1+Utuybp5rTSIknPzru6hVnHBMnIsqefNthol5C8tn5bhoUFuueBJtEXkM2EDQNoGKJ300xrftJ1ummIE0GOXjNTEUo5/HgsdcyAGoAERMRV8ZohkT4KpRyY2/ZNR8pQBnnSqAIOIEMxxtSiqSToz1loTaq2VJqlRK1KpfDE++z2M9bPZqmoiRv+R78FYM1kDIaAGDZoBprxlgLG0I0v75k2eLzxtZdMPLodJdJ3g2GIlVJxo0q8Cn9i8ifUdBx4m1pdBRvceItAIfNK1MK0iQvqoyXzy9XySpX+KxUzIjllrOPrJJo/pY1/wk0WSPmllq0/aA35uIWjDtNY3HzueU5/ND4IokYnp5vcazfaj+/lCDtE62BswNHJ5Y3p6dnZW297q3m7r8KAXW+iWinGsm82mZRlLi2eXl87v7N0tF83Dg16r1W+1D3MFozc83Wmqbm17cU46Ymt/9+GgWQqCqb3DHzocVdQsVjxXiEd3r9dmp8Io6jZ3avXpaS9/9Str9+48/OG7/x3rRq75t5XzHEbtBV7gMwIiYowpkqDIYDwNQSudnF698LO3r5Wn5ubPLGkdubmyv9n2QzVdKl24cCFJEtM0X3755ZWFar/fv3z58mvnvv7gwf0PP7xhme5wEKysrI78drmSi+NYMKNWrb7xxhvawEd7zZfeXDxsSc4WhOFyK+bGaG11rpZEMAqVGHajtlT+qdX59sNdSwzypoEmCh/aMuXsgNJpNW3aZBBUQjwtQAU1LpFNXUb2xJA+9UGy1HkCBMRUxxEY4xyPDNXRvoSIqV1+IsYx1sSCSaufJ7rKYx6ySohQM64kSEAFoJE0YZzhUcl/3zz5sfgwjvu+w7iAhkADMDzWNAKPSTzqcDi+V0g3jmdmy/r4iQkAQjW2ah+xbYiYRnEJOQEhYFbbiTFY6qUiMEBCTQoQQdMTaaunjSLCRIoybVo8YYHJY2eZtOpLI9rPNuQq46KyFMo+W4HgTw/i7vbdwwYsMOHkS6YZ+ipo+RHnua/85m++f+12FIhy5Uwce7duPxoGB2fPLXL1w7mVc8h5s9nlqJQalcrdr3/9pdlpdzB4WKu4zWZjNNople3lUwu+70/NV7R+xGH9zofy4cOH5UrRcaz9/X2HtAwolzcb/egnv3zkuFby9sN8wSnMgbNv3tq7vjK/cv7cl2cesVvvvff6l+d873efeQNZ5bJZ0mWZorEZOKlHeLJq0+z9n1c/4Gx8wsc/4QrxpOOThawVt86q58sO5WUc59nIqgvPun4DWZBETjE/Go0gjosF75133lm5dN6YmTPvH/Bug/rYiqnVkf6ow8MHtpu73TG++rv/6caDbWj1vvFGtVw3ef6NP/+zn7/99gcrZ69oLR8cNhLXuXz5tZ2dnSQOUcirb15dbxwUanMzy2dzxdzdh+9/6xsVV4W1UO6v/+TiymoQzbu5MmNG64ONL82XTuO26ejDR5tX31zZbnYTZFNGBMA0cUlCaR4pSiTTGhLjiCfFUwuZthhSWgEAS1UbQfPUAwOdCIlIHJAhcY4CWdpml3ORBjUZAJJO9wHQJed4uQsdPVaDJmU/x3K1iCg104AJkOYoAWIghaA06cRiDATTBgPBNEPNQDIk7qgniwnNEjVuyANRkNpRlv6YvAYmseMmObW5AGBBHxE55+nOR/WyfdcGACQtQHGmDdQpMQrks3NpxGTq+wI87a2KZ7+3sTQUjddDCiYXn+a8xx4rjtW10yeRNtlFAAB27EZc9lQS+ghKJxoBgVO6FqJUnBv5RybcyVNQGfWvGalhAMqol83oenRSjzZrQcCzzpt19JN66hmBv6zjCCCoVlmpWMvn851OtLfXsL3S61/60vbOI9NScSS7/T1gBcNUU4XS4tL06XOrezv9ON5xLGGY2jX49PTc5asrpikR0XXdXAk1GyqVWC4lWtmOGcfx+vp6p9Op1+tT9bnd3V1TFAqVvaCPMrIEc4AEUVKZwbNnq3u+HMRuDCuH/dPBXbcZLbpzru+UTjYKL/ACn20YhhFGSZIkjANnPI5jg2PedeJIJopmFmcbrQMSzvZua3l+YWqmvHPnlmOZs1M1CuTmteuHh8VLV1Y3d+8+unNL6ASTWCUh1/HuxiOuIs/zOC+dP3/OK1Z/8Bc/L9dn4zDwHEPJ2DNMzvn29ub9+3dz+XwQxKNh9JWvfP3t928wBn4Yl0oljaaKI9ezBxEBKQJGwAmYIiQNKm1cBAAwrlU9+kBExBiAJuAMdKpgyQEAGOd4ZIBZWrSEgIiJBADNABkHhkwgo7R+hqtnRk01PItdTKDJUERSg1ZpQyGSGkkDR8UBOAADGrPe0kbExxi/OOn6gISOOW6u8JHot82fmriP5lNB4sgAp1tSKhZoQNIIGhE5UnoKjlk6EGAf61AEx21wRgidaVJAlFK+gTRCSj9PGB07xpO/ZagBPurWI6LN9TMNcAjAIX2UpIlpkEDs2anj9FCZ//DC1/1VEF/58jc3H+xuPtiNw6RS9crlfBDrzc2NTm83V7CUkr3eIUHo5pBzjOP4+nu77Vav1exqCvMFY+X0TK5I+407iwtzUiluCNslDaNExW4uXyhVT59Zunnj9uHhoZKUxPrenccPHjxaWVmxvTz3jF5Mo9HAsdx80QNSBwe9ww7cO2zI0J6bqU3N0vTiG2dmVpVwhs9HQOkFXuATwUk5AVwYFMZJkgiGHDEKhgzJc517G+u1qfrM/MI7b99JcLS2dvbsyvL6g3duvv+LqZULp+dqOcDNt0fDXtMxzjMNq0szg7J36vRCkkT37gWDQS9nwdJc9bXXrtan5v70z380GPTv3rk5Nbt084Nro15zqmyqJI7jUCbRxvrDTndoCHd5+VS5lOecHzab9XJRcDg82OH5KdctD/1YA2hApVlCEGutCCXBMUGGicYvIAAorZGNU6KpxU2b91BKBUqD2EAK0pIjUkojEkfkiCZnapzdTCPSR3YozZUCEamnyUpHEhWRREVMESREKm0VrIkILdTIiCMwRhyJocKnLVMa/OacASABQw5HTOaxK8wYIjpGMrnfp0wNKn7UShKeWitoQI1AaU8JLphATFceGe/DRxsCptAyw7MEpQGJSBNIDcQo/dVHMRmZcS45vSSeFksfy9CnHzz+pGnEcQMMgKk8pEYiTRpQk4SnVwlP49Pq15tRrfCcKCjPixOT6QH/8u3rKI0w0CoPuVz+tHt6v9m9d//W6tri8tLZw/3B7VuPOOeW6Yb+4N6dnY2NzULOdVyxsFB+9dW1i5eX4qS9f/C40WyHYag0cC6kYgSGbZcKhUK3214+tWgYxuONnfVH255XqJTrG+s7CwsXFSkZtRgLNWPdLt/b1YmKWRgMh8N8sdBk6zuH/aklveasmE4RMoSwsm4se0H2yYagM49zwu2/bvikx+d5HT9r/5OSzrTWwAQiEmkkHQwHTEtKQqXU9PRst9vWJIMo+fJXvoIy+uM/vCcMYnr0gz/8V91GH6Wfz1kbD+51Dw/rRcfhCmN/plKe/fJr3W6bMeYJrFarU9M1Tcm51VPXb9271WzevP7ByupZ0hgG8UsvX9AU3759V0nNGH9w7zYl+sylC2EYbj1eRyXPXJofcXE4GDLhSQ1KU6wg0ZQASAJJ2pwUch7lLNOfCRJoEEiIyIEREGOckU6kRESNwAARSY15W5oBMsY0B9CQAAIHLTUiio/xb9MPGo5rF4/rfwAwUkCaCGHc1hDHls5mCSKlbjcAQSrbgZommlzpT4Ys1VgWXB9JNCMiG/8tw3E7IDjeGQLGLXOJJr00aFKMhEAMkCMgU5whZ8QZcMZ4RmpJTAYTnv6Q7XOmkXlQWiuextI1EUo4Wpo8hYmDPuZ/TY5PNh+nEvAJ8wuIQAKD1P8lUgyUJgBQlMlqztJkPqngRtY3LJv09OzUT3ZHgU9rofBsiK3NlsO9oB9G4e5g1JxbmJqaqg38RElmGjmgwB9JcNDgBSBz0O3lnJznWYADx+EoBo8e3UhiP5/39trB9tbe1tagXK72e0JKdufOYRztVuqFS5cunzq9tHL6bLl8PYmpWKjcvn1boFBJDJTkCy4yp9uNA9+yjCIiM2wjV1koTC3EfNqpzZDpoO0ARZ/2WL3AC2TipB5wlKiUxkwyJKX8YZeSMOi3r1w6O9hrPN64ZzCYqhQHvaaK/Lxj+qYedg46LT/qR/VcaAl1/dovw5F3uLs9Nzc3HPa2ei3bMQ8P94MguHjxApF6cO/uwd6OHyZXLp7db3QY40z6O5uNqdmpeq1sO2c3Nx9PTxcR7UG/63keA+24OdM0i65XK+QaBwM7NzsIuNSgSCeK0v4HikAD6qOJ7Fg4GgCIgIFWjDHUQsNR1nDcFulJzp0RKdLAxVNxV6VSnSsgpuBZBhi58XHrAqmzhhwBDI6ppUdEIOZCqtWMxJ4chAg0Y2kCNX1KdPQQj9nXo4MTEahjnuWxD4JFWuujbHFqgLXWnBlp00KBwBkJRJ4mobMUuI71V35qVDPeH8bGKw/GmB43ckJE4CnZ6qgwavIfe8K4fsoG08eSCOluBmdEqeMLjIgx1IQcxob548jyOKPPeeTyE/eA87lKPJS2lc/njWLBqFQqhUoliOHwsHVwcLC5ud1sNvM57blF13Udy9B69/TKPBFHPhwODxsjn7SwWGWmvnC4Fx3udcKRKbiTJLK5P2o0GmuXygBYLJZ/6ze/NTs3fe/uw9EouHx1LZ8zlMK7d/mjjUOtRL5Q4qZqNhqG50pewPKV6spXawuX3MpCQNQJ+3aWC/wJ44UH/FeD5zU+J/VEPy0oAiEMjqA14yTD4YCSKAmG5Zzdi0YcIn/Qmp+ffe/nfzFdq3g29lUAWtUKJTRzQf8gCfvbWxt5Z6VaKRmCFfL54bC/8ehhqVw8d/aq53k//NEPzqysIuluu3H//r1Ssep4uXa7bTKq1gqNgz1mMAZaa7m3ux4Eyfm1s1tbW4ZbDILA40kc9GUshWH6fak1SE2xJkUgcZxLPFZXCpMPCGl/X+RMEyLTSAxJEnAgkxvISDDOGWDaiJ4UERlMMQaCMcZBIKUJWtA0qRL6qHQi4zKtYUntylHFjm3wtIcBYwxRM5bmccmQY/dOA2pI47SgADQKrdNLmPjSpAFRaiRimsZSlzD2loFNTDU8/Y5xDI/zlvUEhiAAYAgciTFkqDgyRMYz65L5U138JgZe6mf7cgmhprGNlOkHAkilSNIRmwTu01HSTzPIjn4G8ohnjjiW4kIi0mnTwFSoGxkAQyANLIv1ihmh9eeFbA/4ZCHoT7r86aQQtpWnMCKtB/2BBmKG3D1sJMRnZitajwj9+lQOCBvNvUKh5Do5Ny8XFz1hYRCQYKo1irqHQWvncW1ZBoFKJGu1RkkyDPxYa+A8H0Vxs9kcjUa/fPfny8vLs/OlO3f2R0Gbg+d5RdNCw+RKGvnC9Nzc7Ny0krbt5qbPX/lmrnymHxuRNBNSLEub/VcZyIwH8xl7AC/wfHFST/R5haBPun/aZUtrbRjCJB34I60SwVlrf7NgswhUY9COBp3Gbo/8dr99sLQ802kM9jfum2gJ3s3nrCTw17cfnDl/utPp7O/vMg7FcuXV117RWv3RH/3Rb/72VwApn/deql2+e//B6699qd/v//mfb07PzXEGN29en5qdCoORUtRsHUahenAn4bmKkZONnd2m7M/Ozk7VF689fpwYc5pIktYEigEBEENgE5kHADhmLQAA2Zh2SynznDQCEpBBhMQQkSFnHBgRECNSNteMgWDIBXJEBqA1gaZkUq3wESfYZE8qV4+PLk+7CyIgSERkEw/PwLGahUYmATQwpTUnkkwoRZq01kprrdIFBIIEQQRp0/txdFkTAHF+VK/8hICNiEKII7rWU4s/gUjAMTW94/JdnPDDPw5C+8jn1lofCXr4GXReBVxPei9rQq3Tho+oniiR4dHyBdJU/UTq8njOfvi05PPRCoOR1MjSiEYqfza+hwy2fxYQT9pe9qTfsJNVH3xaDnmmB7y1uSvIcoTpOPaFC6em54o37tzd29/PF1m/58dyUJ8uhwFtbzaUjg0Dz52taBho8OfmqwzMxm4QhQkI88c/fnt6ulyrTceR2tk5aLf79dr0uXPnanPBBx98kMt5uZynKalUSvsHW7mcu/dYmU6XAa6tLWxsDW/e2jh35uw3vva3++GuL2OLdLtx77Adl2or+dyCVG7E+n/FQ/YCL/DJwTAMrbVWyjWEAJ1EIYJ2LCMJh2Xbub6zwSFpHm6jsrc3H9mib88UFhdmOtsdRqxSzZcrRa2S1kHX9MSFCxdu377dbB5++zvfWlhY+OCDDwqFYrlcjOPw6ktX/FGQy+Vsi1/+8ptJHJaKlURGOztbpXKeSBWL+QtnzxEa3f3dDz74wC1Pf/nVy1Fj497tW/m1PDPcRJIi0gCp+wh84lpOkq8T4zs2P4wLQA2U1gNrIo6gCZiUMedcIbF05k//nrQwiSMTAk0hOAKgRi2IFKlnSycaqJ7UFk+AiIynSWViREQaQQMAA83RAAACRgg4lu5KGxswGtf2pnHj1ACjHNsmJIZapxxgTUTAko+4j4hIAB8xwFprpRRjTDOGlPKucVyiBUCksjlMfHIdRAiadFr+G2QYYGJjD1gRU2lfCmJEdGSPJkP00bA24lP9HkLF8BiOxlyQTEdcAxCyJ5l+LTNuQDx784kN8K8XhMXnuRGjGWIumVqpaQytAi1Yhd3HrdWzizPTxQ+u3R8NYGGhUp8qvPLacnXeLhWr7dbIdqv5XKm6AOi2Z+fq38h/+71rP291dspV+zcun+31egiG4/h7u9pzzjQPWzLp7e4kYXSrVi95Xumt78y4ThnIGA791bXeW6/LGx+8vbnRwoJZcDGXGK2HD0pG5fTMbw1Hc8xeaDBQ0nTMOuNFP4iJJYapIzU0tffsG8v0dDNeoKz6gJOSazKWXuITr+v9fCOzfvrEK+5nb8+aBk4ass58iidcuPPYD6W2bRvDYcWOR1t39bB/9/6jpZJxiLpScA73Gpu7HwDDSm2qWKjv3NldWlqaX5q9fft2YfoUs862owJWaftgz3DthdPLiyunajPz/+6P/kwpFSlWyFd7veTxzuaZc+djnvRa/ZnZ4Jvf/Ma/+dd/LGW8sDibd/OXz13g3Mp5Rc/LD/VLP/3+98qeKlbnfrrZ7e4dvnVKx8oPybYsSyWKgFmWnWgVSymE0JO+zkfzNjIGACZphpqZxBhqBKm0TEBphsxICCKJqNKMaZo0FSVDaiSFSQSKEXFE5MiBOB8hIgcOAEiMTazLWDs6FeICPRH30IbWacOeyWNNVwaIZBACEWgiJGDj4llE0EhkEDImuKEBWEovckErAK210iABlFKaIRGgGpOV0t6+DFnqQeqUaayBSJNGIpa2e0pJZ2lwXRBDOX55XPHsOuCIfNKoCKRGJZnSQmoggn5GCPqZZC5EEOLZXJkgMZ+5XfNjqb1jXwX6aDOJyf5oP/M4Wd8jOlZ3e3wf+9h5n/pbQwMA6fHjGyt9akCe9mMmhpqTZkgcCIEUckYaABimdeSYxhhCyD3zeoIs0m7mPPC8IqnPnsdELm/Zrp0rFP3w4MGDRwRRrzeUUpYr1W63VSrnpqYLhzRcPjU9Nz/d6TSnZs6MuqyUm09k8Hhjr1gsnz23Vq2WPWftg+s/b7d7uVzeMad7Cg8OmsNhyzaLvu/HcUxEcRw2m83BsDccDqdmLXO6wNGemZ6Tid7ceIhIwsDZhdqwv6shmFnyFHHLGxpCax5TMB3pJArbEfQAhcUcBjbTefVrph36Al8MCCGYlowxz/YG3db+/j4RzReLxXrx+vvvWqCmZ+eVSrq9dhRFrmV69Xqr1Wq1moVCrlwuAwCRarfbw96wWpu6ePFioVD44Q9/ePv2bdM0R6NRuVT/wY9+9Md/9sPK1C8KhcJrL10dDkfvv3ft5q1bV65eOn/xwuLi/LVr1zqNvVIxnuGG6bqO45hOLlCiM4qJeN5zIxN7A1NqLrUm0qQ1JxBa84+tij4yH43TqvDES1ZH3B8AOur3hxhJnnqPHJEB8YkeFmmGiGl5EiJqopRvLBiDsebHJMvJxlyk4w7c0ZVoICDURAqQNGjQilCTVjBuJ0xEAEynUVZggIoRAyJCSMt2UQMBKByfMu12SKRTAxwpAEDSR3wnJALSqBghAkcEgASJESCBAggzcqWplCYRJgqURq3Sut7M9V62wfiMLfT5ca7Ak5dEHTdsx5pWpeXWCASk8OgvOJgcGWiGxEgzBgyIgQbQwBFoQlBPGfLAAdKA/OcAYhS0Y0XCdHzf39oMXM9gnCGKMO44wmh3RlEyOrM2f+XyaqmcUzre3+1sbT+emi5Pz1T39/d397aFYOVyNZ9/cHjYrJYXQBV++fNH9+498DyvXq83m50oCoTghUIun/f8YBQEoyCI1h/tjPpCK3727FkAnsi4Wivl8qbQq5sPth/Lw3JZRHHS7zdmFs/6MjZZ07BdRiKWRMJIQOgwIQXmM6TdAP4yK5TnxXZ7Lod5gTG+qDn79LaSJGG22Wi1lFKnTp16/fXXt7e3W8PY0D4ULcN2eJ9REhXz7uO9zV6vV61Wy+XlOIkePLg3NTU1NTUVhVJrPQrCUqUqNV26ctX3/f39fctyAz8JA/nwwYZpmiuLp7e39t9++91Go2UadrFQDoLg5s2bN67fMYQ9N7dw+ZVL5WrVKtb2uiPJbdcFfzQgzYWYI1AMkXQCCgSiJjL0WFDueFQ2/UB6QmmamLdJgHpc8AOAWj8pSB3FJqRx6XFXKATUSCjA5IiMgeDEEZERBwIkGzTQmFqUhorHGslHIszpqfW4P1Ha0F5P1BilRkWaAJQmIpI03p5mTjWSoNTaEiMkBAGMGAGgJJZedEoyPupUmJZFwdjnxidtFhUxAMZIaMJ08aEJAOIMbUZJHAAkgSamFaTCXkQkMxwMnqHoxzIUAE/qppx0/2ySVCps8rHN6mlhk6NPcryoYqiRESKlhL8CIgAwJJZmOtKWEwCckyatCSWRJK4mj/Lz0tZQaPITSYOBHAUh+qBUUijm67V6EOzl8hYAFEv5U8unpmYdIsmUDtXWhSs1x7FmZsrnLyy3moP79zZ++c77tbqQMTeEs7czbDW7wQgqZZcxUSlPtdoHSsVaa8e1Z2dnlVK1Wk2r0e5Oq3HYPTzomRYGQWAKo9Hcnpn6A5ZMdbotg4lRKF0Xc1bZ76sD/3u1mUuGt+qIaWUUJYDmQ4NLiD8fOYYvqiH5pPF5YTWfFFprIYRSSkrZarVKpVKtVhNCaG6vXbhy98NfbDzeyZk6DANScadxuLS0dPv2TcbA9Zz2duPhw4eMgZRSmEa/39/Z2222W6Zt1ev1wWBQrlZ++IO/iKLkzTffGoVyZ2cniuLh0J+qz9x5sN7qdpqd9uzs9NTMnLO+tf5oc3vvUEL0nW99e8jsm4+3DcfLCdHc33HKVcMypALT4AqBA5mMAzCBkHysYvX4G55mMwmfaGWkGc0jks/RzkNpMAIAjcQRCJEYcABtEhOIXKAhSDDNBSgkIJx0K0obA6b2XwMAEj92aq11qkjFkvFagSkiRaQ1KAIiNjZ1WivNVGq2gQEBAzlxItO1xcS0az5x6J/6GY3n+zTyTDCJmjJkDBA1ShyXXqX0Z5XhASuWxl1TackxB5uIYYbEYzbJKCPEesLpJ2v/kwpcHP/+Hn9D2DE2+PHthgJkgEwzphknxjWiRka5o9zeeLkGE6utNYBEnlLmNGFCTBHqrOvMuq9PSR9CLJ9aQEQpQ9PiUvlSRqPRYOXMguvl2+3u/Pz86uoqgUzUgIge3H84Nz9rW87W1pZjVyql+XotPzu9Uq/NXbu23us22q1GEtPs7OyZ1YWp6XIUj0YDnc+VDVMXi/lczg2CYHdnb2f7cHVtedgfdtvRxqP33RzOzNbRE/5o0Oj80i40bN2PMNY8ttxZw7wfBC0jua2HsYz7ipaYN29wD0kaiAk+Owf8wgP+YuCLunAhTbbtaK2lDFqtVq1WGw6Hf/Znf1admc/nc1qqKPQ9xi3DqFWLw0GPkex0OkHoE8iDg4N83rMds9freW6ZM6zXa51OZ2lxIY5j0xCc89u3bxfLlYWFRY0G5zwMw/39/VKptLC4GMbJ3Xv3uSGmZmbPrK51e/5oGBSLxUIhPxqQDAKv7LqGspg+PT/V3A9BRnYup1ForQwhZBIxNuYif9z6fsQMw4T1c9RTb8whHnvDECYIqW4GAYBmE+1FRJSMhAQNKAUKSQwRQCdPGMgsrbVB5JPAcHpSIGJKkdZIBBFpACRUQEwDk6C1ZhrSfoUk03C0hnGfY8YZpXxlTHWZNbD0yuWkL9DT1DOQNCEbE8LYG06bQ6TpbEwtIqbtfD/Sf/cYtE5Ja2kJENNEaaLbzKobzpqvPqX1amb1gZJPwiT0JGRiTppwwITRlu5vIaaNNxin9D9khIhGMin0epqWE2tIRc8UYUKUaCY16Qkj4bMPkQajtNbzc0v5opnIfru7y7gq5fNS6l5vsLe343pGIgOtQZO6/l5jf++w1eqob87sbd3e3lk/e27ZcY1Wq+kHfQ2xkxP5EoRxZ3u3rVTiWgtaQ6/X699qVPZLQphxrLXCh/e3GTqCe/1e4AdxrV4ulfOOIzc2/8LNGWgOm91DBnzgbzUbN7QcuWD1th+1R/e1qBSmL7qls6Yxw5Ji8mxOwAu8wGcdKb8sCIJer3f59KlGo7H7aP3Uwtyw2yx5xow7EwzbWnDP85qtllbx3PxspVLK5/NRFBCo5eVlAH24c9BvHyQ5a9Rrcor7/T4ittvtpbl5Lvje3q7lecWSZwshwxEy++rVlwH0/v6hZZuWZRUKpdOnzhiGVSpX7t6+04uF0KWwkzTCpjlbCYaLfjtWmsoO0wxjrQmFQsYYh8nECh+pLoUxPfgIOJFTHmPyb+k0qphmgJL0uAZpnDdFhQoxjTWj0KAoLTFiQ0gVphmMbXraZImRPm6AQWtGhFqnKWACYBpJE2iNKQ1LEimttQapMe1bSICgdBoyJWDj5DGOQ556kmg8iqqnP9NGyGkTomMfQIFAGHvDSGkjXwJNKiNEDBNlsTGvjCFAqsWcIXyRYYBlhgXO1JTOMNhZXYz4CQ28ATK1u5NK4/Gr4rGPGuD0szH+lRABGeG4o6WWeqxkRkQaURMSAhDzJQCABkyINHGpIRUPEdm0y5PdQAaemwfcbve63S4i5fMeY2x6ZqpYwfp0YbpeunA+9+jh40T6gLrR3B8OgnptMZ93betUEovv/tsfMgb5EvQHjenZwrd/561ut9vv94locfHU3m7jzu2HO9t7SRiWyo7jiSAa+sGwWpnOeQUpKQxi5GacYCFfE1aQJJHrmVEU+OFoZm4FkUYD7dh5kN6gM5qr1Q77lVZjczjsFYquxUzLcsjNS8xlsZQ/ax7wF9WT+7zj0wpxc85Hvm9ZlpZyMBhUq9XRaJTL5Zqbdw92HpuQeBaanlOv5G3bFoZ1dnW5UikZhuF5zoWLa57nvfTSFc65RbrX6zHGms3mzs7OaDQSQoRhaAgriKKbdx90ey0A0JYZDnut5p6Zn7JsEcWjWMWu62oN3DSqtSlhGc3GQZQwq8hJB/Gw1WnE+7vbzW3JuFEr2WhYiQQ0hSSNDFE/w/rCuItXmuOlJ9MtoHrWxEdEBioA4GM1RBLjpghAPEFAjciQKUBF41hsAAgqNfGISEeELCWfXEYavE1D0AIUsdQFT4PPoIhSvrEC1AQ6NaIECtKCobTaFTUCaaQnzigdvSqTOuQnJKGPWF8A1CgYoARggAxAjsu2Uj/+WUjHMzU5aXt7REBN8mTdgVRm6DXjH7I2P6fpymLjdocfgYPy4xsB0hTAscvQ48KqSINOaewA474gyIhoRMZ4z3RVxCAtgctaQGTh05qfRbczHI0i17Wbje6DR1urZ2fOXZxdXVsueLmcW187c1mR/+DRtU53H4i3220316pVl5BPWRa/dOmlcsU9bD56/fULw2BYnzEt14iieGV1enl52TIKpOzRAJeWp3MF2Ni8HSdhHMe+Hwe+rNenQx8PW51yJV+u5ZGNbNsc+b2dnY3pmYIChtyybWcwGASDfqXoVK/+L+PcdmWkKoVp5hYD0xkYVl/Lovx85IBf4AWOwzCMZOi7rssNIwiCIAgajUav13OHg1G3MVXK9bv9UsGtVWsHzUapWtvb2wHQvV4vDP0gHPn+8P79u47jzOadYrEYx/GpU6cKayu1Wm0wGHDO7VzesnOX7z88aLXb7XbesQ2kbqfRGXEv5+7tbQ2GnW63i2AgGoyxR+uPzWjQavZGuFOu1JOgs7sDA826oWdYXhLOCyxKBSidBDQCfkS7+AgpzWqyDh2HoFOppXSHjyUFZdosiD8RjdKISFwBMUiFt3Rag4QAEGkGMGFBI4zjz4BSHl8KHBWxEIIGBcDSMlnQaQtCIEWYFs2mrQZSoShNmHJoNWDa00hpIEQizMrF4hO9KZZ6aAAMEaOJuhSlUVOAMW8se4WeUrb5uJhmXPWkMvbPNDAZHvPJaVXPB+akCUT6H2PpMwIb1ccNMCJKUJNUOhEhjDPrLFGoETWBItTIFKDWqBFDMgCApy8DaZ66zkA6a5w/Y5wSvPJlx3SCV18/e7gX3b3ZrZSny3W5cJoXq7W33vrS1va653mW6d2+9ejm9UcMrVdem4pD60d/dn13e1Cv1y9cWvjKNy6Uq2Jj6zFgHITD3e1OvXrmyuVX9/Y3f/HOnzEz/9prr1Wr9Xd/+eH2ZmdzvStjRyUGKD+K/VyeLyyVLUcP/dZXvvJmvuDdvbH7eKsdyerK6S9P1RYfPXqvWDjQsGWK//nj3Xjq1KULb7wuMTfoGQzdJO5XXcEccyDVMNEgLEGc68TiLNDJyQbihCugrHpf9hmrisq6zk8LWePzvK6TnteBssgvJ3y+SjhxGHiORVpqKYGxIIxtN9eLwqkcN/pbd3/2R/fe/iHIkeu6YSw9xzQMwzRNRIzjeDgc9vt93/eDIAAAIUQaZKpUKkqpMAyF1q7rCiGklKZplkolz/MQsV7K1Wq1arVqmiZjzLZtz/Msy+IQphdGREqplAWmtQY5nJ6eBoB0HTAcDgeDQRiGlK959VPTyxedXHVvr6FEvnLq1f3QMoX/zPs1MzytrEiDyY78yac8aQWKjT1PYECIhJNfAYAx4AgcmWCQhmwV8Y+cIv3Vs579wGTy7O87MU5EilBrrQnkhNqTeqWkUz1LRpQWODHJRKrpoQk0spTMRURZudssz1JnSFRm9i/PmK8yPewMsAxpSZ4Rm04IGWkDkaMyUAlUBgAgIdkAQKCQgKW5fERkkDf8Zxpak6IjrzdFGtvX2gUArUFpkKSVBq2JiEZCawDSXBFTmmmFGpAII+E88zqzm0CcVFcg6zgnW+hk9XcXX/+NVwolI4oHd7vbhoVnVpemZwuN1qOvf/MNBNMQXqvZAxiGgWo1u65Tun93/8K5l8+srrSaHzSa2/ODvEpEEtnDvk5k3Gr37t/bvK+7O5sd2zEqpcWO33z7nZ8vL60ZwtNqOBpFtuFxzhFFGFGS6M3HByurM7Mzi/1+37Tgjde/nC8+7nTZVL1QKece3Zc7281ymbXaHyzNX60UdNS8b+ZmClYtUiPTC5Puhx5byhvTGr1YA5FMklDrBLh7ooF+gRf4JEBKaq2ljNPKVsE5GdxEZaO8+e47+7d+Pty5Q8EwbwvPcfJ5kSSxlHI0GgUTxHGslIrj2DAM27aLxSIiprwqwzCiIORKxzrxfV+pfrs/SI0xU2Ha7CFJEgCwbdtxHCFEteQZhuG6bj6fLxQKuVwu3T5T9bjp2Lbt5IqmaRqGAQBCCD8ZWIVaN6QoHBbm+eFwGAzuW2aNoPBcxueoqcNHyFliTHsChpqlapKpicJxl8Oxy5pmAgHZsQX3eNIcx3SfPSEa/NmRMw0aEBipVHuDjR1lnYZ2iQESQyAFyAgBKW2zlBY9s5T/9ZcK32blYrMctiwPOOs4zwsmA0aMMy2QDEQOnKFmAExoorH1RSQ2UQN1BIOPhaABwERxtB2OZdYVKiLSGpjWmKbiiYggJMEINCJqRESFjOm/RKulzxxEtTa7u7v98NGGZefml/nWwXvDqGoY1gfv3T9s7jCuEGl6epYzp3HYty027PFodC+Kw4Wl6mAw2NjY+N53dT5fHMUtpYNqrfSl139DS+PmzbtbW49Pryxd/tKs4N7+bv/2ze0ktARzgiDSKrFN6bpuuVw+ONgxRXF2Zqrb3zatsmma3d6hVIbp9A2z6Dh4eJi4tmkbu5XcnB5Gm9tBaf7C/Ok3O8PBB3ff+WtrQdG0E6MURE6cSGJkmGSaIny24MyJkbUC+lWRpM8SPi/X87yu87MVYAJARIMjEaImzoFRxGWQxEMHwr0HH67feq9q6ZlqUYAmlQDoVqsVRVHq8sZxDACMMc65aQoAYgwMw+Sca60Ng7uua7v5tJyJuMEYM00zSZJgMMg7OcaYUooYIKIkNvCjJBk22y04zk+eTIIFT+RyOdM0UxvvOI5pmp7nLc+WuTD9MKrVatNzi1a13DXMAepm+Oz7zUxB/koFIkSkp9vypE0L0tpbRM2A0j5CCpHRmAHNEVLPmFAJfJJrPP7ByLCGXDw7wpHykBUgMa0JZWoAECXxtJOxViQJGOrUG1apjgcC6jSdrDkhISDLetEzBii779Gzt2bNS8+vweYzt1qMEIkjCWCcaUHAkDPQXCgiAtQciCFyJMYBEayJoYWnyVYmPjHMcMwAJ5hoIEYIpEED02k1OYiIKyTUHNMYPaBmyMfFwM+6q8wJ5WTjc/LjnOz44l//q3fCMG612ytrpW/9ztXFpfrBfvuDaw/+v//iDheyUvNyefPihVdWTl16dL+9/nDXNsoP7+8DG62dWyyVvVs3Ht2+uVnI12dPmcvLa5evnltYWCCNjGOcjPL5fL/bPLs2j9K7d+NwMIqrpWkA3uv1XJfXa7OzM4uMsU7bv3P74UHzXix7q6fyj7duVqtVpSrdXo+xrmmhlysY5uNh8P5waGzv+30/npp9mQhv3XuQ747OXJivLCBwUxhcg9YJxBFlfgFe4AuN50amOOHCKwumYBIMRELkoJPI7/ntRhgMCpa2k950wZ7KmzbKXvtwOBxqrRvdQdpOh4j4MZimCILAsizOuVLKtm3DMDjnwSAQzBDc0ECMMdOyhGkAQx1H3DAMc9xYNw1oJyRzXjENPqfnmNwUDkPdG/VTk2+aZhRFSZI4jmODZZss51i26wwllZYvvvbX/k5p6dyvGLiM7Vns3El50oRYBTBpW5j27gXiCAwYIrGjSZzSQlJC0AwRAC2Rdmkag7ExC4zLZ1+PyFSeVUSoYGxfNSfSqJFi4qRBA2hErkERadIq1QQhrQEJUcFYbUSnrShOgiyDmhW6z9p+UgOcHeHOGDeQCMAIcEKsTuumQFOaClfj5wNEDIGQqacPiOkbIklhGtcY3w6kmfuYeGp8FWFazquBiDBNMehUEhSAxrl3+pRS2ydG5ng2Gq3FhZVqtT4MNnZ39qemCxsbW798Z6vgTM0tVIKo6fsjQ1iGsHJesXF4C2VekRCm1e8FiJjzKjE3Q5/3er2LF7+zMD/7wQe/DKN+oeScPbc8HAahnzx6sH5+7fXf+mbpf/z//Ntmc+f0qTNhqAbD9uxczcsZq6srh40dmfQX5k/Pzy1v7a6XSub8oj0/yxzL8gf89p1dLw9rp5nFFe/xvjS5ZYYxWVZ5bfWyP0wGtGbRtOSWYgloCSSYthU7WQ74pAP3wgP+y+HXzQPWKmEIBGAYRjwcdPd3+gebQb89YkM2arpc9TvNvV5nNOhJKaWUmvE0wswYS+UV0zfQdkxAXSjmiGgwGFi2IYQTx7Fpmq7rGobh+36SJIhomibnXCWmYRiImCSJlBIRbSGEaZq2pbVmSqU2+MgBFYYJUnI+PqCdJHEcO47jD/lIh4NeSENSdoHzSmxWFPey2sqojBndyEiZ6UnV71G7nnFweSxYiQyZhpRZwwiRIwJohgBADAGJpbwjUzwJaR4Hy3gjWMb8gEQaiBMQQwVEhOnJkNI+DyiRONNKg0YkggTGOtAKQcG4awUAxCd0ADKLZjJy6hk9Gn5FI/pnI0sYJHPBRDq1eoREChUjJEAEikwASFUyBAOOwBhjHEw44gqMtUjHKmJKT97tCbeciIgSsIlIpXZXo4Zx2VgkMdV10UDpO6Z/5Xf9c+MBG95oEG66TikI5TtvP7p75zD0cWn+XPNgsLN9GMv2uQsLiPjzn/98d3e/VKrFcay0DiMVhm0hhCE8IDEajexRcnjQG41G77//fqFkrK2dIUh2d/arU4aKBp120zTdubnCaBj5QSMI2vNLpVwBg7hhWDyK+37QV2SuPzx0C/lqtd48PMxbzltvnPGXZ37ClbCxUp4t5GY7tjRybr12yXWtoQy//dUL/mDBKy7GDIIEpI6IIgscyxABZnXteDa+qIpLv274rHnAMknGEv5CRP5ob/Nhf+eB8rt7/Z04jMLQHw56o/7AMLlhGFJqc9JdJ408p0BE17VNUzAGUqpczs3nPaWUEExqEFzLxAeKXcewbUtKOQh9g3FTIGOMI9cCGWNEJCUj/qSx/PF3XjBDSonIOeeMCQClNcSxNIuWkqJ9EC6uXPmNv/X3Z1avau4EyQjYs3PAlDmh/6pGcDTpBo+TrjsJcUDNABmmfYIQGTFAC9JQMyEQA0yVhhGRiVTy8Kn48zHy9ceQYSBREwJDBA3Exh2TEAAsmTYIAIY6pUYrRkTIUWsgShlDBBrHHlucxUY+6QI0I9mLn9JSU+tJUj1dl4yDFKC0gIlnzBgIBmnbLKmf3SWJND15TOmWMQvLpLSbFR3pghFAymWftL6YWN+T1hp9BiH+7v/ib+xut65/eG84klbigLJzuRKRoRVGcXT+0plXXj0fxaNr77+7u9uzzaqTs9rtMPSRiBkGz+WEENy0MPLN7//RL6QeSd26+sqp0ShsHPZ7nbjTbZw5s3L79i3Lss6cnXbs/NbmLqD38qtrgpujUZTEkCsIxt3GQXtvp204OdcOBRst1c8w7RjoWmYuCuXBHda0emTizPzMwow77G1acXN2BnYkaEmhrBvMMmwRx2Eiw0g7YP37b/4FXuCThsExmbR2H/a7W+sPh9t3DDmKBvtRkihCpQFMWziOIQwFviHoyPqmLqsQgnPOmOKcdzqdfD7/6quvEtG1a9eiKPIct1IpO47j+77v+4jIbKPgWkopIkqShLQWHIXgUkqtFDfGrNHU1B2ZYYbGUWe99KSGYQghwOZAHrfc01ffmD37OrpVOQoKptnPaiqWFRrNMHj6yGOe9MhLJ+WIkJFAJE5MEzEOjBARLEgAAGnc+ogxYOPCoTQ0CQCT/rcAACQy7GBWvawBbCKekQY5U5eSMdRIQIyYRsVAAQliGohzTURSa65JaZBs7KVB/OzuQ1lgGZY5K8KaRbZiJ/S8s8p1shaykjBt8Zu+NYCYFj5JTLVBFSNihLEmzgABw+SpOt0jUAYJi6uJEhlRWjMGAApQoNAIqTiKRqCxG5zVBPG54Xl5wJkh6Fdf+mY0+kW3875tFg3D3t9rzi8yw9RBINfOnf7d3/0tjb379+/HcWia4uDgoN/tVcrlSnk6iSFJEkPYmqLBsOVBLQqGyONSNee5Fc8tl4tJNJ0vVYEg8YOBVH4YhjMzC1PT5WIxv3+wxRiLQsXQKBTd6anZ4SDxZWywcq+9Zwnc3uj+i61/FyZiqr54+ZXL1/71e75qLF6YPn1KtA/vbz1sGKxl6fD06n/SGeikDYpVwOQKgRlkmBR9TnIDL/DFhmVZKHWiNRGNRqPDg73R/o4HoWPEoR8o5IbtMYZSE2gNwnTdcfBZCJGa4XSSGg67ANDptGdnZ37jN75xeHj4p3/6/f39/aLrLMx+9fzZM9vb2z/96e1Go7GwsLC6unrh4uVOp7O3t9fpdADAtm0ACMPwqJ1cmmkex721tk0TERmBUsrkAgWaXHDOmWUcHjSt4szs/CVkU2HALTRFNAL+7C/YSZ2SIxfzI1DE0o6DRETIOYFGQkAiYoDANCLj4/piREbHCbF0TAgYM0K4Wa4x4ZhbS8jSEiCNDAAEaECmATQjrtM4ODBA5IqIEEEjINOoQWt6purIvw/PHs/MhvafVsQODRqPEkurlQGZRgCmNVEag9cADAiQEDHSFjxtfceGlnMYF4w/ZYDTMjYFY/EyhTCmZIEAAGIEwAghLY8m1Blcus8NxJ27Nw8O95IksUyQMrIsI/BlGBA3RofNjR/96Efnz115fJ8OtgXjbHbeTAsQFcZeyQHgw+HQ931h5oZ9tF2lkm6FlQ72hr1WI4ms1mG/0990rFKl5hZLzAzp9u3bgjvnLywHEW8e9AU3FxdKYdi2rOg7v33hnV/ctlwcWHPBiN+/H4XJvVMr05cuXm1vN7ZhP1eozp95q9ct/fLdm1yYtdrpjQ+GF/23p+a/WqktxT6NEmKGi0wrCFiWhmpW7oSfLBeSlWvBLKm5TwmfsTLgzIFjmQICz0ZWuS8+r4kp6zFmXH9W3+IoCoQQpsmTJFo+f+XvLv2f3n777b/4wz9clo/sUieOhpxY2Sk7dsx5zJARdxAxiqKc60VRxABbzVYcx8ryuOK2URh1t5anrB9+951Lp1chHvzN3/tPDg4O9ncPRgO/VqnfvH5rcX7p1Zdf+9Jb5/b3m//8v7158/rNIEyI4euvv3r15Zf2Nrbv3LmXGng/6K2cWVg+tdBsHQx6SSJltZTvdPvFstdstnP5QhzHYUR1N5g/ZcycqrIcV7v7Rk4HDhPq2RrsKkMFP8l4E/HY946O/WR87Dmp1FudzLPCcAGeYa0kf/ZMbGckS1XG+2Nn1GtmefYyyhDoYMazT5BxnCQzNv3szZBZRpW5sDjR4TM9YDz+vNLHoJEAVeqLTlpijNsaPeupp+VhOHnaky4d6Xb55HukMXVw0/3ZsZALHfuQmfQ+WQoy29PNsvAZz/2EOSrhB13T4rmc2+sMLDOnpFCJ2ev1vvq11enZ0v0Ht9bX1w/3/dDHfD4fhqQSW2uNmMSRYoxJqZUEKbXWUggr701rRY8e7PmjDa2sOIL5pcKgR0HQ80NtmFpw03UtYWDB1YLnkPKNwy5AePr0skAlrG4sSZhG0fKUNPYP4GCvaxkbvd5w5A+m6vM517Ftb2q6sr1zsLU9KpUKdz8cJTJw5yKJERgGE4ISUAlkLRxf4AX+KkFEY6ULgLTC54033rAs68P/1//ZyWOlXjIoTwkwjqZpIgoFAhGl9FutdhRFrusmiQzDyPHy/U7fEfHa2mWt9d27t1fOXPiDi3+wvbW3sbFx+fLlZrO5vLz87W9/+9VXX/3JT35y9erid7/73Wq1eubMmUcbG1/72tfcvPf222/PVqauXLn0/vsf3r9/t1It1mq173znd4ql3H/1f/l//tGffG95eXlhafHU6cWrV6/+j//ifzINm1nemZXTV156xcm73eGgUMwxCJQ62ez2HJHVzi/LlMQZkbCsEHRWG50sA5xFOnuBF/gPgQDsRfGhl1OcidmZmccbe5wpx+aOB3Pz1Z09czgIkGkADmSMBjGQTMMFUajSQggEQ0llmWan3e/3pWWzfMFx7ErgR4ZBWrqhL/UoZjwplEzLtF3X4ZyX6/b+zpaMgmikHZs3m12g0er5mmOvxXGkFAQj0JT0e6N2u9vp7s1Ozdom39x6WC6Hi/NTcRzeuHm7222u1l7hWGbClVolGhBQMM4Qs3Mbf8Uj/AK/FshkyzOWlv3AOOMFMzMzlmXt/NF8ojYNWxtEkY6FIwRn/lB1R61UzDmOY8ZYrpC3XYcQdCItyzCYKuTcdqeplDq1vDg1W/rDf/MnWus48HvtlmuZf+v3fvd73/vewwcParXqqN+7/3D7N77x27/7u7/34Y3rH7x3rVAuEMjdvZ0rVy7l816lWibCf/bP/h//xX/xn83OLHzjG9/8wQ++f+Wli2E4HA39l66+8uGHt5ZWZs6sLi7ML2He7XcHdqEWhBFDg06Y63peCDMcEiMjGyjVsy1wFos4K3qcFVjJGocvKjKfb9aCJvN9eF4a/p8tnNgDbrU24qQ3PWMlMTu7ViVoM8aGQ33v3oM4Dh2rcGZlJg4eh6Mg8EFJmwuJyIi0UppzMgzOOaTJI8aY6xaSJAh8MgQqRUKIne0908jX6qV6zbYdHA7CbtsPwi3vUCYxS+LY92NDuMFII5BpiXZrx7Rpaqq6tra2tnrRH0lgo72D+3v7lMhoY/1uq9U5d+6l2enKxobdarWLq26h6Fiu2Qt4mDBgFgFpigEyQkDPaeA+6eP8+uGk5QEn235inPBAmeSjCVJXuN8fcM5d1y1XZhrtA8NSBjPiWCqiYZA0GoME4pR+xYQphNDApAZFSDJ2LNvmaJtWzrEvXTiXJMnNmzfPrC7v7u46rhFGwzOry5riRAZx4idR3O10tjbW838jv7Z65vvf/5Nbt2589WtfRqTbt28qqX/nd37Hss3/4X/457t7j//BP/j7SlEhX/r7f//vo6BHG48uXXi1VMohmGdfvlDx8PCwtTwbli0RJn6imWkbOkPK8ZNGktWIPqNpgTwhuUlTVsjxkw3tvsCvxic9bp/WcxHX3l1fXJyfma4/fLDRbjdzeSNfcOVuu9cytjc78wuzpDUXrFB0G/t+MT8Xy1ZKEkmLCJ8omCSRYQjPc6RirmuWy+XBkMVxPFvO9zpJs7XvR1oYQNpyXRMZBr6ZzzlE0emV+UKuuLN9MBoMhGAS0HK0UrHgHqhcFCXAhmFyMDV1nnMjCtXm1vaPfrRXKs+UinapsBTBo1jNm7JsqpoHRdSW0mGiYxOfzUJ88f6/wCeBX+EZpEW9iCilTEt1Pc+ZnplvDe4E8TBIwnZ7kHctS1iWlw/7zSSJi0WHMWEYRpKoOJZCmEyQ3xlZeVYqFculkm2aP/nRDwdB+8qVl+u1iufa3/j6Vw8P9n720x+/9tprQMo2RS7n/sHf+v3Gwd4//af/zdzs9Fe/8la33ZmdqoehLwxumuZgMNBacy4eP94qVwrXPnznv/wv/w9/8qffV5JmZua2dw5Pr5w6vbI46vXu3by5eLpdK3p32320KzJhn5YHk0VKynB0QWdwOzL9shNSCHQG6ziDo/a5R9bzzRq3k74Pn/cFyok94MY2uIyZ2o6HuQe3mlIF8wvCgJLrmJZlAAnf780vFgyR+1HrQ0WO1oomlWBaqySJiYhzxgVqikZBZNng5ipeHoDZ/Z5cOTO1vdkOw7hYNk1TKMmFAaYTjgZ2q9kNovbK8lIhX7l2cEfFanV11SooRNAk93YPwnAbkQolAxns7W4vLy9furzmeva7795sHKpScdqyLHS7YbLBuybEcxZfRmdaGUyYlv6U2HGf9xfo08Pz8YA/e1IcAABpUdARGIN8uRbGejgKbKPgOHU3b+okFgaalhXHse04YRgCYpwkmsi2LM60spTnmXnP0TKpVauVcnFxuTbsd1577TXLsuI4/m//4gfr6+vT9cqX33w9jsO//u2/dv3DO9/9w++1O4OvfuPry4tLy0sLSRKePbe6tnbmpz/7Sa/Xu3LlpcNGff3R5re//e0bt669++4Ho2EyP7eyu7vPuRiOWmEc+pHWGoP2XrFYI+BoWuFgKKysCNMnbYAz628yNp/MAEOGdnTm9zqr7CeDlPcCn018ah5wMVfuNEck2wJy3W4zTshkcS6f63b3C4WcYeam58v5EhjCarYLo368u6n0hEdOoJVWhmE4ro1IhiVMOy5Xbc7jRutxErMkAcYhjuMgCCwnkUoDCDtnFkqsWCw6dmU4Ku/vNR8/bA2HQc5juaIs1E0gazTQSZIAhIAqjvigi7ZpHBzuMk69/kCqwDatarU8O7O03fqw296I+m3AWcsbMJ5IUUXDySJTZIcuXxjOLwI+aSGOkx8GU99XKSWEAIAkSYIg2d3fHw7jqanZ5fnzXJtB0NjZfiRjWanVtdazs7MHBwdSSpISmNKAjuBetVzK8XKxpEmtrJxaWDxluZgkie/7L7/88o9//ON/9I/+148fPzZN8403XrMt60uvv/H2L66Vy+WVldXtzY0wGr7xxmtezr569aW/+NHP3nnnWhLL4XB45cqFdrs7NV28cPHs7Vv3oghn5hcMYUsKbQf7/W6jHRTypWFjv356zXVrATBC41eE3J+5/XkJ3fAMA5n1vCgjpJzV1SpL2zBT0SPTzp4sR/5FFQLKvN8T7v9FnZ9FocTCQCZyaAgXGc3OzAuDtVsdQhkno1LFfuOtM2Gyyzn73cob7Yb+5//sPSkVADDOEAFRmxYvFDxEjJI2F/Ly1dPLpxb2dzs7W73tzUan3Q/D2LbtYsnRMArDUJg6VzRNgWEwqFRLw7YedLpJEucKzrf++qtdvznsia31QRQOuEDbsQXL64QAZLvZFoLli6XFhZnBgFqtBpB4tHU4arereVEqtFzbVUkp8HlMLMdPVgj/Ai/wSYCI0nLetCeg1jqOYyLqDfpOLr+0vDpdXtrbaRw2BlrDqTMrh/tbjuNUKpXRaJRyp6Mo4py7BkXDaDgceDlnOBxub2/blhc2+rXa1I0Prwcjv1Iqx3H8pdffaLVa/W5vdra4tbX59/7e3/uH/yuv0xsN/VEY+ihwde10tzPotAeOk3dsN4rDKIquXL3Mhf7rf/3b777zX3U7UuoD27YXT03ZDoYAzVZnpVb1B02B0nGtnq9d25Vq9KmMJ2Z4ltp4NgmLZSzEs4reZKYHnOFhZxzn142c9QJ/OYi9XRPR9HJ2GKtYQaPbLBQKlueqoL28NG8K/fMfv52ofr7gaK3DMHTEaHqhhoKHgfKDhHg8NRuWarFnVNcfxqDd7UdDGW5PzxbW1iqWGa0/boPwZxbnqrVCqx0YQHPzC1/+ylutdvuX79wcDfT+bi8KtBAFxMr9O8lPfnFzenq21x1tbW2fPbtWW1jodA/PX1m8e2u3WDOn5wXAaCVfb+wH3W5HcG1GxaAfbwbDh4ePy4MKmLByuVi3i4kylEq01sAIBUcORKS14vrZOaTn9nXJWMlmhcJOiufVhuykx3l+qm8n66OZFcnLajOXFYrM7NN5wvvNiqxkIbY9PwwNiLghBjKJQjlX8T782c8ahzdevXqp2WwOOtdc25I0zJdLpVpVhe0gCB7dv+W6rjBFEASMYpLQ6yXFvOmYRs4rBX44NZdj3DLtare1+41vvpEkqt/zGfJms93vjVrN3uI809Hg8dYBcoFCE9OkeTKE+9f2TdN888rCb7yxqrU2DIOIer1eZ69TKBT+83/4N/v9fqvVmp6empubsyzr+uOtq8sLGFO5WmWD5rJZ6vthPF1kvZNpED0vNqxmzz7vSZ9LFgsas+qAT3R0SEU7TrL/CVWcs4+foVuQcV9Z9etZ45CFjMcCmBGBsDOVyKJnbpcZ4xOdsN70pO9h1rzNM1+Ik73PIomJCyTNmIAkScJIuq5dLFYBckpH5aptuZWdneHjja0oEPOzq7/3+69//etfGYXB//u/+xePHx8Ui+UkHnHmtdvtMPSrlVIc+9evP5T61GuvvVYqlc5dsg3DWF9/aFlGtVr2/eHC/PLudne/sa2ktk0zCpPBYICkd3b2/uW/+P8NA62SXBTGSWRyzJuirJLe/Tv7BMnVq1cMS/a6w5yT346GnbYf+FoqGSdWFFiWt3xq/je9qYtGabo7HOUsLyWfprEpUlpqpZTiGQXsL/ACnwRIAgM8+hqbphH70f7utuDY6XRajUPLMC1DuI5lG2YUjNL3U0oZhmGqyJHGroUQXAjGVBzHgqNlOf1B0B2E1VLlsNHL5XKO63W73VptanZ+5v79h1Jqzo1coUjIARMmkIBHIenEimLdasdah0mSpPKTw+Gw58s333zTsixEnJmZkVKur6/Pz8/nHbfk5lQQJEEfdFLKs6KGnZ5vQ/5THdcX+Hwje/mQsfD6ggYUhGW5WqswjImkEKZj2kmSbG1t1Wrmzs7O3JJx9sLMK6++dGopuX294ZizX/vGy4US8gDnFyuDoR8lRIotLVzckRuPhk3BBlp7YZhUK9OnTq2sP3p8uNNQUt+7d6dcrp8/d9Eyyo/utW/dunX28tTW5gGHgVLMtu3RoK90aJlesUJzi65WTnVoFMoaRa9c434cPri7/6W3XnI9HgXM98NWs02axSGadmIaRZmUaoVX5+e+xosVn4OBTMsYiACBIQPSCtKuHfjrlmP4vOP5dSPJErXPOu/JtmeBNCAjznlMBAg52xw2dzcf3p2dnnIs07FM27IYEgOdxOHB3q5rpP1nn2jkAgBjrDJVToJBqVKen1vo9hvtTs9282eXzyR+aJldRKxUSsvL0G43g2C0cmaxXC35o54ijOIkjCKDc+QcGJo2KqUYYwZjbs5zHMcwjDiOW53m5ua21lAsltvtthAin/f29g4UCsMZkIqHo8HB/nbVzReM+WHgRZ+wxNpJc6Wftdz/X+LEJ9v7c142mRnheE7HeV77f9IQSZLYtpV2baxUK1PT1dFo8PjxOiIawuFY6DSVyUWpWIvjva3HNy5drI4Cu1gtLJ+u7uwe0kAlsfXzn14reRVTlCvleds2m43ug7uNWmVj/2B3EI72dvcBxM7W4eHeSCa4v98oFsq3bjwsFmpxoHu9XjFfXFxc9IN+HAb5Ig+j3mjkE2Gro4K4VSi4haIVjNi927vnzp8q5OvteOB6Fmes1ew7nt3vRe1uvzpNpKP+oD1AmavlZT9GYIwAgBBQINOCCWBwwlDV88Lz+8JkbP+Ej/P83tuTGcjPOzdFgBYIjDGdJJyTZUKj02jvbxRKWjLK51zXNmUcqSQWDJVSneFQa23btm3baUGw1tqyrFa7HY7aF869Kkzjl++89+57Hxy2e8L0TDR+//d/Xwj2ox//1LbNufmpXM7LFfMaRXcYMMjVp+bQ0KbNgYwkRoadlBE2QTwKh2EY2rZbLJabzWan0yuVKqlbnMsVGPEID52ylbNm/OFo0HlcmCope2brU6oD/qxNoF9UPC/Dlh3wzRI8yUgBfEqP/aT3ddLjiOGoKYySKQSAljIejUZRlJim3Wo14zj54N3tRIaXLq9985urr73+UhAEV69edXM4DDtzC8XalNUftm3H2drZ6xEgWqRsfwitQ/3jw3sbjzqI6vWvXgp8LXheJr29nUOtGGlhmaVcjp0+tfbg3rrv+zk3F8dxHEnXzVk8/+BOu9lsLy+f9qxqrxUybefyJdsM3n37QRLzU6fnZmfmObNv3ViPkzDuFKNQtdp7A//2MHgH3LKUVjKcsoyKplTJnRRpBMZRMMZURk7ixRf7s4nPuwcsOPKJ34aIIKl3uMujkT8Ik9AwBZeMRoO+DH1h2wK15XlSyrSVr5TS9/04joUQO1tbgut8qdjsdK/fvCUs2zKTn71zzeYWF6Zh8ps3rw+G3bm5mfPnz66urRjiyv/0r//do/WG4+a4UKVqqVKdLuSr1TJjjKVNf/P5vGVZluu4+cqwO0DEc+fO7e7uSik554ZhFIvFsOd3I4ObrmMWAz/UycjDYBQ2gM+cbCBOiBce8L9n78+5B5xVvqUyRN4z2emfdw+4Uuech4mUWoHsBo3mYRJLRKzVCkk0OtyLG41hp3nHHyIXse3w3cd7cwteRJ1arXL56go3rebhgB8qJoVSycbGI9KmwUtSyr3tQBjql794MBwOg6BRyFeKhbohLNf1tre31y5ecuxi4Ee5XM7Luf7Il1LPzS6BQc1G13Xy9dpMIV/c3FofDvtLS4vFQrnV7Dy8vzMajS5eWo1CFfjSsUpDv7J6bvYMG8wtG7bzyCstOHFVq4E2yxyQiCkNpEGRRq0IP4PdCV7giwwDCTQR6VSLY9hv72+t500wBVdxmCjOSYGKLVM4JgNghmX5vp8kScqX7vV6KQu6WCmFw47ref3B4O79B0vLayur502n8v4v356dnW21G6NRcHbtwtWrl7vd7k9//O7Xv/bmQau7vbPvePkwGap7iVTImW0bJgCkJta27bTjYS6XKzhJPp//x//4Hwd+9Itf/KJQKDiOo9TGpbU1w5oKQ4wZy5XqubxhosRkC8XspzKen7UJ9AVSnNxTzPCAv6CPN9MDPr1aLRUrcaz391r9XqA1E8Lk3Gg3B/X69KnTS8Nh//Dw8MNrj4Ig8Dzv7Fq9XHHtojkYtnO52jd/6w0tzfc//NBv5jQlOzu7W4/bpAVDRxhUqljbj7v5fJ6R5Y+UYQD3DALp5cxbN++//LLnODnOheu65UJxMBiur2/MLE5prR3X1lr6wajTaXW6DS6gUJoqlm2tVbPRuXnjvml4hdx80I8ix15ZW52eYqWaQu6bvG+yfBQmh2oghOCGjWhwBqBRERLprH6Znxeps1+3EPQnvf3k93uymDhH0gBKa25agKzVONx5/DBncY4JAXEEzsCxDMkx7eO0s7MTBAEiep6XWsdxa0KDBSPwPC+XyyWJeryxGUuzWpu+9NIFEDqM4wuXLl2+fHVvb+/tt9/L5XKWl9PANQhAA5lhOzaQgWAmvkTEJKE4JqUUY+Q4wnGMvb0t3w+63d7Dhw/39vZ3d/du3bolhGh+/av7Hfzh2+8navCll9bOr565ePXK5VcvPFw/0TC8wHPGSeeTk0YOPun5MJuEldXmLKs++2T4pEPrJ4Uola2vfvVVQ7g//PO33/3ljSgChpZW2rGKAKzXayHTpXI+9Asyilr7caPQ/8mPt9/42qn6tHv/wa2tncNzZ6+8+dbVUzOvdbvNn/zkZ6Ph+wdRIhPwfT9RvXr17Gg08LxCu7Pv1b1iKf/o0T3Xswztra8/PtjfP3VqiXN2eHjY7w+iIJ5fuEpJogmDQb5Wnj+9mDfY45w9PQgeDUcNz62UK1NKQn1m6dyZr/3JH77bbm90+23XMatVh6QkP4h6PX8APc+wLdf20DI55wYgMs01Mjphm6oXeIH/GCBpIkVEQgipqNfrtBoHyx5wIWzTsEzBAQfDXrfdHg0GSiWSiTiOTdNERNM0iSht3BsFEeccOYuihAuTMXZ4eOgH8rVXLxHB9PR04EcffHDz5o1bjuNNTy2EYSwTDciVpjiSKJjSSRIpx+Scc42oNTGhtZYKGLGkUCh8+OGHzWYTAOI4Pn369Gg0un379t3798zc5Xx+eflM7lvfequ127x9+3ZtUQCsfdpD+wJfQJxUW/vzDjHs2T/4/u393U7jsM9YDbTvR4NiMT8zV+ScEzHbzHXa+5xzJxdxMx74RtSxf/KnST6vBwMriLauVTqLSzOXX+6dXln87e98o1Se/96/fefu7V0/lCXXIRo4jpayX8ibnKkoHM7O1MPIn6oVg3BYq7leTjOma8KZXii0222nsDl/qtdu9SWFSeysnl7VMhn122+88tWra6Nmp4mIlp1zc/h455fKfGiyx53dTtgug/iN8pnfImd2f9guzjoleypdvMQEaY9tFGl6ISvJ/9nKDWedN7OI6oSXedLjPL/irWevZDOVgLIEiDLrmE/Go8wig2RmKjL7oz/7ODGzgIsoGNWQh8Pd7qPrU0UXWBwm5BmkgtFeq3vYD4TtFcqe9LsKqoy3o6Tj5u0kwk43mJqqRskQh6znb55entrebM3ULyoMe6POex++Mz9j/Kf/m394886d//q//uf7u345Pz8aNEeDDmdDCcMYtFKM7Fw/GHmWcF2RL1S0VsPGAWPMdB1ExhjuHOwWCgXhnP/hz3/6n/2j3/1v/ul/3+xYi2eWXqosLhRp4et/e6ohF2yybT2yjfX9aHWv+mrt4Q2/nORnedDTMgKvPoqkrUfIni2Ac/I6+AyP7YT7ZyH7e/18clQsk1SY9Z6fkG14Uu3lzONnhIJPrPV90vHPqK/NfMJZ2v7PZ34WGedV+Lz6Cmect1qZajb63W6/3+8LYdq2bZolInmw3+KcE5FlWf1+37IsKSVjLArYaCSH/X3X6xgmeXmRJNEHH1zrDYZT9dmFOe+tt760szm4cf2+65kAMBoFRASgbEfYlufYdhgNZRI8Xm+aFssX7Dg0wnDY6/UMw4oiSGIql6vLS2dkYuxsbvf7XT/sCENpvrVwarYyM7W32+r1G4YDjut6pe5qZdFBbOw379/5YMmcXn1pBetzw/7oRa7oBT4LSBsRGowTKCK6detWa2tztppf39iquHxlcZ6ZbqgiGw0y7bxtgc51+yPDyhmG0W33wzBE5IIbg2C4sLBQLBa31ptJEiUUeZ73ja//Rr1Wv3vn0dbmXrVa77b3BsMuQ2Va48pjROScEwIJAcC01v3hUCll2h5jLFaSpGKMWZYThb5hGDs7e36o3/zq1+7e3zd7FmM2L9RsCFfzaOukNaI+5YvzZw6bren5eTOEOIk556BZopQQDOJPe7hf4AU+VxC3bj4YDEZxRK7rcs4ty5Qy6fb6BuOc8yiKDMPQWivJiMh17UE/AOBaayAjjkIvZy8tLvpBpd3UH76/LhNcXT07PVuo1Owo1J7n9buJlLHSSRBgkih3aCuVRLG0zZJr5xzLkjGOBjDoacZiALa9dVAoOkEQABmxjGxXFcqJ40GiW72h6vXjZruVSCowx7B5uWp8cGNjulxeWJwp1+ejoL9++7qVW67VF5phkN5haon/0vb4s+YBv0CK55UL/6Q1eFM1GOQISh7s7+7u7tVL1bVzZ+vzZ3Q0CPqd1jDJVefAcA96zZLDbR03mu1CSWjCKIm5MDXQKPCnp2e93Mh2rNFosLm5sXh67upLV5G5h5uPJT3oDXsLCwugnQd37wf+ADDi3FCStCaZaGIyDWUDoFtwhwNfawCpiCLTFEIIKZVjolGwW+3+7m771TffuP7gu6F22/3heeawUfNUIT8YxY96uk+55ZVT2w/fOye1Z0KYDJlhkLCUTkxh6Rfv7aeNk1cNnGz3E+dQT3bWTw0nzYVnc0dO6AH7o4ghNwxKEhVGYRiNOOeOY3EyGWNKAhA6tktEUkkgTiAty7Esa2ZmptU66Hd9JK9WKXuO8ed/+ou33357ZrbC0CxX3L3dbqFQ8If9tJZRqSTwZRL7pmkYIheGoSft0Ui2OwOtpW07nBtE1Dg8KJYWiWg46CrSxHBmvnT2wuzNdzcPdrciFduW4+W9fr+/u93qdIeJFGHIDKfkurlRb9gaPvTqBnccEC48bX0nQ/NrlmR4gV+JT9pgKKlsQ3CBDOT1994rlUrnz52eXVqok0Hx8Ad//L3q7Km/+w//cxLO7Q+vCR3e++lP9LY2TUsI4bq5WrVYLufjxHedfD7PAEAINjc/s7y8bBr2xube9qNtFMubuzuG5S0tL1gGv3f33TDqIaKUmjSm1b6MgdKkSQ/jxMqXw1FMOiSVlEqFxcXTjx9uohp4OZsJvP9g662vf+fcS5eL9Xm5/hCTQI46LGcHQRAOQ2KsUpvd3p46ODgozuQCmYQS0HQh1qQTJvjJG7N/vvEr2lCebP9fM3zuy6ieE4TjOIg4GPYBo3zBDsNQKVWpVKMhaq1NkxDRdb0gCIhUkqhi2VRSSxkSkRB2p9O7cf3hYNCfmVtuHPaiyACAmZna0vKM70etViNJMKVxCsGIiEBpjVojstiygXE5CkauaxeLeSIkwvn585qCZrMZBIFje6bJuaAHD+5O168cHG4w3apULdfz2m0d+cZUdSZXzJVLNcOr3Hl0uL0/8CqL+anlIGpbhpfe4QsP+AuJz4sHrLUmUgy0ioPbt25euXTJ8+zbDzdOnz7nOUXTK1546bXV86/c3djytbn9cL1SqniFopt3/SiKElmfzpuO6+WLlWJt9exykkSJDF955Wqs4nv3HuQL0+VSrVqpfXDjg2bncb0295WvvDU/53W7W0oRAOTzeW4W/XBABJQkWinLy10490rrsBeG3VbjYa7oXbp0qbnf67c7Xs5Uyrj23o2v/da3T51a2D6IbNuuuEoI0ZPm/mAgg0HBUDZX3uKFze0fvzq7VBAw8jWziwwjSmJhGC+68H26eOEB/+XwaXnAbDQa+cFAKr9ay62sztanc4ChVD6ADkNfqURrSaSkjIlUFAWmaZqmkCpuNg+jKLBtU2ulVLKx8aBcqkQhPF7ff//9G/fu3y0Wi4hYLHnCgCgeRXGgSQKAlDIIAmGgYaLjmvmCW6sXC0UHmTRM0Frajnnp0qW11QthoDptv1peqFUX79693em2cjnv1KmFV1+9+sorV3J5p9HciwaERq26+Ep56RWRm+70gySJKqXi8eE4GhQ8OU40mi/wucNf4pU40XuSy9lABEpurj8ilVx9+aVY0t5h5/Cwee/BQ9fNzc4v3Xmwfu/RVn1moVSfPWg0AHkuX4wTRcgs202UNG1r5fRZz82nguoEam9/R0q5vHzatAzHcXJ5N1WQjeN4dXXt3NkLMtGci1ptql6fzuVypmkjIgD+jT/4g69881vnL71ar88TQCxjItVp97lhlMo518kf7LbioF0vWVsPHrgGefmyncv7ZHaVFUrtoU+9vdlKaeT7atQqcCk4JgoYA06/jvUFJ30fntf7dtLzflHxeR83YdkCmarWq7NzNUQ6bIRujtXq+VHHGPl9AlIa4iRIZCiEUEqGPiIKziAIAmTSdtiplerZc6//+Q/eYSji2DFN03I0AouigEhNT9c6nU6/r7XWQnBEROScc3/U2t7aF4ZyPXNuLk9E3c7A8/KFAmmtd3f2+70g59VduzjsscEo8INeHMexhCRoD7sVqY3GYbfdaZTz8/1RLO3awqWrxbmXth6se84U0w4eM7of+fC5wOfrav/j8Xnvh5r1vCwL+qPEEfDh+++eWlqs1Wo/7w8WTq8uzi/89Id/wkD7vt98tK7AKs1MTc307rbblmUVi+UgCMrlXL0+fXCww1CMRr6ibrlcXlicu3H9rpSyWpseDQOlItPitVqF0Mjnio8ebU7VnEuXVgGAobBsD7ghpZZSAqBtu4Mg3NrdF1YuX6ig4KYpHMd56aVX7tz9GTDIucUwV2w3NteWr144vTQ97+75oRMrYUvDzkc8Z3nCP9hwp0iVKt3GTmXezOVq/VC5DIVgidaY0Z3ms/Y+f97ft08LJ32Oz8tT/LzgpPfFgmBkGOzc+dWXX7lYruRMCxYWZi5fuVCplBzHMk3BGKROsGFwzjGJjEEviSNCRIIkiFrM8K++curr3/hSu93s9QYI5sL86fn5xf39QyJqNPdGfg9QGyZHTLtfac5xqr4gE+y0hzJBxy6QFr1u0Ov6lWrh7NlVIjo4aDl2YTTQNz5cP9gbeW7BseooZ1t7xTsfJrc/7PpDXFxY9lw+NTPtlqdDdAxveuHU5fmFc65Z/I8clxd4geeCkQ9xEFqW+f9n77+CJMuyxEDsnHvvU/5cy9ARqSIzK7Oyqrq6q+VMixE96MEsZgfkAliQ+ODaGvlBcr/4Q6MZP2DGP/zQjIYPiqWRH1gQXGDAGWAw0xjRurROrUMLD9dP33sPP567h0dkvJrOserp7uk6lub5/MXz+648Wjx9/GR1bdn3/a2tncXllXOry4HnjQbD4XBYqVTW19ellIPBgJAL0w7j+PCoG0SRIjrqddvdzu7ubi6XI6K9vV2lVLlcNgwjjuW161cuX7mwtLTwxS9+8e/9vb9Xq9bjWL54/RUhDABQSvle2Ov1PM9LIxru3b+/ub17/uKl85cuKaW2tjYePXpUrVbjRHW7Xa21wfiH771uMXX13Iqg6Pa+f9Ttmtp3XScyS5CrjTp7tHunVqsNu20uk3wuJxUhomUaUv4qCsGfwWfwNwZh2kZ/OFTKqNfXdnZ6V194OY7DDz56d/8JIgrOOYCQUhmGozUzzZzUgWaxYRm5QiEMWb+ffPxBbzT44Xf+wTUnZ5ii1O+3t3d73/iNzydq/sN3t7yRaZqu67pHR4empZtzbix7thMpOVI4mF9q5nK5995/f36h/uIr5+7eu/XOO6rVZERlbgQf3Xv9ygsrbqVSLjU+vBPSoF8ye/kS3N4+HIam36Hrqxde/Uf/HTBn5LnIXWKmXS17FPvRgGWUHfy06vJmwS8Npc/ICAb0fHVenxeyJI/nXZbMx59z+j8tQYjU2Q0ZAuYWa+//4Ls21425lY/uPXnplVcaeWvr1juD9oFZrM4tLVsOe3j/vaXzF51GJZZRKZczGTaK5Sigvc2Dbme0fH6utLZw5XK187j39tu7PlqP7t81sGsUHvv7cr89fOfDjwrF8sbGoZaymNe37394/eKcjoLBqC/cVqk67/l7cdDX5N1/+6PVb80ND+5SEF5f/8qPXv/J/oC/+NIct2pWybZdufUEb709/J//16MrL4z+6N9ulGLzYJ9a83PCf/jyYn2kDePcjUOKrPttS+w1S4fdg4+KsK5zbnfQr3M+yvI++gWTOD+tU4pZoVeYdY4+pXnIiE993jq+z4+vnjMn86dkS+YZ8f3Pi8+fW0LNbCjjdkY/M8KegfW6XVLQPmhvb+xbIp93qhzccmHOsqy0NGmaiIeI0kgG0zQBQEninLuua9v2aDR6/OjJd//0x4VCScrINE1vpO/d3qmW57lAxokxnSSBm7eVjqIoXFpaajab9XqzXK4AsSRWQpimaRmGVSgUAZOd3Y2nTx8PBoNWc/Hc2jqSs/m0Hfa7SSL3O6Pdg27sBULFjm2i6RDkNdqAQkOarowAgGWU1PgMPoO/ZQiDKPCGu3vbAKRUUnTzgrG7d28/ePBgbW3t/MULW5s73W53bW1todnkRJrU/HxLa93r9UqlUrFcYIKXihXf9znn7XY7DMNisdhoNAzDuHfvXq1eyLvWUefg/oO7zbmFS+tXNRl3bj8ejXwiqtVqq6vLS8uL1WqVc+55wfoL1yuNxlvvvnf73v3l5eWcbW0+fiCDQblcllIDgGUZnV7v/sMntXpzZWVp+fy8MFS3sy9UtFh1q1zbgbdgGlYhByyvlFUrOyYNpZfk8yX5Wa3tz+BXG57XxizmWgu2bW9tHuxs/1lqnY2jJJfLGYYxJbppgVKtNYwZWURExphhWLadU2oYRdHHH+zMzS0QRAAw7NGj+73LV2rFots9ihQnDma5ku90vDiOS6WyUvFe78g0cog8jpMoioeDqFDIr65cePjwoZK8XC4nSejYZhIZh/th98jXMc+VFwdMS8vm8WjQHrilZnPlKrASMdSMI0NArUFzjUC/PJLozwmy5+dnO29/V21vWfNpchb4o93t7UohH46GUaJNA/uBt7f5tFSfW1peHSZxGMYry4tSyg/f+glDZXLR74daKsbB90fIRKO1xDQ5jvP45oPt7e0byy9euHDhaN+79eiDfJ4bpl5ZWQgTtn7pBd8PNp4+3tjsKklJIg0tkyTy/VEcx4ictFpau1BvLf/ox29XC6XFldVatdhv7+w9fYDCODjsVJxSoZLvPAo+/ODO9euvKpSGY/hRvL35VMaqUZ0nb3S42bVzTgAW+Li5NWqeq1XsIAxCkTf6SWwbxt/yzP984ed1jn5+VZvOhue2DT+3LfkXa7yfFggZadO1Ay2PDrtag1aoFFXKwrRASa0VASFDns6XVhRFCSIKYWgFMcWcG9VqPZ/Pe0PdPjx0cmI4CFWSi3zn5kcPWguFQd/XlAAikWRcKwWdo4FlGaNhjMiklEEQSik7R33LMirVguMyJLtcrO/u7h21R5bZ6XfIYI25xbWFK6/5WBCcH23e3917veiszl/5KucGY6hRa6YAAAgAgbL0qz97FfFnhP+T4e/q/GSl7nNscbjTHXY7L1xZ971hu9uba9SqhcIuo4E3qreaBTJ6I9/v93USDg92XUcM+t0oiBuNlpTx9t6OncvPLa1G/W61Wt0gOjo6evLkyXJzbnFx8bd/+7fl4FCR/7Vf+5Ii17Ttjz562BvKvOtYlqO17vf7ntzZO9iWciAYc0xbKrIcZ3HlnGvZcaJc24o4HGw+rM5f7XefEPJyJfcE4cGDrf4wPGjv5hsrXOQO2r3HDx+5pQUF1t7RYbCnV69dZtS4++BI5J1WZXkYJjKEmDH7b3neP4OT8LMmhL9o8PPC589b3CILP4iD3U4SkmXmTJ7TCFKTECwYJUprpZRShMhTPbvWmkhrpRgTACwMIyJNoHK5nOsWDGZ3ewfFksVQO3ZBcGdvb7vesi3LiKKIcRh5vVQYf/Rwu16v55zSaOR3jvpSynzeSWLc3jpotzurF0q9TtLpdPf3jkxTjPIUh6aW/MZrX33pS98J7Uboxd3GkyBqFuvNYvMc0wOFLAEhQShiAECY6gE+00J/EnwmAX+6kDWfTKvtraed9p5Wq4ORFwcxyGIYjKSUTp67pRIkePBk6y+/+12KRnGv7aBkWsVxks/nE4IwHjXqrWKxabiOaZq+7/d6va2trbLj5u36xYsX+9uUzzk85+wcjB48fLq5uw9ktBaWEQRnhkYiSLggZJwlKITV7xyGYXDhwiVSOghjblpE2hB8eWVtONgRpgFSS9JHnWAwDCvV/OOttmPZI18cDdVIw9zygphblCSWl8rxyL75ztvmw82XP9+q2Wor8O1SCcPkb3nmf77wmQScwmcS8N8MhGXmB/3INMn3QqUUANq2PRoNCsxJn2CMEY212IhoCKG1llJqrRkDRPC9UMpDFTuFQlFJbVk2kqW1zOfz3c4oSSwism1ba20YhpJsZ/tAJ3654kahJs0FNzmzZJIkiWYMoiiJwkTG3LbyrVar4NZUFO8fjbyQoigQZuyFwdzK5V8rVBEixwwstSnJCqgQUSEBWyESkgKFn2L5gOeBX3aO8mcNv2jz8zNPxKHijSePOocHTx8+JGFXGk0tw72tTQ16eXW1VK66wvlivnz3w3dvvvcRBAMfeqZYDLyQNDrFnDC5YTleJEuciCiKonw+73ne7u6uLcosV/z617+OBvvBW+98//s/npu/ZtmlIIg143EsGWMAmkg5ji2liiJPSQp6B4Ojg0ZrRQjbZLS8cv7x7febrblEKyZyIz8USpmmCWTv73WuXLuw29+zDXdhoZgQFqs1MpnFcgZzDMF80j5Y7T4Fg7Ccjza9CGHpZzqZn8GnDr9o5/EXDZ5XAn7eojICpCHD0DGEbVhgkpSxYwmVMKVUKrCm2eTTa8YYY4IoUVJrJg2Dcy6UUr4nw3CYz+fDgEgjY5HSiZOzAj9AYIZhMxT5Qk5rkMjnW3kpqd/vKakFd4QQSmlNOuc6lXK1fbBB2gbNS6VqozEnuGMZVui37939CePdUn3ucMiSi59zLZMlO9gdFiujmEqoWqRNTbZCplAhUyKjXM5nG+4zmIVPbT9kNNPvHm09fVJwc4Kh6dg5x/K94aDXSZLID4N7D+5X5tYW5xeeCh70OxAHRg61lAYzqpVKBDFjrFKrERiPHz/+1udesW374sWLD3cf7OzsXLv8ai6X23yyXWpWR/3hYDAw7M7nXr3qB4N8uUQaOTeiMFJ6iEIxhkoRM414cPTk/u1Wa5kL087Zy+cvJsTsfMl13Zzjjvr7NpPlasWyCh99fOd3f//rsXqEiI1qYz6uOSgt6Zu2lWg16vQ39r1Sa842zN3d/rnLuYJldMJPZy5/ieAXTQL+ZcFvn5YE/Lzt/KJp4EQcaQAGwKSUyHSSRKaVb+TKR/1xQaHUCxoRhRCImEb0AwARESHn3DQNRNQ06PV6hnCSJDFMtGwWhr5lWfl8GUAnidIaRsPAEPn1S9dGw2h77+ZgMIqi2LaZaTLODIZCSlWvNwOPtQ98rdRo6HOmXcdFYO3dj+7FDxcWFg6jfBz7WuuCfnptiZbrC0ypBNyYKhHotFycZpRZ8fkz+Az+FmF7c2t/f+/SudWXXrwmmTnwwt29HSnjay9eV8LY2t3pBdhpd2/evOkPhzlTLLSaSRJVq9Xr127cfPgxev7i8lK5VI1yOcbYw4cPDaO0traGsVxfX9/pPH3jw/cuvbBeLlcvrV/Z2PWG3iiMvIP2PmMV0zQxAgJtmaZWkB5hFY4e37915foXYgg458LMMdOWil5+5VWVBLc/aEsdFwoFw7Dv3rn/bfXlBD1OCBTHXtc7lGVzcaE+HwRiZOaieH/5wotGZG1vvL56qVAsNobBz3u6P4PP4OcK2bbhs58XuQpozYJ4GFHEwbDzpaEv4zhhKCYtcQYABCoBlWhAxRjjnCMIkBj7WkVSCGFxG22WJJEpwDIsgxnCNpIkWb9kRUmwf7BrOCMhVffooDssC1aI5FGshnbOCcOR1Mbc3JyS1OtEuYpZqFm+HK4srh/uJVubO5Z1iCzm5rDd90NJL934/FJj9Ojxvcdbj7pHbhAEw/jQqFql5YuYK3ENAoGpGODs+r5Z8YifGueY0b56zuZ/1vHK2dnin8+Gx4EDAIKG1PuN9PgribS2tsbxm9KvGeGyP3PQGUmKs5c9o240nb2vLOHEidacQhXlcrlRr1stFgzkb//Zf1pbvtA8txwWat6wP788v/H0Ya2xdP23/mfz8/P3794Lhv1mnpbq1r6ZICjHrXYTrnP1jl3phtwx8wbJXufJYv4IiNWWWlViF9ZfC8Hh1db3//NPLtXnNz23uTC/shiAehL6u8PO4eXKslMxwyTnx/1yNXd4oCkG01CVCkagCkXro1tvJcxtNZebleL5iy+/9/7G3/8nfOH67/zRj54sF3ZaFbb55HBuYf7jt979nVeWX39K7fy5/PpisPV2k6tgsBGXF7e3BqOtI7kaG+tL3Q6LNnbOL+a7dDgwKgaQQUqQ4oASSCEqBqbK2s9nr4vMclrJkITkpyQhZQHP2LcZWAb4c5Zm1Bl+o0xnxM1n+rg8b13hrLj8542vzXzB2c8/r4SUGWb8vM5QZ8dPZ80zyYz4/qz5Mayz7+uz94NIksS2bcdxoyiKomSayyZbVE+jk2j2MSKKI6U1CWEaBueCaZ1IJTUlUTzK5a2vfu211XMX7tx99OfffePBo4/zuTpnFmmfCMvlMmMsCPxU1x0mg2ZxwS00kSKNo3LVkDKO4pGDLjcNkMnDex90j54wrudbuUajvNd+iqLRrPdLxkCiO1JMadQc2adUWPsz+OsBNRAA0BiZjr/+aoHWwAVKpQTjWiWmMEwhnjx6MvBG61cuF9z8nTt3Wo1aoVDo9Xqtat113eXl+sP7D958801X6KCzyxhzHXc4GgXadAsIpBDRyRfCINi8+eHvXHc2nz5OkiSXKwyHnqci4VYbjZohBvNLC4dH3eFweOn8BbPYYMsLZUuHQeS6BSsKDcPI541Rtx8GMSICQb1W+9o3v9nux8DMaj5fqVXvbG88fvz04kt/f25ubrh7z11arFaNfr97/170hVdeNja3o8gv2o5RKMdo+AkOeiOKgzyXefAx8Su11v29x/kl2zaEjwo1MAIgJKC/o64zn8HfNXhum+5zQqaTJudcCCGEMAyDMTapGzohs8/AtFvpk1NgaDA0GROp6wcy5eZFa74cRcHO7vb+/n6n2zZNsbQ07+QYYRD4ulioCW4FQej7I8PEai1PEFWrVcYhX7DDaAQgq9WSYQjHcXRkdQ66o8ERwpCxHmMdNxc16lYoe56/Mzj8uLv1ur/3LngbnDygKCsg+pcFPpVV/9sA1EiQyreMpl81oEbQAJqRxpmvP7du/oxBkUKOmqQwGCjtWIYh4OYHH1iO/YUvfpExdrR/oBK5vb2dJMnS6ko+n//ud3+4v7//6quvWpa1s7OjlPJ9H5FrmZgM+t2jIIjm5xaWlhZMjrVKoZDPzc/Pd3u9jz7+2BsOQSskmcShksloNLp9604cS865Y5n1SjFKYqlVHMuVtbXf/y//4W/+9m8VyqWNp1s6kXknd/nC+WqlaDAkgObCUkS4u3PouoZh8F5vZBrOyuqSEOLevYegSWg16uwYQpdac4lZFIWGZPZoNDAhFn7biPrzi2v7vhhGytaeQC1AAep0EwAgILFfQY7slwR+6fHPc8LzjjeLDma3o8/8hwRn/hOGYSRJEgSRUkpr4JyndFZliN6CT2KCJ+mx0vturhzHoYZIaw2UmBbWG+XWXD0M+oftwccfPrx7b6tYqhYK9dEI2od9nTh514kBuEDOwXWdRrOKTEZD7jaa5UL+/Td/1G3TyzcuRp7e299aqDU4JtWGWF6pVGo2YDIaDba3HswtLxwd9A937rR3Dgr1y60LX8wXi0FmHrhfGvhlOQNIYy3QmNASsJTKEgBA6gl3bJHHn9u4fvZlB6UpOESac66SxLSs2Ese3r2zfvFivV7/7n/+0+XFpQura2+/9RO3kK/Uqu+8847W+saNG7Zgdz98WynVrNX6BzvcEA7CfL0UJFIjVJutVqu1s7Ojo8C1Lcuydnf3t/a7ijmFautgZ3PpcmNnZ8t1CoNeLwoiDtg+2L+ycH5hYalcqt7f2j7qdvN7e73ewHJytuAyTkCpXucgHA5Js/5wML+yWplf2trcb7e7piUQzKP2sNVy643K/vbR5ub2XLmwd9QxIM6XK12vPzdXt704QsNwcl7n0CpVjPKiXagNO+1WK9enAjBGmhMCACPUAIBI2ev+nOXeMp//2aqgs4sKZD3/Kb33lwQP/F2F51XFsww0wzP2gwjDUEqZVg9lTKRPIbIs3X2an3LKCKTO0koprSUXyNEATABRGIxzZIyN+pxR2TCx2+17o5FqFHwvCYKo4JT6/b4w8Nz5ZcZoOOqGYVipVBiwbntYLrrnz60cOkHnaGd7ewuZ4kZycX2p3nS84CCKcGlpAUE8fbpZX7qsIe72d/1BvxY71eUbnHNG/Hk37s96o/9dPUcIlDq9AWogzQBS5SOAppT0IgACA9AASAAZ1XJ+5v187gV4PoKhEDQAY4yRBgRUem9r0+sPvvyP/2BrZ7vX6/3ut3+r1Wr8yR/94SgYbe/vzV9eabVaCPjw4UOllG3bRNRsNmOpLMNcbDX2j7qGYYyCcOPxk92NR/Nffa1cKOTz+aWVNSNfz+fzjmmsLS1cv7Z262l3bn7l85/7wtX1y/l60xbR6srCQbvjRxEzBGfG9u7e9tPNyAsE6LJr24a5u7lpinwuX9w96q2eu3D+6os3P3zn1/qdtbWV9p3q5uYOAFiO2Wou3L/3+Au/9tvtnm9BCMzZaXerSyuYROAUC1YhikbUH/RHqlwodrYf3Vhc3tCJIkMiU8Q1ISFD1L9oiaA/gyn8qhH4zPFm3OcZNQUy289Q8mUJAML3fcYY5wZjTGuI45gxJoSR1dGp0TcFxhgiMsb8sG/bpmUayIw0G9VgMIqiqNfWfhgXi3nHrsZJMuj7iNhs1oe9KJEhF+ZwOJQy8oNRkiSWZXGmtncOhTG8fPn8q5+r3bu7AdzkHMNgl1kL3HIGh3Gn50uZT2KjkD9/605/0A3DoW2JPHPqwPMAJsPPEvL8LcGM1xUwAExTlYIGGssALCXF2dUf/m4AclBKCcGUliYXSRzev32rnHdLlcrbb761ODdfyLmbj594nhdEAXJ248aNjz76aNDrVwpus9ncfoBxHOddi5lW6Huj7sHu5t5gMNjZ3Y+G3dgf2oLt7Wz0ej0vCKWUcRwf7G3pyA+8AUPo97vVUjUIIv/goOTmSkVnd9TVRF4QdvsDb5Ts7e03yryQL5VsI2caXrfrVM3+oBtGcbnROv/Ctbe++5+73Xa5XHLsovKGmmS3N7TAunf/0a99A68sNzojPwx4JKNoNDDjAGK/NHcu8T3bdtTIc0x3f2+DvJyZUxJQE5PANTAgjQD8+SXg53aWzPIp/KWRgH/GzqGfwSdClqSbdT/LqZNlEuCz3ysKhUKSJFrDVBM+iTs6m/KnrlIAkFJfzrlhGIZhKBoJw0AmpZQEyrJMJWEQhkQ8jsPhkGw3xzjEiSdMbloCMHJyIpez2+3DIAhyudxIx72uH3h+c95qH/ac3Na5NXNuvtRo3tjYfKRYXC4LK2cQ2p2ON+z3HKdw48VXhu0wVruGKxZXzi2uvpCrrkrKEVqZVUoy4BdNAv4lOngp08dAH1Pf9D4BISABw7H4Sz8/FfTzQxYDevbTnKOUsWGbSRAajjHsebdv3lqan7t153YYR/V6/f7de08eP6yWK+ea58u16vvvvx/H8fXr11ElP/7LP9VaN+Ya3b2thZVzh7vbG48e7OwdWXbFsCwpk5WFBdtkf/Xn3xvFQioVRonh+x+89x4D+FC0dwaMYeHg6ZNhfzB3bqV/2L5XB7fZKpUqtpUzbRshT0SDkW8JYRVyWirHNJLA/+j2o/L8mrCdudXzlum+++67jWatXpuLwcvl7MGoG3hxLLtbTx5evnzZv/+k7+tqMR/12w6FedXLO+ueLlgcFmvl/kEPuTmKEtNVACwBBGCEDFAzen6X11+9lIo/L/hkQetXB7II7ac2D1ne7K1Wy3EcKWUURQCQumJNs3A8C1JKpdS0QkNKgE3TzBds2xFKJyNvEAQBY9xx8o6TD8KBaWHONfIFy8kxYUomIs9vlyt5LqhQcFutVq1WF8II/Fhw65Ub33Ltxe5RImNx5/bj/9v/9f/9ox+97tiFuVX33OWF5mIr0TyMTTu30GxdXT33yle+8nuXLn91ae1zl67/+oUXvlKqLSuwZPLZafzbAkxxqz79NfUxgMm/469/N4ExJklzzpVKBONJHO/tbDVr9cPO0fnz5w0uHj18eHR0ND8/f+nSpQcPH+7u7q6srLRarV6vl2qh0oRxkrTv+4E/yju5K1euLC8vm6ZZLLilUuFHP/pREAQvvvji1atXOWcP7t1jQDnHGvT6cRwHfrS0tPTtb387DP3NJ4/PXTjvFgu9Xs+27W/9xm9++3d+Z3FxcTT0oiiKwrBRr3KOj588JIYojFy+6Di5N978yXA4XF1dA2BRFJmmaZp2omlna3uuVjKZjkOvWnT97mHSP1rIoyMgCKJ+t1ct5H3fr7SWMFdB0kg/T2+7z+Az+BtAFr37ZGfks4DO/JcFYvPhPhFxsohIKwAgBgwnCbBmO5dqmwnY9DrFGkEQhGGYr0LoSSI0zKKUsn3kFQpYLpctN5RSEpphoIbDiAgrlUqlWtg56LsV/rVvLyPT7YPwnTee2m6ToZVvcirw85duXL924+69m7/2O5+fb61tb3jhx1V/azdfO6jWuNILFy5+NUwYlhagsP5C63razz4AKIVMWeYnTXTGX86O6MvkEDPrQZ59PzNq79NKxPTzcm7iqdsB+ykxrsiIw/u06hB/WhxrVrwvz5hnHWmLMOz3C64FFLz5k7+oFYSFvmO7N+/cnJtfzFXdo/07/lFgnV+6cP4a5kp5WxSEGu48Gh1uLcw3QhUEppF0N85fvqD8COL485//9R2fLVUXWmpntz8aitYf/dWtr4fmiy9fBost7p53LTtRhd/8g99dPnf+9g/+/dra6nff/fDdDe/6+pWjhw/ub+8sNOajp0+9iwevffk3Rgf7QMZw+LgTr/pOK/D9r37lmwWXHz58Z/ni5cJCOXz44eZP/sRaX9872HQgny+UDpCjWP7B6+9+85uvyKgd9JJhx4PE2+hvC7t+jj9hLPejd2+9ffPeUj0fHW2HHecf/NruVvkbH/RLWgWOkYwkM6wS97WysyJmz4bs3ZAVH5xVh/i5XpsJmc44GarI523HfE6VdbYqPmvAGfWDM+v7Pld3MselMhAiZkxb1rgwI7MhGQYAIGgkTURskndAMwdIMdCglUDNgDgSA6jwBE4aUtMLJRUBIwKlQRHXOhVZmRTmbMem3ctBf3p/1o+aJrLf7EAQsc/O3tHiFFX/ZJ/sMycovROHyDkXXBBDhqbW2vPC4XBHa8kY48wkTZyZQgjSrNsZuAWoNfLVWjkIRloPDFMhKZn4b/3kdasQrK01DW5fWb+2tDy/s3U0GHgf3Xkyt+Ss51ZBOI2Fc9XG0mHHe/R0b/76+if09jP4DP52wDRFtz8qlFzBcNjvHu4fzM3NCSEePrjfas43q6WjJ1IIAQCMsReuXv7+6+9+5A2PNsp7u9ux7/VZwjkVSg5KACaSZFQqVQ7b+9ppri4vWUd90nD9+nU7d/j+++93+4df+c3f+epXnY2PbzIKBNOMoHM0CKLHUX5+fmHBytt+TPXm/JMHT1UOHjy4v701VIl/dLCth7ul5aFWSc6xfMcJwqDb7ZaGg5X52qO329CqWvlKc+XCqL8zN5/3MXm6uSfqeOfBBqHZH3RJiO7h0f72Ri7XsysNt7mysjTHDLNVLxvNst9v//Djp40bR/PF5pFvJgCGMAQowzDUZzLxrySwTO/052snW1WeFsHTlNpf0wvSCDGSZkAMSYDiiIIBQzJQw6Q2URqnTkSAEBEjIg3IAAGJME2krpHGmZhTTm5q2scTDAdO2R4NYzp9gu+gsa/M7EDSCzGN+v1pRpv1J0QEshgapCFN5cG5AcCSOEwSbRhcSURgnFmWaWtFg/6wWTUWFxc5M4ZD33UL9UblYL8by8QynIVGuVpsHO0NFeowUffvbR22AyXqg4hxZ7VZXlxceK1Sv1rpeqNwmNXPTwuyveae6/YnvOB5f5DRzC+9DewXq//PK0kTAudMcORE3cODp48fnVuY293f8UaDarXaO9ja3X7SPtg/JNrrjJzX33arzad3eh9pqfwBqMhElsg48ZQiUCqSSldq5d3treJqoVxcYL5IEiWEsCx+dHQYJd5LX/r64uJimVOtLPeC3v279/Z2jwwrFAsl03UlqubKuS9/vXz749vc8Pq9zv39zcstx6Sg2JgHTTsbT+xCbXFxPoqCURw+unu/ljOYCqRWyrCt+tLjpw9fyLmGd1iqVoo1a3t/sLq6ykQPTCtXqefiQETDXM6ulPL5WsOPZbFYKuWXb3343oeH+FrncKG05HP7UFoFyzCSmJD98u/Ps+Hv6rh+1vC8tudMNwKdKhc1EjCgSeSj5jLiQAhaMDQYGQw5gmBoYvqWcatElGIenVJbQgmgNADTWgMjVJSM3z9LhhEZ8dneTi/0mC6fHkX6y6l4O5WnBczI4z/NZpp9ZjYe2RtJ2wbbMS3LGKfmYMxxckaqIkAOwLRWcSwRkQiTILZ47unDg6dPdy6vv9Coqsf3t2SiLSyGAb3z9i2prGqtlq9YTm7hpRcXA1xqd56Kwnq+ulpqrUcql6sWLWrEn5bq5jP4DGbgefdJEAWlckHHETB4+vDBwd6uoWU0GrUWmv32fhz5Og7snGtZli/pyc2PFpbP2YIzlUiv7w+7BgQ513Tt3KOdTjGftzlzXbcbhznbODzcXhQ6CvXh4aEfeK1Ws9Fqcm4miVpbW12co3CHfXhrc3f7oFRr1OY5cuj0jnL5SrlmcMPxvANuhaHXC7xgrlnyvdi1LUaRbUC1Wg6TnBmESmtIhi9euRiBNgtlU4pA5BRyrWKJSgszoVyttXb1Wu7R9pFba7JinXUeNuebhsNylgkBS0glwuopbi59btQf8MGewedj7SASgoq1hucM5/gM/mbwvN7mP3Pn0yyT3PM5swPos1XoHAAgrdankTQHTLXbTCkA4EwbGkzGDAKTMcZgLAE/Q+YVgWKaUvKNgAoVArGJYYzG1Hc8XQQc2KweGydtIkc4izCnJhIExInSenw/vTpFfYnok6ttzA4gbc40TSnjMExMCxMZhUFsWblyqUrk+L6fOm2FYai1tixLCOENoqcPO0E42t/fzlstIs7IBol2oRIEo/324cra9fmllwoVJ1es5KwmK65vbj2qNkrCcANl9fqemy8isszI508JPpOA/7bgF6v/zysBay0Ng4eBTOLkw3fecwyzXC5W6mXkRhgMOvs7pGSuUHZL1appNhdXHTcXDgbbjx9xGRZyjmMZQjDUuliqAZFtctM0m+X64mJr5+HbV9bddvvQts1ms1rLixdvvHL1yot373y80dsa9pP80pe4cdjp9hTylsFK5Wre9Xd39999927qqxFFQaVSYtyv1+tbW33bslQ48D2nPyr7kUzi2BsOONOvvXrjL19/t96cKy4UDjfuH42CIIz7gyMO0dHK2sF+t1quvH/n/kJzebF57t4P7/thJNTAzoNrOIMwOjzqJCCW1j/v3fneqHtUmms6WiZxwgmBfSYB/4pClu9LFmHOosCzPkmzIJAQkWmd0mCOAKkoTBpAGxo4A0bECTkB1wioAACfWTjONCPSDBkwpkkBCoaKAPX4vadswEiAmNJNIKDxBZHJUskYIKXNx+PRiAgzZHjc/0nqK5oGNn2yKJw6hs1+TT9tS4y8oYYkXywYpjMYqDAI/PCo4DaJVFpPSco4jZU0DCP22aP7O4haEW1vbbi5UrlQZ4XCMOBa6sbc4rd+6x9duf6SJ0duvpQkuZDl18s1znmUEKCRc03TscPQf96Mz58dmM/gp4Hn3SeGbQVBYAm+vfF4e2Pjwvm1l166VijmB55k5aLXOyyVSmuXr3O7PPK9aqVULuTfffONt37yk6prrS4tOhYLwmEQx9de/PLjhw/yjlEsFu25eqXi7kTDcql+850dx3FWzi/Eg16ruQjEtzZ3aLS55bCrc9xy8/VGxfOG925/dG6p0lxZOdjduv3xR5bghYK74/ul0rxpaj/2ubC9QX/j4V1WaO92h8NQ5m0n7vdKplVwmT/oJJF/5eWvHGw9+Pgv/y2GXilvSCk7Pe/hw6cv3bicM4WRy9XPXbn1Q6c/CKolYQEVXDtJvKd7u6aw8oVK16x0fdmAuGFgV1LMHcOylMpwvvsMfq7ws8aHWYxslm04i+/VGX/goBGQkUYEBsiAEIkRaEBkDEgjAWpCAA0KCNVEETNJOTWVRKVGxog0EiITjBSRAUwehw+lZHFMHLk8Jpcz3UE0aFYynl4DnaRUkx+NCfBs/udJo3+NymJKp1MJWOkQWFAsW9durF64sDoY+B+8f+v+vSe2VQCUjIMQggubc84Yi+OYCDkzDEsWy5XF5YpMMInF2tJ1aTQeb9w+v35t7dIXNCsFCcS+GcUiIq9SqXheIEwrUcowGamAo4Jf/qyTnwr88jMWn07/f17xi9xgKgyFMN95/c3l+bkr6+cty/J9n1kVf9QPgmDl/KUbX/iaVarfu3fP6xz4sao0ms25eRtUInUsI9My8vni4vLKw4eP88Xy3OJCT6m97S1DoGWA5wW93mDp3GrZrgPAwUG71+vVbFZtXSKzAKZ5+drFva3Nre5+z4p10EBmtiqFW0/vm8y37LIwDJ7L77X3Otu+kuECn6s1mlLGg4G/UG+W67X23iPPPyo6xq2P3v3ct/7BhfWrP/jjxEGcr7pJ4shIhiPfEXj96vmnvh9KvXb5JUmxa+ds0Cz0MQj6+wel5qIBKjd3oXO4kWtv11stH1yPOAKxX/L9mWmb/AWrR/u8KuifOWRVGcoUgc8GniFpCSIgQgQGxAEYEAIhQ+ICSSMiAWmtEyIiYFpPbbFjxfVkVjhohhqQATDkRJpxZACA+vihWSGYs6mYekIyZkxPaWiq902vEzi2Gc/SZpGGEsEM9f0bACIuLDbanZCLxM3zy1fXHNt1XYcx2N4IGCfOuWkKy7JyuVwcx4eHhwBsYbGZqH5zXnz+tctbm4fdo8O1c0tf+MY//df/3/9XtbkYS3PYj818lZmW5g6Sx7gYjsJGo6CUlyRS6aRQKITR39nQ0s/glwiIyLIsVOq9d9/+9je/XqkUPrz1Qbff+Z0/+G8e9ds5t9BszXPL4XY+UfDOBx9fvrBmu/lypRYMeokCy7aEycMoAeRBELiuOzc39+Tmw6ODo8WCkklUyBeHG9u9XsfIFxgTbqFcq9VsLZ1CU5KIE1WqFEv582tWteY6JdsuV4pf/dIXP37z9QjD9evrIEp1JwyhH/f7KpEM6YUr69Vz15/u9Fvlshz0ej1b9dXqysKHd27GSTi3tGQXyxbYcy1rODAO9w9MFe7t1Fvn1j7eO3D88NzFaxv3PtQKguFg1Ot6vvZ6nbn5VRNVdW718da2vbtxqVnM2eXuCIVSFv/lJsCfwd8MsmgKZeiasxiIzDAwJRkgInFAhpReIJJmjAiJkHSiAJC0ItI4dl6eeEJNL5AzjcQAgKdJDHgqpDKcofwnCfCJO8cEmHTq20UEGoFoSnRT0y1orQmIgDRpABAJRnESE5FpmoIxpRTn3LKs0SA6NXfpV41MaSWlLJUKcRIGkVcrVpIk8aOdS+uryPTGxsbb737v8uX1KOl0e20/iN1c8YWrNx4/2tKSFdxmX3Y5GxZWtm98eb1Yqg+Hw1DGrYVFDc7T/deXttSLV6k3OOKwX6uuHQ0jQ1hB0nHNXBIE9UqeZGAgAnJgXAYJQgKpkxdyjWn9M0ZEnBtnrpeBQKRIaQLNSDNEROLIAs1np3J6kWSpRPA409aJkC+wYIbTOd5AGRxfmqSbkAExQtCAREAIBoVntq8y69pmaCyycnpn2VqyvBMzfGiy4n+fm5l7zjrEmc08J2f9/Lbeswesgtgtlf78j/+kWml+7gtfeevdd0gU7bKjjh689ePvz8+tLa28yBL+0etvHvbbX/vWbwTbd95+/cdR1J9brD55cLdhll3hlpxCe3sDI39x5dxPbm7kyo3LRmz2H+QMXLjwwu9U1u8+uPnGow/mL/M1ay2IC0wER6NRYxAVRMunfhJvtZpGe/tRsvBCmOSVacx9/ls3/+rfX9Vol+sf3b69YM8Z58LRUW80GjhmYaGxeth7uNXebVTs5vVvPnrnu9Xzon/vzz9++7tf+sbvXbrx5R/8+3/zhUuXK3OFjjjyBpvvvzH8r65eqjr0+Ob3Vm+8VMszIXRl7vzD3QHlhLl90MgFYvOvrMUvraxfffCTh9e5mUtGrorK+VKQZGSmo59P2dDn9cJlz5lJVekEnkHQiKiTjHq0eHbuAmRn2z4zwmI/QQImAGQpUSFglGI+JtmJ/kyFM/PkwZ42G6oIERlj47QQE0Cwx5GzoEFrQH2m7DttJ/XJm872Mb6d/OoUCpWUPDuZACAYV6TSbGuCyEBuMGSIFvOefTlk5HYmIqWstGQIYyg4IWpEhYh8Unc5tdMedzjD90jGxvRls1J7HMXpTYYTZQRnkMYBT8MT05nVWsdxDDPm3tlNyTlP96Lv+4mM0jqGxWKx29sGOhQGKOoftrd+9MO3XKdxbm09Z3dGQ7/XPyhV7ChMHjz6iHNyXFEtzwPZ7YPh9va2P4L5OTsM5OPHG41WsV6/kHM4JZ5Bkc2khdLJW0qevXFJCK2IiBRJ0AipqgsBKcNrjiQAMIYciTHGGQjkiIjj6k+n1QBZVSxOJtA4tppLUDAbZzZ94sxWAAQiEBIojWOlPqWqj5Nx3NNrI+uAZSUEyPA+JXq+uMznpGu/cmCZRpIkb7/95gsvXK3X6wcHe1EYfvs7v/PhD/9seXl5fmHl0aMHfT9uLS188QuvocH+3Xf/cGdnZ2V5cXGu0WvvB76fM02nWk3CQc4xkGBtZaVUqzy9/56hItsQxI5u3fv41q1bWGalQaez/ygKDguFaG/rabFxqV5xt/bj0B8aorG82Mg5Ym/vSRDVHAuKLlPhYGfzweHe08ZcXoBRK1Qb9ebwqH334/ejGG3gwZFHVT4/t4J9KllWd3snz8ARdqXa6veHbtHMFctz9VrOoO3t3RxXLkbt/sgolNuDQaFliFzxqN3VhrPbGaFdGh0dWUaxVioe7G5ac+dr5XyvNxJWRqHyXyUgokxJ7rlzWT/vgUyDbY5fT0QEavp9ogGl1Ms21iex0MQB2Bbp/ZTTTUuhESCQTMuRAAdCpgGAizP6P0Nx1aRTJ/4kgaXXOPlMv5pCTCfkhD9UkqTUF0kDMKI0nwZmVcDMZLjx+IGpCzMApHLqs0pizJBIshL4CDx73QUACCGmtHZKgBHNWepLk4ijMAyF4KZpKpUUCoU0jWWSJJaZ90YhMlksm5ZdGgwGOgmqJea6ju/7O7ubhUKpVCpoNF3XDsJh9zDuHUrTsnTsxL4o5prOaj0J+Y9//OMvfsmuVRyDR60SL7uW1KQoifnZtl7JUHOKJSlFCjQBZwwAETImwtQRR8YFmlwIjpyjQATUItazs3w813i2JK3ZiTiw6XmI9HhjEU2ivAEAILUBnNEflIBAwIg0IShAIKSUiZjCzJ7hz7mxdIaNnDI4OMzyW/y0vL4z4ZfDBpyFEE0uHt672+12f/3Xv/bo6aP9/f1r11546dr1H/7x//Dg3uNOd/TVX/+ty1fPOYWC0vLx3SfVci2JEktYkR9Zhk1xpBIVeCGRt37+HGdwuL99cLiz9+j2Fy5XSetq03LLUJ8rlhq1smPJ4GhpLv/yi+v3Nwe2oW1DGyJGHYWj7uVz81949fK//O//6ADD0eCQpEfaUwS+P9g7HCy35h1DNSrlJOzr3mG1taYT3d3fnbu64iW9KD46t7B65913+7995No54O5Be7OKliaDVSpWztzfP1g5txJ7T+I4qZfrHz7eqCzEuXxeH3WXVs4JnWwedNlwu1GMXdsYHu1X6y2T5eM4/lUjwKcMh1OPmUzno6yMVFnb+XklYGJwQh+W1lA5KWhOCB4iqJn3ztK8Ah8TyFkOHhElhYCaI0MkwYABIgMOiFzADOmavZg2m5pLNWkiSvQY356S/VBNCTBM/aEgpfcADIghsPF9DYCZjE5WCq4TsUPj/2GicXxWECV9dvuZGpQME8yx7JskCUyIsVJq6ic90y1KJU0AMgwDEYvFYj6f393d9jyvUDJK5ZyiUaIGOZGr1oqBr7d2Hpbyi3E01ts1m/Vz5xcqVRdQ/cV33354bzNJEkRsVJxSvqEUmXwbSAx7Q0aHRXdXtVZqxToXVpIkg/hYWXE8mYieVBq0yUmj1oQaNWMAyLOM/zmDGCOTc85JcM2RAAAJOD/h1Xa8XdjZkvRYIMfTkz6aLPApITjLBOZg2hDTgApIEwIiTYz2pxonojHn+Axkki99NgFWGT9gWTabTytn5s8Yfl5enajkrZs35+aalmO//dbdarUy32ptPn7UPer0B12nVF0+v9JaWLl5+06SJDnTWJpfKOZcrmFrYzMJwpztCGTdg7bvd9zL7s1bt3qjUDBlU+/ydz6XSHn3zj3TNpaXVw0zp3151L1vmzjquVHoyf6+zhUFSxr1si24TkIlvW4Q67KDluknUaRUdWFuLpBRd/PJ9r5jqELFtRoN14Yg8gZHI05YWSx2t8XhMHjl1Vf/zR/9+Z1bH1Ua9Vy9frTzcb251h0GR53BQrM0GnRefOH8xbp983Brrnje5JD4fQtJD9qNVsOx3YBXhFHSw0DLpD84qnptUkarvjCKsxDfL9a++nT3z2xr6c7JIqhZpqKs/BNZKvGs8zumoEAMYFIjFACAVDR9YBa41rMq3+m1C6kqdkwvJ39DiREicgTGwOCcIzIOHDC1UdFZgJOUxlprjVqS1KSneOkU/kyeQXtplyyByIgBYwDs2BIMItPEkJUDc/aZY20oKf3MfQCAzGYyBJss/D/GzlrrtAADADDGhBBaHjNuNMlSCQBOzkn5lSiKgiAQQkgpiWgwPPjCl746t1DYO3g8Gg2UImRBHHm93mBra6dULAMNdnb23LwhVeXVz7+8srq3t3sQhrFhWO3D/v17T/L5POeGTszdrUMdO3PV0bC37xqGmctHoW8xY9qHWaO31AqI5ThqwQiYHjNGKkNwhYIhGCJjIBghEZFCUgTEJwr7E/oNwCxCFZI8JtV4TLCnHB+c5F2iDEST45IINUhFSIQ6ldwRaMLxzfKMAGA8Z87qOMvGZp4tkWciggzJOMsW9fzwyy0BS8/bevx4aXnh9r3byPHShXPbmxt7W09Nxr7xa1/jbvnRk0e73T7n/Ny51XKp8K//4k9ISstkoTdIYr+UKyGo/qCTd4Tned04KJXrjiGtJCi4uQ9vvn/71k6rNR8E/qO7jyFJ4qibLzo3KfnxrYeLl14kov2HHy00KtdvXOv3+5tbTxJRKNYW6y35yCoQWpeuvHT+xS8PNu798Lv/cRj7R6PRvGmajn3r4b2tRzvXL68LB4yiezD0f/0LL6P4i+/++X9cXb+er7lHj2PXdQnNnd3Dw85wf+vw1z9/5YWL83c3nqqBs9Yquxix8CiXdFxwm6XyvX6YtwBMEXJz5HuWDiosGuhgBL+iEvAU0p2p1NmYO6vubFb8K8vQbGX5mgjS6V8ZaeSERKnsMX0rIjCGaYE7xpitPDiJDMc22ig5QYDHnkxocY2IDIlzzlEJBowxhlOHpBP/YOL6lMqphKRAKa40akmnBY8J3jsx3ulfbcYQGbKx71Vadw0RjAwJOMkMh0M8zS2dlnpPrGlmnoyz5z+rPyLVOU9dS9IMVoyNTfCzipT0mnPOWColJ57nRVGklDJNU9jCyfFKzTadVhzX+r0R54dSJuFQtObzOcfZ3z88bEtg1f398MmT4qWLrVoll8QQ+NQ56t/++Haj0RBCXFi9USyU19YuXDh3sVQoai2DwAvDyLA0nGTT0q8uI0SNwImlllQEYkSUobGGnMkZAOK0aLxCImDaYNNhHjupA4DKkKRBnLYNpNf8LM0BANh49sIbTAExBaQ1aEIFRBo0ULqQx3v3r8tWllV/NMsWnmQlN88yMWeo0H/R4HklmE+LYO9v7zx5/PBLX34tjqMoCW3hdg8PvOGoXCqsX7pw6Mc37965cPnqb37rtwTQO6+/+eD+rSQajvrtJB6BjE2jFIchyWBh4fLFG6/GZoUJ4bW3uK+lxtff+cD3Ws65OoNgsDcA6RVzycLiopUrFIvNpbVLOVu8sLaQ47xcr+1tfdDrj5bm147IwESXTKcgrLlqszy/tofUe+n64daDIIgMbi3MLR8eJf3cYdk1vMP+0lzjrlMsFesvXbv+zoe3bc7PLyyM7Hz/qOM4Tr2UN0zzcNS+/+DJ56+fbxbMp/duk7CBdLXoOhDYFMtwNOj1aDCqlZrKyA2ChKJhraZGoy5a8xkz9/ORgDM1Gc/pnJUFU+Xq6Z9n4JMsyel5i7tk1aO1gVKpl3PNkRgjhgSgc8bUlEaMEWPEOTFGVnzaOSu9GBIQpYFlMEnXRAAkBKYSMKLmjHEgxhROfYBnSC/NJGUcYzkgzkADEmP6GAFNPZAAAMDEZyeTiDgAoiZERJ3SBBqLKM9HIBnysVr+pIp7VpU9y4hQFp7JsPVykcEYpRoAIhJCEFGayZkxRhNO5JRqYnonn8/7wcjzPNs2pZRFu7KzfdDpbQAmrlvs97x+3y+VnVwxOH+pTJrHCqtVM19Epfybt99ebNUGgyiJBCmnVMw3GwvFYtHzvH/8B/+N67qGZaLgXJiKQCt0ig7KEJ8BALBZqhIhAKkICBgyTcDEJ2xoSs2sxAGRIxeIyE8eMJqsBMiMA+AYADChjTMwtdE+s13O9vJFDkSSNCoOSmsNmJ5QwY894GbjyWSGt2QWGBnvJX22iiDJ8nbOQkxZJqefUzzu88KnpXJ8+603CjnXdXPdbrc/Glbz+YKbP9rddVzyfX9xcZXcolt0B6P+47v3/+j/94dahwyS7a1HSNLgZHBNQi/M1UzLac4vY2mpO+hbEJe5Va43jFzp0ceHaNLKYv3qlSUe8CgI51fd/aPo9//hP2tduugNe6q39+YPf7zb8YNB3/nKC1Vk79/8qP3oaQNBDHr3X3/Dqm0ePLrNlWdKGh32du9s14v7rmTL5bLqtr2Ht2vzcw27MNgbrFbm3mp/f+fDt3PBJcN2Hj+6d35p2WBGEmvbce8+3tg5HDiO8/DpzQQtbzQommgaXBs54akH9+9FnWG9cY7nSyrUj+7dWUe2tPJq2/9UpvmXDHDiJwyTE5FZnCCDcPIMhP4Jbzzzvq0lIjKmOSPBSDBiHBDJFagnQIpYSppn3G9npQsiQiTGjgkBTGQDIUQqeyAQI42MQAMBIE6oGk5tq9Me0hTTIkudd479XU4pETU7NhHO/klGAIw4MZzY0TUoor8mk2PGfRzT3RlCO8V7s+QPIFOnnGWqy4xjTqv/AkCakSNJEqWUEILNSDzpu1N9fS6XS5I4DMNczgaANLVkHMdAlmMXK5VSIn1vFO9sdRIZzs3NCWtkCMcQ7uWrK65b2NzcRDRM0yQ1KpScyDc67SCOgHGwbVsp5RjlcqmaqMQLA9eylNbD0ci0Wc2ynyXAiIgyUkpJRUrR2GiLnFBnlSdLJEEq/jLgHAUTQjAxmYTZbTe+yDgYhhinHCOClD6menqmT+ul04us/ihEQCZBM0KGKEkzBgTjXKNjmHj7A0CWKjtLVWVk2IriDAL56QQD/erB++++96WvfKl71Llz//bCXOvChQujoyOVJHm3oJRaWl3Oz+mHm1u3bt2698GHd+/eXXEDAuX53ly9QjohHbuOefHS+VEk9tqdUUflC4Xzq6t5dWRaudbisu+996Mf/+DpQuG1q5cX3ch0/HKRHm8dbe22K2sXI0V7e+2/+MufXL3+YquWyxcqH/34j3/y5iOl1AvFONjbvPPowKwt8bAXxkdFy5S94ObrH9y/vR8TWTyOhwfhd7+3tnLhYOfwca2RM7gdJAIHo6ePFNNef+CsYa/ff3rQzZXccORt7O4buYVCtWmVW7vbTzfu3x4NuuWl9ZJZv3Lx3GD3qFhfal28XuKXn77+r9974wdfKK+BqP28l+hvFfBkxsApZDoHZeCZrOeft7YUB4UAgkAAcQYGJ8EBkUwdK6WklCRlmo8ptevGpgsz3P9UBhCcIQLnbEqQUu0p52ldUkJA1DQhzDotN3CCdAHgTLlbmikogIjGSd+X6RxKJeEs/IxaECCRAp5SYAWgNJHK0BGMqzE8ex/GZnGcRgeflIBnpT7I1lgomUXgz7wNeO7KmpQyteOeDu1CJCKlFBHZtl0qlQqFQrVR3d/fPzo68n1fKVUul6vVKgBceMG+cHE5l+eaklKpsLm5fevm/fm5Jccc5As5yzKC0B8MetVqfWlxWSnaeHh0eLg/HHUXFxe1Yp0jr1FbMQ33/MpvXrv+Sq26wIWrSEfx0HQYQWyiA2ctJE2qUkx3Sbo23DhbB22O9QwnbMmzbNGphY8nbvFwcuHThTlrYyVntvO8mfiyGIKAzt6gPGvDzW6amd6OMvoTqON46NlZFWgTgkZQCIqjSlPOABDkn+0MAABmeH1DTOOICNQpkwEMsm1XNPE/IGAacZoOHXV09gAyVHxZ8buZ6BANpVS6CmwmlbEjqN3pVmotqQA0oUpKOeuv/vw//8W/+e9Xzl1ilmtY9vz8vNdrP713k6JRiGYul7Ntu1wul0qlbrd7//79w8NDY7TDOZdSGoZRrVbL5bLrusVisZA3oyhaXFy4ePGiMBgi2bYdx+HO9qbveyqJTFMU8k7BdYQBWqp+aJcK1ciP79y8+6Pv/VW/v//SjfX/9f/mf/nf/h//D4dPdgqQq9nlWmUuFqYolz3SBDXHcbrdrmVZnHPOea/XS5LEUGNmWsrEso0g8IQQSikj8igngOKcH35ubnFlrl6+srQRdb/4ta/ce7B30ImMvHVw+LRzsHl+8fyF5cuw/KI3GkgpG7WqwfH+3bvdbrdZr/7Wr79wez/YU0W7Moc6Cb1BqVxt971iztFak9ICUCVSMMaRCcYDfXbccGbd2SxbaZYiJmOfZKkKtcp4b5azbQbG5RkmIaVoUtJHAxASpIXwpHDOfN5MgtkXHe9PNo4gPYXi6pacPj/7k1k8M3vB2LE38hT/AICeYeinkauIaBvHPz8pwIRwJr5NzkbCeuZEztL+mM72jj6TywGAKD4e7+z8IOgpKU17noKZJaFm1Z8+Od7pp1ZZmRn1meMVqcibemDRjGv49InUO2AqH3e7Xc/zGGOu68ZxLKUMgsCyrM2NvXw+f+HSYrFYrNZKOafAmYlghENklPOG4dOnR4P+qF8VkZdvNuYCP/ZGIUPTGwWFQmV9fbFSmsvny8Vc2cmZWitSMeOGZVmWzQmYCj8JQc9ukZ8GpuzF9GI66tMLPKNSPjXdp5jcLJ53djKz+v9TPo+IBk205Scjncb3TrqIP9vg9GZWfDPj02coZYABNZHWSgEiMmQcgQBTThdB62PO9MS4ssOlaPzAxNFxMpyz+5OqlYgBAiPSOFby/Kwthzj1EDl5KIBBvdn0gxg4T+LIYhBLuP/gzsHBgZlzrVzJdlzH5N7gaNjvqsi/eO0a53wwGGw+fbDDOQAwSKplN+e2DMMgIs654zhEdHR0dHR01O8dxHHcbDY++uijMPK1lvl8HpFazVoQBLZpNho1BOgcdpMkEoxb1QUl+6Ef1puNf/LP/mm9mu/3959sbf/j//KfeJ1hnts22o6TH0Uxz+fJ4MwppSy1EGJvby+KonbbCcMQPRaGoWHyJEk4x243SD1Zi2ZFmVyp2A1lsVIkzqJYEuH+/v6NGzf+9M9/zCO2srCIMjx//rwBPBxsrzTmNra2KbI8RYpo7eJ6v9/f2torVVf92A6iEJQyGA/9wBZG4nUROEcEFAxQa62UjIFlSSrPC1mMV2aKRHk2ISd9NkOps85RluSa0R9SU+sVpTGsKUdqZBBsh08FiWODJSJabIq9p0d+cuMYxaXIKu3niRSJOMEnOGPDflY+mY5lmkhx6lx2Ck8iHhcnmDXApuG1k/7DdAiGcWLejps6e1kywWAnqNh0CGkK5zGx1Hp6tFWG6jhLMFDqeH5muQEtz17fNDb6FA0GgLEPM5yc2VMMVOoXrZQKw1CBIiLTNBljUkrf9xljhmEcHoxqtcH58xdcpxKFydFRdzAYaK2f3NtC5EBsOIwr5XlS5Q/f3827I9vyhoNo7dxSvV5NM4Hs7W/NM5prGE6Om4JrYlLJMIoSDQSxxWw86Y89+TqNSztBg7MI29QpWE8dyVO3An62ZElwtvEfJqh5ejH5K5tcjItNfjJn8AkEeJYtmL4oFbwnP0wvAABkQqdWFycKolONTD7Pfu/UW4/SvC+k07rWqCQgEiFDxoBpRCSGgIkOz6T0SYb3tQaGQJoAgRiCSo/88aSdhglW0inCRGI08bU4E7LmOosBykLziMQ4EmMT5dt44/WGA9NyEo2CIWNYLudvffDu/Xu3HMeulUvlalOR9gZHh7vbnjd0LVNgXKvU5pulIAiUUkmSDAaD0WhkJYbWejQaBUGQBhT0+30ppWMzrbXv+1tbW4ftfa1lpVIpFvNbm08ODw9Nbly4cKlUKB7uHbbbbYMLq9mwDavdbvsjr1wqXrqwHCeeabHd3RARHTunpXRdlxCXlpbm5+c39h/EccwYs23bMIx6NScYX1i4ZMvicNS3LItzZpqi0+lYtpHL5UwGEaPRaGR6yRzPUSx5zQUoj4a+NxgyrS6eW2s0y72D/VF/WCkZ2N8XBbMkJI+HAy+yLVGrlKIo6rU7FxbXA00iThKZFFzXC/yC41gG1wSJgiiOmbAABbMFIY8nEt5PCVnrm5U5LosAZ+UP+CmiV079IGP/Z0nqCsfCGRBL+T9ARBRwtibAFemGhOlneiFmVKYwMy00Q0loYjCDiWQ1dj0imH4qmtbKxRlUc9okl/ITiChnavnADFpj7FgiPHHGJ82cllBRzspCU6UmEZtt5K8Vt0wOZ+I9LY/XZZZkxFntZTBSMjl7vDojbAbpBAGe3j/OBX3mnwGAcy6E4JxrrcMwHIUDIYRlWUolmqRh8lK50GzVn2z0PvrgwaDvf+nLr1y9dt6xA6UoSeL+MNrb3S+XmrXq3PzCuhBiY/NoMOxViwlDSyZ8NIxtmxmmUkoeHu4Neq9LrRbn1/OFFptYrgU3lAaYln+YDB0R2USmOvWZmTIQpwQbYGYN9EnnqWNam1E/crrzYEb2RUQgnD47u6Gz4BMI8OwGmrbP6Pi0jbs6/naCvTrVMXhmcXnGxrKm1bGINABD1IgEwFBBmr2OdBrLAIDAUICcFqmebZ/B2aqYBAQAEGNEpCdLSZjt3Z0aFIAYkAbUkySaPAvhnnn3pzixp9+r0y4hAqY4IJ3TYqnUG45q1VoUJchIcPr+X3wXVfKNb3xjaWnJdd0gCAb9rst1q1rIO3YQtoc9yRgLgsDzvNFoNBwOfd93wJBSDodDpVQul0uXzDTNfN42TbPZbIRhOBz1EalcLrdaDdIyjpNgFAGJvFv1c6qLoUqgXKpprTnn3BCjYNQZDVaWF1544cr/+f/0/zBdS3E86O47jl1wbEPo+VrpG197TQhxeHjY7/dd1338+PF/+uN/f/78+bJTu3fvnu+PKpXKyurSaDSI41jK5Nq1a8wwut0+eMk2y1nMFJ1iaACaGPg675gfv/+eZZmOcPrdHmgtpRwOektr54JgGA+H9WpDDtvNgsn6/nDrEUhWLdR7o5HDYwgDByM/9pBxBJ6E0i5UJYFSqJ/bxPnckLnfMs4FZRgrsjIuZUrYGf0RgAAp0WUcIaW+HNHmZxNgR0yOzrEQDHDCB+hYMgaANDYETqI+GB/Ak/7GgESkn6m/O34Gj9HjLJ6RWp16cnKdYcKbCaM6IWFDPL0zRkRpKgx2dnhS1jqmEvAz1B0jdgYhJ6KsxBpRFqOGZxNgyogumZhCaOYTAECk0ifOmH6nfaVJrHSqTkljhZkBpVLBMIx+v0+khBCIJGXsusWgHd2/t6E1+H4YxYMnT7dr9fLKytLB/mGSyDiWu7u7QjAAWSrb7YPd+fn53Z1D0zQXF+fPnV8tLOV2dnY2Nu+XymXBHcadnFs2jFQk05NwoNMbTjxDID+ZRVJqun5wcrxnCLgAQGn9yGeWOZUsZzfB+Cudlpg/eaN8AgF+9isishlVz1RTDACI7Fn+aTrA6WoeE/KsZOhsbHdBRgiaYXqC0Bbj9nWaKQQnzYqM1GtZthkAANDACIgAJ5SYActwv06PHzJFkMriE6Xf86kon1cCJlITRQZg2lkgTSTQFAgyjgWASqJ7H9/d3Xj02kvXlufn4sjf6x2oJBYMi66J2gijIAr8w/290WgUx3Eq7Kb00o/HWecsy8rn8+lBS5VMhmGkIQmcc8Pg4z9pZhq5mGkpNWlmCMswLI3aNfMHB3tH7W6+4JTKBSL66Pbd9z++ZZpWzilEXKoe85OIofK8YX9w9OF7NwuFQhiGAJB3SiZ3XLtYLtQ40HDUHQx6rbnq9etX84VcGPqDwcB1Cyh4u91+/PjBh0cjFapQ0yCOvvqNL3tzYaVUfXTrThJL23W2dh+35ur7RyMiunL5cqfTOTjYW15YTEVtEQ9HXuAUysvn1x9v72vinGOrVm1rUSpXi7WWNswltwiMKVJRop2MOPXnXd+s+NrM8J4M79YsGzDTZ7stZvocZPSTTXyLGYMJASYGwLPcZ+EE5klvIaLSGRI8myWEM7hOnZHpiYhONXPMWM9MJ80ocrNS4WY6t4qZKIyZtWATvDolSbM/nH3vX8NSZxzsscT/bJsZ3uZZvgWzBPskns/S/J3NoAic2KJTtJuK/KeUAKmuP72Tz7vlcokx5vueEFxr1e/3wjDQAMViKQiCe3c2D/aPDFNzQzYa807BEYbj+SHiYOQFTo4zMzEc0ZqruK7T640Et7xRfO/uk3PnlqvVRj5vlSp2EA4Gw64wHaUojOMwDNxicXZip9PLMnRDmbaWs2YBsjdiypSeIqKzm+PUX6cLc6opzEiBlrWNsiTXqep4hmMgeMbmpE9qhM5oPMvmqhXRWIonHAsEiFh2Tv9g3BF2IvHI9HWeOntcJqkxxU2rjoBOv8oMhkCy1EJDDEkjpmSYALNSZqrnzpF7NjAYq78YY4JzGDOgOhx6rUptMBjVa/lAxj/58MNzrcZLVy7u7+8fHR4Mj/YjfxjHcRRFYZyEUdLvtQeDAee8WCwyZnHBGBEiOjk2Q2WNOI5TjwqgyDTNOI7DMNRaI4rhcCgE63W8KIoQuVLa930/GMVxaAgRe7EgITQw0jnbKZfLw6F3/97jPBTRNrhr2o4JQEzwoRc8erLx4/f+UxzHlmW5rouIlmWFIQQhcJCMW8jMvf3Oj378RhB6SZIoJV+89qKTy+9s7e+1u7EXOWZOE3LOEUW5WHry4F57d7eQrx4Nj6rl2ksvXfvwzk69UTMY7/f7Mg4H/U6ltDLsdW7fvts52J1rNTqd9sEwfrSx5VrmjRfWi+tfUmgoYlGkADlyZpoC+Nmp/P8m65gh0WZmpMqKE81KpJDRT5Wls2ZZqWEZggZEgtQVGRgQIcoMTVJ0slD88cXJYgbTi2mmPziJE/RZ6kMAmA1DBThOM8BnIpRmFWxTd8ZT/ZlqCumUgxE7o5MAMBUIZ4VgIlLqbAEpC5JUgzXGzJP+EE39Tk61llVvOM7KxHQi38Oxlj4rkRGjY1v7ifFKKVNnyGm30sFPn0gF36k07HmeZVmImDpwphiKcz4/1xgO/TiSqWLZMKw49J882q/W6sXi3GgYEVjIuGGJUsWt1nPN/II3ioUwEcwkRs8blUujlZXzjusKI+8NgpHXs50yQwOQMcanFOUUQZrlXE4Jf2dOhJqx8Zzgmp/ZgukFp7Op76mNBZMdmZ6LZ9th/Pm0arP9n32LmFXFTPywAEDSCaeAWeYRZk7LjIo4g9PXEiabizHkfFz2pJgfHwkOiIhshkWbheOQ5YwykaaSGhiRpHHEFqRfM2rlgK8NImKgdbq3x4H8pDOSoWdJQlmQ9bRgXBJpIs6YaRipx0MCYAKzBfTCsLsTdQ+2Nx/cywt6evvWe3fvhaM+Sl+F/tHBvhfFhuNyYedy+ZzLHcfJ5/M0ibOXUiqvlx6i6XFLKbFM9NT5y7Isx7FHo1G/3/dGEhEtwzBNkwtIpC+1ZwvX7/q2ZRacnEyCo/090+C26VSKFSSumeTEDWCcM9fJMcM+GnoKhQQFCoSCdvswNQY/fLpVL1U02sIqD3157+FWt9sVBrcsyxIbbi7/9MnOcBQgcoNzraUpjHfefu/yhXMqCntHbRmik8tZwnjzrdcNo+R1iHPeO2p3+57UjJltpfVuxIutleJ83SzVv/3bv/7x3Uec5N//9m8MeMswzYRga28fOE+SSCBqJTm3z1yXv0bu+enXPcuEkSnxnN0Oz6pOlvHeLEQvGTEiIGJILC1wkFoNMwh/rM6wKSKiMeMgMjn7AAAGncCfM9enrb/pD2fbPPkWfebUIfDZ/hz/fKJCPyUapnQNYeIJe1LkONFCKu3Is/Fz1n6IAWeUBMfaeA3HqvUT7WRl+jvzLsA0AcLspAEAy5CA08fp+HVjEClGeFbh+axMk9LpSAbD4VBrnSTJVJy3LCsIvYODA0Pk6vWmUonvjaI4kFIOBqpem0NKDg+O+r1BGLNGa2VlZXn30V3bKrRarX4vbDUXzp8/H0Wh70WthQaRFXoqSZIg8DizTdsyTTNTUpxRxZyilGdP6IztFmZ2zJRywMllTu/NirmzxOxZMvms6PnT8GtZ8Ox7uZiqkk44R+DE9nAqbi+75bPvzx6DtOZYSoNzjkYEBsgYE8gQMbUiy+TYVDPVoBBRkOFNymksGitI65ZMEENGnFaIBgEQMiLgQECQJrz5lATdTOCcaY1EwBgaxjgUQCl5uL1391an1+0+eXDP7x49uXs7z/QHvc5+FMjQLzm85IicY+ZLxUK5wU2n2w8LVt51Xc657/sakIiCKBZKsVl/t8m81Wq1XC5XKpUAQGk3n88JIQC0TiiOY9LEGHKBREmcjJRmiR+hQlRUKuSFYxjMCJSSsSzVC2EQxXEo48RwnHKp0pyb11rnDwfNXCsMw2KxWKlV0yCIcrXSaC63e6OBFyOKQrkh7EIURUHgWWZeCNs0cuWKnW4JfzgymWCW/eDBg9AfVQrFKEg8CoRHXf+o5sj7Tx5eunqdMVYolqtz80MJV1+40TZbV1caJsXDIL7yuS/vRsbGowexcBWajJkENM6gzxgXmKmfeX7Ixhtnw/MSYJ2h8s00eWRJzJw0ElLaIE3ikSBUGYl3FHsWiQEApip3TLH8DKrX0VSWnXme2EQ8JKKpWwkgAkzax+OquQCAqM6c0lOk95iCstP3089oqnGcUl8iAFDqOEwobXnyutN+mp+MV6dlZGf6nv7s7PVSnxgGecZ4jwn2tBtjseXM588k5UQkUg1+SkrjOE6zcHDOgTOtNWk9zQ6qiaSScWg2anO1WuXp06eLi8vFYvn1n7wFiv1v/7v/1dbWxg9+8IP20UGSxLadu3j5cr/fR79b5i46mi1UllYvXHvx+sUL515//ccDuT2I/ZyVOLkKmrUrL/1DwsLG9vYo4ojoVBjnPGaMc5AqQURGBkNkDPm4ep8ELYlIihycXP6JoHaCgTi+YOZk0k6AOE7UArNcoZw0azBmCGYKbhgG53w46ieximOpAZEZwIRWoBUZ/IRQOO1YkhEXyzJUtcJg027S8RVJfYZBBQCkPEF32TgTK4AmIpWSLSGYMIBzBAA+yfU93QrjeF+Lpay3YCC4FoJMrjnnDnPTeZgGxaafljUOFp++Or2vyZ92Us9UFJHiRAYurYlIaa2rpqW1lmlNMUANqJSSWtvcR0RChohKk9SgtVYEfqIRUTNGaBAySUwRKCCXEE4EGSMhIyIBWQTeREQGyJEANGmlEqm1doY7dddtthq7W9udrc7m040nDx/t7u7u7j7d3d1FRNd1j46OELEXx9VqdaFYq1QuDgYDwzBS9tQuVj3PKxXMXq/HQGhJSTR0HAcAGHA/wVCOzYcyDIQQwrY450IGOW68cm0lTgIpY8dxgS4dHfWBmO/7afSB67q1Su7K1Uue5xVK9U6nM3fx2mAwKBQK+XzePDy0Lp0DK5cqt5r1uud59WqVARSLxcVGZTAY5ARQ5DEA6XvFYrHkGNyChZUWcTkajUBgsVJut9uthUVWbTHbdubCVCXOOLfdiud5NREpIJ/gSI3IoMAPRLQQ+RDXaqjM2tK5kWIJEyuL88PhsFXJsVF/fwe/+MUv3rx5886771Yh6aPmivqCOQQMpCEII7/g2H4YmYZJlJESJkPCSOAMCQ8AeIbpx1QnztH0NJl4+lyMLzKKoKQm42ePJDMybMZ0QnU87a2lwxPPTQaROvU8S96UPO3FkYoiKqvesGWe2Q6TyeQOQ0SY+HJyQbPoZwpKC0izP59sP6YgfTYl8DjRxQo9ZiBO0kuK9NlRJypTM3cizGlK8Ka6Wzi5apl1zYk/OwkAoDIEhkQe64ZnLzg/9g1KZ288nxl1zU3gx/ISHHM8YopPp0LMODEKw1mt77S7n//cV5tzpYP24+Z87ju/97VivuXmiqvL63Nzc+vr66+//noYxAuLc9vbW0+ebBApEfUqzYUrl1+qtFYrjfkbL71ysL9z7+4jqxjNNcoUx2GsvaEcHEXMcN576+5Xf+1lAARgRIyIac3GvBhDICRNhMgoVbwKAsWfWcUJ53VCZXHMyGSpgE6yuDjh+/A4c+kJvsyyLASpNSQqjdbRqVOUHqenGP+b8l9ZnFRWMQOZpdp6RsU9HTXi2K8nHWeaWh0JiBiBBtCpTURrANBpFeRxHyaG/7HUC4iIBkfBmRDCmGihZ4d/aranWtPpMFOWLjVewESeRkQANiudp971AGAIJjWBZJIAkHBc3BsUsukSAhEHYkgcSDNODAkZASgEJGIE/NhFCxjo9DAjacj0OQMknaZxJ5WKYdrgCBxb+YrjOO2D3X//h//j00ePGeBgMHj8+DEysm07CIJ2u43jxHAJAARBkKZyM00zHVR6oJgxDjRIj1UURSmnm9YTS7VKqdeVEIIxlhcFYZlWrlQrzHGOQphCmOcvmYDJaDRKLWSGYfR6PdM0Lcsa9Ib5/PUoijzPMwzDNE2iy4PBgBLodDq2bQsh0pcmSWLbNltbAFhI3x4Ege/7+Xy+0WgMg9BSZj23lHb76OjIKJlra/OxCvImHzk6ACWldBwRx2RrXS2UHcfS2j06ElEUmaao1SrLy4tutXbnTr99sKWln7MZ6FAwyTGZb+R3dzfv3RLtvd3H94VSSsdxEnTyxZrQiUDtAAelUXPODCADIDx7wTJg1iXm2V36LGh9xgkCGHvd4zR6cIo2Ms7pOH/isQp3rJfKih/FY6J7yp80I9xlzFikzyBNQnizUlSKDKetiQ/KiaBhgHExeHiG58jSBGQ6BU/SSE1I7wS30AmN4PQteoL4Tr83SzU3ZXTGMzhZIHY89cdmRMzUWED2lvhkwJO+PqeiYKafWeVi1Yw2YnYqxLQ5KeU0I4fWesppzu5mxhhpZlkG4wnh4Onmxyp5AIiXLl36wQ9+2Om0y+VqsXj09OlT13VTqcixzcFg0OkO2/0nb/wPf/zyyy9fWj//+Ve//O/+wy0Z0+rCfBBEdzYeM/jTcxevvXT9EnEb0tAXREKmAZEQAblmiMQ0Amqc+Hoz4myWuM5MMYq0/1NZdqpUz1iZGWk13eKTgZ9tM7YsC4FrDTpOEkl6HLPDYGx7OCbB6U9VxqqLv47je7aj0zHCzGbCib/61GafRm+TVmmviBhAOq8MkYEaB5gBwDQVGiJyjhyBc24Z3BCccy5w3Pjse2embbwp+TR+SWsiMgzjlFicEhvBeEqKplOtlNIaTVNwhQnTTJIkrRig0kQqAQdJIykEEqAYUipzCCYImCZUhAlpAaCAKaBojLCYBuRpoStAzD6OXEvGGCNNSmstBQNTGEKIkmuXy8VKIff1r37J/ubX55rNu3fv/smf/MnqhYsrKytvvvnmW2+9VSwWy+XyxsZGrVbrDIaOYxEpzlNzhkqSSGs5Gnph4HGW+oAoBM05I8EKTmm639J5i+OYiPwoiaJA2O9oirWWuVzespxKuZ7LQ6/XSzfe3NxcSoyVUjZjhYLb63XSlwrBLMtCpGa1VMnb5XI5lVynC72+vpYec9u2U+1XkiSMsYODvRcvLudyue3tba11qfRyGrWchpc08+S6brpqYRg6juMlmOagzRfslOGoVCqGYcRJcnF1fmlpLghKBwcHKhxYDJkKqpbSedZ0kVes/s6DJElWV1dLIrZZmCQRY8yQgQ49beaYMBPI8F3+6eDEFs04R2k87ngJTtikaLJjU8+JyQ7PIJBcHGvLpmcRssOT2Fn2LwDADA0ZqmcIZ3qfZUj2Rlah+BnhJKWXlPb/WMKbFVcoa94yOBGR4T0u9dn4alYrdoIyZanuT3L/M1/TdRw3MP3UWVXgpjB51dii9dOVW532QakTEvD0gSxnUspgRMRUTEnR5XRsOBPQnWLV9OL2vXcePiUNw3yRf/TRzTgCBvk//OP/582P78Zx/Nprn8+5dpwUms3GkyeParVa3sKF5fkrL1xdvfC5e48O//wvfvL46fbXvvLaP/j7/zuD+/UKvPf2jw/bD95574c77Sf/+L/+rxRzaNIHTRNtBwHg2DmIpZ7JpDFVq0t5amHGE/Qszk0nOitVIWmgMQfHJtqYdMJOtZxOH0PknJumqQg0KT3RJGsCGEeOwizHmuV8obM2XGb0Ac1czl7r1DWKMVSpozEwAALQjHHGBNE4JwFDzjkHHQmD27aVouAogmnaRc7QNE3T4GZKgSf88vSInkruMYXZB1IX3+n9KQHmpiWlTMn5tBqoUsrkXHJkSilBXPMkUVpL1IqICJADMCADyeRgcOQMw0QQkUSUSieKJLAEpAZKQBAyRnqWBn8CWJQwYghakSIlBaDNRc7iDGHQ76tE1svllZWVSql8uLtrcX7x4sWLFy9+9NFHQRAsLi42m83RaDQ3N2daDiLKKJZxEoZhFEUkVZIkJgeDMwYkOAfLNE3DMAxpiNRIl/IiKaQHMPYkIu3tdw7bu6PR0HXzvhcWCiXTouFwmGqV19bWOp0OAAwGg0rOXlxc3NnZAQDOebPZTJPT5W2LMba8vHx0dJQuU61WMwzDC3zHcRCxWq16nuc4ThzHjuMsLjS2t7dN00TE1AKdclGmEI7jME75fF4pVSqVfN+3bbvnqTSGan6+5ThOikOklKATWmpVKhUp5epSi3MeRVGSJNfXl/ylaqlUWm4VfN/XWudyuf3Nu53wYZSoQqnsJ2TZYBXzhmknSfK8Nn52MuPNKUT/LOiZcJdZzhvVicxu04ssyWxMd8Z/PVZfZ8WpTyWkU7g7K0U0Owu5fQKIjEdohkRNafmplnHGtSXTDJ+5LgxPYMjxhcrwrdF0epLHEnBG+5zzCb1ERASa9nmmhXFGAsjmH04Anp6TM+DZnTD57dm6QJXhNT3TnxMJmgTNuM/AxNNKCIHiWEc/FWsQsVLTw4GHyFGX+h0FKA2z8/Htu2HoIsLNWx8iEuNq5PVq9ZKU4Y2XLy2sXJVauoXiS698HoVTLucO2p0bN76+sOB0Du87jtucmx8MI814ZzAsNgSMlbcnNqhBBKAZpOWXx/wgIzjBNMz8RM4Q2hMUOksFrcfUFwG1hvEVIqPjdGvTCdFa60QDsbHnqgKpVUpr5VRbOtE5pEaRrIw8mME5sqzA/5nuz/5S6pgRIHACIlAEWhNoAkMwITjnXCmM41jKVFXOBBJjYBhcCMEYEKk41ilWSiXpdCcwNjYJpxh2SmKncz4bZzmL0XDsUnN8LNPGbYZc8DRMfqq41pqTlghkckMjU1pHLNaaaQkMiIHmSCYHiwuLgy0YZynCBal1TMhJx1ozBkQ0pLHOeZYG6+x8CYISgzigJtCESnCeY2QzMk0ziqI4jkej0eHhYRSEnufZtu37frvd3tnZGY1GSinf90ej0WAwaB/uE1GaGA4ATINbprBMYRkil8ul05LqmbTWcRxHgT/rtgYTdsQwDM7Rtu1CoZAkcbocq6urGxtbpG3BUQhB2t7b7TuOg+iQNtqHw0E/SvXbbq66vb3NGLs97Ekp14fR4eEhEbXb7fn5+WKxuLW7wxgLw3B5ebnX67mu2+12C4XCyvL8w4cPhRCGYTSbTc/z0ljhUtFZWVnpdrthGCZJ8uKLL/b7/eFwWCqVXdetVqu9Xo+I0jgrzjnTknMehxHnPEkS0zRt2+bIDI7lYt40zfzivFIqjdSyLMt2ouEoMoSHyAo5mXcoZGEUxznjbC/oLEA61huPz196P6v8H4wZboZsctiPpS886fw4fv4s4BOqcKJtAJaRQnJape0UfsuKHxUnMzOO/yPK8tqFDFv1yZosx3NySpLDiUUpqwhNtn/cs4pIgLGqf8qXnEyqdTZhzhjXWakrERHoWQ0EAKD8BB30zGCOf5BBgE+h7RmG6TiuehaSjHrP0x+eloARj6cDJ1knOecwQZ0pYz7VGHR7BzmnBNoaDRMAclwsle3Vc5dRze3s7MRx1O/3g9AThsrlcs1SLVL9c+fnY2rV6vVf//o3X3zl86agd997/Xvf+79fubz85MmdRmXu4qXfevik/7kvfK25sDpKxt09tSdMphBRcMYYciQkrbVGolgdS+qzv9Izbvo0axbKNADgLHVOtU+pBAnj+ow01QQgotKJ4CZjfBpFnW4srWBCfsevSg92FmfHMnOcZvyAjpfz1KaZCqZTuVMp5djcMDjnHGLQGpIkkVIrRYZFAHoiFuv0H5FKebJ0pGM7EGkA0ErSaSevY+J6aiMyxpQczxvnfCoeKaVsy0BEQ7BpJ1O9RhxLjmkVbyZ1mvhFAWoEQOQMmclAMDRFugHAUkqRBoUKlCZlAkst3Cx1rjlJg1mWIhLABsWAODBkBAwFJwukodn+wVEul+OmCUIgF8I0Y60POp11KXd2dobDYS6Xi6Ko0+kEQdDpdELfIyIGYBki9cPiDAHAHw0BII7j9DOOY855mgxyOp9TP0fOuSlYEHgM5dJi07Gx3x/KhF64emnQ62uZJEmSzzkrS4uH+3tSytFodP6Fq0EQjIa+5JI0Li2u9LqDbrdbLNdM02zNL+3ut4Uw3EK5UmtKKe18kYgiReV6s+8FfixHYVxp5J7uHMTEheEcdLto5qSUvh8Nh8OB73ZH8cHBgRAiCAI/wb29PcZYOOzVarVCoXB4eKi1dhynXq8Ph0NvMOSc1+t127bTki3NZnNxcfHpk0eWZQkhFhcXh8Nhyr6sr68XC+yg3QmlTtC68RW66JR5cd7MSmj/U8AUs090UGc/xsdVfwAnhXLTf3qS6elY+YxARFlFHTBVgU7I0vREZEmifKI6PvMIPwvGMd6a1dNCkvG7TEZhJoPGCYlzQoBn4RME4Cx4Vv0wJqjT6kYwI6QCTI3fdDJCMiuT1NQHa/a3M3A6729Wju5TvZ0RJzIe1dMHTpCS6ecpgppBfwHY2RK/SGN5T7HhiKhPvmncCGNxKBgRYkSgSqU852p359D33TgcGAaPYs8LOlevXmaMbW4+/eKXXq7VPacgciLfPtrrD/xSqXLl6oWcy/7qT19/9+2Pjo4OKq/9xvK5lepCefnciz0/kuCN3wup2854uh2TC8aFYKZgDJBAa5kopUiekQgiFSvSsU5am7gLZe94ms7OjEoh3dB0DMcpvKdLkqoQETkTXM1Q37EhmQCzN1ZWNRUlMzhowFM7IP1M84Wlb2ST5CGpJTKVZSdkFThDhpxz0FqHYThrNp6OUSklkRBIa50qzZRMaEYRMqUZ0y14ivwrlUyfnFJfrbVp8NRNacrTpPvKNLhO2R1EzplpcAJTGEwqnjY4Lr2Smh0AGJekCUlxTYqTBsUJCYEprZHBSRoM2fF8BigGJFAzzgTjnCFjxGQYazSBI2CkINGo0WCGIyz3+9//vlJqY2NDCNHr9SzLMk1TKVWtVtNMGoiYJMk06ZWKg9QNKrXCxnFsmqZW0rYLMKMgnQ7QZFILtThX/tyrLyHSw4ePX3/9TUuo3/v7X+v1eo8fP+73+9evLc61rMFg8OMf/9jJ64uXzzfmcmEY3rp1q95yPudcPjw83N5uc87naqXFZtUwjL29pFHOm6YZeD0iMHLWuYWW1zn0fT8y2MXlhYjozp07YeC7OWdpcWFrayuJo7ybW1taBoDI8x3HGQmjmHO7XDiO4/cGbq7EUCiJSgFZHMHY220X8uWRF3AROg4GIcQJPzgcxsmeF8D2/mEcxwOfUq34YDDoDBLHkJ2jXijJLtZXr8agbJAGo6ww9UyY+uJMtU/ZrDbAxHt2dseO8UO6U05WOgHM9M4lOi7/johTtVQm4ccTGP9YLvjEeGKajZQdq7jPfkGWqueEtzYQTWyeatI+zSA9AKCsOuIZiUGmCzaVbMfTP+VEaOYTIMM5HSijfKo86RR2TO+PqyTNvBQAeYbm4yTJnH5mJVqBk57Iz/bh1Cdl5CdQqRrlGU3AmFtPNWOzXEyKGtgkEdIUCeasuSgeuAUOGCdqoIiFgTIE1+RFMQWB95u/+Y1Gs7a7u720/IX7D27FEju9777w4ncWl5ZrDTdJ1MHh3vbOlgqS3uHRxUsXtraexj/5q5c+/zttb6/nhUW3MCaWE9YUEQHRFigEs0zD4IIxIJUoJMUoQSPdPVMSMhbWgU2me3wwJhdZIuezqcUAADToCTEb79L0P2GktGfsvyal5Hz2sWMYC6NZqR+zMnZloA821b1MWHgAQIQ0PngWlaR6iyAIJowCAgDn3BCGadqIvtY6iqLJvqHpHtKalFIKCYEYG5+sdHqnEhtMtALT3k4HO307TOhK+quUBsdRwBmAwRFAa6WVSuOlmOBMa6k1aGJMc44WmEKINEyLGE+rYiQKFYHW2mIEpDH1ftaaGJsiPwZaI6NJzqyM5Z6uOjEgwVAw5IJxSJX3ShLzwiSOogcPn3z08W0GuPH4yb37j5QK0uQVqfVXKWUYxmg08lEHQTA1b6eOTimfkfqjpRFE6W/lxHEh9UY+cbbjEaPINmBpvr66unxhbbl/dGAb8KXXrliW9eabzl/8xV/kc/Lar73kOI5go7393q/9+u9zzg8ODnb3Hls2ffPzXzZN83t/9sONjY3r62uvvfyC1vpf/at/tVAvfuUrX/l7v/nrb7zxxocffnjtwsrl1YUkSX7wgx/wxP/2b//2xdWFzc3N7e3tqxdXr62fe/LkyYMHD6r5/NraWr1Y3N3dxSR59cUXK667s7MzyhfPnbtgmiYR9nq9QqFw/vxFrWF3v1dv1RYXFweDQafvm06xXC7X6/XNDz5wnGJroVquVDZ32uVyuWYXy7X53t4e8ko57zSXL1y7+oXV5UuHHvR7np3/FNJBE1GWkyMb51KFySfhNERkBvCvU0FPVLWIiDQ2nSEAZDmRHSflp9lUTZilIRu/l+iYBqc/4WcTwizfkWPKOpM4CE4SpBO0JCNsLysxCGOnUzxO2j8uKTb76p/CnH0CnqFzk/k6DnM6/gSArMRHqVA15a6mcnmWcy7qsxOPzA7zRN/QePZhAKBjlH7SBiyljOM459ph5KdWmUKh0O/3c67gKBgKRM04IjdT1CxlXzCMfYmMyZCEQTkrx0i7pdGli+u2nbct8d47b3qjuFJukLTufLzPUGnv48VvX60Jpzc63H+w9/b3/9DgUCyuablwbu1yrjA3aAe2ES+WmiPQQJqBEqQMSkwGBgJDsi0TAJRKpgV3AQC44ahAI9PEEmSRQkk8Ai0JCG2GJEAZpAUltgE5wS2DmRamyJGIUtEwnd8D79hER0BTC2gi81prJZGYybllGBw0SRmPvACZQkRJxC3T5kwD06hVfHohU1Iks/z3xdkb2hS2mgBNtJSIGLNZqfe4HqdKUhxwLJcTMSKSSkQecT8wGJkG1FyjkHds21IJ9IaD4dDXxA3bZSIXJzKIYxu0QMa1NogJSYynEeqaVErgxmIr58xCw+QmDyQRAaZaAWIp9eMgJxL8lCVKZY6jACyZOFLkbDQNA4UJQIqAEonIGYr0YKBSTGvQWvDJuiilNBAyBsCQ+YFCREIuAIkpLZVMpNTKFbaUUsqITta3RmHSxNNw1gMzxJgRk9rkyFESEWqFRMgZGZZ99+7dP/uzP/NGQx1FpHXBdeIwUUoBqd3Np0mSTDlXrTXnXCWJYdtRFNm2LQE55ygMRLQdV0ppGpbnhw4TUiWNotPtdm3XjaKIce44zmAwqFQqucJSf7jjFExDgD8Iqk55fWkFtFfOlw8ODr70+S+9//b7lUKlUWkQ0SsvvvKXu2+4nFdq5krrwtbXv364P1hpzBdL1sI//S/+xb/4F8KMXnrlRhzHv+d/67vf/e6FS38gpbx46R/c/N+/IYxweWX+1Vdflar3/e9/f32h/sVrl7rd7j//5/+8mROvvfYafv3L//pf/+sHD+5/65/+vvrSi48ePfoP/+E/lB39T/7g21EU/Q//5v+jvJ3/6T/8Z0Hwhe9///sff/zxlbXK569/czjy/u2/+x8vrSxfuPByu730/e//yLHFb371K2sL5fv37/d63W9//bfreZYkyRtvvPHSN16Ll+1+p2MWK6zaqFxYfuwPiaHIjYC5Zx+XrHhN1ClW1aSnYjAgCH18Rqa7kYhgjCg1IyCtcKJ7nobNTNEum9GEPQtGKoEd+wSNfyVBTa9P/EkrgDGhpqliE2BaP3uWqQUAT52U1Kc1BvC4it0sARDqbAIg5RT/4MwnSBjn39Az0gUAxGCd2T57Ri06HgI7Pu+zoxDhmfOG/BQDMWlP07ET3OxnNGsbPlY0gJzGT58YFtjagBmxdToKXwZ51xWce4OhSqRlWQYXyNBPRkoS54YG9Py4XKv7Xsi5yArHOpMqwydYOAFgkvZrtj9C6ShfNAtFsbSy1GzVHz54urO9BSD6fV2pVIRgvu8niXJs1zCMrLQvAJDLmQSy0ajUaq3Hjx9rrStV9+Cg3Wo1TLPaaFacnHnY7rzz7lu1pvu7v/u7u5v7yIzmwury8iVulhJtALeBYkMgI0IgAdpkYBtoCm4I/mx1jhS0Ao2aJunTGCcBHDUQZ0iaEzIGHJlhcMs2LVPYJk1RcCqRpNNhxMdqWJjxkleKSCutgJFGkEoaaf2lVERkjKlZH7ZJfU14hunLKk6QVZc3SVMyIx/LvGM3MUCVwAz3OiXMQGpWlqIJ6DQPBSNCwqltVUvLsqzI4TxKIiWDiBsMkAkhZBIB01ozrZROCXxaqkifYJwBYBJKlHL0gEiMMcYBcZyWaxYBHQNgHMdaawbaNPKCAxImiQQ61mDDxBTCOQdSBAxAaUIFQDoVatPwYjbRNR6/SOiII5ki1X4fR0+FGolAAWocV4AYq4A0AwJSKpFSK9A6dXoAJ8ePDg92d3aOjtqopGWYQehHvhdGXrra06iBFNL0LFrrKdWf3WPH+EiIqYObaZqmaabPGIaRmkh7/Y5tG96gf3i4v72xbzK71miS9t9+6925ubnNje31S1cO9tsMheM4hrDm5+cHg0Gv71mW1ev1Ll662G63pXK9IDp/7uLC/NLhwVGr1bJM5/y5i2EQVyqV0Wj00o1XAj968fpL9+89fOnGK7du3skXxWB0sLDUevlzV4KoW6k5nuf9F7//2//y/7LlOE4ul1tYWPjjP/7jfD5fr9fr9frO/t4bb7zhOE6tVvvOd77z8ccfF4vFL3zhCzu7e+9/8N7h4eE/+kf/k+FwiCjeeP2dc+fOvfTSK0+fXvmX//Jfovb+2//FP+l0OqBGMur93u99p9fp3Hv8dDcEIJ1EsWW73HAzbXhZEh4hTjJ6nqAZBIA4I39MBF6GRIoRaNRpdWsgAkCDGc9if/iEnNJnUlkAIDU9++Mb9KzlMhNmyfCskHr8OjbF9Tir0tRZmraMF01x1DSFwPh1dPynn6qrNN3kJyQ8naVrzoDpmTo1/1kmvEybMR4rPie9AiICmYTeiIi0UpZp2oJ73qjb7eYKtmHZcRQoDZwJGQbtg30hzGK58kmjfgZYVq7vs/TVACD8YMgNs1CyX3p59dL6BcJR+2iHoakSs1wuC2H6vh/HgWU6iKgzfVmgVi/GiRcnXqNZvnb94ubGfrWat2wAiH0/vH3nw5xbc3LlnZ3N/si4tP7NL3zut/ojTxPnhp0o1BIZ1ygIkgQ0MVAMyUQ0uZkzuGHwLJuoIiAATWpMgwkRiTNUJFMHWtAKBTEGQjDTNC1rTJxwEtuaYlLDUIhjSqXUNKsUkh4f1ERKoERLgwsmxqnEldaAWo8LeWqlgQk2oVKTXCfp14xqV5lFgOJk4hzBx6WoiIi0pmisAEj7TwxIjTniE5pMOB4mMUhVbsgISLFJ/WPTNG0rlyRhkCRRQlxYjBtaSkIESBigZMAYcsYQiaM4Rd3jWCpFiU5SNoZx5JyjolQMp0miDwIiBsRIayIGoEBrnSRJEIDgzLZtDqS1HiuEJtR66uSVJJRSX621Gks3qVczatBIXAFpICAEhqCYTeFEe4GIkJrDGWOdQFNa3HhSYHQyTwYRKaVVKkXHSinSWidx4vt+t9vxRqPI9wo5xxsMoziwbQsmqFAIMcta8BkQQqQy8XSbpTfT0kCQmr1Nc5q1AxHTFOuOZdlWcv78+YWFhYf3Nkf+KF/IFQulg87RX/7lX7ZarfX1dcuyRqPR9773vbW1td/4jW/tHTw+bG9JKV966UWZwPb21o9/8tjO5crl8g9/+MNarZb6M7darfv373ueVyqVLl++PBwO33nnnXw+H0XR9evX79+/f+HChV6vd+XKFd/3fd+PokhK+dWvfnV3d3dxcTGXy33nO9/p9/uj0chxnMXFxfPnz6eJvRYWFi5dumSapud5qysrn3v5lYeP7lqm6bZa166+cP/OI8e2K0XDubT0wuUVRv5cI88hWJovcy7rrVqlWhj4XnAUu4bhRUIlQDFx62wEl+Uky8f1oseHY4p2FRABzCoYkSEAJjpBAAU6TfqoxnE6WsxInLMXWV46E0T/jFCrCMdK6YlshkgziWLGmStOUsbTVOdZjeuU+WYnSOP0OoswZEFaVpRSkssw1cYCIurT1HdMjyHjRTOdnB1FVvRHVjdnc+nPPkYZjEXWeBOtzsSHgT9yHEcwLogi3xtGnW77aHt7+8L6+eZcCxkRN0zLicL4cHdHKXX5xVfO7mfGuHhGVMupyZleiLxbCoLOyOv1Bvu7e5wgnptvBB7IWBiGMVZ7TFL5fAIB9n3/hRdeWFiYB5CGyUZeJ4o9zoxCPpfL8Y0nezdvvX/5yotR7G3e2Tt3fvny+rdNwwriKEnSRIMaUDJAQ4dIwJAMZAYyM03SKbXKcC+TRKRJA1MkFaHShISpVgmBiAFDYgAEWmstdUI0rrYxq59USjHQggGxtN7HdOGJC0xvMUCGwFEzAuQkxhrftEguT73WNKGcaLBm2UAA1DLDFpVlWzprXyHiWNCcwPRx/cxBPX4FomDABQrGGWNpJpM4koxxx3ETiaEM4iiBBLggg6MaF0TSGolzrlM5ktPUIQ5SVR0pqTSqBBG5SMmPHhdVQyUYziKF2W2X6qLjOO52Y8uy8o5t2zZDNpXaYULhxqIkodZaEkiltdaKEECjTsVspQGVJg2oCAkhL5gQaWxVantORVJtoiIgjVqjpplgCmaaWoOUkqNigBxZqgdhTLg55/rVF26tf3Dn44+UUlxgwcizGZPBrNCT5sNKgwjS2Js0mmAWi03ju2ZlNRynItEAEARBgaGMo5XlxcFg0O12m42lh48fAyZSyiCIOp3e3Fxw8+ZtRNzc3K7Xm2+8+aNKpRgGidJycXHestwnjzfeeOONQrnUbDYrldqdO/fu37//4osvVqvVe/cefPjhh4yxV199NYqinZ3X33vvvQsXLty4ceOj9x//5Icf7e7uvvzyy8Vi8T/+0fcfP368uLho2Wxzc/MHP/jB4uIiIlar1ffee09rvbiyLIT4wQ9+4DhOo9G4dOlSHMcPHjwwuVF08y9cvvLg7j3TNBnBjWvXu+0jFQ+11t/8xjc8z7t3926j0bi8vn5wcNDudVHGpoEgo+HRgeEuKw2GlZMwOvNcZPlScHVadTzeb+zEvppySySJUCMBgQYERpB+nU0Rc6y1yUa4Ctn0UEz3OyKyjIBHfdLyOu3rtIrOmWTsFCUmIkaz7z2OoMosIpVBqLIks1mYZUdIw6lnxr/ScKaTUVZ5xKzcOET8zBnI0ohkJdBQkgCOXVKmUyfjJCRATUIIJaU/HHU6nY0nT7nQSGTaTqFQMpBZBXdteUmqzLryWYQ/S2Wd9VvB0LQtNwrV40dP0koXpmke7rdts9rtdpNEpYETqdTyCY1Wq40okm++8XYQRPl8cW5uTghx69YdN7e2tLRacOdsp16vVxuNVhhHK8sXOv1YSia14JwzwbhSUsZa67yBDJAxYIwZnDMGpHSidJJBqDQhEVOpXlnBJFMyCADBmZHasTkyxhRQmukLZlBnSn2VUlpqojQHOhpcTPEmcsYZMsY4jj0PkXQqmKo0BA0ZJxRay1Rojo53IcAxtlAZ/c/yyhYnc4oyPvZOt83c1HRNEwdsKWVW7iDOwOTcFGgKNDgaLC33rROpaBI7rxXIRCNXgEqwCVcM6TjSDKAAxqQu/ZRzJwAALTUyYMS4JqaAc57y5hY7toFprVMRU2udWpGVUqQSBEJEbZmMMc6O7XPTC6210iAJUuqbKNJ6XKcXCQBYKvtqQJm2jGRZfOr1PVEVEyKiAiBCrWdTpyEiEDAgwTgK4IxplWogmWFCqeDON+p3b3349P5dLaVgLJ/LDXxvFi9PP1MVdCoW60kekvR6+ro0jUaSJIiYlleLoiiNSiKiVIJ0XWtlbbGQd+/fe9Dt/f9Z+/NYybL7PBD8nfWuscfbX77cM2vfFxZFUiJFSZTklmXJbruF1jS8YdztGRvtaaDtsWaMwcAYw4A9Pe6GYEwP3EC3hVZTkiVapChRFCkuRRaLtWflni8z377FHnc96/xxIiJfZtWjhxhfJCIj4kXcuPfce85v+37fN1hdvRBGlV5//wdvvPHpT3/6+eef/+pXv3r27Nnf/d3f/Y3f+I07d+7cvn3jxRdfZCx49olLvX733Nn6nTt3Xnjh5bnFuX/zb/7Nr/7qr0qpfv3X/3f7+/sHBwdLS0uvvPLq+fPnX3/99WeeeWZvb+/5519YXV29f3/jiUvPfPDBB6dPn7UW7e7ux3Hc7w9XVk65eL0oiu9+97svvPBCrVbr9Xrf/OY3X3ntE5cvXwaAr371q4yxJ554ghDy5ptvdg6OPvnJ1557/ikL6gc/+MHS4urZs2fjuLJx7/7+/v7Zs2fPnVnrdDp3br1TqVSee+bVo85AZ6Nmrd4c6nw4iOKVVJSI45PQvOakhXu2UD4yoTAA2KmiMyAEgAwgxGagRcAEOdS1Of71R1bYHxF7PLiXjtkqgh8YrSk/BAIAbB/UKhF6YKTd9z4aJ8HHWV84OYI8sQ3mhE0eM5APnfLH9V2hh8UaHzqeYyQkx89CnXA8JyW2XTH6o/s/Sf3sRANsZqWxya7cfrgXjcfj8XDUrNfr9brHozyTUsHi4nKlUkGESqGPOltBVOXMp8yexGCITjiBkwzzSRsFpM6cWaO8KGUviqJKzKSwUpYyD8bjcVEIQghjVCurlMKYnPTD1XghTwWjcWbs++/ekFK+9NIriwurd+7cPTgYFxlqz51ZXr7geyFYnmdWWmQxlVKXUhLpePOBMRryScw9yQ9b6wzbSdzIYF3fqqPGsgQQIEDYck4pJpRhAkCmsaKa8h4464WPeceuzxWsJRg95AETQAgRBM4bQGCRscYoi12gbA1YTLDFGGmrrRXgrNTkYqBjKaMf60J6+AHByPHIqRp6s9hdKSUElKVGoBDxHomA3XcpGBeeUoIwMRhZNOnxtcrIslRCKKUUAMaIUsqtLVxSDSOKwWIMCGGErAFsrNF6FlNOTtBqJzWtXM6YUE0IQcha/AABMS2aGmMMpkRJpZQiyAaBH0WR7/vuatuHq+/uidDWGKOmlXblDDRga8yU0Bdray3C1oBByGBmAUk1OUc99WGdwZtts2GXsgBwFSy3GE8UnT1GGGOVKGw3W5M6LoADAKKHu7BmK6+7QC6+nxCqT50J9wEnxJvnOWOMYwoADvZopuSdSql2vf3JV1+tV+LllaV+v/z6n31zYXHuzIXLrWaTEPKVr3zliSee0Fr/zM/8zObmZpIkr33y1cCP8pxfuXJ17fSSsXI46odBYzgczs3N7ezsOL7MO3fuZFk2GAwIIQsLC91ut9PpbGxs/Nqv/dr6+vqNGzfikAFO/+bf/t//o3/0j1599dUPPvjB3/0//u1bt2596Q++8hM/8RONRuOv//W//q//9b92x/+P//E/vnLt6htvvPHkk0+++uqrZ8+e/bM/+zNCyOrq6gtPPxfF4e72zpNPPcYpCzx/Z3s7z4o761uLi4t31rcAeWlabG0fPv54K8t1PyuwlIsN0oxjYkqQqRKk0JKekIImJxFrPCgWPvQBAvT4Ou6sBEIo4C4TBhghRzAOAAhZ5Hl22gQ/g+w9MrOObzPH+pGU8iNPZqbLee2Pfhgh/CNjX/iYrPjH5K4BwJ6Qoz/p+E8Ch6KH2e4+9jNwzLCZjzt4OJlY4yNqDpPNTCNpmDoZ7vEkB+ik99Uxgqbjx8n92DNYSCB+bBDHBFXbi/PLa8ogDYQiT1k7zkogKq7UkLEntUWdtP0H7e8jo0r9qFhaqbTnlrt9DkghYtbO1lZOVd96fTirZmFMXRvoj9hvv1scHh4SwprN1qlVeu/evYP9QVmW585ezAtDMWo22xcuXFo7dbFev9aoLR50e0EQOOvGue/ueI45QuVk+IwLZ601SMOJfXV2Sv2NMUbYYowJwgjZwKMIIYQtOHtpEYCxiAjxoON5tlZqrV0/37QtAc3UBzB28jsag8GIEAQWWUBGa9dt7NIyxiJsjTbGznBqj9yI+KQb8QR5LJ9ojDEheHoJJgdEiSPNAISAYM0ZYEQ8jkbi41NtzhQSZBECPGmaEmBRIYwyIIQ2Ggih1AIg4gg1HV+0C/oxxnhCTYC0ttJhw5CZZb+NcdGqttZiAoQ4Ihfk+vDcIRxHLTE8uak8RgLfC4LAcT/ZYx3GsyXPuuqssVprqa12Ho9FAFYrYyYCn9a4KhYGsJAKMOYBBzUAcWhwY419wI4ypbKzYJVAiLhiwqREbKy1FuPIKMkCPwx9Tgn3/ZIgRihQhqb1i9nchmNtWmYqZ+IA0ugYO5irCjvPD0+JOFzQTAipVCrj8Xi+3VpcmHNRMsb4G9/4RrVR/9X/9C/9yi/8/L/4F//iO9/5TiWuvfDCCy++8PJ3vvOdNMnv3r3z2ic+Qwj/N//T/+c3/i//p2az/oUvfOF//a0v/eCt7/36r//65cuXu93u//I//1az2XzhhRdOnTr1wQcf/M4Xf++pJ59ZO3X62Wee/863Xy/L8hd/4T+pVjxr7e///pd+9me/kKbpq6++du/ehjHwkz/5k450+sMPPzx9+rSUMoqiw8PDOI5n1WuMcbvd5pyvr69/9pOfvnbt6vUbV+Za9VdefIkxv9/5cDQYAEPPvvTclStXrtz48OLFiz/zCz9rrX3jjTdOXX6uSqvD/thKha3Ik35YaRNqxQnylN5Juq3Tnt0ZA517JA90ap3P6N63SBvk7jc0YdZzYEOFPl7N8yQjpO203fGYlUUI2ROYsAx8fG34QbHzI3ng40v27LkxH2+AT0rRn1RDPWl7xE+dntRUCmf6gdmCMzP8x60m/EjjfcJ2nHP+GHPWSangE6n9H33p3hGWBHEDszDgXpqmxphKpbF8+nx3cNRapGAxZqzSmPc8XwE2J1OE/gczIo9sH72IEwN81O3nZefpZ58vxeKt2x92eoetVkOYvN/P8jx3AYRbEtG0GPyxP/DWD6/U6/U8H+xsH66srMzPrXAWDPrj3Z3DSrXRbi/5vi9KVavOnzp1ptlYGOIo8HyttZFKG5h0+fColIm79Nq6at/knmYnUMs4eAVGCAgiGCbUihhTrAFAa6OUcAoTbt0vtZ0ZYDzlIj4+mujhzVqjjTRSGYzAUkyZBQ3GuuXVGWDAYJFVSiltH4D+Hr0Tf7wJwJChBHM+kcqZobXTMpkdJ8aYMex5DCE06pzgyU48dIIsWGvAGKOQBpRl0gA2FhNCPA8DtkJaIQQjGjuOAlfdRgAWwXRVcmc9GzoA0AaMsdpoYxRSiFJswFKg9GHv0xirjTXGUmsD3w+CgFOM4MEEdtdo6vRgO81SGOscoEm13lhkrTXuqoEFwAaMRXi66qKklLOS6tRxwRYscmsv2GMrEUIIEeyIPggANsgYJ3eo9WjQLz2PYijzIs9zGlhkwYL2PH96eR+Kk5xZdX3Ax2Om2bk4vSPP81zUO6sYOCQXY6xSqQRB0Gg0PMqkKDY3N9vt9iuvffLO3dtZlu3s7DzzzDOMMUcJaYxZXFz88z//82R88IlXPz0epa+88sqFCxeuXrvi85YQotPp/Kt/9a9+8zd/c25u7u23386ybDQa/dN/+k+/9rWvffGLf7CyMvcP/sE/mJ+f/53f+Z2yLD//+c//3b/z977yla/8D//9v3nhhRd+4Rd+4aWXXvqH//AfdrvdX/nVX/jUpz518+bNf/bP/tlLL730V//qX200Gm+++eZgPPr85z9/5syZb3/727/1W7/12GOPPfvss6dPn/7iF7946dLFz33uc0EQcM7/9E+/HoW1V199daDLpBx7MX/i2ccdQ/Xde3df+YmXu0O+slTfu3ut3awsr65sJpYSO85GnAUfez+fxLEM5AEhDBx3fB0YBx6KhKy1MhfuSwghjSxFoAEwgkTPBOQnq+R0Hfj4n3WsPI98BeBHmLvjQi/ukNzLR+3uo197eOGeFVw/Ejd//NdP2rN92EY+MPAP1zJnfuSP3vkj3oO19mRS+x+1ffRof3T499HNOTqzhiULk05co8BYW0iDCRjEGCdBpR7VmlneD8KqEEoZHMU1RFhZSkwIxieAf09sT/oPo+WPO1IUWbh4/jmfLV/78PuHR4dPPL1K7MIb397f39uuVqtRGEgpRSnd8oEQRNVKWZac86eeeipN0ytXrlhgSlNA9dde+8I4GW5tbeRlNhxl4zS3YEYjm6VZwGHx/MrqwgoCfun0ufEoqbXjUuYKYxN4BmOqNTJSlF2GsOdzKUuGcTX0yrIQoogroSg+/tr7DwFR3ZhbMLqYoOmwBc8gY62V0oI0JcfHsjcza4kMmggGoGkPiVbaWquky0hzZFCiXRs6QYiWWj3cbT9hXErUx0eiBMTHXxgzcZsxGIwAIUsAIYSCsIIJMMYodSSLxlhljAlIZK01YK1BWiMhnbsCSoO14PDbyAknE4IRpkgjg5QErQAhOvPuBaIwTQMwhqlnmRBS6kyDsMoIY0x+/I7R0DDWao2M0cYoAOtYZz05Rg9SskgZVEoDIHiAnTreDOjrDFW1HhljMGgEKOCMM1fUMLOGbCfC4+wxxhiQRNgAMgDYaKMUaIU0IEVdY7rLWE3PF2PIE4IQwi5vb/A0E069oCzLrCyUMhYQYIoQWGRjrhFhgLDUpFS2UFRpCoCJSA0ig5G5tbEft5YxAsSlUno87FSrVQBQSiOERkkaRVGSpJVqLIQI46goCupxA1BrNpIkETLzfd8YjTBSuhiNtQVrLJGGGGsMMlk+Pn1qbWG+ba2OgjMkKL2YSymP9g5XVtjLz576S7/42uHh4Q/f/O7y8vJrn3ih1WqNRqON+7d2tjeefeax557+z69e+bBWjz/z6dfisP7HX/72xQuP/fJf/IW4WqWUbm/vt9vtf/pP/x//3X/3LxcWFu7dX//FX/1lBer1b/yZycflqPff/Nf/h//+//0/vnPtSpp1X3r5qZ/52U9/97vfff6Fx7V5/LOfe+2LX/ziH/zJnzz+wgthc66xtPrlr3/n/JPPX758OTfe//2f/eaX/v3vbx+O/erc7c2dRKq5Uyvtduv63kFX6nfu3Psrv/qXteXnn3zl3/3u76WKPP/K83/6p3+KEDp39lKvO9ra3Lt5Yz1Nypeee36U9qBWufjUM4SRsLNb9aEB0C1EGIYAYK0tioIQ0mg00jSt+AYhVJZlEAQYY+fNAIBCREqZZRmlNAiCB4ZWWmN0WZau0cv5LpRSaWFWI5DaYM9zpRC/e+C0KAjBTjSi2WwWReFznmWZNsrzGCGkLHOpSoRQCEAoxyxMpRkm0tIAUT8vhZKqWq0Oh8MomghpOwyN4j5FYECKssBgPc8DDWVZEj8+nvGGqYetEUzfmSZOXMeuRBjjoihdJ5tS2vf9oigKiSknACC1AII9j1lkhRAB4bMxmcxorbXWHD/kr8xMRSn0DGviGjAmYwU0CIIizz3PU6XAgJVSoR+mYswYQwBuhCdUd8YYXUopHULCMbBSSoUQhGG3YCIgTsjBWmStFaKYppcswtYYrR3Mk1ed3XGsroyxLMsIIQo/cEFmVs1a65GKlJIQghCeya/5vg8qwWCpR4wuAp9SSkbjrh8QqhWUWch4oRTBuJSKUGKMOAHUDDzgH/v+CYmb4wb7oSiAxlHlnbevvvfu9Z3d+ytrns8bIuf9XhLH8cyj931/tjJajNyfOp2O1nphYaFerydJ0unuvvHGGxb03FyrWouMUVrLvEgx62uLR6k3HJ8qRRoFcZ4V25v9min8Sgv5dVVKpUxAIfQgZMQIdXSwwzlvzbem2ddQSGtOSD1J/YAY8rhzUaoHNcXjFlGdgMrTLg01hQ7NDIaZtiU8sv8TUz3TWG36cvrkRLUTAshMumwREEIpctSMLvmMCXXpSpffRlJMBIKcDoUFZMEaA9Y+dKZuwxgXMKHIQLOGKGeAp20GM1ZIRytRaHf8kxOZnXJRDuyERMxMW34RxrhRi9GxrqFZZBx5yOGBGWPHUfTuRnTeqNZa4wc6J/CwR+82j3GlLVhljdFGWwNALdJWOqg2AExTVNaAsQZjPIFeYGwnUpYIph10GFNA0mHiLQKEiNSWgMVkGu5YbY3VBgKPI4TGybAsy36/73O2srIiyyKOGABkWcYYc/lYz/MWFhaUlm7Bcq6Do8FSSgW+DwBO8o8xFgTBjAbLWs0pjaKQe7QsS6UEslYIGwRBtVpdWVkZDAYY48XFxSzLBoOkKIqLFy/6vv/mm286Kq7V1dX5+fa9+7cYrwSBPxj0d/c2kyQ5PDys14Jf/uVf/uf//J8/9dQTN25c/4f/7X/ted7/7Z/8xn/xt/8mZ/if/8v/5zf+9Ov3d3aDOPpP/8qvvPTKy7/127/94osvnjl//me+8IXhcPjVr33tM5/5TC4Ej+PRaFSrNr7whV946aVOGIZ3bt9dWVl56+03oygqiqzZanzmM5+RKrfWZFn2mZ/8lLX26gdXvvGNrzPmvfjc85/85Guu0NBut99///3d3d1nnnnm0qVLjLEPPvjAPPfc6uoy81l/0Lt7f/vgsL+ymly6/AzzIjeSnHMhmDHG50AQjygZjUbVMAwCf2NjA2M8f+bMeDwuRQYAUUCllKNBwjl35NVloZz1ZTgEbQkYsNqjBCnFGVgLnHvuopRlQYC0203HTaQ1RshyToUo8jwtEr28vMg57/aOZJmGvi8lDIfDlcXWKEmFMAQYoxpxwByMBak0AVUJOWeo3+/7vh94nhBi2idKAx4Yq7W2BHAQhHmW44fJWRFCxhgvDJz9OG6bAYBQjDHCFCECGGOLMCJAGI593xhjAQhlUittlIsosiJ3uauJmRTClQ9K9UCMYToHDQBQzidZtynDLXbERKXO8zxNUyGER1kQhGmalmXpV4I0LzDGnHOrdSGEWz08PwbE3Kx0bH3GIoS5VhpgNtn1jOHHpaBmYC9rDQAx1iJsjDEz1xxmfX0IH180jj0vCVKylIwxgrFFCmNsVIqmzo1b91zkwDkvy9w6EVWkAWPKAFOGMdUyO2GdPyki//FS7rTI8O2b23meC1FWq4tH+7rMiiyBS5cu9fv9wWBgjHGEt+60R2kipZRSOhbDMAzdcmOt3d8/sE7SnBELJoqiNE0xxo1Gu9VsFOXw+s13OK30uune7hEfsTPnnp5fq0Y8NhQoLrUcdke97fsbBwcHp9bO1Fs1ALCAgrBSSCHkSX3AD7UNwPRmKh6gkR/knQAAiRPAFBNs0VSNa1rPs1NOiUd+wp7AYGWmec4HETAAAiAnWWAE1iJAVlvEXNxGKSGIIEWQJQiIQyEj63imSqstgLWgrDGArEUGrLXI2gf2dXIkTu0VYJqAeahsU06quQhNU74TmJNm7sDdpIMpBYGHy2mkSynFlGGX4K17DyXr8JS7lDNDCKEME4owRtYCItgYEEJijBFGxhgpDVhNKaUE2ekMnGV03QFjjIm1CiHsynygrAZjjdHqwRWxFixorQDAmzDsTAp81lUxLCgj7fQYpTYGNADG2CgNFgBboyeuiUbWgIUkKedajWu3bx7u7/mcxXG8MNeWUo6GXcfuGUVRkiS1Wq0sy3q9Pk5GGGOtdZ7nhBA3OzzP43zSaz5zTdx5aSMxQBSFc+1mvVozRmHAvu8/+eR5IcTdu3eVUk8++aQx5q233iqK4tKlx/I8z/P89u3bFy5ccIsFxvi7r3+r0ayUZaZNCUgdHu5JKR977LHID373t//tC88+Nhx2z59Zlvn4/vq1l55/YnfjZrNRycvisWeeHY1Ge7tby0stkXav37jVnls46vRe++RCp9u/fefuT332p/NC1ObjH771zpkzZ7jvnb9w8eiou7m5eemxy9/89jc/8YlPtEgTk+bT6dOjcf+Fl184dWrFiXk88cSlUX+0cf/+pcsXLl26tLe39/7VDxaXl7jvEUa3drbX1tZOnV7rDfqbO5vUw+12q9M9GCfdUmS7O/fPnj0jRNrpdPr9fp7nAFCv1xuNBgAIPyyKIh/hbrf7gx/8AGP82muvVavVpCz7/X4QBC5oa7fb3cPBlStXTq+duXv3bhRFZ8+eXVtbi2vxaDQy5dCnxMlYRVFUWVpCRpdlQjhXChNCGtVAKeXgm2VZRD7xWLC1ebcoimqtUq3G1iolc87QwcH9Xn9IWNCYX45DPxcJUqIW+ZYHWTaSQhDwk+FhwOcqYbg/GmKrwGKEkOd5VtsizxknlFLO6Ywt3FpLqWs8UaLIwC0gyNVxJ3O2lIIAkUZqOXH1pJFa6wCRMk8JIYgSrUqrgFKKtAZKrTLG8RpYI41CCDFGrUJokqGfLpjWWmuF1BhPy0DTCgvGmFKGEKpVqwghI1Wapru7u4HnL1ZOSwWEIAbUAmKcYoyd9AsActiR2c3v9jRbq+0x3QHn98MUmuN4jbSWAJYQzBillLgw2qUEUKFmy51btd0cYxw4wYmUHqWUIgGWc1KWJWDiWmystY4/H2PgnGIA9z4CDchii5GxUsuTSh4nGeAfM1MOtMyx1paRKg/xqI/ff2fD6iBL7Npa1VHdOl/ela8458qaoijyPPd9X2s9Ho+FEFJKzn1rLUJWa1sUqbGScx7H1XQALz37ycefuNAfdG7cfiMvRnHFry3GjJyJAuVjUahcCm1t1u/fO9q7gxCJItJohB4jWSHGmWC5kUoh/PEh/6w4/4gBlpLAwwZ48oUTquoKELIPegOsBWuxMS5DMum6Ob5/ciIlj0vpPHQlrLXqBAFtMNhah8y0yBAySU7gqc+rCXEzZAJ0muj9AFgEzky5W3tmLI9bWYRQaR/iaH3gRJtJQx9MEY/WWkCIET0bz+lstwihiAcIO4ZO5BptCUUYY2bkzNUAADRlipZWaqO10sQSfEz5xyhLCJnKm08IEhBgQA+qqrODdNV5ZbRR7k50hJTaWusIKWdGzflKxhh5vHp3rD5nNYDj7gZsXJMCQgiwMlRbAFDWgjYGgaXEEmyDIKpXazevX+seHV44d15rOR4NpJRpmroZ4ZR05+fnnRaviy3cYVNKXZjLGBMi833fhYCzN4MgMKLwfT8K/Xq15nlMCW2BBT5HCDUajfF4fPny5TiO9/b2Ll++fOrUKc+LiqJwGam5ubl6vb6zs1Ov16uVYHFxIa74eT6OY/8v/5VfqVaar7zyaplklJrV1dXHHruUpuOrV69SYv/W3/wvRsmwMyr/6Gtf//W/8XeefPLJP/2jPxh2d25cff+//K/+3pkzZ95///2jzmBpee2X/uIqwrxaaz377LMrK6cIIdeuXk+TYn9/v9PpXbly9fSFtSeffjwIvP2D3es3ryTZuDfoVmphGIae533upz/d6fTGXx5U6pVGo9Fs1eNGxVrLOU+SpN1uX758+Q//8A/v3bt3GPPd/c0oDhqN2qm1U0Ew3Nk+Wr99ZX5pVaXdYniUpWkcx6243arysiy7hxu+73f7fWvtpz7xbJqmw+72oGNLoYQQS5cvA5iDgwOd9jqdzuHmbaaL/Y37Fy9e9JHo72/0AbTWtVptv9fd2trqdDr1ej3tn3ZZPct5p5+5DHav16vVarVaLc/zZrN5796dd955J4qCl19+MdVlko5rtcrqwtz23a1+d7vbG61mwwuPPUkRdAc9y30j7bjf55yXAl979/vz8/M/9VM/deHU3PpOlzEPI8YZo5hZY5g3sSUOoDebfW4euS5Q51WgY4AVQhBjBIBba13fgdaaMUKRMLpg1Pc9DkCsRczjxhigxBg6C6M9z6lv4dLgqXs++WVXN8V2wmQ+nYaT5UuUKQDEYYisvbe7ee3Dq9c/vHr27NlfffySIyu0VislGGMI2aLI4rCCEJLaGK0nZ4ExY0wU2YMVGwxCyK0nWlkLlhBmMdZ4gk8UQiCKLGNoUoy3GGnMEEJg+YxkFGut7XQNF2A455gzzJlFSFpDMVJgA5c5wGiC8LIagaUEWa2UECXJjTYEU4Ks0koKibyT2p8+3tKaE5i5TtpoGNTzsq+MIjjod2VRHGAUpEPv3r17SZK4OUMIcUaXEBLXqlJKZ4+FEEVRZFkGAIz5Quac08WFZcrg9u2bu7v7Cwtzzz3zidNrl6KoInVSlzyQkJf7nWE5Xw217GjVQ6DAmDzv9Tqb+zt3Lly41FxZajbiPB8LRQBIKS1CfnkCByyaoRwfxt25lPUDiebpn/FJ1FPTxkM7HV9rLWCLjlOLHYNX2BOK7VMPEmbVfzRJbZ6EijSADLaAESjQSCGEtDG2RBpji7UlBCEMMz0IBdYaF/ViY0CDtfYh6So8pZSbBJQw4eGbApAmyR2PPmC2gmNGy6PyeEQ7+5NvEEIYYcAIYWuQEVYiDWaGDpt9xRl+LTRCBmOD0Czjaq212Hm4FmOMLVhEsdYaI4swmqXaZqE5AFiDJr3egCgGIBMcJjLWTaRJfhtAW6vBlOohPN2Dy2sRQsgAVkYbA8Y6o4+NxUY7FlKNEXKwc4zxyvzSrVu33nvnbUrp2trq0eH+3t6eLPNCCFd9dI6CK28Ph8O8yJwskhDCWeLj7o7jwLLW+r6PEAqCQGWkWot97lmrs2QkS2FBYzBLS0v7+/vf/e53P/GJT6RpihBaXV390pe+9IlPfMqVJKvV6re//e2XX3650+m4etvXv/71L/z857XWu7u7v/ZrvzYcpG+99fbO5s7P//zPYYzv3d/c2Lz3yU9+8lOf+fR3v/vdsxfOHt3djeL6vbsbL734ymc/97M7G9d6B8uSzPlxPL+8/NZbb1Wr1Uaj8cN33w0qlWeee6HRaHz44dW797d6vZ62qFJr3F6/51focNhXOrh16/rde3fW129ev/HB8vJyENPAj37pL/zFOKxq0FmR2J7OssKPwvF4HAf+Ur1GCLm1fufe5saZ8+fyoucFbDDu11uVZiNiBFUiv1artJsBGJ/iaqNxutFoBEHgeV6vV8arC77v+wziOD579ux4PD48PNRaG4B+v7+2OjcajbKEttv15cXGk4+fu3r1GsUi8Ox8Oy6KIkkSznng2eeevBBxu+2BEGLY2WHQbrfblOqdjTvz8/Oe53Gs5xoxY3hnY2fQ2du+f78Skqefuuwz+OEb30rT9PJjF5Phkcz7i3P1Mk927t/ARlA/LAvdaDXvr29vbm4uLhAUVHAAAQAASURBVC5evHixGVFui2J4mA+syMqw1raAQUmMCKWUEZKVY6uwS+EoJQGAEIwQopR4hM/mjvM7YbK+aYop4UQIQTHGFCmAMPSJKZXEgDQF5REitbJSKG1Vkbnks1UKACghYLQUJUb+bOezKYwQ4owaY6xW1lpkLZ1OpUrs7+7uHm3dD4Ng1D1I+0exR568dC4fHo2HQ9/3W60W8v2yLDHGUatSCm2tRURb7ERWCKUEY6j5MULWGXelS2sNIYhQazQ2BhgDrSDPBSMII5Ayp4BcSzog0FproSnGCKEUTTChxhgDk6weJkQpzAnnQYwoVUoZRDUQIJxhAlNErJ2U8SxGSMhCloXneQhjBEZrA4j4Hheq/Nh1G50YGf94oDMKyGgjEBCMidE2SwWlAhA7PDzEU7Y8AFBKSSmFEK6d0nUmGGN833fS5VlWUEqEUN1ur9Wuc+6POqNeb/DJV4nFg06vY0H4Pie01uv1RuNUDq8DRkBZVDtlDRTZUZkdYciHg/1GszoYHiV7h17QpF5daE0ZBu/jT4zYqZ17UEgE+Ahp+Gy0LPt4snI07feyU/SySx0/MtAPIqoT+ueswYAAjt3Q4AoaJ3KWWmQmItrIgjLaCosQIgxhizAABoSMnXiKyGo1wQZbC8oYA8gaZBB6ZAodd6XhmL82m2AUmZlnDccsqM8fGL/Zfqy1xNXCJ0KHriHYWquB8+M/TQjB1mKEJhyt+lEtEeridjsBbc0mv1bKgQymxVo89Y4JsoAx5tRizAyn1lqDoCinKC2X0cXg/pXimCbo8VYBzKyx2iqtrdLWACIIaWSMIS68RmA4wx4jnscoxVqKr3/tTzbvbzz++OWyyGSZWy2VkC7g0FqnaSqlTJIEALIsA2RngIkZDZZSqhLVXS7OzSbf910FB4xyqh5GCaO0UYJzhjGqVqvXr1+/cOGCk/ttNBo3btyo1+udTse9fO+99+r1+vr6ehzHeZ7v7x5WKtXtrd1nnn2q2+3u7R5Iab74v/27r//Z6+9/ePPv//2/99/8t//X3b2dv/W3/vqnPvWpf/n/+s3G3KLnR08//0qr0X77h+8sLjQ+/PBOr3s4yHcYY3meJ3mRFuXG9o4QYm5u7rDTwZReu37TWGssIozHVdY56vmhF1a8nd2t9z54dzDqFqLo9Tv1ZmVjb5cAWVhsPf/MS0vLc9VGNfIjA32s0fUbN/7061//6Z/+6RdeeOHGjRsI40qlMsoP6mFV6GR7526vu1uJqo9dfmp1ZU5I0+sc3Lx58+LFi0aVaZouLCwopXrdcZ7nnudFUXDr1o00TYMgkFJmWTIaDDqHXrfbLfJciTDP8yiKmvWKUeWw36HY+pzkyFTjgCCzt7VRCbwnL190lVEHlRqNRp948dlZGiagQLA5v7bMOV9qxr7vz8217m/c29m8lyQjq1Kt9ac+8cza6dVGrXJvY4cYESA/qnrVgLRqfEOOdOk/dmHl/Ol5V6+5ceMGsSTymsoaDCYXUsqcewGgkrLIrVzco5Ob11pMkMeIUkppBdYySgmZNERIUfiUaK1LUUpRukkU1WuhRzjDWVZoVVDMkUWFkFabMGATljo6Ke5KKQEMZZNM4fHVAwA4wUKoCWbtGLMNloVO+rv315fmFxo+bVU8OYKku/eDb9zpdruNRuPZZ5+N43h3d5cxdv78eS8MpZSuJC+lJAQxhoUQLp9prCxlbkWqlNTYEoIoCZC1GPtgMLVlSGueFyAJezubjUbD0QYIYdIic/kAz/cJIRhbg4w00liDABEgIfGoLhlFShWgddUjGGnfI0iZmRIPAFjtSAQwIxSBwY5XSassyQnjURQVJ8lEnoTGP4EY5KSNCpFhogPf49QrC6yhQMgyDkpj1yDhahJu+TDGZFnmVhmnLu5oBNxKHQRRUWT379/vdKK44p8+fbrdbl+5+v3zxdlarUYo2t/fK8ucEP/yxRfG3Z3xYOf+Pag09jHy8+EwH3Uw0teuvsM5bc2fEjqkXHuUB15MeZTp/OPPYCo79Yg9fKRv7IHhPKGx2pLJUj4zVZM/PEygMSvuniw3hma38kO/Tk7qA0aAgCAEyAAgY7S2EllIDELIYgLTyrQFAIQBC2QAWWu1dX2xrlnLhcKPFnqttYgYl64GsNNaD0IIEaMoAkaws4JmxsOuJ6glNEE/TiPpSVOSxQgDcu1h1gLk8qGWG2ItpQgDQno2ng8BLDF5UFlneNLfbCdCW8pJFuJp6w4AgJ4wfSCEKJuksAAZBA8zbSHQCCzBmXnod2dPGGNCSS2sVEZZgxwCXmsERCsDxjAKlFLPY4HPKMWvf+f1ax9erdUqjOL1W7cBmSLLiqJgQWCmG+d8PB47m8o41Vr7vk8IcdUZjPFwOHSH57SBpZTWWq01pTSi2BiFgTLGLdNaQDWurCwvuhj63Llzg8FgeXmZc/7++++//PLL6+sb9Xq9Wq32er1Lly5duXJlbW0tjmNG/ccvPr6xuT4cpD98890///NvPfnEs5W4/vjTz9/Z2PudP/jqMy++tvPHX/nSH32DBrVae9WvtbGF9Vv3AhIdHR3NL83f37znRyGhfpqm1tpKpWKM4YjU6k2tdRAEUui9vT1joN8fCiGk0EmSYIYPOod//p0/f+eDd8oywxzPLc4BgVo9tBauXb9y/vxFwtC9e+uvvvoT7fbc937wttNeTJKEUhrHsRBiNBoVstw72A58Ohh2tzaGK0urC+1WvRpffOL5/qj71rtvdvqHmAHG+Mz5NYzx7/+7P97Y2Hj88ccvPnaZENLv94fD4Ztvvnnz5tULFy4srS5Rj/Z6vWEy/OCDD+I4juO6xQgzCgTfu7uxvr7+yiuvnGo2fO4hhK5du7a+vr6ysnL58mWHfdvbP/rwww+jKHruuedEkbgK9J1b25zRubm5ne1kd2ejXosW5utra6fm5+eX52vjwZACfuaJx8FipQzCBGPMQdRDGhAt074QQiLkeV7FQ3mZUSqwodqK8WjQG/UWaJN5ZNgdujvKNVg7wRLGmHtip9Jtxpg0TYuiWKhXqTFllnV2d/M8d4swNcZfrVKii2yQ5rJWb3k8dBjjOOC9Xi9JEmd98zx392FzjuIJGGmi1GIc9lQYqxQF4JxzzowxSZJmadqaq1YYrF99753XBxThZDQuy7K3t2lNlmWZ7/vj3fUwDLe3tz3PS154YfnxSw4kEUXRaDRyq0Sv18sGAwAwVhRFmhdjpQTChlJciZsAuBI3XKLeW16rBwvWE2+vXyuaTVcGdUXPZrPp+37sEWINMkhKicrSVXkIIVaM0jSllKZpyjlvtVpOkztjkRtS5xM4ijSELQY7HA6zvKzU6n5UBauVKAVjJ0e6J/Z7/Vifp55PTWmEzI3KlARErTFKy8yCdnk2xwngsP5SSud3uxVNKVWWJULIIfjdHeMZL01T7uEXXnjus5/97B/90RePjvr37m3UGzEhOIp9ZzuUyHvDEcnSFYLq1Tltk6JMZJo26vHCYvvC5ctSh+OMlJpqi6TQiJ0EIz7euH3shPFD6D475U01J+gBoxkjOXooXpz12z0ymie1YWOYsJ89EgET9PEm29ExIowwEGS1tWAMGKOEshNbgxAmCE2ZegLjuV5YDUgbsBMzbO0xAWp7jNPRGUo0qfMActMRkNElEIsAYUSMy/NaC4CU5HAsjJ4WjcAQgSaczxMv2YGiC/FAPgxjSynS1mAMLgk7O4wHKW48GWZCyLEfmpRwZy28s7hcliXAJIOMKQaKnEySzx+ktQ1CjsbZWsvYQzJqs41y5mq9k3oWdvkq6/R/ESAPu1ZdTCnmFP/O7/xOp3O4uLg4Go12drdOnz6NMfY8T0wgspoQ4qxIvV7XWlswLgKeob4BoCzLYX/kZgqltCgKZ6SDIGhVA4oxYyQMPNAmScZxJWy32w7q7GJlp4jwi7/4i0mSPPfcc3Ecp2n61/7aXzs4OPjCF75QlqW19vyZy9vbm88+86Lv8+9//40fvvluMpJ/5a/81ZH4/vvvv/8nf/qtX/qlv3Dm7N39/V3A3t/5r/7+177zg/Xr1+Nm5Sv//kuf/exnOwedvLQ09rXUUVzlnHe73SRJFhYWuBfked5qzzPGmMfTvDg8Omo22xZpwijj9Pbt29/7/ncHg14Q+JxTAPNn3/izp589W681t/e2jVF7e3t//EdfG42S8+cvfvmPvmKM6Xa7v/N7vztKxhcvXkyydG5uTsji6u2bp08tUmQAKanyD668v7uz8/QLry0tLXHO+/2+tTYMw6IoDg4OVlZXu72em1MIY8Z5FMeNZtNa64CiCKGVlRXP83Z3dxFClUoliiLXZh3HcRRFp0+fPnPmjLuPbq/fKaU4dXrtuReedxWQOK5+48++HsfxmdNr9XrdVdnW79w+2O28+vLzlUrlcH9bFKkS2Gq5trq8ef/2rVu3Ll64tLJy6r333rvywdWLFy+/8MILGJlKHAQ+A6vAKilVno07R/sH2RAjqnWkrb++sbO5t3kmW51fbNy7NbDW1uv1paWlOI5dyoQQbrQiGBFCHa3paDzc2dnpdDr0wnlrbafTuXr1aq/Xcx0+h7sXH3v2NFi8s7OXpMXq2vlGc14ry7k/ONi7fv369vY2ACilBoMBQqjZbH7uZ3/OwYAdBGyKANeHu1sO6FCr1YIgyLJsb2/v8PDwhhw1m01dJCobAaUBRyHzZT4Gk1R9T4hk8841d+vWarV8eGTVipEFJ3HoQYaEg3Cko6Mfvv5djMFYJUReirE2gjLMGFmYP2W0DcMqJR5GPB8NssXlPC8HR3tJ/2gwGOR5LqWs1+svvPBC7dSp/ubGjFs+z3PXpIQx9jje398nhAyHw1qtFukz4/GYc25WnnQG2AGbZuvSeDze3NwwFq+dOXu6Vo/jWCoHITkhc3kiM+OPaYDLNKM4xhgbnSNrkEIYMc6J0I4XCVHiIYSswa4woIXymQcGijTXSlFKfeZFfqgVsjZDZNSa09qkL730+PwcfvOHf3zu0tK1a9ea85UwDDzP831/b29vsH5P5kUU84gbm/XTkiwvXnzm0svrd2/evHr79q3u3AJtzi9JZKxU4zIBPK6CDwDGTuq7CGEXOgqjZ320ABYDcvIG0pxg8E5K0aMHDMgP/rcQ6PKjYRxCSGoxiybxjDcLoZAZANAWuV4vAwgs1mAr+AG38zHDZnOLwcLEK3ApIgoAVEnqDsAYa/SD6zee1BhmyWFwppUCAGBjLQDWE2g0WARIE3scezW1bSGPS4vKEhwBOMCMZNSliB/cNM4p0bokhDBggIhL/ihH94gZHEvgS41AGwAT89jBppQS1jrBYIsQaIQIRpwQrcBYlZWCgEUAufYAWQBqrQYw1koHZwv5A7SksQYp5BqZnCM/hZwbjKwj+4y5sAZNR3dSbwYAgWWh81xpY7kGrKTFBAijWJVKlhisX6tTBFEQiyL77X/7v476nXargcAopdrzi0KZsFqXUoa0xBg7Ie2s6Ftr+8OCMTbs5YSQ8ShxISwA+L7fbLQK5u/t7XFKQBtTFBKjC8uLjWbNYt3vjbkXb+0cEmyKUefUUv1TLz9Zbbf7/eHt2/duXL+ZpqVWNk2zWq02v7j89NNPv/vue/v7+0tLS0mSKKXiOMbZ6Od+7tMy3a+3zv7nv/rXDrcHQsnf/cPf+dmf+wt37767v3Oj13nyv/zb/9nS0oJRKkmOdDH2fAI+Wbl0LkN6VCYLi6379+8rbT//+c+PRqON+3d3dnYuXTzPGC1yYyTpDYedw+5w2F9dbZdlPjfvc4/vHtzv9Hf7w26SJlElynMhpTx37vHecGBxHseVL/77383znHP+7ff+5Nvv/cn7H77PmScKqZT59utyZ+fiE0+cuXtnfa7ePAgiLW0hRZZL3T3iHq0t1e5trq/fvdmc97M8LbTmoL7/5reMwcyGC+16kQ6xlVc/uPLYY4/tbR+ALr2QdQdH23ub8/PzURR1u13Ckda6XqlapbWQo/7g4rnzu1vb6Wjseb5SMsvz5dW1vYOjQmhlCCBCWRBEaGXt4uHRNvaQQtKPY4P8J5569f6tD0O/wShPkkIKU6kEjUZLCEH8+Z3DdwzdfvaVT0TNZi9LDeMLa+fTD791ffPDIAjOPHH6xRdfDrzwzt07R7c++PPXv0YIazbmCea7u7ujcb+zE9ZqlSxjg8EQY/pzP/sXVp5+4er1mxv3t2u12qXL5/v9/sHBYbVa8QO6f7B19971Gzc/vLmy1m7Pd7tdgunB4WGn0wmCKK70s/z6zu7m8ko7CPyNWzdqT30SVPzN775TafXX19fH47HneVprDNCoNypRtn/rK6KUUloE9GC/2+kMOPOEUEed7TNnztTr9bIsXd6lVqvt7u52u/er1SrWJYHx8sIKY969u/cJwcRrSiUw9zCxuUqQp2kouuOttfz0wc7O0e7ds2fPViqVo/5RlmX1KPyZX3z+a1/7mgMwugCvzBXkwOMRwR7HczyoFrn+8NbG2x/o8TjleIkQkmcl46SUGQTMa+QHybVeLzRGjcZ9hFxWGWsFBwdHPNI1r4qHKj/qzvveY2fnD3IzKAdEfph3D9MkjedXas3lvZ3B5sYBAg77N2orS0fjXvtCfKp6+qArWNTOc6SQQtjm+diC8gNallmv3xGiqOje6upqmqYbGxtCCHcKc3Nz0HrZOjlxRKzBgLi2TElrcc/JnblkmCtJKKXoLNSYYrvBLa8zOPjMZqApT4Kditk5l1MpNRqNEBDu6/n51umz7STtDgajQf8ORqw9/9SZMxcQQkdHB0edAwCT5/n8/BzYPC8ypfR888knLr9aqTQGo50k2//Jz3wuiOrNZtMYk+e5tMAo5T6DY8LO2JEAWwBkwYAFQyYQXLBgNbIn8C7/qI2c8JUpZ/sDu+2GRdtpkfKhFjqLCbbWYoRd7Df5/MNy3hbA8UlaAMfaf3zP7tHJWrmoFI75VUjbY7uZPU7A2+gjlD3HvYdHLuiDNO/0HXSs6Hv889ZaAwQMBuVIX50DAcaAmaK7Z7tyTzJdTv0MC8hijDAiE4leNxoWSQ0EsAYDYMSkUd01XKEZfk4IhaZ9xq7T2PkpTh1rGt8e6/2aqi1Ya42x02Qz5pwTItwRWUAIW2MsaFWWxvcqvkdKoQMvTFLx5g/evPLh9UolAjBJMnIsEBgzrVWWJYCsa0Z0uCqMcZ6JQZkBGKkm3A6c8yAIEIKiTKvVqrV2PBwYrTzPq9VqxpibN27ncoyAtdpLW1u7YcCYLcsyWFhYSJLinbffv3nzdq83YNRjjA8H48ODTlaISqUyHA77/X6aps62jUajlVoklTh9aun+/fuNRuNv/I2/8b/8b7917/693//93/vlX/pP5ubmVk+trC6v9HqdN956iyDUarWGw2G3252bm/M8z/kxw+HQ88P9/X0hRBRFtVptNBoRQhhj3KNvvX290+kAUisry5cfO39wsPflL3+5m3Q4552jfhRFStrRMA2CoNloFZpSQsejbDRMJ5xfmGutEeAkSTj1XEhab9QuXbqwurzyu7//27VarRR5o1Fvz7WEKJrNupLm3XffHQw6nU5HyNKRV9+/tz03t/Qrf+GvSikdnzaldDAYbG9vb29vex7p9Q7fe++tVqt1+vRpxhiAyrLxlQ/fWT218Oyzz0QxZxwuXT47v9AY9PYV0hjRXAyDmAJR+0ebzUYbY9wb7rfmK9JG46xvsRSqTFIBRCRFUqiCAY2r1fZCO02Tg85Ba74lVbqw2KxUvTvr17e279YboVTZ99/41tvvvtUfdu5vjqu12plzp9vt+fV761s7W0IIURZpIjjz8zzX2iTjTGvZG2R5nmNErt98u9vbuXnz1miUNBvtYXpvPE47nY7v+0HAlc6oJ85fXOgdDAlBe3t7AIAxXVpaoJTmedrt7Xa6+xYlzWa91VxoNMNWYxUAvvn6v41iFsVNh0gQQozGnf2DzWbsM+YZJYtcFnIkTaLKPM/LsOIFMW/O1ba3t/cOt4MgyEVisWo06lobbWSlEp06dcr1mu7v71uSKasYRmElxIQKURik0mJ4994txli303/3vR8SQpaWlgDg8PDw9NnW/Hy7KLL19XXf98PQx5hWq1Up+sDMFHJU5IXMszJJkyIp/sk/+Se+H/7hH37pxs0Ppcq2d+5pU4q0gTEdDAdSaCllUWZBEBCCCLNZmRWDZDjok/305nqtU3RyW4asmaRJlmfbO2I4HFrtK53v7twHUQA1tXqQpEebO9cUBNUAMKc6z+M4LPLB4cGOH7Ao9mR5tLV5P4ZE27G1tjfY7vf7ADA3N1drsEbQK4WWAhEWcj/WypYipRRbo2whAaGIUsIpAFirgaGZapt1vEUIoQkW5mE0l53y1mLsIEYGY+IMtgOVIITzsqg3+cL80ipfunv37t179zFiyhDOmR9QxtjjZx7nHtrYWFe6QJjVGpHR9LC7DTc/8L2asdJar9FaYDyygJVSbqEmQJDFdmLCJsu9C3OtscSpZEwjQVemNCcTZZyU08cnpBQotbMAd7rigzFG44d0Qx21BABg7PTAEcbITuiKYWrsHkDBpt99SDDrod9lDxhqjhtCYun0+YPH2d4A8KTW67gXEXqEnGO2f3VM+mV2XAhN9A0++ruACDjNP6SP71Cjhwzw9DCgMCVMjLrFGAhFBCHspKsMMtYajTBMQlRkUamczoHFBGa5d4SQI0gxFpCxGNtJa9GUWOORU7PWSmustUY7kmqYYtGtSLKykEopsAxhhNGE0stiJjSAtKBltUo3dna++eff2dw5iDkAgJRSGwXIFmWeJMlgMCCYMsYYYwhwWYjJvABMmGGMWUuLoihFKlXuMmPUEt/3RMGKXIRBvLpyilMyHm90h/vt1hJjrCgzAFrxwPe9xcXF//Hf/t7O9l5ZijQp+r0D3/eNgSzLXnzl5ffff//atWvuTkrT9PLly0888UQFy+9973vnz/ylO+u3fvN/+J8+8ROfe/HFF/tp9+WXXnzxpReCINjZ2dna2Jyfn2+15ra3t+U0A3n27NlOp+NqdSsrK8NR4uBjzrwF01L3H/7hH968ed0RPyXJyJ1UrVa9t7vFGBPCcG4PD3vdbq9arSoFYZVqIEpqpxSCANJEWmujqCKEch3S6+vr/e5ASlmv1glBjIVKi+FwbIwCZKMoiiLU7Xbv3Lm5f7CNMHDOwaKtrd00Lb/81a84F+Huxr1ut1ur1a5cubK3txdVyWAw2N3b8n1/d2+rWq3ev3+/3+9zypaXlw97W4e9rUajobXe3L09GAwwRbVa487dm73eIEm7B4f3z5274HkeZ2GtQW/cOvjyV37P87zlpVOt1pwfxk8/+2RWJHk5bs3X49qT29tbvX7/9e99z4toUvRRVnzre3c3NzejsKruy/evvnPv/l2EUF4kt+9c//Z3/tz3wvfee29/f78sZb83TJI88Cu1Wg0hVBSFNhKQYNwaI/YO7hx17/f7fUrpKEv6N9aVNEUhfN/nHsZERzFnHtJGjJNBkg4AII6qCPOiTIsyrzc87tkk7Wd59/BoT2sdBq2tzX0NqR94rgwvJXQ6w8HwMMuyrZ1by8vL3PO5x/ywXmtwpUySJLs7B0qnYUTac5VuV1y6dDpJEsr00WEmtFBWA+gkH80tzr3y2kvWojTL9vb2ev0OQoZQ4gdeXIlarQbCIox8Qit5EQ+Hw8HwAABKMb6/MZyfn5+bb/UHXSGEVCXn3PNZtyeMh1yVUyptrMBU+qH2OOG+pLys1GizFRXleG//flzh586eXlo8fXd96523r/R6vSCk1TqmzAgzjL2gtcyjKBRiePPuu520SyMv6d8uRU4I8XikJCoyC9YjJABKB6MhD+1Bb6NfHnpBHCfbmPpI4SIne3s7Gxv3othfWV0QRabEdr/syu0D3/ctETzMrLUKbGdQqn2BSIih0vRPt+sNKW1emrji72/u93q9PM/jOK7X665T0YXC1Hn0LggmU43SR1C+DisIAL7PJhAUq5RjocLW0TIUpR0Oh3t7R612JU2LIpe+z25cv1OpRmHE4ooXV/jqqYVLl89b0OvXy0aTlLJ7dHR7mAzPn3l1beUpSoJxrgOraZZTDpwzZEAZsNKCs2DYCYcBWEeoNNUdcjYUTbi5LQJ7gqE9CaN2UgRMrOsRmggAGWuNNcgaRtgjhsoeb4d9oAQ8KS0bmJyCO2ynIWE/rpaAJjwvk1cuCJ7uDVE9Q2s/eIQJ9ylYMAgBsoCQ+xuyD29o1iY0LQkfHxMEoM0xo3scPj0FVRmjj/9J4+N9w8dR4s62G6eRQRAQMNhCVjwYJWzBTrUolFJOx5CQSXMRJoAQMH8yztZY0A8S6bM66yOPJZhpCtrFxBosBrDjPDUaY0ysQdpobY0FbZFhzNNGCqV9SvYO9779zT+7cftWu91Syb7neZ7P81zneVYKrY3yA8w4eB7mnFg7Ycb2GWOMSamcFJYfIMZdH7AlhCidYcIr1SAZ96VEzVZDFuXa2trBu5vco8Zoz2NClBLD3HwrTZPvfOuNOI7PnTtXrbSUvN3pdAgh7Xbb1Zsd69DKysrLL7+8uLg4Ho//+E++9Hf/7l+Xsux2O2mafvWrf/RLf/lXfuM3/s+6MFrJIjNWm1t3bqdZHobhOMvmV5dXV1cxxmtra1euXJmfn280GkdHR7V689lnn5VSvvHGGw6iUhTF9vb2vXv3AExRZlKKXr/z+uvf2di4f9Q5EKXWCqQwve7QwVs8HuaZGGd5pVLhnGtl8kxlqSxyTQgJA6SUMRSGw4FVtnN4BGAuXbgIAL1+59SpU472Z3FxvlppPPH402WBbt++XqlUSlHs7e3Va40oijDG6/duEULOnj17dHTklrPe4KgQ6d76LqWUMZbloywfMcbG43GSJI1mfHR16/a9K5zzer0+Go2CIKCUKqPn5+ePDrsHBwdlKXw/PH36dK3a2NraQgjt7e/UD6qMsa3d+2EQY4xFShBCa2trURSNRoPrt64nSSKEIIEwRs7NNw4P9zc2NqrVehhUAQhgOxwNueeVsvzqn/zRRBMTiMcDhJJknJWF9n0fIZsXOS0x9ShGVKhsf3+XMVatVirVqNvtEkKElEJKqXKSI0JBaR4EbDQeYkQxtp4XADLd3oHRUKvVPN9vNKuejzBGWpuDo/tFvr69tX/qdDsvRpTSWq3GONGmQFgtLDbvbd0wqAjDMIoqQRB5keIW/DgsREy4TvJeox0JnfgRzoUGImqN2C8Z5Wg8Tg86e3E1vnDhwsLCQm94RLyS+kJrZUHneZoWA3mUnD732P7BFsb49JlljFedLCYgqbU9ONhrtVrPPvu0q2pbq8fjodZIKciyQimFiaUMRxWPkBBU8/d+/7eU0ox6gMvB6EBolpd+EERhTCwqqjXP85uIKCDjUmVa9Ynx/LBRX2DDgeyPd3b2dxGjRjMH4GrPt8ejcntnY2314l/65V989ztXdg7uWylkkonxnrZQKhsE0Xyjlud5v99NkpEomSw3MEagBWF5mo8BR77vK1OUZZmXaX540Btv1yoLleiM9iJU1MaDYad3EMW+STvD/c2Dg4MgCFZWVmq1mtbaMadSfWzDU0JB0A8iMHg4cHTla3uMIYUxxj0UhDVM9K2b6+G2Nxz2Maa1Wo2wwtgyTQsLxd27YjTux3E4HPa37qnFNF5dq1Urre6BGg8FPVWpxi0/wszzLULaGIQwBnCxk8ROrgQTBAgsBgTOEiBqrXUiCMgijdAJxfGHzNtHN3xiY/VDuigOKGStRQR9bM7WbcbYCTHEBAJlj0ecADOuj4mQ+yO1ZACgU3m+CShsCg0j5EEg+9BPAwKLZwAyB1L5CDb8wTb77swkz47/0T07QwtoVrc+7jTM0GgfDaZhBm2z1gXWxphMTIlKHlwOPDsSTBA2gDEiBFzzFZ8a+OMjDAD4GAcsHLtRleOs03ZaRkEABizGiFNOjaFlqZUUGhTGBmFUiD5nVOvCArl188qbb30LQVqrzuGwOpkaJiuFxARq9TgIAsLKPM/zfATWhrFr0rPGFIShw8OjsixbrdbS4hxCKM9zpVRIK2ma1ivVXhcQ1p5HDvYOW+3G3HyrVqtIVc7NzfV7R2FAnnjiif2D3Swr8rwMw3hlZeXSpUtay263G4a+q3xfunRpbm5uZWWlXq/fu3fvrbfe8n2/VqvMz89//vOf398dHvXSz/zkp+bm5o529jr7R93+YHF59ZWXX93dP7h665bvhU8//fS5c+cYY5ubm1EUvfbaa4eHh+vr66Nxur6+LqXc3t4+ODhwE7zf7wtRhGEYRmEct/Iiffvtt9JsjBAaDFLf9yuVahAESZI4j2c8TkudIEQqFWIMMOYBgDFACC4LwRjHmBoDS4vzoR9EUdCea27u3EvTtFKp1Gq1zY1tj0cEe2lS7u93KKVra2uDYb/b7XLO5+eWV1ZOZ2m+t7dHCBqNBvv7+64QRilOklGtVqPUo5Qao/JcEIIoxe7R9zmldDwe7u/vIYQajYYhFlHEApYWab8/rNfrG9sb8/P5fmenKIokSdMilVL2hoN6vVaW5e5GL4qipBidO3euWq1aYg+7HWvt6HCPMUx9UFYjipM8yQoRhhUAO0oyzpU0ZtAfeV7QbreNEVFc9f2AMc8YSJJMa5kXY8+jFdxkjFkjR0lCiKzEDQR8NMzr9XqelaNRniaZ1jqK/YXFVug3lOpy5sDkKkmS8XjMqBdFUb/fB2Q9L6pUKo4EW6hE21G3i2Zt646+MI7jVqsFUAhTJr2xl4x83y9L4ft+FEVBxc9EevverYsXLybF+PrtaxjjQhYLc00pdRT7QejnWXHU2bEgNzbXB9lhr9fLsswPuOd5GolC5mmhx1ffcUpf2uRSym63mxcZpdTz/SRJxglZWVlZWp5P0mFZlsbKwI8xBil1UWSUoSBkfkCjKNjZPOx0etaQRqM1Hg+Ho25R8qOj0vO8/f39LLGLC6eXV5c3Nm+Nk06zFUmFur2Dw4Od+bk53w9Dz+d9NBgNpUJB4Ak5HicdbZGBMab5/FLcXlw66O0ZKNM0ycohZjTNRJGl+eCui1OjABdFstvf0UZijKv1SGuNiREyOzg4SNM0DEPOeZx7nmVYhUNS4Zbv7h9cu3ElzcZPXWbJuFfk3Sw1CDbLogUAaZpOlOdddOsqWI+s1DOT4DYpS845557LXbtGMa11UQjP8xBGw0EKABgx5lEh1PMvXXDiowjgYP/oYL/bbreTJOE+kZouzL/65OULu5uCkooX+I05rlTAfS6lAGQxBiO0sWANAAWLECWIIkSxITMZQiAarDagDFIWjEbIiW7+mCIc5gTDLS0gAKUNMjMDANYCMVOyK+sCWrDWoukYaoucrp2x4HgztDWznDM8bOpmJvChwTf4QRg9McQIwHUzHUdgTV4aa10L1MTqgZ2oAH0EfT0FNM06fR/sHADsMQKT44/K9R47tPQkrWsB4AGvyaQfe3KCbPpbGE9ZmQGhKRe3MgYAGYsMwoAtAkKBInAOlMXEIuOaoYA8Cnab+CgzatJH7tgSa2uQ4812WWoXASNMwBLHNAsAjBFMsEVm4+77CEGejaqhf3hwr1HVXquSZ9uRz6W2SinCyrjqWBE0IjnlmlutrZZSKlMizRhjnFOjWVzxuIeCkCLsGqpybbRFRJskjGtnzi0RzOIq6/b2uYeeeOIxSvyDw36lEhf5qN4Iz549fe/O1SiKgiCwVh8dHbTnmk8/88T+/j736MHBwWg0WltbO3fu3HA4fP311w8PDxcWFp698Pzi4uKNm9furt//1Kc/2V5YG+bjN974/lK9NR72x8Ph4vKy54X90XBnd395efXtt99+//33tdb379/f3d3d29vrdrtbW1t5Ifr9vuM6oJRubW1FUbS2thbH4db2RrVaaTRqm1tDY8zKyooxSuOBECIIvEajprXs9/sIWc9jBEIAKMvStTCFYeiaIyg2WitKqAuv/YAn6ejo6CDLEmvtnTt3FuaX8rwcjZI4rm9u7r7//vtBwBDWZVnWajVCSJZlQohO//Cwuw/EDJN+b9gxxtRqNWttvd4khKRpHoYhxtgY4NwzJs2K0vM8i3BvMJRS+mGU5/n6vftxtSpK02i0sqwYjxOM2GiY5plsturD4YiSwFqUZ8M0Ka0dHB4ehEHDYH3t1hWD9M///C+srJ166913+r0hCXSlGg3TglIa1RpFIcrClKMMG12vtaTUR4ddIRQCr3M0KEvRmrOO4MgalCaZ0iUmllLuMPYAYLQtimLQT40mokBHByOljMeqivM0TbPEdg5TiiOMuOcFnucfHW0VucCYYkzH4/zgsGtBNxq11VNLhFhtJKUkrgS+V1FK5Xm+tbnvyueMsTQRC/NLxhijE4eyFqIEsMboTqd0a7trv97d3W00Gpzzo94+pbyUpUVKg0zyEU+47/uYWM+nQqIsS9M0cQ0yQohKteYmqXun3+87vJJSolqNe72ulOXi4mKjUet2u77PKQkQQkWRFVKXpSrLUgothd3d3cOYloXM8z1CCFiuJKpUGr1ebzhMR8NcqrKU8/3hfpL282KAtBqOxkoVlHuViq1zLwzjIpdSFZVqJERx+84Nzj1Aau/g/u//wW83grM8VIag7n5/MO6FcUUJo5XtjrdrtVq1Ws3zrNfrSalcc9BwlCilKpU0DMOi0EriNJFjU7KWLYOUol6RVW2rPj/n9XuVjc3O3a1rjDEembIs+0lWmo7LPVMXgR1Xxp3mEo/1Yh5LMKJpD6rTCSYEFUUhhCRYlyKnLPK8II7qQhYAqizLo9763NzC6qnHw6B25/b21Q9vJRxq1VNxS43H+fZ2r1GJn3/umSisG8gtiLRQmHtKG0Yww6hEANpqqRGbLMGUIE4QsYAsRVYDwgaQMBZrsBq0RU6K+STKyZNg5ScEwKABOx7KB1RtgCxYfCxDMLO+cMwAWwvGWkeUYREo80Bub2Y5rLXsI8QgzkIYcxzt/MA2EzwJiGfH7F4qgwAsgmld2U5efjTinxjgGVHXNGc++7O1dsr5ddwMT1R3EUYTUVX3SGb7nN0tFiFElcumACEIkwf6ypYQZQEMkhqMBQvIIGzBEmAOUIdc6+8kiLfMmJn1xXjCfoUQEupjcjPgHIUH0HE3bgacbKERSiNrgTFmkByN+v1h78oH3yzylBGoVUJkxOIClSKTReewIxGa6EmEPtNaF0VaJEUgAlepUUoVReFkeYIgKIq8UvUJiZRS/cGhK+sAgCpHBDOpxssrLc59Qg1lBpBYXj7T7QzzPC8KUZZltTrv+3w4HEpZ1moVz2fd7uEo6a6uLi+vtBGGRmNhbm4uDMObN2/euHHDkWS1Wq32XLMU+e7W3f2D/bn2mu/zzf3hzu6WGAzn5xfPXbxQSPutb3/n7uZOofTewWEpzWAwmJHZ3b59GyG0sLCQ5aWLjRy79c7Ojud57Xb7mWef6A86UpZb2xtFkc8vtLWW4/Hw9OlTe3t7aTrO89QdTK1WqdVq43zgZsF4nEhZKiWklEEQVMIoy7PlxcVqtZplWVlkRZF5jC4vLxtj8rzsdruDwSBNCrC3wjB2de68GPuBxznv9wbJuLh9+17ciBBCWZkFcVBr1sbjcVZmSqnYC0QpB4OhUytRSrVaLbCY8bgUUsis0+lrrVdWVhC2o3GpIQfEtRlRFnqeTDOFMT7qDDFFaSLzTPX7w7Is5+epBVwKDWjoQ4gxPTjav3r96u7+DqE0iMJC52UJe3v9Wq2iNU2SzBqCMTZCVKqhkLmQYC2TyuZFrpTCdDAaJtYi1+xrwQZB4Hk+InkhSqVNGDELqtfrSak9LxiPh4SwarUWx7UsLbI8SZPx7u4hRaCkrVapFJZSnzOPUqqkadQXR6OBFFgUyIKyoOqNOIoCnzUGg0FZ5EWhlCpcn9t4JIz1EULGgI8ZwtgLAkLIKEmkQkVZxnF81OlgjEshur0e53w8Pmo0GkoprY0oFcYUc6i3qxvbe8zz6qyW57mU2hiDCVXaLC8v37179+DgYH5+vtlshmHY6/UGg0GrXW2320qJ4bBfr1d9nweBV5a5JtjxtnIVaKOEEAORS4GVAqPNaJhS6jcaDYwQsrjVXNnYuuH7fqUSGJvmRc/3qZB8f/+oGFrGgQVelps07xXClJkQwszNt6IorFRCISJjwPe0kujO+o0nH8csHhMqo8LkShV5f9DLjaaFGBtLlaZJknQ6fUZ5pVIxBo9GmVIqT7NajQVBzCnkeT4ej+caCmFpUdod3qZBubh0eu1c1aDGB1c7ronZGKOUGqepa+ymbiq6jJOjQZgYiWPc8cfLe455QynlCAc45651rNGoK6UqlapSKsuKfr/baFaq1driMq7E3qA3ItirVmrVSqtZXzl75uLV228iTMfj4cHRRrt5ukbbaeJbGvq+9nigdel+kQCi1OMYF0hMjosAxogijI1FQCwm1gAgZKzBFpABhIiBRwmYHmwnGFpzAlcztsQ+HGYhhACd2AfmEtQGsDPAFmGXbp0xa81Kri6SdgZ4ls+fZbyRxlPrjqyTa3AvvY8//ke2WVQ9C7jhI2Va+Ij1Ov7mI9lpbTVCaNJuZB/8c4zt0y8++DpGFjv4FQZKCCZTj4hyoq3S1hoD2iiDwTpvgQAQAEeviZ3rAgCIuhAbWYuOK6VMHR6YptxnETxy4cWxsbQICGHEKYUQQhAho3S8sbFx5+7N2zfflrK8cGYtS0ZZOkJaSJHPtWqdfg9jjLDnPC6EDSaKMmM0KQvp3FZGQ4yxkmZYZsNRp1qtMsYcCV8YhtbaNE0x0ZVqmOb9eq2iDYzH/VotbrcblUrU644AoCgKz2erq6utVmt+fv6ZZ5/Ksmx+fu7U2nKns4+JPbW2/Nhjl0YjfPfu3f39/fF4vLKyQil1nSFOpSAOLj3++JO72/3vfe97C6dWzpw5owfp2bOnh6P0W9/85vd++PbqmfMXzpzDhC0vLSVJcvfu3bIsnbxBu91WSuU7e45pyI2aYxTp9/vXrl0riqLdbl67vlkUKSDT6Rw2GrUsTzFBjFNrbbVWcaCtjc37S6tzjomzLHNjjNYSwASBp5TSyq6tnW40a0f7e3mWUEopI4PBIIqilZWV+/c2GfPimN6+vX7q1Olmq7K72/EDWq1Ver3ecDDiLBwMEo3VwsLCrJfD2WmllEhLjLEQSinj+qfn5xdbrblcql63zznXivR6QyX3MMYer2Rp6XElylEUxWFoDvaPwjAej3LPo5wHhJCyMAhxjLkQuiy00GV30G+35/eP9r/81T/K0pwQZhAEfk3KspuOKOXW2m5nVKu2WvMLvaOdra3tspAIkTiOo6gCFuV5TqnBGHNOMWJlKbVRLo9YbUOSJFKZ5sJKFHt7u13K0Fy7TahJ07woU6MRJjgIPKkyAEOpX5YKAFfiOgAejUZCZAghzvl4VGSZiMJcm4JQGcchAB4Ni/29nrW2VmsqpdI0VVJQSrO0JIRggpQCxlAlbngek0JLzzrejLt3787NzTk2YqWUa+Cw1jJGKaV5VnY6h0mS9IZHtVqNc98lfxjlYRhai7rdfqVS87ygKIqtrR1rrdZGa5vlyXBEuEfDMCxFro10aZ7AMw5+H4bEWptCWhSFFICAGaM8L7IGp4kwRlNmDvZ71uBZIiFJh6PRSCvIsqJVPUeZNqS0QCwAoz54DGze7fR3d3dPnVpeW1sbDAbJuMd5GIXBIL1XiqxS9ZZXq7UG3d3uJ+MMc9wdKm3HUlGldF5AokuhKMaY4YoXEIxxlthkNBFNMAb7Po9iblG+tXnn/vbNtdMXGI12DveyEoZJ4i6Qa0BCCDHG0MLp9vFcqPPu0VQZ1+UNrLWe54orJq4Fg8GQEj8MY60l44h7KM/TIKSMBQg4wbzValqQjJvnX3gK07LVnAfAg+GRkNmN63dHffyzP/2XN+4Ov/v9L9fb5Kc+99mnHv+Jev2cMT4lnFuFiaIeAEOlUFlhtfYwDi1NkZWBT8DKyPOxpeNBHvk1a/uIMEQ9BbjUUEhTajCA7AlcVScZZnQCQYfV6mMdEZdKRRYIuHAcEAABlKAHpvp4DfWk352BicwxvDIAMDTho5gZUffoT0Df9viHrbUZBDA15McrtVp/PPXmSdtHaxBuM5AfP54H2wkOjWfV7HaaPaJZCmW6zcifS+x99NettRGa9oFNvz4h0mMPFJOOjzOZMlk6CVLnVkopgYadTqcaR0LmcYS2tq9+8OH37t2/Eam83+9T5gg0AGPked7yyuJwMO73B54XjIZJkhSBH2ptMabJOE/T1NkY58O6ZhuEyGg0IIQQgoPQ45wXRcYYC+KyWq06b9UYkyQJISTP80Y1aFSa2VhZRUHin/r0586fOX/1ww+v371vrY2iyE77DnzfX11dLcv8qHPQ7XaN0bVahTGmjYzj+CeePBvHVSnU7u6+lPra1VtxXHnxxRfHXNy5c+f3fu/3Tp05vbxyant35+LFi7VarV1d3d7evnHjhrUoCCJKaRxVjTFKovF4rJQKw9AptjozjEOWZRnnnDL8zjtvd3tHzkcvZOb4mSuVShiGo9Go2+1aa1fmY0xMnidnz50ej8frd+4tL59SEqIGc/ZSKbWwsOCIrIMg4Mi31s7NzW1uboZh6Pv+cDis1+u+F+/u7mqtL1y4UK1Wb968eXBw0Gq1/AA5KK8jXijLSaZUlhNeoGq16lpdXS46bsQHB0ej0dj3Qkp5mhRZVgBArR5zTtN0bKzSWghZhKFvrV4+tcoYS5JsZ/sgz8s4qjHmFUXB8ERokjHPGigK4dbQsjC1egiojGIeRr41pCzM3u7h0uoprfX+/i7nvNlsADKMMUIQ95C7IWe8b+6+rVbrbkbYYyKhCKEg8BhjRVF0Oh3Hwel4XTihGFOtcJoUo2FRFgYjznlg8dBlXzyPVSpRFIeu7ruwWB0Ohy5nU5ZlFEWuQc4PaJZlQRC4yeU+XK/Xu0dFv98fj8cIoSiKwjB0oKEwnmB1HduGtbbRaIxGIylwu91I0hHGwJiXjAtR2k6nV2+EjXqLMdbvDweDkbXW9wLOudTDeqNarcaUYmOllGUp8ixLZelRCkFIGce+77ea81LA1tbext1hWeYAplqrNBoNBHg4TPu9YVyzDlGMMZ7KSpae51HCXfhDKQojPwx9z2MIw8b9bZfWmo2wWzracxVtJGO00ajFFT/Lku2drf39XY+sCSGUUlLospRaGzd0meiFYYgxCYLg8LBzsH9Ur9c550vLJAzDspS+HyqlxqOUEJYkiVI68CNrkZQyjsNGM5YqPersP2A5OI4AAgAnvTAxBoy5YBcAELKVSkVrbWyOqTYggjg8e3GJMnn//haAV60tYpZqZa3lB/sDRPtJktVqNSlLIYpqNR72xl//+tcCv864jaJICZPneRQJSgj3iRyZShh5AU5FYgz4vq8UL3JRZP0w4IPuaH93t16tnl07zwgeD3tRjQLCYK2xRhtkpjnYk1LKP+6GyKNiDFOgkcNbg7HgcEQIkJ6Gnh/dz4mGzTxqSKafnyGUZ0Ezgino6Vjn6/Tl5E5yX8TWGiex+f/PuR/fEJCPGl93pB9/Xi51D67VyAkqWoSAUjI9RgQWYTrhg2bHOq0fitGnKejZYFhHrT3thz4+CDAdNxcuu2K461cuhKxU675PN27c2du5ubV1ddDbKMqB5xozhC6KotGotVqtPM82N7ZrtToApGmqtfU8z6mnWWsdA+ssMXBs7gDnHGMkhBgMchfuV6vxaJiBpZ7nEewVRTnoJ84z6HXHlARxVA15FPBofr55eHj4w7feay0t/eAHP0iS5OLFi0899RRjbH9//8MPr1koAeDo6LDX61GKGZ/ItD1zdh4znmV5bziIosqZC2c489MiTwr8rW++maS6LHSajputeJQcGJIe7XeFEDzAjAaMMSFUko3zvJxrL4fWaK0ZY8YYqVVZlmmeJQeZBaf+5AMycRxTiiuVyig7klIWRTpOSoSr3ENz81XP8xpRQBkkCfd9XynlnI/RcAzMi+MYY5RnYjRMpTDGICWtEIm7891I9no9pdTh4WFZ7Llm6/39fae+7Pt+t9v1A+R5XhzHM7ZtAAjDsJtmhBAnV0cINkYLUQohxkUmpcSIjsdpmnbKQnDux3G1Uol6vV5ZlpVqpBSq1SuNRq3f75elxJh6PGg0GhiPtZYAQCkVRYkxppRrZdI0TdMcIeL7vlRZkihA2lhlDGKMGWO1EY5qyhlaYzTjpNFoUMqyrGCMEcK0toyRKOKOWnw4GCGEXGnWRUhpkZVl2Ww1nI/ueYErFbvDsMp4PMyUGI0SIUwcV5Uy3e5+sx1EUcQ5t1YrJUejEefc8zytbb3ezLJsd3e3KEQUVQCwlIJ7+HhGk1I6Ho+Pjo5kyd2Jz4Ixxlgcx+OkU6/Xi7zQqoyiapZlo2Hm+zEl9ujoqBR5FAXVat1o3O3sY4y1ss6rKMtc65IxJlU2GnfnFxpS6NEo4RwHoe95njYSAGEMpSgIo9VagzE6HPUx8peWFrSkR0fdTqfX7UgldRAEUhUWFcjWGPG1LPq9/piWjUaj3Wp5ntfrdaw1HmdxHDFGhJBSSsYmXpS73xxnjiOIxcQ9Qp6n7blmGPJ6vS6lvH+7N2PF0NpgRAlmlPh5XmBM4jg2BqIoOnMmQggdHR1laaCkMMbkWSJKJYRgDDDyrCmltFppKRWlSinreVG7tTCxLse5nNxC42g7rJ10wbo8CQAga13FS6qcEQM4CyJ+4dJCvUUrDY2Az7dXOKttb/bv3tlJk6LSHFNyiDEm1C4stmv1aJeO1m/djPyAh2xhbmlhbq1aaXOKlSnLsiQk1kYqZTm1GBOptDY5WDPu77/xrffv3rtdq1Q//alPYaM95vlVppEEAGWt1KC1MQZZRADhk1LNP+7myq2TYXH21b2PLZ4CjR3WxzjTYB94VcdTuCelrGf9rB/7/kOh5qR9aGZoHzbAx6Ji83Dz7493vid83lHFnhTHf9wXsKu+TiK56TioRxyOKccmPxboH7dtxnxEMBycAX5wtDMwGgBIrRFCGKzVxpF0KqW1sYU2UeANx6M7t67duvZmmmwTSMHkCQ/LUlprpRS5X5alTJJ0MBgIoZMkGfRHQVCJo4qU2l1ZpYxSBk1EJxEAVspIqT2Pcs6C0NPaF6LQWiqlMEFSQJoWxiDfNxgzzgPP88IwTEfjstAezUtsGrW43q5laUdJc+3GTYvw+YuXFpeXj7q90WgkpWy320rncRz7id/ADUqxBR2GYVkWnTSBwM9l0UlHkqK5+QWEyM7R/re+c60oyVNPPp/kveu3rtXqPvVRNQt15sdxHMUeY1QrA0KXQuZ5vre3N+MBnS1MxhjwrLXWWCVVJmWJsSEU+wHzKtXxeKxtpnUuNWaMUY4wleOx8HxWFEWSjDjnp06dYsxPkzzPNGcAYEbDQquhM5xFbtJRz9nRVqsVhuF4PMYYDwaDwK+4dd9BluI4npub63a7lE06IH0/CMNISoUQqlQqvlcBgNFoZK2WKldaGYuzPK36yzwMC1yMx900yRwm0TWJARilhTF+HFc9j2FMwzA+6naDQPq+z7kfhVYI4Tw5YwAhpJVRypSlFEIRjBQxjIPSUkmtpC1y02xW/YAFIe52uzOskxClkIYxVhS4KNM4jh3JM0LIZRYBoCgch6L0fcepSTCmCCnXa04p9TzfGWalFFigOLKGlEWmlPIDv9Wul6VI0oFLn9Trda3lcNgXsnTM291ur1arKaUZ442GH8cVrU1ZCj+gjHmMeYQQ96i1HY1GRnlTMIpxkDrGmOd5Upo0LaSUCFGtQSlrrfI8bK1yBsJlTJ2wByEsSQrPE4wRY1VcCWq1ijay1yuEUGmaE4Iq1aBarbbnGlKWzUbe642U8v2A1moNxliv10+zcRjaZ5473+vNbW0c7u91i0IAsnGFN1vz9+70/UBxzn0vKss8TbLp8mMQQox6nHvG6GScKaU8nxkDeV5KqeM49jyPUtDaGmPyXFqryzLv9Uye5/MLbddMUanUlFJSqiIXohRaS2OwlNYLAim1lFqKAiFcq1UcHKTbyTAuOPOEEEIoAAwgfC80VhlNMKZguSjtsF/4AbFA6CPc97NV24liOiCJMcax6wEA4YhSaozV2mKNKOZasdGwPOxsSSnTtJ9l2dnTlxhX46QH1qvPM0JMp3MYhOxstFTk5TjpeT5mHJBBzcrK5fMvttorRamEyEVZFKJLuCd0MUo7FgxnwXCQbe0cnVqYy5KuTNPTjz32xKUnKpXKoDcGi3FALWBjjNYgNVI/Pv75R2/HDdIsukUIORpvmAanesKtAY9kstHDfUof3fQJ8nlGT4w9QrN/yAIIeKjfabZnNQFpT4LgYxb6P44nMo0s3UGiKU5rNgAfOa8pyGtaLp6+rx8Y1OOPHE9VwRHAMfDYVETqoZO11kpFjv36sXEzFmNkjDVgnJrERF8YAcZonPT6/b1Rf5+TshIQo7BGBAHlHiWElYXuHPW01vV6EyPqe7ExiTWgNep2esZYhIg1yGhwCDkNFqwuS4mAGFuWZW4hJARxjxDCyzKnFEdRWwhRFrLXHRBCtDZGl6JUoRdneWqhzDF4nKbpUCrRaLUyZJZWltfW1vr9/t27dwGgUqkUogSik2I0SAZRFHDOer0xYmDAvP72W6dPn47juEBKZUM9JGma3rlz56Dbv3Tp3Dgb9gY9AzovJUN4sHUQ8UBDyWigVE8UoJTVChVFmYwOZp6iC3cYYwgjz2dKCUp5FIdJ2lfKCJEdHhbUR1prSnxGEVhS5BMO4cVmjRCOCaTpmLF6s1W3BvsB93BACC/LEiEqpdHaKqUQUi7GqlQqDgPsICbOZnQ6HSGE7/t5njsBcs/zCEFpmva6oywVlFKtEAAk4yIIGSGkFGSSjQwDz/M8n5TSGqOzrCiKgjEWRREAjMf9g0PpeV5ZFp2OWFtb6/eHg3u9VqvV74+zTHjcd7YziiIhVJ7nlHhaa1GWWlsEzOPY+XaNuq8kKIryvJSyqFZj3+etdi0vMiml7weVSiVJxlmeFEXBGFFSi1KCRdaANjpNMsEkQiiOq+40y1KGYRiGYRBEQRApNSE3nvbUYXc8IWdZNh4Oh1pbSikgwz0yN9/sdrturIxRUsqynIBprFWdo57Tymy32gihwWAgSjUej50WssswI4ScaKMSpauzuMXfGOP7fr1e93jU6w6DICCRN+gnUsowDMejXOmi1WopLbIsybJMCssYU8qAJVIoQlAQBL7Pmq0qJjaK6eFeoVRhDBoNM0K6WmvX9oKxieNQqtJ5DGEYGp0VRTIc75VCW1Ba67IsKUOeF9bqgecPsmyESdRoVkqByrJQWlNKLVBKGcJWCNdHra0FrVCr1XJOrZmm1twOFxZOCSGMRqXIknGJ8UDKcjQaiwKMMaJUZVkqZRAiCCFrgBI/z/M8k9bqMAzzPB+O+pVq1DnIldSkQrRiYAkhJBlnWoqoQhEwa7AUKs/zNCk9H1GK6UdDJffcOTL2GJBnulaaoigAMIbAKG2xP+jCuz/cyMteGHmAiiCUy4vl6tpcr9/Z2T6Ym58rCxXmtFINinK0u9cJI/bYpad0oe/e2bPab9eXfV4ZD48IYQSbne6HwOpZ0blz5wpCZnl5udcdv//uB0/+6t/+yZ/45PaZPbB8Y2OzyDUPfEKwsci1IWk7+QfGIoIBPj7i/HE37JginOGZiR5awGQKRQY7IcGwrgdoIu91PA6Gk2PHGZjo0bT5CXZTTSI/mDYTT66btA8xZ81Cw/9YuXjzQFjw4ZL2CWjzR0QyZo9aTzyVibWdxfdiYpjRtNzrXiqij5/Ug/2cIO+INHZiw9oAOFE3i6zFnAFAmY17RqVKpR5IjwaExrQyn6ZjY4yjmaTUDwJSrVal1J6nk3FOqW8NynOhpHEhi5kqFh//3SjyENKEAsaIMRKGfrUaVqrRxv0tN8M7nQ6ltFqtOtlgYzKlc0wp83map5s794ZdiZh58snHsiwbDLq3bt3c29s7c+ZMEPDxeJCqLkJo92Cn1WpVa7EwRS6QEEWvn3eH/SBwCABTrVaVUv1Rf2ElLHWvO9jPi9SPQoRCIzFjcVZ2LCYe1870YsSFkQoUD5njp3VrrkvnEkKUFULmYVSvVsPBkANwpdhwODzYSl1amFIqCq2UlRKkNJmfRZEfhn6ep6PRCGPKaFCtVoGEbh2PosiFvFmWEUJWFufKslxeXp5p9RRF4fLI7njCMAQAR89nrXVhuZRaiMTZSISQlIXSRRAEDr/jyntunI+6I9/3GSP1etU1pAKYNPVH4y7G1mVfi6JI03R//6gsFSKMYG4MZFnBualUIoRsWeYUKtYiJUFKba21BhmDtNbGoDCMKQn6/WGepy5o4ZwvLdV2d3fdSAZBYKyilMZxpHWAEMKYMOYJIbIsR8gRdvpghdHIGCOIZtQgtyYY4sA3aeJy4FRJSJNSs7EQoizLoijcpHCVe2dN8zzHGNxouI85qF2WCUJ0EJSUUiGMUiBKJbnWKnclbYyxKFWRCwQTWRE3JV10yzl3RggAa21dCOhq6oBEpVIZjQdxHFtr+/1+pVLJ89LoCXwSY6q1HY/Hnsc49yk1vhf7PhcyT5OSkDHntNlsUooBcL8/Pjw8jKJerVazVislvEBluRFCME7b7XalGnIOSZJFFcI82mqHS0tNQptSlkqXZVkWGfU8DyNaFLmU0vMYpRwA0iTTymJErUFFLoqiSNNcSnnr5l2tNSATBIxzlGcCkOU8SIal1lpKpbUmBE2QJWAG/QJj0LpwvQPGmDzPOacIiFIqz8uyFBhRYBNg4NxC2xqS5yJNc+eKIRRRwifqkvCRUM9heWar4Ywqi1HqUuGcewghrcvRoFS68HjUPRzMLcRRGPR6g+XVuXMXG/udq0rPCSXac41mq9LtHXS6B/OtS/MLdaJgf7uTpcNx0itFcnC4GUYVxoKNzTu318f94fZotEeIun83UBJEka2v37546YnVU+eFRJh6hDJESCaFR5FFSFs8y7oaQCdCsH78zUNqNiZwzPAQiy0Ca60G637aTG0wfFwlmJCPPyJ1PLl6/BKccDzSPmRlZzZJw6PUle7xx6XF/hFJ5uOH98BdOwlsro+Frg/lANAksj8W24MFOc0EIIQc36R7OdPUmObbp31Z8EA06fgxz9wB+7AWk8oHhzu7V95/Y9Dbo1hTipU0ygIDYg1J03QwGIeh32qGWutut+9xvyiEMbgspFICJlLohBCGMXU5BowRQoQxz/OCNBsoJTw/BlClENqUCFmEdaNZc4QerpapjTQWM8qYR0HgIhcUE5rlvWHf9yurp+Z6ad4dHACAsoU0ealSzBp+RN99704UBf1kIGwJfCGsRZ7HxKhsRu00TTudLc4ZwrYUuSMXG6Q7oieXl9c6/c69+5ura+eVtIx5CLTRgtVDRrnHMcYUYU0Z8b2KI7Ww1uZ5nmWZlKkBHFcjpSFJB4Bkmo5q9UpciYOQjRNXSwMH65lSdePhsN9qV5vNGqGuJU9Thk+dWrl5Z6coCsddZaeoQ7ewAIDD0QCA6/c1xrg+qCiKnPkBgDRNkyTxvYhSylkgpZRCW+P6IYkUimAjhCYEnPONYkawZ0w/CCpOWrEsC4Ss5/vt+UqnQ7MsazbrABhjXKvVpTBpmlajaiWuIIRG40FZlpRipZRUQknheMiVNBMbbJG1djgo/IVqFAVlmRNqKMVJklmrKYuMMUpZa20YhoCMEziy1rpUgUOKOVlAKWWejdxpep7HmGctyvNSa22tZoy5T7rEAMaEUkYpVCq1KAock1eelRirNE0XFtvWWqUU5zSKogiFzgD3uv0oijjz0jTt9waNRoNRnibZ3HyTUprnuTHW8zjnnBCW5yVY5nxN58oIIdyvp2nabNa11kIUcRymadrv9yqVCvdIURTj8XhuruW4QdqtCkKk1x0aY4QgmCBjBCYQBH4Y+kYjBzgrcpkXSZqmmICUGhObZ8VwmGpJyxxSIsKQV6tNIbLAjxYWa4Ff5plCCBW5kkoxbttz7Uaz7gckjFgYVdNstLu7u9paopQWhdDdXBtFGbFWFkVRFjqKokqlMtV8BACstR4OEoQJox7BTJQ6zwpjtbX69JkLSqk8K7OskFIqpYs8HQ4LwoIw8oWQWZZ4Hltcas/NtcqyrNZCykApjbHFWGNCK9UAY2yMmrLZW0qp7weMcQBMXQXi2No3sbgOGuCmhLUTAnqMMbOOrtJ4PgkCPkrGiBanFudA1ze3Ckp8a/Dh4WF/EC2u+q/+xJlx3y4vLwRBQBmU0p9faPmUbW3fX52vRlU1HG68/8E3eED3jw4X50+vrlyUiu7uHB12drQaSDGSZdFutE+dOmsRDJNEaC+O20CC3nCEKKF8Qp05WawBGwvGGoQM+f+5WPmjN3/KUfkI0xNo5Kq/GMBYMADaWuOoID9SAHa+y8fuH2N42D7NnkxUB9yPz6BY2pgHdd9jZeAZIZWzT3C8S/g/xjYj9HhkhyeqcqHjZ/TgEeOpS2DdW7M2p4kM4sMZa0BGT38UHT+7WdvRLEEz3Y/DoCFrQRswxlEAoq3bH969e/299173mcLE5kKlaY4sJBKnaaqULHIBAJ1OTwihtVxYWOr3h1laFEVpDWHMQ0gbDfV6A2DWHaAwJghhQqjv+8bQWq1CKHLZvyxLx+NREAQAKIr8Vqsehp6L0sIw1NZi4nUOR7I0UKWilK2ax5hY3z/aOdgIwzCs8iUyN7/cxNz0e0f1Zs33OeUEIUs54T6zYLnPvUndTnoexwSCwBsO+1IJYxQmqBBCKGmM0coWpTw47DXrNMsKazNCEYAhBBmr4zgu5EhZanFAKVU2S/KelJIx1vIalUp8eLg/TnpSSr+kWpdhGC4tt11fipQGE+qaK5JENesNV4PkHpFSYsSKoiCY9fsdSqlj83aa4loLY1Ce59bavb29oiiiKHIvlVKUevV63XFTz+DBlFIptavZz1iAPM8LgsBapRVyKVY376KQxFHFD7rGSqVKxok2pihTJDn3wkaj5nnMGBiPUq1NGMTVat1ho8pSYQwICKXWGKONstaKQjl3QWtLCKOEu9xskRdgEcIGERFXuB/w0TAxBgwMnUEdjUZxHFlrsywDMNYil2O3FhljCWHWIq2tFA5izQhmRkOppYP7GatmaQnPA8enHYZxFELg+1EcYoxHw0xJK6W2hjnwF2NMKWYMZ5y6EDzPhBDK+eQuJnMhaRAEGGPnQrnEg4PrOwLRPM8RQq7XVEpZFAXGwBijNFBK+b4HYAaDnhCF50cugaGUcnB6pRQAcrIZUhIHZ+OcG6XLvJRSJ8nIGKO1DcOoWq1Yq8MwTtNxlipraBxVCSFG6yxVadobJ535+eUwqJQiOzjslIXi3KeU15sBo9F4lO3t9eOKv7DYREhzzrlnjSkBCS8AQn1jIEvzLBtrxTjnSZIURVEUhTupPM/rtbkwDD2PIWyMUZxzp7uKiaYAQUg8PwLAQohed5AXI0IqolTcY5VKJUkSKWurq6t7e7uBx1rtalEUxoBWxhhwaPxx0mMUaUUIRdZSBwfLsnTSAWynpc2Z6MwstnDAdHcTYIyFkL7va60IVZVamMsi8uC5F89cebdTb0TVWhhG2EJ/Z/c+sGD1dFW2l5cWT6+vr9+/v95oVp988nFkGsOeVXK/UkNHB5tvvvMnfsjKUnIPnb9w9qknX7x8+fLOzvUPr7x+dCjnl5fOnDrdarR54IdRJQgqXlBRlmIuCMOYEWslIDCAzKy/FmFtgP1HCoG9qSV/JNgyCgxMGJ0tWAQWWwsIzMfZOzRtnvm4Pz3EZ3n8Wsy+e/xyONMCH8VhHbNa/7GM7iOncPzJMeN6Qj+0ndlLOO4QKGXgY7wNYNSDY5b3wQcmFv5RfwrbWZT8EEocAZ5g0sFaa1z7NUL49rX3Dw628vGgvlgdDorDw0MlTK3WSIpuUWSuobYos52dPWPUwsJClhXdblcrK4QO/Ghubh4sVkq5fvcsy9zsdfPFGNNo1JIk0UaCJoRgzlma2qLMAKkk1XEcayMxMVLl46TIC49wjyCa5wUnnrW4EGV32Nnf2U4zmRcJZYhzHoS8Ug211r3+UaNRK8vS97mbif1+TwhRrcYEMxawbtcMBgNMTBAsRHFIaVwWKqxU793dCsNw+VR8eLjfnlu8MHeuzMZlmSuJ0jSTKvd8HMdhrRbdvLmOEHLVx7Is82KEMWacDQa9KIosaGu1U4g6ODys1Wp+UNPGEApB6BESujYVC4VSqtvtAigLijGmpNzdPcSIWtBxpeooB/IipQxzj2qtG42Gg4A5+zoYDCZdLp5vjBkOh47R0xnmarXaas+7ZLWbU2YqVm+MxZh4nu95XlmWWZaNRmOldKvVSNLRaFw2GrVqLQgVMfb/y9d/NlmWZdlh4NlHX/WEy9CRmZWiskR39TQJNJroJgTNCAxhY0OaYT6MzfxDGAdjBmBmSKABEqgW1d2lMytFZGjX/uRVR+/5cJ6/jFZ8mRbmEe7+xL3nnL332mutHYSE9WrbNNOuGxaLhRDajG677SaT2e2i7fueUlIUuplUnJOYwr5ydS4wJiaTqq4m1rrtdosQOZchOO9NWTVaq3Y7UqA+RM65c+bq6moYaqn4MAwASCnP0DohJM+/yenFpG5y0PLe52Irq19yCZ6jIArwLoJkWpWU9sPYclbMZhNG1dXl0tmkZA3Q7e05Y4zoUmZBv//+dy4vL7fbLSJmAhTnnBDa94PWOjvFDsNIqZ1Op1oXmHxWCeb3OQxDDsbNpDBmnM1PGWNd1yktprNmsVjoQsYYZ7PZMHTX19eEEOdcCIlzqpRAhN1YM9AxsKG3zUQ7F4Z+JBClLBljXdevV1skcRisGZMUrCiKqi4TmsXi+v79e9PJjFLOWMcYUEqDB2/TaJbWJMYTkiQELhdtngZxefU6hEQIVbKo6tK76D2VSvBiAgBd1+cOSF03QsgQ4mKxQsQYpfMGMUymtVIlpeTly+eccyl19mNVqjJmaDsOwPq+PTh4dO/+0YuXX3VdVxTvcc7bbjmdTrkgjDEzxmEwjGtK6Ww2IYRb247jYE0AQMah7zsePMYYhGSckxAHQslv/ei3rq4vljcpB4Ycd5VSeUGEsVeCS84wxM1qMfbt6enRJx8/+tP//DmmcblYMzabH8xcRy6+EYu3pK5X0bCbi5vNYgijSmMolA82zY6/f9u+7GMXrrd29LWeiQ8L6djTo9+6vH7m+2dVOd/oy6P7x6wsjx495WQ1djeHk/fGbTJxU9fCRTOp5pvt6IORVbVYLJt60nBOg3fGWrLVepKQO89BKAQakqeccy4pEgKJJARMSBLNeBhjlKCAJBlRjCgGgiKnhBOx16ziOxI9oXsEkqgISF0CF4kLECKOMVIgjCCjRFAiOAgGlADGkfyNKA4AfbRZC8s4U0rldCeE0AYRA/oYYwKkAgmNSEJKkpCIJKWUSIokEpKHPxEaNL7r43H3iMwRpJQKShgjjBLIRmae5h/OHVaEOz8NBqUxpiiKzIlNKRlj6rr2yb0bgL9Fff+OucslV86ZlJIQjDISQiCAjDG5syljgkFV6sXNTVVV1tqR9ZzLYRiEkASpD15KbYxhsvhrCEF+cJY7cCn7yeTqJKXkFaOE0JhY8kfTan399qd/8WM7tv32i+uL5zS5YLXkpWS1LEhVTkMIWvHgSYw+RjqdHBCCi9uNqQelWGChrFRVKSb6PLzPhSWwURVRe3Jzs2R8cnxw6tww9KV3xIxOaam1RETBS2OMd1QIBUQTpJt1xzk/ODhSSjnfL26X3sFi1QtVffb86xDH6az84ovtZFr31qy6pdb686++9I4S2mw2V1XZMEq323a9ClprKfR6MfCDdYzRhHi7agkh1q+l1M65alJ11gSUITnnTFFSSse2G8pSM8XGse3HXgihi2lRNuuNZ7yklDpP3GaMMQLVCXHbWl1sEiRCZUyUQLVcL/shNFM22luEKBQvy5oxEbyjjDx8dELBMcY8Sc6FcdOGEHjBhODN/NAYI0TR970Z3Th45xxj/PnL27IsKZ8RQtbb5GNhjKFUa15fX7R939+tQ+Sck5hSvGGMZQ1rutN8A0CKYhwiIcQ7IyRrmmlKsW1bXYhKlpxzQXQyNAWCKELgiqM3bTDm9PCAM922QzTuanuOUB8dH2bDn249hmjruqzUJJWr7XVLUB4e69MHZH4Qgme311LIQnByc7O6ue77Fk/v6bLUzo9IJWOM8ykhaK0lkA4PD8exz0Auo8J7nyJoXTKaetdjiiQmSCgZl4wHLvqEwTpkkNvhZVne6YvQe48YgbDBDk0jlGZSI1DwvidIx8FSSqUsCUmMUoKwXq8JtowJKYq+s4Tz9aolEMtSD30gmCjotm1jjFVVbTfGey8V1k2ZUL99+9bakTHhnEOE4Bhn5dXlipA0mdRVWWaKAwXtLLu+7CeT6ftPD3K0HsdxtRj6zjdNc3gwads2eyZPp5Plrav0PQBv/dZar3UhpXz27FkKZVUVUgalUzMF626tG07vTdbbSy4jZ/r03nw2nzz/5vU4OMbEMKQYI6XMGByHdujq7OQ6Pzxypt9sNpyH2QyAYlGK03uPhw6Xi85ZQmITI6wG74MjSVVVGobB+xg8brfD8gbnMymltkQoIuqmEUoNdiSQuEZdw/r29eHhASGrg/l9aw7W6/WsmRQffjz29De/+U0/GK3VOFoAQsF4749PZvPZnFFtTdysu/W6syZUVcMza4D4RAggASllWdYH86PV7Q35Wxp4pCwazsRoOgL24eHh7OC9quSvX10BQFVVQGPbtgnt6b15jHEYXNeav/jzX5Rl+cEHH66W288/+3I2PQ2e/E+/+z/N64+//+H4y5///OLsHIj+6V981lQnx4/wy2efX1694Uy9/973tIZ+WF/dfPP44cN6woFZLig61256VWhnfNPwr78+OxHvHR89MMPYDx2G/vLsZXN0pFWlRJkISRhTjkIMMggEiWTkOEdfIESg55QIzhQjkhKeQWxEoJy8M4MhSyMopYzxiEByLEywo9oSAoTlyi8lTEBiBEhAGSF35CPyLQUJEAkwTgmQlChjhDJCGSFAKGKCRBLmAhNjhtZJIjGRSBCRJIIIlBAkwPc3aI9Wkbuy20WGiOADpYRTygiJKaYQx1ypUZY/HUkpF3MYg/c+D6bMWNauH+F3cX2Prv+VMPw3HvvDkVIK8C1lafC95FxQHhB8BGSRCuQE55OCUqpUwZmIMXadBbCM+UTlLrG4K4/vih5FABjnlNKEmO4cDCQoOw5KCq3lZnXz9bNfP3/5GUbzzVeflWU5mR44652zJ6cHKZHFYkFBSsnLsiKQxrHP+X7TNKf35nnOZk5AKaWZh0IpzxlYUaSmaeq6bpompSQEySfOMAzZL917PwzDRNTjOOYUtiiKHcU0hHv3jr1L1qysjdZa5ziBlBIxtqdd5JwSkM6SGJxzIUWiK4ZIGWOcy0xkQxKRBES01npvy1JXVVMW9TAMbbtZbTdZg1uWNSKEkBgTSimAmMuvTChrmgYA2rblrLLW5pZkJu/c+UxtY4DtprfWZ4ChqhqtdVWX3nvvozFuGNbOhrKs5vP5pJnlpiNBWugqXytKqXc7Yl2eo5xNzXKPfu8bkwHMrNTMtXJm5+ZKsSgKrfVme7vnZ+XfitEhopQFYsobM7fPum47DMPp6QkAmNGtlpv80aSUnPNmVqSU6rpmEyV4UVUDJlivt/2YrLWIKWEIwTEGUuqqEk1TcboZeo8I1kTvCEGWjVmKgmGiAMzauFlvdSEYx2HoQgh1Xdd1JYRw3uQPxRhwzimFmEgM0Zje+zCO49Zsc8sv168JE+NQlKobu6ZpZrOZUgoR8yQApcV6eZv9nzEbrUbinHc2CMkIQe+i4y7PFA8hxJCyKMiaEPMIO4xC7tynM982Hxd5weejab1qp9Ppk8fy5mYRIwquz88u7t+/jyTzokOMux+uqqrvuqpSMeJqdZMF3GVZxmgZjyGEopxNp1VCg52VigD1EbfREQCSEM3ol4ttWcnDw/l66ZwfnTNSNdPpNGFxe3s9jr6pD8pi1rX9zbAoi8njx4+32/b8/Lyuy9lsUpblMHZ933lvvbcpJS5SURRHR2Ice+eCUoIAbjabi7eDs9FZTIligoQhRBuj1/qAQix0IRqmlPDeB9wGu6WCmtFvaO+cU5qVlZKSIgmFmEwmE0JI1w1V1dzcLP7yL3/2ox/96Phkcrs4MG/6nDsSQsK6z0t6cbulwLNxpJRca+2s43vYDwBSghRJ3w+7zQawP833ZBbvkRCDGKezyaPHD2O0N7dXv/z580wDAxq5wA8++O7f/73fWS5vvnn+9Ze/eT2ZzOumFEIeHZ20W3N9fZUidBv/6P57bbf8l//yf7y5vvq3/+bfNTOVwBBxdfKAfPjd/4pSut4s/vQn//H88utuuJjP9LTeXl6/KPSJLhUicAkXb1+uu685m0UbiKA0id988fnrlz+bTegnze9TCkJy530iyCB3JROg33UZASkmCjumkqaBM5CUSM4kRcjdR4yE7ufv/hWSGuWSJBJjQgwpIcFECSYkFHczgElKgSIiSZRC2tGX3+my74KxjyQlSAkSIQhIc9WZsoKWJEIR0y4KJySImdaRCV+EAgIFBEK/VWz/tYaCYHUIIaaQEkEMMXOnE1G63MOnAUPK+QIwSkPOyTJVNR/WxpidCeXfGGD4d8HdefHd8Zm/pYIXVSmVEIxj8MiJLDSXjFDZ9gvOBSIClQkJ44GQxEUcokl3Q7fyaZ6bZxmXy/+SAYp8wAUXGBL0brFanL/94qsv/+Lq8itCTIZztVbrYHwYi1IVUg4jN0MkhDtvrLXD0JVlUVWHk2mdQ0WmGOCdv1hKifMdOzRFsrcoSilVNaeUWmuMMbpQmUrD2DCOozEGAOq6nk6nOSqnlACoEKppGiGMEDtx6jiYshLj0CMyzlTGJ1KK3nsfkCSvC0pBKkWk5FIKoCKmAABaayEQEfuhDT5prddtZ4zJjj/5KoUQOOcx+qqqpGTW+hCScyGl1LY9JXXbjlmhkZXKShFKqY8uht4YY23k3CjFOOfOBqlYUVRCpMXtyrsopRJCDYOhJN93prXMxMO8nPq+995LqaWUTdOEkGKMXdfTguYfyIstE5QopXnwYpYj50+RQ4UxJucHOTXMkuUQQowEMTHGKCVCsux25L3POyLnUllWlE3ws/UKpawsNIHEOdeFJOvkgx8GRggyxoAyxph3IYZUVVVVEu821prtJklRMAbjENbrPngWPADhuXiKSU4mZQjeWquUpLRhjIFnggsp5TBuQ3CMMc7pbrIZEKCiD2jtaK21lucUQSk1mdTh1tV1OZnUebEZY0JIMbIQSAgGCBW8jAHN6L1DAJZSylYqzoay0oSQrFOKcXAuOBspSLgzeBBChOCNMeSO65Mvr1JqWI/OhbqeCa7N6CmlVTVFZJvNRiqRF1WufTN4dnBUzQ/KlNJmE9q2dwF5iIR6oRKwVDX8+HSCYIzbjHZtHEzmYhxcDBQiN8YubteMTw8PD4+POSJmOTgimDE5Sxkr6vLAW7JZj9774sH04OCAEHJ5CVfXF0KyZlIdHMzLUhk75Hud9fpKSSjBe48IKaS+79utJYSmCCHkOA11rZWuV7eBQKoqOpk2s3mVo3KI7upqDMF7H1PSQpY5L0zoNdO5LbJcru/du3d8fHp2dnZ6evX0KT84rFdrfX3VpQTBpxhR63K7GZ1zR0dHZdGsodVazGazzWbDKaVScSGEUqJtN31vX75427YbKabvHj37Az14dOh0SSeTkjG4udm+eXUtZTmbV5xTXfCYzDiOr1+/vro6v7i8KErxgx9+mv1WiqIoq+8sF23XDc+e/WcfHjx6fPz26jebzfr4Abm9fv6Xv2qXf3xz/8HRP/mnf6BUQdp+sbgxowsh/Zt/9//74fcGN9Z1eTg/mk5nxXQy/+zXn709+9VHH//XSszriVRKDf3m2fPPHj2o7j/89MicKFUiSRQAOI0YYoicCooEAAEJI5i/IJBKlgQDxoAD4YQASUATpBTvKsvMVstBixACjGMuQgilmBhQyolA6BMiIiREQnLykkeBpvjtMAaK39pNWHc33xCQhV3SE2P0QGMucxEQU8IIhAChIc/EBQIkP81dTEJH3sGH9+1k7xNlVBeSkAQYSSKYKOMiCRZCsNblsYmEEESw1jfVDs7NpVUOQs657IOGZK9O3juT/O0VML7jQILk2+TDB0IIBupJQh4QqLQOQkRGmeQKEb2PwSdKGCEUY2BUEYyYB0sQRhBSjCEkxQPnXAgCgJRiZkwwhjoS3dS3l2+//Pxnb19/tlm9JNALFt776Mn11a21/WRaIUnGtpw3Dx6cXJyvAcA5Z+1IKehCFqUqy3K5vGZ3j33lvSdD5NG8eQdSyrXWm00LACE4QpLWGoAxRqTUXb/OYSOrU4qiyL+12bQppboppeKc5xyFEUIfPDx68/pqvRyBACKRUigtgKKzcRwiYuCCMCYYo1xQzqkbYggBgFGarPXjYAkhUmqtCmucd4FRXugSExnHcehHxqnWJQD0/U51qpRyLtQlKwoNQHKc3ke4kBghNLc5U0qIPIS4Xm/bLpyeniLidtsSQk9PTiilV1dXq8WQWaZSgnNhn4fddTeH7PAjhCiKwvuQF1gOwACwtybNBcR+Gee6YRgGqViMiBhSyj7qlDGRTd/yxjHGAEWtdR5xeHV1NQxDCKFpmtlsnnleXdcXVZ0V8yEEaz0mUErUje6NC8HntFIyiUjadgwhtO0YfMrd5RAkZyOA2266cQyAjhDKqAJAgJBTt6ouGAfGIecQIUTOBSLJgrG7Bnbw3iMJlOHBwUwIlpW4+ZBRSlRVccpOGGMxBsSUiYvGjNbaSpfeBef9dtOFEI1xiFAURYw2t7HyWs2rV0o5mZDNpkUMlFFKaUw7h42srH0X2crsNu+SFKrvhnG0zoXgU4pUKR3ikJdxNoUOd2O8lWLW9lLKo6NZXeuu64QQh4fTHVcObUI7P6j7oey6rij00XG1WZt2Q4YuORutjc4mIQSBAABA4zAM2f7C+zSdNmaE9Xq53Y51XcaYlsvVdrtVSuVZWKvVCoCkFCgjWuvJZGKtXS7XWuvZbEIlC9FnQjfBlGl9iBFJAMrmBwf3Hxx/Nr5EBOf729uBC8oYdc6M4zj0nDLknGKiKVIzOsqC80Ey2bULzjkmuLlecM6rsnn18o3SZDqd379/akbXdePQD9YEJWtrE4CQoswHSIiOMtJMSk4ZIYTdKeqYs+72ZtX3/fFxnd555BSJUjqZ6oQ8puHmZmGMWSw27dZPJ8x7P44j45oLent72/VL701Z6e988MS6tqwnh0ezrtsenshPPv3+Zt3+9M9+fbP8+bp9kkhICQa73HTb2+VKal01N5v+BTPQjVZIkhJ98c3lwwfvzWenZ+3yz/78P7qw+t6nT3/ww+95/3Zz++bXgwtOfPRxiVg+eHh8cnT45Ze/UPKJlvp9WTKqACOiB4KMJpoiADIEoEgJUgJACSO0lpQQQiGSFHcT7XcQbiTfQqmwP4tdJClhREQgjANDShgFAGYc5lkAiFmKEykBQshO9g1kJw3CDES7CCntPCPpHRMrJRIY3FlqJEQkeGfwRHMpTxJiNvxCzLKdb4Pu/jBCxBgiI0AgYrLeGUSQrKBCJu/8OBrjKGWFrrQuETEEkuGjd5GPHISyaGQfWffx9e9CoXPhm6F7AikfBCklQOZdYgBKCAqgJE8+AJAUAaKgQI0ZMRGtyxgxICiUCAgU8tsAgMRS4knI/u59RiUp5yqEMAy9oIlFcXX+5ctnv9huzodxQcHNZlVKaRg7IcRkMtmdTZwmjFVVIUbnnFKTZlI1TcM5jXHHrsqvmK9GRkeFiFLqvPEAaI4TMcayqIex8z5SSkIIQz9SBpTyPCWUELJer8uyzFENAIbeAZCq1ojBOUcZCq6UrKSU02mVIjMDGuNipFLWStV95wik4HfTlBO6EIIQ3PS+7/sYsCgqzhXnpO/GoW9loTNjNoRUFKIoqr4fh8FU9W60cA516U6plUhf1nwya3K0CyEQ4gCAR84oB0CCFEi2ZwICEKLruj5GtCZSil03EEKHwUVvU4QYyN7INp8tTdMMwxBj8t6nSBgTmfvD6I6RtF+3u+12BzLnQm1vT00IhBBT8pR6KaOUknMhxM5ILcbovV2vxzwmOeu5+35ExOmUU8r7ftxut8ZYY2QMwGRWJJuUEkEqpZASM/PIOZdnz2VkZTt2ufRJKXmX+jZQFkIImMC5gAhCsKpWXKBUoLQQWoRQMiZSJNa6zD0eeqcLngEhygjADngHQEZI3RSTaZUT/QwDSMlAaGvtMG7zZUmYkPiYLNCSiyx6pogoJR9H65wBgBgwxoSIwScgjBAKwJqm6fsR0eaVnDAa42P0k2mVEZ280/evntPuYRhSIowxCjwD1Nk2UgiRUvA+IKKQTCkF1Fk3AE1SVVWthaQpJa1FVVXGmPV6zRh78ODB4eGhlPL09BShC54NnYnRE0KB0OCx7w1CTxD6vg2eSFkAMO/d0Nub63Xf90oJxtRq2fZ9n73Wlaysid5tuaAZ60nROBu8j0PvYsC7HYdCcK0oY9E5xzgpCp0weO+sHb2L9+5PQwir1WaxXDEq6noCIGLI2l8pBEuJ9P04jB1A4oKKilbVBBGLolittsMwNE3jXLy6umqa6Xw+3xz0hGysiUNvN5tNzsv7fkwpeR+dM4wttNY8s8O9B6UUIghRALCynORmwP7xLYRYcsbEtnWXF8vloudMclZYGzebzntLWXr0+LQoubHbyWRycnrUNDPEMI7jZpOE4EJQqcjp/alk+tXrrxfLqz/8w384nR395M+eSXVIgLXtDbvdXF69ODicdoOtaqW3crXevP/Bxw8ePZSiev36s9Bvi2rYbp7fXD+bleXpg4OmtCldKHX/wb3Dw4N729X2zatvnjx+7/GTDwpVuYgueAJJFRpNACSUEkqAA1BGKAEAFGx/ANCEO31qIrDXp/+1Y8KFuD++CMkzmgilQO/mBmdf6ARZdQN4NzgXAHY2xogABKjIbshkr98lSIC6kCNuxrMTJcCBUAqCYUSSUlY95f92DiH7oIvvQKaH01nXL66u3iwWZ8PQKa5mzVHTzJfbt8YY76JW1Wx20NRzxkQIkZZH2dM8pZQFrDlhZExksDn3h2A/SPjvmMaAZP8uAmWE3k2PrgRLMRIGjKMdjB9w6HulBK8mxljBFecSAAih49CHEJomZy4EMaTkYp6lghjSJgJkc/nJZFLMZuO4vXz7Zli/cM59+cUXi5vz4IbN+lYXwE8P1+u1FFpKuVptum5omoYz8fbt2+nkhFLGOQOaJ45Q50zuYmaIO8fgTAXKsTavBKUUIZA5qymlqqqcczGMEZJzQQivqFJS10rmeq7ruhij1jpr+TfrUUo65ZUuZEw2R8S+HxKGZlIoVbRbs1rGGAMAKKWdi8ZY54IiAoBmCwXGcHWz9d4DMGcHSnnwEYBLUZalyEsij9HNaloppZI6hhRjlELVVTObzWKM42CcHyjTlFFExOBDtLhrarAcjZzzUipElFLUzcwHnSIRnN6//9Bav1ptzGgJIYzSEFKeDn43Fsn3/Xh8fCiEEIJKKa3xzgVCyDiOZSHgznVgv8s45xhhn/rnhU0p1VqHmAHnuM8Fc4T23gvBhRAhuD1/WEp5eHiY08eMPWSFjNa67yznPOcTObTE6AgE60YgrCiKEKIZnYuOEFrXSkpZlEwGpJSQpBAhhiQk8y6llMtxKApd1ozxKBUgCBExN+xjTNZ6M7r1epv1WpQlABSSai2l5AAkht37zyetUjtXa7MdEGPGXxCBUlqWuiiUN05rXtcTINxazxjzwRrbKVlZ61MKLLK+H5TKSk2jtcwbc9evoZEB8d7noJvz45wqZYBnNpu8fXvedlslNQBUTTGbHbRtO44t41mwRPOFzfeiYLsqbu84ljsIQ++di9vNSKGbTtw4hM16YHQDNIxD6LvBGEeBAzBjwmZlEmwmk9lkMiNIAXi77YehI4Qsl2tKadM04+ByOyPGyDnJ+HlRqIPDuVbae9tuhxhjTL4sS87lZt3H6OumZKxCxOm0KiuhNa+bwpjh8vL66up2ver/wX/zf7LGx4ibdRcCMWOkFFIQ05milMQYjHHGhJhC9kLvcRRcLZfL+eywvj/59a9/HfxmOp1eXd6WxVRKnRltha6UUldXN0IIAti2LSIKoUJIfedT5DxbkqaUQtAxRs5kiiiEcs7Sv6qc2RVwMAJVjCpGS0qkFDrPfyvLsmmOlWbz+dzYdrVaITaLxcKb6vT08HbZrlft4ycPgJCztzdSykenn5o+zY/Un//kZ4fHJ1VVvXl9y3nDuLd2MMZV5cE3y5fewWxePnjy+Itnv0TEeycPTu9NnhbqR7/9ydmbt2O/fXzw6Pf+698qD05MdEJ2jOr3nn76g09+7/Mv//j0+FBJThnhhLoYkCTARDDlqe4cgFFCgXAKu8BKaJ6Li4Sm3Uxf3Afgff2aw2QW45OYSB5bhAmRpgRsNzwQEEmkGTZmeNc1zZEWv9XYYEJ2F672xhGEEAgpUYrkrvXKACmlnFImEyL6CMFjSBgJ0hQS7Py682bItWbuhdz0z6+uXr149eub61cxmKKomvJQyfJ68WVKSJArVZRFo1RFQSDi/Y//UR7Rms+17F4EAPit48Zfd3/8Wx8hhHxqEIIANB/ifd8/f/VTQkhdFVVVrRa3zox9398/Pf7ot//hcrkuiqKuJ97F8/PzV69eA8An37mfP1qW+Xddl99SXbGUUu5ZPn369L333ru5ufn1z3/edr8c+3G7MRTE0Ld9Oygx3SwtZZRSDiCGYbNebQTXda1ihK5rsw9iwuCccW7YW9oSQiild6IOTu+EkiGEzWbTdyNjPJ/sx8fH1o4AlHMek6eUK1VIuRP4ZRNdRMzlxZ0Nso2R7mpfwaQU1qSuG5CEoigYjyGmhNwaEqMfescYCdF674VkiCLPZiHEt1vDueScD30044iIdd1oVRCSlCoopZvNxtqxKIqUCADbOzwQQpUqpNTee86lYDx60rndlB4AxjnnVCB4xgQmyLFwHKz3pK5rICIEyxgopSiIobcp2ZSSUJxRIYVWUjPGvPfeWWvdcrmUUgqhcrDs+4FSOgwDkF11m0Ps3sRqu+32/4iIef4gIYQg5UwyioQQCnTvDJru+P/7bhEieu8JUsGVc65rhwwgc84ZFXVdF0UhJGOMFYXKYlAkUly5/ZoXQgCIYRj6zk7mIJXUpVRKBCfHIVpruIxIIlAAkghEoFFKQXkEGqyN1nrOBOcaEb2L42id8xQKzmnw6LzhgqSYvYhDVSjGRUw+A+aZsgcAQImQnPEdSLbv6NuhF0KVZdl3I+NkMtU+VMPASNLOmZw25eAkpQiBOGdy/hcDeO+lEJNplaVKOQxrrfMmzdf58GiqlDg7O4sRyc7r104mZduu7oLfftqYjzG27c6UmxDCGMlJWIwxODb2CaN0Bs7fLrquW6+3i5uurifex76zKSGXJITQd4lR2ZuOgs7NBUKc84ZxrGoRY2NGG2McRzv0ToqCpOQtTidH4zgGn9qtGXrvvQVArXVIgTOJiTpnEFPfjdZ4xhgSrjRIBZQlpUVdN0Mfb663n/3qZYxxu2mdxVz9UxqqqqobESN23U5zGDxLgQYlOj8IITabdjbrT09PtS7bti2KYKx9+eI869fLsnzw4EHdFF2/YowxhoIDY5ogeJdSIt5Snp83r9cUScBgrRMiUIZ4Zx+xhxkBgIuUkcy6mnOmYnKMYjMpJzMSgnv16hVl8fGTe/ODqqr09c3lehHO3nwpVHr46Gh5O1JKiqLYbG7fP/j0t36gN8NbkO7Bo/vb/vnT7xyTVPzwB799cf1lVU4ZaZ5/ff369duiHj/69ODpe9+tJ+zgsFIFKUrx+OHDeTP94OknP/mjz66vzt8/KBlnz56/PTn87scf/rAUh/fuq+nsiEuVUqSUS8ZGF6wdNQhCkCIAQwDCgAAgJTREpBQppQRYIhBjzCUu3tnTwzsPQkjYWT8migmQRECSgw0CoUgSAciQda6l6V2huA/BO6tIHwO5K6z39SshJAIFpEgywyoCBQaUcRCSpAQJEJGkkBICQiIkAUi88+7OZ1beWn/+X/7Dcvl2sXqdUluXEtLYLZdD71W1ZUwwKoLj29VlipASJUiX/jjzOKqqOjg4yFRYpZQx4W+FoP+uR4wxg+IAOypWVnP++V/8+0Kp09Pjg9n8+vLcmDGGUJUf/OJXP3n9+vV0Mn/8+HEI6Re/+OXnn3+uZPHyK7GfD5PVt7uTmtCU0nq9TimN7Q8kjVdXV19+9vOjezcxkum0YrRc3N5S4Fo1t9ft4YlarTZNPamr6Tg4Y1yh4fjo9NWrV9Pp9PBojojOme12PQwDF6yu63wx94aLOb8xxinFyrLkTOZx2ptNSymVkmfmZ+6XZ9i56zaE2qZpMo83x55xHFNKQijvh7bdUhYAoCxr0BSTz9mL84MPfVEpIVS78W3bn9yrhvFulksCM/rttnMuSKpjgBQTISC4JoSOg++7G1HZuq7n83m2csyzifq+z72QeOexk0suKaWzmAvEXPoXRVFVldYiA4xCCM4jpbzvt84PWsuYnPfeWk/wtqqqoqgIoavVSkqdTZsRSdazEkKLohrHNoSAOHZd13ejc2E6nSqlxnHMPg/pjjafC6n815y7EEJyHZ8/yB6W2B9KiJhHLaWU9jhqznW8y7PubK6bc4zPOVBKaRxCdi+hlBJIFOi9e/cuLi76vg8hSlFyLglS70PbDqpIdaMqXgShxqEdTc9TSElQKggBJDGhR8IBIiHJ2rRcLimIup55l4ZhdM4DYdYEomRC4mxEJJQywVVCFoInRBGC1pphGMaRb7cb7/3TD56+29DdN0SOjmeZ/DyMrbOxaaazeVPXZbfNvMiUGQmZ7heCH82ACEVRBk8QsSj04eFhWepXr5/nwXf5yfPilFJeXV1+9NFHBFLXdU09ffv2vB+2n3zy6Xa75YJlj7NMEswFsbOjMYYzUde1s/766ub29lYpdTD57jhEwVkM7PJiSQgpi5n3frMKKYUQg1KSczYMIyYoC/Lw4eOcWCPibDY7OJjnmVqThr58+XoYupQoo5JzjSkiEiACSEAMMZDgg3NBaSFEoTSPEY0ZGAeliq5rjVmVZblet0pxqagQrCwnZVkeHkiMm4u3LWJMGHRRCcG27SpGrwtgXMcYMk4suAaSYsDggbBEKUqpr69v1+tt2/YAjHMJlrfbwTkfgk8pMQbTWaU0iyERQqu6YLTo2tGMgVGZQoSDB01Oqcg7kE6GnnLTJW/RvLKllJTFlLJpHFBKgaIQXEpJJ3YyLQ6OFAVzcjxlQC8vrx8+fExieXZ25b09Pq3rafJh4Ew19RExP5pN7/3HP/rPl9fPfvCjk3pKp5PZpD599fzi8GjyO7/73W+ef3F+8faXv/j8m2cXf//v/f0/+MN/Yjrou/jF5z+tJ+6f/4v/pirE4nZlx4ioHj76brcVZ+d2u2GffPL35genMd1WdUEI0aqMEdvtACCCTyjsnj+Zi7wcG6bUZe1NzgHziW+M4XXDOTdmBzOmtPPxEbFkDIWkXJAQnDEjIVAURWfEvl9I7prHlNIhJGeGlFJVFqWSAEABOefXnvd9b0bLWH5XSJByzt1ogRJKCWMQk4vRV3XRNJUb+mxVk4ubXKQiIuOT/eaJMU6n0/V6+6//9b9eXfzvmWFEIGitdMERo/de8Gp/HCcMRaGKovDeKzlZLdsH95/+43/0z77z/vfGngx9UEr3MlZVNVg3jqNUmlBmrSWUV8XRu3Kd/QGR0BBQlBfexUnFv/ryz/7LH/3PD+5Nv/j5T6uqAEoYA11w5yyl5Pjk8Op8lSI5OjqazQ6Wy9X19bWzAREl3z1h3Cm99ubkOQkgQgLn9PTeUd+3+VuXl5cpEe/SMBgzBgD68OFDF7bjOE6n06qq8jDaw8NDrfVms8hQs9Y6e9ZsNpvFYnF48MA5570lhEglpMy9MT9tGGMMExjjjDHOBmud9/5mMxSlOjo64pyu10tErJsqs47z+NW9/UIOOZzTTOPKBtFVVQGA9z4FRynNVJ1c3+e65PT0OB9MmaKc/YZevXoVPK+raVE03pEcPjknSsuIyAUtClEUBaXcO3QuBk9CcFJqrYvb21uAhMQ9eHhU1frqbbtedYzKcbQAcHg4j8mNps0BtSy1sf1qtShLfXxyyDnLFkL7aW5N02itrbVAZK5Wc8qS378QoihUNg3O6HRTT7bbzlpLmRdCCFEAoW3bxwBNMwHCII137ns8u/h6F6y1h0eTbNuUi4y+7wkhZVl++Mm9YRicDYSwrh3W621KWBY1F3CHwGO77SnNbo60nrA81wGAVHUxjmOM/vT09JuvVl3bhxBixHG0nPNcQM9OdQaBBddNPWVMLW5XFxcX1SRl3njOVjMnQGuNieXEMVPPcp0jhGC0NGYYxz6h14WcTpvZvKmq6ubmajKZ1HV9c3OTuyp37ZXZer0+OTnJvmOc88VicXx8rIrgnDk4mCmlzs+v+85K0TgbGYO27fu+T4kAYSklREIpffBodu/eva7rzs7ONpvNwcHBxx9/XBTFarUJISyXy3bbcS4JoQBQliVl/v79+0qpvAj35YFzrigKAEzohWBckBi9cy54EWMIwRWlqqtJ140X5zdDb//bf/x7t7e3m80mEwjG0W63W2OMoNPMe8/svDwK2hjDBTST6vj4cLtdx+SUEkjikydP1pfx4uJiuVzmlrz3Pv86L6kxg1KC3FHbYsSDg6PM/7q6urLWZsp0HuPdLrcZtZpMsiNHl5fH6NNd313udmJGQbgeTScV5ZwOw4AIWtWYKLDw+PHjtm1fv35Zlvrk9Ng517btw4f3x3HUWnLOF8ub09OT09PTx48f/uwnv8jPv5+W4ZyjlO7GT77b4LzjzmXLyV1IJneSEkzEWk8pkbKgDJGEuilPT0+tvGQ8Pnx0VBaQogMSHj89evr06Mmj77/45ny96mNyCMOjh01VTpeL/vLmsqpFgtt2OH/9pi8WbDJtmnqBoaKMvH79MkQzmzV1ox88mC+XNz/+4z9aXPdnb26fPLrXTGc//ctffPjBe2YM25Wraw1YVmV1dAR1Jaq68N5SJRII55zxfYyYCBZKIkuUkOgjpaCEBgBnXAgBEdeCUp8YYwCKEIIRE/LIhek9pVEIyQXrh0zRFM4GJlKMMVjCIqWUMqEBIBFug0dEJIgUCCGRYEwRMKVEMpIpBScEvfcpekJIP/oUCYsRgwPKBaUporcBCGUAJKFzDmgstBQQvWlLLbwfXr58uVqtUkp5Ek5RFNttUlwRkihDTLbvrlfLK+9vYki5opWyYJw465BEzpkxhpCklMqTOGOMiFDXtbNpHHvnjJQCKLm5vUyRPXr8fbQdIVRxAQVFoABAdZVSMr4lhFBBCCEphRBjjpRKCkSM0VtnF9acvz07Pz8PbjWbTcZxRJKklF1rQnDe+9ubzZPHj7My5OLiYr3ebLdbglQIkSjdJzT7Bnw+VjhnXFDviTG+bIsQQllqROBcj4Pp+9EYx5nUuhBCEFDbTbvdtEAoZ4JRHnxcDeuqrnKjYRiMc1mog0oVXdcRkt2ewTnnnOGcS8nXq23W16aUtCoPD2rv/Wq1en25yJ69QoiiqJwz1jhDzMnJCUCXGRx5N1lrY8SiEJTSbO6R5Rw76S2DPGQ+B+x0Z8ab+cP7xmq+p/P5HGMZQhp6GwMwKgvNGUfOqTehaKrZrBECvPcxBkJSwlA1lFEQgkgpCCEx0nFIzhpjzGh6BhERdhAu2QEAuc1fFAXiLATXdR3n/OTkRMqxbdu27bKeR+tCSkVQpkSMMXdWxsgYoxRD2BnL51MlxsgYaC0RIqWkKIRzATEChZickkW3HvK9zkwlxgTjtOS7EW05d8n91Lw8Li8vvYuUMsbEXW7Ni6JYrW9z010IJg81ADPGLJdLH3RVVd7hMHbDMEopiqIkyKWUUjkAIMQLwRjjXFBEMfQuxohIhIgpEkr5aDrKkhBKSk0pNcYB+HxMeh+tMfszM2dUOTu0ZmAcm0mV2R3OheWi3aw764YYMSWCCIyJDAcoVbx9+zbf7owrUEpns1lKqSxqIQSlPF9YQoj3NkYsy7kxAYhL0acUUsw8Stq141q13ntGJWdq6O3V5a2U0nmbJ8xTYMNgjLEZ9NoHuX30zZZk3nvv7eHRvCxn1o6MgZQyJRI9l5LlyjKhs9amRBhTV5c3zoUUKSKRglVlTZAR3Aa38wPfh5icrgED7/319XUen5DNXNu2NYZm3OJd5CPH76IoptOmH7phGHLHum1bpRjeTe/OQuecF2Y3KUTIXJNxtM45Sr1LuEdfyB1FkRAS/BhT7LohK3cRwRqbIpS16PteSjmdTtt2MwxDnqcppdxsNre31/P5/OHDh0+ePB6G4ebm5vHjh19++eXV1VUm5BeFYtliZT/yYn85cjxGhLxV9tE3/5gQZQhBaT6Z1j4M681yszXNlP/ov/ruZ5/95upyURUqRTeflUqrvu/PL7755a9+8/UXV8Ng7j84+u//2T+ZT+6/ePbL5y8/O74P730seXlEkO3MBGpCnPqP//Hff/d7T9//zoPV+moyLR49enT29moyE019LCXFEK+vb4wZZtV9QkCxe015WhWnlNZcsBilLlTbmYTgIhofUyKcc6GES+7i6kxTdnh4KAS/ubnO40pOT09PTk7WI3rvKY1a63xKIqKUUlJinK8EJ8AH53IaG6NNNMWYMCLs0CEOgKOzNsYdYY2+Q0tOmCLLjRxjDMWUdX4A0GCUUgOAdxGA5tWcB8Lk04eArKoCaHr16sXz58+/9+lH4zh+/cXPXr9+rZSKbpOTx9P7v1MUytjROVPVgnP46uvXL178MvWbEJzSsmkqH8Iw9ABYN2Uu+/KdZUx3tttuOkxNWZaz+YQLePP2xTfPXv74v/yEgv4n/+Sf/s4//MfWe0qo5GBcSAjAKElAxY4Ok3uHOW3kgkZnEZAASEYRgXNa16UuxFTVw1lvjEkRAVhZTieNznkoENZ1Xdv242icc5zJPT1kT6LeA5VSSsZ3Wg5rQ9d1wzC0LZvPjhiVlIYYMQYEEodhuLq6OjmdAzDndpTXEELb9m3bPnx0kmWmcCcY3Xnw7vwoGCFkNEMIrmmayaQe/BBCIsil0FIqKTUiKFndv/9AShkDttseSQwhISLndOjHoR8zypLbiphIipiJM7lPHEJCdABMa8mA5VSAUg7AABiljHMeQiYN7XDIDEdNJpO+5WbszRgpCM4VIYkxIgQblyulUi8MZUhIQEQk3vlRIScYk00xekTqfdxubIxBMGSMMQqMCsZYiC5hklIasxtRp7WkjKfkxsFXFTejy1YbTe1TJCmScbAhBIIeAIBksj4AgRiSs8P+RMuOS0XRZjVLVWvvfVXL1AaggTMVgtGa391ukt88uRsOn7/I380+xsMwEEKczUpiQkFKKSnlhAAX9ODgYBiG5XJJCDT1VAiVCSvORiUhRtJ31rBwdFQi0uvrhTE7DlcIGXFxebUA4TsX1RRSanN3djav6qbMmFPf94iYoQ7nXPCYc9E8UiID6THGEBdFUShZIOIwjMMw9K0jhAALZozO7siYQ++zbi2D8Lkdnlf+dDrt+97aEEIKoZeSN03DmW63JiXfteM4uOAREyV453Gb2DjE25stIhIiGC2scctFVxQFoVZrrbXGRPKo4/x5uYB8pwAgQ275siDGzaZXWkgpnQs0ECHEONqhjUpTLiNlMblgrbEmpCAuLxZCCO/jOI5CqKaepkidxRh8ziZzXylP6aiqKqQ+Rr/dtqenp1KpGJFS2m77viX7kbjpHWMAoKC1PD45mvnq7OzMucCZosDbts8SAETwPqa0G+OdsbTsOZM5CvlpkX3r97An0zDGIknBBS4Y43Q0QwyEM8045JL60aNHWsuvv975dOabVdf1OPb5uoUQzs/PEePHH3wnRGvdUNf1yekhY2yz8YQkvo+sf7OrB3/V1SF/cmdDSpQQyhjlQsVUSAWUxUIfbFb+xbNXJKWD2fR732vIVG4JHswloLYj3a5QSfv1l6+/+vKbH//4Tz785MnBMT1+cO87Hx29fL767FfPNpvNhx/ff/32etuuf/Q7/4Pz7bNvvhRC1nX56fe+c3x6eHl+/eTJD68vli+/efv1l+fJ1v/nf/4v7h1+jwtV6UOgmkCKiRFKGEcbCbrkApVSSi0TuvPzN3/+0z+pKH7/+98viuJnP/vZV199NZ/Pffiu88uj+58Eb2PIvGK0pgcAJWskEFNarlY7BB7AOmed864FEEqWgMJbT2kEAOtGrtVeLPvu/1JKwWBHeSCY65gQwkElGQNEcITE6FlCACYVRQhlWZZVcXt7+eLrX7569fzrZ18ul8tu/QYAXj3/ar1ea62ffTlst1tK6e//I1qWxfn5+e3i8jvfef/9D96LwXKGvY8xErDRqcwLVVKKsqi6bouIbduOo62qKoTU96O14f59UddV27Z/9Ef//vpqfXW5/OEPfnR0NAdMilEfE4bECVrvkyVMCsFUbpUzIJSzd1JUHxMJMSqpCHolYDopBQ2EJCHYOJC+HwmhmEQqBKC+ujpr6mlOV3NpmLVc2Rngju4R9o0DIXdKr4weS6HWdtO1PaPlMIzjaBCRsuwHEscR+17msJ3Bn3yOU0o3m7Yoipy6ZtR0HO042rJociKco3JKuxfyoxoHqxTU9QQRb64XOZQeHd6Lya/X62HotFaMScpJWZaLxSKjdoQAY5wxEUKKEYtS50DivbfWpOTymIFJrfcJTQZy82fft0Xxzg81d4XWq421ERNlgqVEQggsAmNcijp4WK86ymIzKWazSYbs+n4rBSVoY4wheACgFIXkpu8QYwg+EowxblvPBSkKVVUNAAzD0HXbDAZQSgmhKa1zWTydzjmX1tquG4wxjOqcWeZMKb9P72O77bTWRVFMp9QYk5m9AHhw2GzWW13wYSBCUqVY1xofTFnWubWRUqCUIPE+5FJM5oZ67rjjHc17ymeYcrBMUkohsla7Ozw8zKWPlIpzvt1u1+s157ws62FwIQRMXCilVBl8vLy8jYHGGAGYkJxzni8pIlIigACBnUEv0FTV5WQycTYJLgh6IIwQQoFT4IyiUph/MdffcGceV1VKay2lssanSIInBCXn3PoNITGGPm+fHeOPkrKoGGMxpNVy3W676XSaIsaQYgBCwNnEGE6ahuB4fbVaLtcYijzkRwjFOc9sE0ppirBe9fmWUVBASIpM8BJpzG2CXG+UJTrnxnEEynLfTeudxy3Z6YnrxWKRvbhzWjwMZhicdyyh5dEyrspSlyXhPAwGQyCIyYy+6yylPjjIVmJ5yhMi5lIk17IAcHLvqCiKYaiBkr7vnQubTe+cEWmSr+d+F2QGQ2Q+BCckHp8cG9uenV2mxJQqnPOcE0o55zTPUc7prJQ6j0zL85Up5ZTGtBOD7WYD5xQkH/h5gtn943sHh9NXr16tum1dS0Ig9yKNMWWp67rOEzsybJB7IvsWSd/3zpkY/enpMaUkQwgpsbLURVHsRn3tW3f7MLxnveYkiN75ngsuGGPBx+22rWo+mx2UlSi0Oj+7kFJrHW4ur4ONWgnGXTMphy4uF2MMnLPCWf/y5cvprPj44w8OT8quXxDwB/OHR0dM67frzdaa+OzZsw8//LAs65df/ObJk0da65ub5ePHj7ft2theqWK1WjiLVXH6wdMf/fYP/kDz02G0ISJjitKIBEMKStMYWV7ElNLtdr1cX7x6/dWz57+sSD+Obxhjb9++HYa+KPoXL9qvvw6///f+WRaKZPpMPvfHqiKqiTEul0vO+ZMnTwDg+vraOef9bVnM7p0+baqjGEkIUQgGhHEGu5p3Nwcg07Do2I+R7zSFijMhhHem6zqIKYSw428hArCiqOqqstGdnX3T993F5dnr18/fvH11cXGulPjpTxda69VqlaGS5fL8+vpaSvmTP/s3dT3ZbLbtto+uXV5fP3v2jesDBZmIcy6sV21RyrLUnKmUMCafDRD6fhNC5ExiYuPgz84u6roZend7sxmHOJnU9+6f1o3GYKqmsdZbiKUsh8F0w1CpwkVKEqGESi735K8YY2IupuiDF5I5Mwx9m2Jox9XlZquU4pynFKTUOchVZbPa2LKId7eMIaI13nvfjV1RFEqp3JIPIdz5BO08ulMKzoVxtMNgnHM5BFprpZRVVVBKqqqq65pxOp3VRVFwzsdxzOR/RFyvNojYd4NhtigKIQQFRoFl3kOWbCqlAGQOgdYGQkgIaejNONrVap05qxZ5PoxSopwrIRgiEqQpUgqSURVjDJ4AQWcTpURIm32a9hswQ3BDTxABKHM2hJCkVIyxYRg4z/jTjrKQnStyxoDfTk0nMXoADNHFKJxLSBxQrzSLEfMB5AwXNPuEoPdDVev5QTmZVjcXXHbDdmMISVJxRCoVKUqdkTdCUtZ+5AUMRGKibds6G6fTKaMyeGOtDwF1VRCkzvlxtIQQrTXnQgqWJ8KmRIDkW8zn8+l01jSNGseRkEQZ0Voqpbt2GMe+5EoppbUOwTlvMmQtJOtbC3eqhGycmRH77bbPGG+Mbn9hc6ecMVZVVebt70XtXdtzbgnkbEakmKW3LEEqCiWEUkpxLvP4dO/jpnOISGlWRkR+xxswYz+OxnufLavX603eBXm6EQAEb8zo9o08VZAQEiZvjLXWp0QYpUJIH3Ydh4TIOS90Wde1EGK0a+dCXU82m9bacT4/NMY1TTMOoy4EpSnnqYQQIVjTVNtV2peJIYQYcjkAKbJx8JRSzpBSBkR4hzGAKFjutefzJ1PYnHMxvuMnf+dTVhRFM6m4oJvNxruo6sJa2/dGCFVMa+f7EBwQ3tQHFMNmFc3QEaTOhpRQa02Bp0RSilLqEEz2bc2WLHg3pTGhrurDx08evXz58vLykgJz1gshrLXvaiz37Qxd0RBHHzom1OxADWNpR2jbFaVyD5jlX8xfMMoZTYiYIgJBIJQCw7v2a/6V3ETL98taKwSTShwfH08mk2++eXF7syLIGVfjOL5582Y6baSUjOssdickbTabHIxz+lJVVddtl8vlw4cPDw8Pz87Ost1KDjTfBuB9D/hdkH1fBOd3s0NjgMUY2+0YAkfUzoWb6/Xa3wihHj89mE64FKwqxGK5YWM6e3t9dblt245zzgVPGA4Ojt57+uGqe7lejcvlUn33/nx28Pjxk5ubm2++vqJUnp9d/bt/+/+dH8rv/+C71lrGZIyxb8PR4cnNze0wDO+/98nR/MP//p/+XzBWPhHv0uh8RWXOHFN0nLOCc0TKgRpjnj/78psXv26H8xjXRNrXZ5/nzHR2KJG2y80mxviXf/Jv83WHd8ZAMcZSOd8HPApra+3Lly9jjDG00+ZEUTEpJhIEEtRCEMESCZjlRXdaIwAgiPTOuhaBuBSdc9YM4ziWfNfzS5FkUovWejqdomR/9pM/vrw8pyxprZqmvLoOIUaa+GCCC0YoFpIDAKFYVRfjcLtcnGGiR0f3JnV5eX7+xWdfrFfbSVMQwpx1IZrML8tFZFlLpQpGRYzrcbBCkBTB2eicMyMGj4yqqqJmDL/85S/bbfc//sv/2+npfaEkJyBY1ApjICn2DGuaGdchpDvxkhLCIhVcUpqqQt9sXd9vKQkh+mzMJkQkZOScpmR9CAhiMpkIIXIWnBkQ+UTbnwJ7ym7ulVKGlHEIpO/sZrMZR9v3IwXu3MA5Vbo6OJhprVMKVV3cbf79ACVBaXLOxRjy8J8c2veS3xhj7gJwThljUon8Rd/3QFhd14TQ1Wq92WzydNjlYsvLCYF8bcEaH3xCEo1xhAClLM/NjTEWRUEp01rH4NLeIhuBIMFEgo9jTEIIxsD76H0QQmXtkHNOa13Xtfe+bVvnHGNsNpud3qN9N6xXw9BnzwSgDK1z3utSSKU0AZrfYYxpGEwMgJg1LRBCIAQpQynp/funm3Xn3BUmmEwmQjIpKWU49JYxVtd1Hr3OqNBaC65T8s6FlIxSRYwxl/U554wxxZhylWCt8z4QQlIkIaSUrFKiKBTndDKt67ryfsREnAtAWCZbUcqttWj7pmnKsggRYucIYNOU0+lkxW2uhBCx7/u0m8bBVsu2aZqikDFGH4OUoigUpUUIKRPcbm8X42CrqsmgdNv2ulCMQQghBLdt14QQKUVKVgghBBNCaF1IGXMsb0dD2U6XGKLzngpuGO0AaG6+5F7+3kzbu299LXKSlF0MrQtCBEZFBsNSSgDBB5N9JKwN2aA9Jh+TTy54HwkhdT2p68ywk8MwFEXabHpKGyGFc2693nGGT0+LK90OwzD0xu8sGbMuUQHsqsZ4N2Ql89eaeeSc576b9z7PLOKcc54t9nAPxuStvVot67rRWpvRWeu7zgyDnU3LqpZxO/R9aDdBS+tcSilQFoexc85R4HXdcM6t8XtFCbnz2M92rVrr09PTtr2dTpvp9GnTNEBoSokQ2jTTRbfBd/QX+ddjjA9OZ5QVqog+LmcHrJk8Xi3sbz5/Hiz1bmfAlyK5C8NBELYPsRlbyncnW5dkwGmfc4zjKCSrqnK5vK0q9YMf/IBSut38HEDkoN62LSEpx+CMHDRNtW8v5q55XdfOzdu2f++9gjEhhKLUAdAQUt9v+b6p9m7QBcgZxk5dum8Mp5S2240uJMDurhBklBFr3aNPHgvBDo9mk7qMPqQQCYro9ABtiN3hUd1Mah/67ab76os3L79Z//B3T70tNgtx/qZXyiOm1XK4vnz14N7D25vb7376/oMHx+t1u16vpCiKomD0aLO+ci58/NGnv/tb/2zYqhjk7U07qQkSmlLI1ZCQkngSYwRKoieMSkjx+vLtF5//DHhL6MigGs2QUuKUeetypVvX9auLzzMJNgtA8zDqcRyRltnCFwC+8jfjOC6XSyEEQAzWtJv3IUbJlPeexEBIID4BIfyOpruvhtvWckoYY5xRG3wIAUiSUhIaVVEIpYbBhNEY56z3o7XfvH3+689/FaPXWlKGy+Xt7XIxn8+aok4pcSkoZ4mgklJq5WMooNqsbr2LgulZs7GmVwrvnc7MGCmglEoSDhSd9Yyxoig4JznkNM3EjAEIJ5gIiQTpOARnAyKlIAmhXTt++eXX/9t/+l/u3bv33gcfNM00IeFKe++vrq9P5vfKslRSkmQzYTIrWG7arqoPCKgU/e3t9eX523HoMFhMpGt7AogkEfC64ABo7Go/bisHPwAQXKWUSl3ktZcD8D6t2W7XjImsd8xKIa1KSpkuYDabFEUxP5gwBsYOjIH3w2B2Cum81BlPghCgZOhDtlpEzHpHkvWyGWvNCKRALmVBKQ3B1/VEaz2OxhofAwqhUvLe95LyEBwQhpi22y7LOlJK2QWMUm6tDyEoVWit6nqCxGQEL+/bzDmglNalyu8zE16stfmDOz/uVTT7dGQymfQzUlUF5/IqLoyxUqmiFABIoFKaS0UpJTFGa/04RDPGqmZS5SocUiLep/VyDB4rXVEGiHEcPQBIRataA2A+4gGgKKoYIIRoTTBjCyzEiIztVMWU8qIQIQRnw50EADCBCyFf8xCdEEKXxenpodJ8NG1KcbG4ARqtjQRjduh11lPKgcTgo7WWMQAapeRCiul0MpnWSswzBEVphrIxM8YZlXnAbQiBcdBaS8ljjPnj53750JucbGVXstms5pwPY8dY1qmb3YmHYRxDLrkIoQkjY/zgsAGAEGLXdbGPmOjQe2fXs9kk+BRDbrUCQUoQCVJKv51Z8m4LL3jqbQJqEDGlrJWPIQQuMaZIIJZVAQBd1/lg8jKQUq7X63wZM4V4HEcKwpgQE/GhTylyzpXSKYnprFaaa62cc+Nohj6DBwgUpeJ5zMAuEiffDy2IlFsDnPF9cRljpHRH4c6BKuNtjLH1ptv3g8axtcalBNb6mIaUgjGhazddGwEwRn9wVJnRx+hT8jE5iCRE54MFAIKUUlqW5XQ6jTFeX18zxiaTSTOvOJPWjvfv32+33YsXr6w1AJssVmZ37uL5rVprhSR1oxNsEzFFUUhRa1UNg/nmy3VKe03mDmF6p4YmOWu8Q3+B0t0NSneC8gzmVXWhlNhs+4vLs4PDGecqzyrdbNp9dmWMoQwAYLvdUkqklCmFrut8sEWhAeD09JR4Yk04Ozt7++Yi3ek8pSj4ux3f/ReZhEXvRMB5w+f1NJ1OudjZ3zsbOEtFqcuiWN3GmMYYRLddLW5uUwCCqn5wzPj5/KB8cP+plPLLL7/YbvuxU+2mu1r95mD65Pqyv74cyhqbpq7KCap6cbt++PjxP/pH/93rt58bO96//+DVyzeHh6eFmnR0c+/00eWbtXfp+9/7nULMQnApGqllJBFJ9N4prRHRh0DQWRPLotGCQvTd5iaRtdRx48g4mhDC0OcTNgHAdjMAG0QlOeNjNCmlxNFae7u4nTcTI11OcN6+Oc9s1bJohFAk2RQMg8QpuBjcaEO0O1Z5HhtASLwr5Z4+fcopAYBx6M/fvH758uVmvQSA9e3z2WxW15OUUowouJRSArCzs7M3b96E4KTkRSkRY1EUR0dHq25NKU1AgDMAkIXGoV+uVovL3lojhLi+vDGDTSn13UoptdmEEBwXVCkZgun7MYQghOh72/c9Z7qqJpNJSUF4jyluF4uF1qVScuhNSKEqa4K83bb/23/6X49PTv/B+A/uPXzU9eNsNgMmPv/sM/No8fjx49nDh6XmZrCb1U3fYqf1f/izX91/+P50dnwwP3rx8vnbt28rbUpNHz9+ZO0oJJeSx2QBSNdtX795eXL4aOgNISTPyclZJCJKyXIc2ueV1lprrSooAGZZOaVcyWqz7vq+P31wdHg0l1IIwQgEKalUInYmph2JCTHkpjWBJCRkfcgescxpflVVm80mn0TDMDBLhWCZqyWlGoYxzx5vmikAE8IzxrbGhRC0lpxLk4ZcyYVgQghKMYI7y4gYMFOWuqHd81p3XW0hlFIpOO9DPjJiTNY6pbSUygfYU1Kzzjj3qAjEpqkYE8a4tApKi8mklkpYR0Nw3tt8ZgWfht72vXv83oGSauhDDNSYglE99M6agRyQqmrKshzH1bZdQ4dIpkWhxtF2XceZ0LreQZFAYsTkHGOMIN1uuhDCdDqdTqaIuFy0zoVsAZEfWuuyrGL0hOBmswGIuhDOD1qLGKMPVnAFJHAuYkRjHKOcUi61DiFst1upaDPRTVOWlQbAvBPzNsyITqbSVNUMU+q6IQTXTIpcf6w3SynK1WqllDo4OCwK2G47RGyaxjkjFZdSAi2bpgKA1XrhnBMiD9UYY8DsRgLAuGAn84M7qjNgghghRTL0DnGF31ro4L6bwFjW5eM+5wshIUatmhBC8D6hB0DGs405hrBzHZnNJpRSYwZCdmJIrXXbtvmmxxizueNyuRzGVipgDJXmWTxjjCEoGIOqVhUpirEQojXGIiIFxjnlnI1jj4hKVUoJALB2zOtcCsU5z0MyrLUpydzXyHcwbz3OeVVV+6DlnGWMaa1CSEgs40BBjL0ZulYqODyuHz46NmParLdd1yFiiA5JyDA+IcR73zTNBx98cHBw8OzZsxcvXlxcXPz27/7e5eXl9fX1xx9/96OPPrq8vPY+rldbCZLePXI5m4GHzfYWmALeaUqMDePoCnny9L0HL5+17wK676K5eVnuv5vjnVAiP+H+DsId08I5d3BwEKL58ssvH9x/cnx8/Pz5y/wMOQscho7x49lslilyRVG8fdutViskcbFYWGsPDmaz6mC5XF9eXo+jlVIOg0GEqqrg9MkJ3hHBc5TNWUBZVgDEe08Z4Zxaa0Nw+U6MZkgplKV+/Pjp829ebdZj00wcWcxmM8a+bd1XVSWEcPG6rprLy1sgcuiD4CUFoVSxWRnCV9//7eMHj2bBx+vrW6VExOF3fusfn54eEQha675Ns8mTpnz4H/7XP/3gBw8///UXv/rZZx9/+L3DycH/4//+/4zOK6XWUBGSog8Jg+JMK+m9N0On6NF6c3t0PE04/qf//f/zF3/542276Prtg/sn+ajNJHuCIEQhhADCMpuJQHLOTCZ1URSr1cp7nM/nGZ/Jsod8ZBcloaAoVJ9+8qOPP/5uUah794+PT+ZTfT+vrfV6fXl5+fr1a2vtp59+uu3ibDYjhDx//ny9Xq9Wq5/97GdnZ2ca2O/+7u8eHh5eXFycnp5mz4cQwp/+9Fdv3r7qurXz/dHJ9OCwXi5vQnRUwuHh4Xq9zrVmXpHDMHQbF4I7PJrWdd33PRABRN7erNc3KBVPySEJSjOgCSAqLYRiXddlpgAAnJycZAzt7NVr7z0FXhYN59KamDewc6Fu1L37B++9/3gYtovFommmnEuX+kcPn5RluVgst9uuaRqC9OXLl8EGxthkWnNON5tN37dACSI+/Wgqhe66kSBPEYbBDb09P7+8f+9JCJ5zDoDOG0qpUiKlNK2bffe3KIpsk9m2LWWQIgy99w4RYbtd98NGa/XBx7NHjx6VZblXqRJCsnA2V5k5lzfG5A8e3G7YeA5s2X0zhBA8ywLBO+mFV0p9/PHHXNr1ep0LEa310dFRCOH169fRTvPuzQgbu3PPppRneCalkN0uq6rUWqvS5RCyk43eSU36dZc1SNmfKycfiFjN1Xq9Pj4+zm87N7kJIbe3tw8fPAZgNze3ZgwhJDPaEBJXkiB1zjkXKM2cg9j3PQcpJT88PNRadv3WWhtjGMexqsXxyRFj2A+tNb5tx75zjIqmPsA7+lu4m5SAiE0psuwqv5OmaRhj1tqh94vFoizLuq43m02McTabCSF8GACAkNyhTIznVgKbzASjQggdA6xX7XrdAeFlWXIRs2tVzsOKophOp0KIzWaT+cZ5yKMQIgPRduTGmH/4B7/36tULIWmM3rpRCH51Y0I0B4dTzglQolWx2bTLxbbRFQBUVTWdTlNKGdWXUgIlu5OBkEzZyywq70LCqBRTmm+324vz62FwgkvBqzugC/f1Uy4xyd/2yL4o75Zx+U/GpJSMy4joAYAQbgYcBju/p3PPBRHzrZdSKqWub16VZVnVRV3XVVUC4DAMw9gxPpnNJovltfdWqYIz9fLFWd9ZhUVemRlGyqUtpbTQjfdeSi4VTylRSvJTJZ7KsuScSsmllKMZjBnKssxjdY6OjiilX3/9ddd1p6enVVVNJ4fnZ1fXV+vggYJERMZBKXEwqRBxu932fZ8jfa5lkVNCyHw++/Cj937wg+8tVzd/9md/EkJAEj/44INCV1kZuNm0mcSuVZVluIwKAFBaEJK6rrt3fx6TPzyaHB1PQ+yN3UoFZalffBZWy03b9tnqBEAwyqWUXTdkVCnnKzmL9d5Thjm/2V8iQgjn3FqLGE9O5/funWR/rq61l5fXMcbVapX74imlvD4JIZ/+9vuLxeri4sJar7VOEUNISqknj4vTk8fjEH7x88/fvD4rK310PC0Kyfcx/93eJ+zojhB3vficCaKUMkPWjCPQRJmfH5YxmdGsVCnabccYy3sVCM0DWA5PWEokBozRhoAEvXdms2m1aopSj+NojH7//ffLsgzRT2fF6ekxF2Ctb1s7DqmuxsOj+h//09+LULtBfPHrrxbL83Z78+M//g8ffud7s2Y2ANWFklL6gNba4F3etMnZZqIJ+NevX7x69cIHqws5jMSMkTFkDBjjKdEYwbtoxrher0MIVVVwzp2LRgYhCKW877bOhrwVY7DjOOZIvFyaw8NTwembty+B4pMnTybT+uI8vhkWV1dXx8fHwzA8e/bs9PT0wYMHZ2dnujx89erVcrnMAXgcx6urq7ZtJ8eVkA5JF9PWWN4PMWtJ54fy8sbBaO+fzO7dP07o1EBZpD6hMTk+qQyA5MA5n8/zuG8AklLqu23wYKylnFOGQFPCBJANr0mKZLO+KYri+Gg6DMNqtVouLnN4u3fvyFprrSdIlGZlWVqrh2FwLhCk69X2FX0lBCOEbrfdarm59+jo17/+rGmmQNh6vV7cbihlbTsozgkk730ImFlRVV1qrc3ogwdnAyFkHMJ201PKp5P5ZrNJKVsls1wK5KRwu93uWa+5JMroS1FWwSOAz5azmWk8n89OT49jjNlzNZ90OwmjJ8bsFIHsbqgzpXQcx3ws5hZdxrX2cSV7sOQmBSGk7/up3PWS67rO1DBEPD09ff7VOkNSOYTvTvO7Dk7eWVmZmnXbvbnMgW0f3nJhRwJm4HGz2WSdRo7lOd3OP5ZziJSSlLKua6AIBJVSmbaWKQWl4Jh2h0gmtcW7GQyIcb1ec059yMSWFGPkQiNGIcVUTEIVi6LqCmtNbuzsTLD3kSbD/nvDqezan9MCgrtBwnll3rHD8nTN3JNDxiBzhmNMmEAoKYSIdzEvRfTexxRDSFLy3GP2PrZtTykdhjElUhQlIbTv+2Fos61BQickjGMfY5wUDWIcR3t2dR2QGztwAZNJWdUlpTRGzLnC/nOllPKQZinlZNrsg2W+aPmzcC58SN57xkld148eyfW667sh+LiPpnscEf6qnOTdR7yTKb4bgBGxbth0VteNQOLHcTDGUuaZjO9u9uzpkRnIZVVKqYHs0kStlRCCOwmUZtKZc8J77+JuOpMEGe4meL7LdMkf3xgTIs3cRiH4ZDJpbeucQ2SZmRFCoHTnxoq7EdSeMTadTimlfd8rWd258TAK2V4jEJJWK5ejCec8R7hdL7nbZs5j27YXFxfNpMznZNeNmKAsy5SIlPrevXuI8OzZsxfP3zb1jDHedZ2U4vHjB0LSs7M31tqy0pzzYRhCHJQWdV0SErjA2bwSEvrOxxApZTGEcfR5bFqOerlJn68JZZhz9H0EzA2O3A7PfLHT09McgJVSb968ydKJnHVtNpu2bYui+MlPFrPZrK7rokBENKPNDJmLizWjRVXO5vP5crkE2PnQ8f1bebcZDACUsjzNBve81pRSSreLi2ZSzmYNY+hCW1YwT+X11S0hlTEj+9a7g+c5JLpnnOsMunBe1FWJiRljEL2142qZ6obFGLkAYKCU/OKL33BB7j84aZoKMd4u3njvBatTePK9T7539qNvLi5fXV9e/umf//HTp+/L4h5YZo2zmBiDsqgopGHo+rbdrjcnJ0chwTfPf/Py1TdIXDMphOCLm2E2LyYzSZkPAc2IzsZ262KgjCrBK0KS92PfOcE9EMlZsd20lNqyjPlcVkpxxtrOlYVDDVfXb7bt8vLy8ovfPGu3I4+x67o//MM/jDG+efni5PDg4b1TO/R/+YtfvHnzZrlcdl2XIVat9fHx8dFJ/M5HJ1JKFxanpw0h5OLiYrO5eX12btyKclvWUx/6tlszjlLJEBmnjCmdj2NEVFLRBrabMQTX9z4EP47jcrk2o5eyPD09JIT0Q2uMjykQSIiYkJzen0gpmymvmrpq6N3RPEznTQyq78dxcECDKpSQkvEYPS9L6Xw/9Ob9D54+fPgQE1xeXo3OeAfvv/fRwcHhm9dn19e3y+XSO+TUJwTv7W65A+bRYL1dmtE4GwHI0Nu+s0KAkiWiQaRSSiEYBNwDTSQRaz1AyBc/3g31s9bGkLz3zpnsDDOZTI6ODwjSzbrNSUxOt3Os5awKHsZht8f2dOIcJuGOhJxPK875Zr3M5Wkuv5qmyX8NYUdmqapK691M0MPDw29wlemj+7ibT653T2d8pyOYXyVv9axeyGnErGoypmqM8d5KyYXgIWCKhDMZfHI2AGGYwLuoJNvNsCMsF+qEpLIqgpcEIN5JRwiB3F/Pr55fztqQB4VwzqqqqioOgIxRKWWMKHhMEfp+lcK3td0+mSCEYGaIE0oQQggjmowS5YHz+Qoopdid7QbnkCJBkq0ihRC5RxOHwTImMQljbJ5cmwBDSDH5fPztMY984/ZSNHI3ny3X36EI4zje3F4SQK2KDMZi4pQTxihiBEq01inuBPeci6w+sNbHGPNcZEpTipjy9EtCUsTgY4pICJlONWUqJbdv4DmXxsHEO/f1/eP/IPrmXbb/gXcDsHGbMhAmmqLk9bQMgWc18vk5yWlilq7mhS2lzKw358IwDH03TmcN5yyENLSt99Y5wzj1LijFq6oRPIDddU/frbXudj3GGBLuJqakBJxzwRVQ3GmadwOM+TjaPC4wZ71VVeVhHlnHnwESuNPUhBhSCrb3+TbVdV2W5TiOISTO5cnJSV7kb99u+779zofvNU0zm81SIsNgjHGZF3Z4eHh8fMwYvH5x226H3LtFxGHojurm0ePjly/fxJgl5oxSxhgDQpHQg6OCM9luy7O319uNpURSyp11lCbGduOQM+nHOYdIMuyU892yLPcoNABoLb0fF4vstIOL2+1OEY642WxCCFVV5WYBIoaA3seUXM45KAMkqR86IMEYc++0ev/9J227vbq6WCwWyyVmtwfYHxD7LyilmR2AJBKy+zEhhCzcBx++/8F3nqxWq7O3F8EDEMGY9N5nuCZPw8jE8aIopKRlUU8mvt2OjEmlRFFU1mpCwmK15lwDsIuLs2HclpUytl1cj7eLm/fef/TkyZPpZH57u/ns819hEqdHP5od/P3f//3f266///Of/ernP//l5199PT84kWoWgsMUAMg49ovbq6+f/ebNy1eI9v33368q9fzFl8vVtZSMcfQ+rJZeKVFPGLDow+gcsRatCSkRzlkMJGFyFgnG4InWJYClVCDiMNjMRC3LBoBag7e3y9yaIoTc3t6sl2bo/VSnpmmODqfOuSeP70sBZmzns/r169dff/31er3OtV2eV1rX9aOH4ke//QNCCMHw4YcfHh8f/+IXv/j5z39OKRwdHY5jnyK5uVl0XTeZ1IN3nHNA2LN2c4CpqoqQVFaaUmAMyrIoijFFKEu92WwBiA+jkHBw2BSFBBqFYEXhY4wptpzz+SxP7HHDMBiTeb8QAnFu7PvAuZSKaq05pwTkbDb75JNPfvjDH04ncwBKKL++vn706MmjR4+EUM++fv6v/tW/+ulPf4a4yiQIpUQzqWP0Zam11iao4J33GLy1JhLCgieYglQcMcteaUy7hMB7L5nOpw/5VoDPEcG5MUWIySOJiJFxCkCcc8vlkNtmhLBc1mQNbtsPiJgipAiU0hQhq/SaSblvLOVln90PDg/n6/XaGEspZQysHYdhYAyspXtJbu7a5Mo1a6uyrCKfOPlb2dsPAFLC/IopxXEcZ4diz67IYTiE4JxDTIRQITilBQAwRgEI5yxE5FymRGLcuUo557RO9+7dyzizMQ5JrKpKqWIYButTiju6TUq7IhsRx2EAKBDRe7uf4FYUBUAYxzGh11oSQgnuCGKA9N3CF+4eGUt4t1jM383nTj6/Mljq76ZpEUJSgjs+nQLAlOjQ9zF0jBnvYggJgAFQzmmIjFLYKzhzpGSMnZ7eu7m5GQaTs3wpIUaMEU9O58slcc4cHZ0IIc7PL7ebQYpS1nQ2b4pCME6B0BiT9yEGZFrkYJRfgjEBkADYXhSb8799sdj3fSbDAyRrbQyEEFKW5Ti0f+0iIH7b9/2bjxyw/2YRvFl33jvrxoPDajorq6qqmxRj/OabqxwYsl1GXiS5JJVCCaGsHfeN7XyT1+uttWPTVJRyJYuiIJicHeye+rtPpwAgxpCXa+6QZhMaxlikmJlZbbdxzhwfH2qtF4uFlEXOtBCxqqqyLJfLpfe+0PtPlAjGtFe3EppS3ikis+S8j5Smo+N513WUQlFWTVNZazmns9mMEL7ddpzzk5OTvu+vry+FYNaOZVluNr13eSxbMnaMUdUTUVWltaO14/zgkDJhXdd1A2PQTCrGRAiBC0jJRxKVZGVZ+9DuxRR5Mmm+47kTdMc7kfkoyA1vrSWSHeJNCC2KQusyd7Uzgp2RsAxHORyHfjTGEMDZbFYUirESEYNdX11dEKQAdBi3ITqgIsbI9wslr4a8PlJKIcSUdtOtc1arlKiqqj44+vT7733wwQcvX7x98fzNdu0pFM4w5OPp0ZGU8vz8HGgK0bbduiiKsphOJlPGZIo31vptu8nnRT0BpWRZ1koVZaV1iYeH86qqPv1u/Ud/9EdnZ69vb68/+ugTTgsuMEV/efUn//m/XP72D/7b73/69w4m37m98W/f3i63m8i11lJwWG+WL59/+eUXn715+6LbrjkjF5cvhRDb7ZoQEiMuF+u27YKr23ZgwqgiEkgp0RhTiM5ZwnmglBKS8pGaU/jNuhNCSCGMMQRpVTaCq9VqNZvNEYO1LoRQFAmTxIjBkzBsCaTVetH3PZK4bdfPvvkqxvjmzZu+75VSs9ksu4bml3hy/KRbj9bazaLbHvTz5gg9Vax8+PDRzc3NYrE0YxxHO44JMPW9mx8Srcvsm1FVVfZWPTo64kLUdU0pxuQ5J82kSokyBqubXkgQkjST4sHD+WSmQuyRhO2i11rnu++dcc4Jzo+PDs7OFgCMAueCpUStNSF6JXVCMo5BaaibkjEchm1dl48ePanqo5OTe4jImKiryTCMFxeX3nulWLZQaCZ13RTee84pIanQJWcKk1l062FwQDgBiAGHOGbRrZTc7wwiSAiBxJ1XKNwJD3ILJ8TRuWRNCCFSRqSUXFDvbcJQVdWkmYUQKPTZ2imGuF63dKcE2x0HiCBEyPli5jTlozO/3OHhEQBut9txHPu+zVUI51So3TmYbZyllMaY6+vrjGfCnYYqJ9T4ziwKAEx3nh7GmLKpc4W333QZAM/0rkyhYHdOPQAQYKcszO8wlybGGGvz2MGYp74UhZJSbrdrznXkdzOh7xAsAMhKaO+9EKKZVEopzpnWer29MmZgDJQWgquiaACYFNq7bws7eIfPEkIAyJ0CllEzQoBSQPTkTl7CGNsLuJVS2QAh7RKIwDkFoJwpM/qUfH7a/aGWTEqI42DWsKGUWuOCj0Aoo9xZv595Jzgb0jgOxvuirmtGxeHh4eJ2vVwut5tBaz0pJrPZRGmeO/cp0eBTCCQ3kvc0zP1VynrruyL125yjbVvpRFlKpXlKKYTEOZ/P5+vVsE8N3/3i76qD95EJ/uoAb0orO+IyWjuSbhvrRhUVE4KWGXmLOx+YXLHlyWCMibJogs/GnL4sEYiYzSrvnVViMpmEEEKIXTt03Ujsrt+xxyTwHfP2/IlDCJnYiIhEsHE0QnAKXMosHBd7BtY+UOUFnzfC7plDoEDv7iNPZNeF2XMp8uodhgERnfNKM8ZY13WIUUrpXei7IU/p6LqtsZ0P9sWL513fCiE5U+M4eoeciZj81dXNbN6s1y6lEEIQFAhSH5y1QVTUexuTKytZN9rZSGnSpR6NBICEMWH0wSEiAWSclqzMnZ3czOJ3Q2iyFWtRFgA72ZsUKosAGWNPnjyZTqfX19eXl5f5Sm42fZ7LUlVFrosQoy6UIWocx37YzGazx0/uHR8fjKO7vr7m78IR6c5kJKXE2G6YGrmbRk4pcc55Zy/Ob1Nk61U39D4GmggIXqIcmonSWl9dx4SBcR7TOIz28tJzLrMKMyeS+dm4jdPZFBPpu/Heve/oMlVV9fDho3bbf/zJ+30/vnl9/vbNpeB6Nj3iklE015fPv+SzsRenJx/8i//h/9qbbYi8num+37x9e/ni5ZffPPv85vqcgJ8fFMHF1WrRtq0QIjcq1ut18CAkG3oTkpvOZDMphBBcGMYT9dlEwkvFq6qy1gxD13VbQphUPGHwwVJKgWKW6F1fL8uy5IKmSAo9q8ppipSCmJfl0dHR9z79OG/42Wx2cHCQwZbcM5hOp5kcNI7jOI7Pnj3/8Y//xFp7e3t7dXXzq199dnZ2llKaHk7fvHkdQii0ihHa7YhRlmWT/EiRlqqMLpaqhAT9tk8+DaHThZCKIiLjrCyLGAATffSkoTQltEpDiONoxoSWcfQuSkG88/lAt9bLRpdFzfnGWk8wFUVVlopS532MMUolnfO6LJC4N29f3txeVlX1+PHTk5MPyrLsuoFzboz7f/3P/+8/+ZM/fvToMWPgHCJJnOfyAgmkmDzjeeQc32y2ITjOgQJXSiSMuQKmd4rz3XEGwKhIkEfSOgDQSipZaB6H3qUIzibnAmKK0Q+DreqSEO5cNtWjiKTvbc6vETGlmFKutLLDhlC62AeYfeVKKbXO1E1FGXR9O5owm824qKUS+5Ild1sz6X0cR2t3sq7cpkXEbFacY3CucpHQ/NdcKe7rpH1jjFJaCIaISqk8SiREZ81ICEEmMjWaEHDOcy4AaIzpdnHT1BNEoIw0TTOZ1s4G5xyXAnZyhny+70yY5wcH1o4xRqXUfD6vqirGEGN0FmOg3gVro+ApeIGJUlCIZp+gv3tWZHVyduXKvNbcpGJ3pqGZq5hJhXdOihQAY0x9N3DBtNZKibqetW1rjMlNf8S/EsCy53PWBGYI/ebmJjdxCCH5JXIFc3F+e3p6qopiGMyrV68Yg8OjaZYL0qw+GMeu7TkrUyKYIKQIAEAAE1DGGCUJSMai7xKmXQRljFEKUgrE5JzjIoMWEHfeHXQfyPEdhu3fGn3/rm8BAGfZgp72Lem7Qap+Oiuns+rJkyfL5fL6+jpzuafTadM00+l0uVhbE3ECjKkYiBnt0NuYAoLknGldFkXR9+N2097cLILHWhTpzmdpj2fktM85l9MO771SoiwLQogoys1mk5Kr64oQ0nVD7rUbM0opq6rKwEb+7O+6faV0N6E195sxEiQxpuxdmiIBwoCwzWaT2zo3N51zRioGgM65oUfEuN20iBiCOTicZWvV+UG5XPRmsACcIGw2vVBeFawoFGITU1iv14xjVZVKFv3QhpBiiEqpBw+aSePXqz5FppUSknjv84iU7XaHRwrBhVA5RUgpzWaz6XR65/PcIkallJQ55XV936/X27Iscxc84/B53JYxBghzLsQYm6YqSx2j7wdjrZnNDiaTcHR8cHJyJKU2Y3j54s3tzZL/XYuGUgrAhRD5auZmGyJuW99vXuniXGs59IFRGaIVUvNKxGSULqtaEkI++ODxZFqcn5+vlps8CH0YBik1pUQpoZR4+t4EiFwsVqtVO46DrnjbrV6+9JSlx0/uHcxPfzN7fnvdBg/z2clisSj5PdHA7c355fX/8ujhJ3/wB/+c8Yft1jQT9fbs9he//PMXL7/qu1uCjnMSMQlZ5Q55PoiB8BQFQZVSjMkLxQWvBS+990LAdFbeusE5h8brYjafz9mdP4azIef7k0mllKIUQ7DTaR1ipwspeAFENvURQZ7Q3X9welyAlLKQYmCUxPD866+eE6KUevjwoff+4uLi1atXedNmMs5v/fDBRx8+3RNtjDHjsBFChJrUE2B8zrmKyRujAJJUfOyHRUxKKUASfZhPZ0pIANiYtXOGMlkUinOJiREUACzGTVEUCTFGO4zbfkhckKoqTO+j67OfuFIqOBzBkdhLqSnIGJEQoJRrzRkNIaRioqyLZSWM3V5cboqiAGAXl2+Ojy/Lsnr9+nVZ1EKob55/6YPt+k1ZSSQp5xmEJOdNltmMpieESqFmsykA8w7HwcVodaGynDEfl4SQHKgyZjiOJnu3zmazbHquq2oc/NDbxWJze7M0dkDivbdKqaEfx8Fk0DUn3ZTSg8NpBu7u2LyeUaa0yIBEDoe5dZLvjjE2N6UyVpEJWdPpNKYxE/HujLEs53wymbSrcRiGzHGtqqooijxSDfFbwkuei8xYJn8N+eTax6ocrQ8PZnd9wVwWUyGYcy54FrxjjCGScbB1NVGy4EzWtZzOJsHHGJFRIaXu2mUIzkfKmcycowy4ZVJ013XD0KWUUgp5MAshaIwxYxBSEqTOWowkBZsSxfQt/ryPi7tInDDTrPZVVK56s2/wnunTNE0m6XAmGc/eokM+oaSUnMsUIRM2Q4yM78jD1o5K1pRyY9w42jwzBiCjl1zKzCmJw2AYY+NovfcNNn3nlCxjMOvN6smTR3VdSylbu3HexuSMGdq21YoSwiilkguyayLwnBESQgGCc4bdTYeDO23I7mNSSkjMxTejMqU0DsNfA+f3vYz/gxj8Lpaw/8eELo+gB8JiIt4lxDEGUgWRWZ956W632xCCUgqA3sl8EYBlBZe142iDUiIETwghSDNzrqoqSXai1X1ORu4ML/Pylop3XZdxhTz0M2eTMaZMFTImpEQmM54Zqev1Ok9j2zEWRZnupDsUdnYf3vusqk8pGeMIyepWjgh5RFjTNEKClLysFKXk7du3KQohpTEOaFdVinMmhLj/4PTRI/2Xf/7rrh0mTQMAfbedTMXDR6fDMFAGQLn31o+eMTaZNE09Tc4Skq1na60jY8yMjtKk1Czfwb7vh2HIBGbOOSLZm2I+ePCgaZrcTur7vq7L3AWYTCaUDuMQMrrgvX/79u0wDNPp9OTkZLPZrFYrzoVzqRsHACwrVTdaa5VSCD5JxYehu7hwk8mkrubT6fTevQffOmHtsei8PnJOerdGc9sAQwiVemwHs91sZ3MIIQYyjKMpiuL4UI1jCzBtmkII8emnH223p96PkgetdQgphCTEty5iDx+dvnp5NQwDof3t4rqeHhJCvvrqCyEJIazv3NnbC2ehKg4YU+dnNzo+kApt2k7n04ubz9+cvf/0ye+enLz32Wc//uLLz1+++qbr11ICBWZsO/QjTY3gijGx3XYEF5zrvhutDQStEKws6rqaUyDODozTZlLakW42G+dG57SQs6JQUnLvXSjQWqtB5nP/+vq6bdu6mVI+9444GwWnYx+ur14DTR9++N7x8fz29vb58+dZCvnLX/7ys88+Ozw8XI41ACwWC2PMbDbL01FSSk/fv/fxd5/OZjMp5TiOi8Vi290sFothMG1/HTwBJ5XGx09O1ut2296Uig/DkNsVjLH79+/nDfPLL39hrUHiOc8O+4OzkTEV8LyanM6aWYwq524xoB1pCpzJQnJQQgkmPAIlmtOSoCuKIp/yxju+s25BIWhCoDR13YayND9oGBND///n689+bMvO+0BwzWvPZ4o5btx7cx7IZIqjOEklsyy53C7bKsCFMuyngnsy3P9DvXU3qgxUG90PtgED7Ua/lA3bso0uWJZpiRQliqRIZiaZ83CnmCPOtOe9xn74zt73ZFKo8xAZNzLinL3XXusbft/v+33l+++/e3R0dHV1CTMDnDP37p0EQYBQ7ZxTqq2qyhilTZemaRgGTVNpbUejyXiSRFG8XlVleVHVnTYC6LicU+jHhTdcr0vA3DDGk8lkf38fJvUWRYE8CYIgTV1Tdx7ZIBDGsgFLBD8B6dF4PKYUwQgUoEsAiAQtBOB6IRBBCCb5NGk6gulD+/v7q9UK+F9SSmMtzKFK0xRqZtCMVCzXg3j9bDabzWb9HiDOgYH2CG/MH8Y4z3Ow7MBBxRimyrg05BDvgo+H4YOEkHUJU9AZ5Hzw+5zzspxjjLtW1XUbhZlSJi9WWmttfRhsZqttvLvTWuuqrLRWcKfL5bIsyzAMnHOLRTkapQg5Yz3F2HjkrBdcOld8xgHDV6v9p7IfhDHyuGd4QT4UBMFkMgmCoKoq7zBE8xC1IOQY5UEQrJYFPC6lWhkIIQRCrmm6UbbjnAPR0KEZCaoPaCOg3cEThGa8KMyMRoQwyDziOGQcCYkzma3XS2Occw5kOggSCJONBFmP/6NBhd945L0nkO57zDDyBDK2OIko9Z3qjDFJLAYdhu2kZfC7v0rO+lU3jLaKwYRqrZx3nLOIUWFsU5V11zXLshz6xcuyBNEoxlgSj7z3znnOeRjEhAKRFgnCtdar1ZJQNBnP4jgejcZpMuryGvdzoKEA3GdZGGMcRVEUB8YYzhkUPm6u51mWeO+LokjTJE1GnWqstU2jwB1A+wA8ApDjHvi8BFPnnDHae8vQZtgPBL64b7jHBC+XyygKZzsj8ILQ53N9WTlvuq7JsixNw7Ztb+fXUnJKdRRLIdqqbLz3MsRdp6+vFzIgTdMIwZIkqeuyrmsYdXx1du69d7bxnjqLEFYOtUajUTIlBEVREIZyPvfWWim5975pNpwy6HW21oLgUl3X0+kY9WDMYrFsG5sk2WKxCMMQyk+gptkj/GIyiTsVNE1xcXGRlIGULAiCsi6nMjNGV3VuraUkgBozQ8ZuoljrrFOmP2xUSugf4IJq7aF6JKXUnWvKjhB5fZlPZ0mSSowX49FUEOqtvz5fKm2ef/bZu3cOP/4kV92yzgPq7Xq9ZkzU2pqOIh2Udf3xu8vb27yq2jiJ339zfXuKj473jg6/9MmTd3Z2R0bjQI7eefNhXS4mk2VRrsaZGmUTpaxW6mA/uDk/DQhT3U9/8Cf/4ebmllJKVXN7uaaUam2NwQR3xlRCiDQatW2rsWGUaGzjSHrviae2I02h5rcdQghPGbEhMjX1zip7c3kVxTKKAoTc1eJCELEzmt3d33vpxVd//NOfvXnzzi9OP8iSlGB352Sf4g6h8/FIShpFlK6bKtuZ/pv/8P/z3pd11WplY/HGgw90ESVJsjubCiG0Nm2jmrJxDj1+tAyDT2CGxuXl5cXFhff+z374dm47jDlElIGUCKFQsrbWUTJ2pX348JMvfO7zX/ziF7/y5S/vTGej0ei9Dx58//vf/+Uvfzk/LcbTCXYuSyTnnDjDjagXLUJIEJnyxFGXRdlVe32zvk6SCEtedasgk2FMm27JOOWcEsIZDbz3hDprlTbdzUMnJScaYR9i4pulSRKBlKvr+t133zXGhWEYhtFoNFoul13XEcqTdD+Ow8vrK2O76XS8LvW6vJV8ennx0Dq8f7Cjm3qxvs1zhbwMJTGueebZYybMw4cXukWHB/fPTm9QF3jlZ2k2nWVcEGy7tlJKdaMpMqaTEiUxkTxYLSujLTGsLHQY4d29sUfdfH4bxnR3dy+QUb5u2qbDGDfNRvGbEBeFwmi3XpeEkDSj3rcYY4QcpdijrijrxVJxTvf207rBZZlf3348nRwQQrpWr1cN8txZfNMVZVlT1M3GIUJea2PaKmB7HKNGK85C1bbAAHfOLJfLzpkkSRgZUULbmqrWEiIppRZzxlheOQD3OOeISq8ZQghRJrhy1FlrozBJk+nF+YUx5t69ewhLo3FZGIS4d0wph33gLO+WztBGCDso3Xd1q9pOMiYlQwhhiwMSY4dNjRAis1HmvfceCyyxRRQ7KRilqjIWg4xy76bgP8ohIItaayE0Bx4KcnZvZzYajd54440okA8+/ujo6KhYr77+ja+dn5/P5/O6WoeBaJrm5M6d1WoVyqTrmqIrMSIUU8FEGAa6M5979eUkSd584xcff/zg5ur25OReU5quM2aKCBZa1YwGdaW8a6bTvbqu5zeLKA6ee/Z+libeOs6IFPTs9CElO1dXK2tt22rBEkmCqiqklAiJPmtHxoAbwowRhPjgj30/zw4hJKVcL9s+fzDrxWoAXYfcd3hhjGGc5UAdh5+DbwN2Hud8PB5776Fbum0sIYQyj2mLMGYEOced9aimedESoowxSZK0nSOUMixW60UQBF0nOU8mk2me5/m6wZiFWHYdEjbML5vi6iyO473xpKoqEWgusDGIMbFa5ZjYe3fvx3H85ptvI4TarkRYYWwRxjJgL738/K+F4dnZWdM0xqgwElKKslQYs85Ra2iRd3E0adv2+mqVpmmWRtSrLBYc43xdGaMCLpSjnErkdZ4vdnZ2dnd35/P5er1mjFmjKfecc0lZuay01k2uFpcl7K+20Wk6ZlQQLAPJb6+vrbV39u4HJEmCVlPHOWcM+Y5Wc2RCR2kYRXEkxDgeVfV6dTsnzqZBNpvtz2/KT957Eobx8Z2DcaJWq9uqvRA8QogibOMkRMhTijHxEY2fffbZ6/miKZU39Ha+nC/aIEDO+vntqsgFsDGcIxjhIi+nk31jjHfMGPPo4TmkyJxFjLF8kWvdSRnb2t3mtZRyNBJIWHVTwkbyCF/dPAK2x2bcm+873obXsJOGr8DEs7aLU0cZKooujEbHx8fQbnV+dk0oSpLIe/zRh580Ta1US8hG2QC2qbV6KHpfnF9h4jmXRVEtFrd5Pt3b2zs4uPPgyQdxnCVJgl328Wh1e315eBiMxker+doY7x3WWq/X64cPP7m9vV2visViCTL0bduGYegcWq/nzvk0iWC+JsYYIQJSnxjToijSNMUYr9fruq67rguCwPZq45QGGBOlDCiKCcHG2aTMK2Pc4eHRwcEBZEjIO2NMIBljLBCCM2Y0Wt4u33rrrb39SRzHl5eXzrlWdYgSQshsNkPxSGvdNJUxSgY8SihuUF3Xp2cPb+eXsC+dcwcHB4eHhx5p0BGFqudoNILBL8659TJ//fOvvfrfvPr5Vz+3v7c3Go2aspJMvvT88/fu3Hl8+uR7f/z9Dz/88Ga1RmnCk8Ra35huGD8AaVwY2CTOEMqNgQ5IBfinUkZ12miEvAaqLeeUMowxjmKhVFfXHRdYBpIQVFbFfH4zX8MEBUGQ6+rm9nZelmUUJoj5OKacBYKTrlNVWVKKOefad1EYeovWy5VWziitVRvKwHnDOW2ahlkzm+0a7SEUvV3eYowpE853ZdVorQh1zpmDoxeatvKeYIyFCJKEGkWVcssix5hbq+MkPDg4KIpitVqFgRYiksGGf6G1RtgbqzvVGu3BwmKCpOQwxoQx1rRAUgucs9A2FoYxQgjGckwmkVKuLDqjvda2bdtRIhFC1jjVqfW6uL6+vb0BsRTCOE2SBNSXqqpS2hNCBN0o+/h+wAtkVNBQC/Uk4C5BObmpVVmW0+k0jmOQ14miaL1ey0g7i8qyFDyUwmlIfnt6l97MtN+AW4B4D1na9ukGiQzwOgAmQ549CEr8Sq3KA8zotwb+cM67rlqv15C+x3EMlJYoin70ox9B2SzLMmgBgOQPRFqstaNRaqyaz+ejUcYY+9nPfvaFL3wBUIEsy8IwrGXbQyNkSLYACYTWEedMURRCErj4JIl3dvbOTkswQa5XIgQ417unwn+oh9a3woxPdYWgniI3eFxYW99rNw5g8vAnIJZJexFH+DlEfnAM4avvRZBIr/QEDT89MxkvF2v4HkAR8OhKKRYRpdRyuYRG4UE8BJ77IBKA+/66/dnMbwZfeqVM23RA0QcQiFJKKRfCh1EQRQlAF3meO+ek5KNxSgher9d5nhPJhRDQhgT3opQaj8deu52dHa18157m+RL5zlniPRYcw1CNMAyn0+mwFS162ocN6Drcmt404yKlSdvWlCG4wcVisYnwkNt+TG2jCUVCcIy9D5n3mFFOKddWLVbzqu2iNJiMR+ko7hTCBaGWE8KR54ILghLGGKUYE2RwV9eboZm3t7dtp5Mk8d4LFgsRUEqNcQgRByVMrTFWqG+E8z150xjDOfVeE4IwcUEgUhYJwaSUtelGo6lzbrlcat3FcRyGsqoqNpQE4LV1IDcABWOg+bfZGYSWRydZNuIffVgulreEiLZbBpHnPIIa9WgUB6F0FlMqtPJDfxghyBgL0C4UBbMsC0KR54t1br0jhHCCxYcfPBqPpxQHZdlIGb7wwgsvvPBCWS0X15VW0MvReb8yVs8X18vlkgmJMW3bSis7Ho+stet17jfdF5vYE/UDMTjnTivBA4xoVdZlWRFCCGbWeM45KL9g7JVuvKeUMCkiR2jIImLRerm6ury0Sk9HY0QwQogy3Ladaq1gnBKBkLPOgDUH94kIxnhTWgiCNM/zssw9UjIMg0BQjinHX/jia7u7u6PRKMuypmmAL3Z+dbazbpbL5eXlZdu2gvH93T0hRFVVX3jlc1/64hefe+457LwzljpkO5XuRleXH925c+f+3V+/c7x/eXn59rvvPDk9XS6XRVUbY2AeAABQ3iNjbJQmm8OsW62t1hZ5LLisy1Z1jdHIGEcpjaJAYkqpnO1Eeb5CyMdJmCRBEMq2LRkjWSqRxxhjRolSxlkVh+HBwW40YVmWSRFa12rTQLeuc47RIM2klNJ70JGIZVCHEauqigm6Wq0oM/sHe1q5tgFxPkcIcd42TWWdkpLv7e9PJqO6rqtSO28IIW2jtfIwpo0ybK3O8xyTOI4j53yRVxhBcdcRQsKQgw62Mc6YVikMQ4RsYZuGQIGtbeu2VZMJoZRaZxhjUZhFocMYz+fLpmmDNNrZ2bk4v/34o4da2TQdUUKNMQgRgoU1MHCNBEGM0MZqt23btjV4CymlJZva8ACYDwgziA7CWEbWz0WPooQxMRpNwjBWylDKQSrL+sJa6z1iTDAmutZhTKUMm9XT8uR2YRIM9DZZF+y+8xtMcvirgZv9GdcCXzlxFHmMvEeeIm+sccZ4gnd3d7uuWy6XcRzfuXPn7OysbaEMYdpmNZ1ODw8P33zzzf39/VE2uby4BhkyoJtap6MoOjo6Qgg9evQYig4ADsGbrFark3t34JJw3z9dFAVjLM1iGA9XVUxre3u7sL3CBqwwKAUC+RYhNDSIg/sckGTy6fahwTEDHDhU0NBfBF9v//6Q2PQV/U28Ar8/kMhw34fWmc5CvzVCDiGOMaeUUIr7sTloo+WyoQE6yCiQs9wzyShByhmtdd0phBDhAppthBBBnCjrMKbQZeCcxYg4h4qiQqhhVGinjYHZJJa0CkTBzs/Pq6qilIahhBsBvbayawghYNVhl7ZtmySJVSpNR9NJag0Kw5RR6R1lTBjdeO8hAA3DEDAAIYQnGhahrus8z6GrzRgTZVnPZDQYe+4JSCaoZlMzotQRQqSklCFrdddphBxjxDpuHSfEY0yd9QQjbZooDsMw9N6W1Qo6MrTiGDOrGXJIchHIGCojN+Uni8VCWUcob9s2G00+P9tRSnmzaWdo2xaYViCFW5Tr7X0yPGUZkDgJ4DFygdM04pxZa5F163wJXoMy7LyRAc9G+2w7DNzeTE5rQjDnXEgGZTVIyKqqycY4ipNslJZ5Pb8pW1VmE/Tyiy/O5/Obmyut9Ww22d87iOLwY/xEqXIoWCKE0iwk1Cldd52G0eiEiCydCB48eniRr39wc10+fHBhNL44X9ZVO50cgwrJKJtSStu2Vp3CGAeBoNSHIfdYtG1ZlQ0EhpyLJEm0stAx6b0jBCIX2L4yHEuMaddpaz0hDCEEiXJ/9ohz1hrkGDaadK1fF0UkA+RQVdTnpxdVVcmAT0imreKMcc6dxm2jlaq88YQ4IDm3bbter6Mk5oFECDnvlW8xdjJgmGiPW49NEOEoid7/8J3zy3R3dxeagOM0qKpqujN67Utff/Lkydtvv316egosfyBAEoefPHyyvl2tVqvpaDxKs8ViYTvbNuWDjz6MoogH8vln79/cXH30wftX52dhJhgTacrDMDa9mHDTdLXuuq4LAokRryul1Nx7zDnlXKjOGKNVZxnDRjjhGOE0jBjCsRAsSSJMEGhT7+/vGyNAykDKwDssKHEO7e1MRaq9N3W1wF5PxyOj7XpdrNcFFToU2Tgda9NYa8dZpveMd1TIWAgqBEEYSxFh77q2RgjNZvvGGGt1WXTGap8w7IMk2r2++rBpDKEOY9+2qmst8txa5L3VxjnveY02Gk9MeI/LKgdclzFGmdAaU4MJRUIEhDCEwCE5KWHogkOItK1BSCHkBA+QxIwJzvl47Lvu2vUK9XDqOOdW+66FKB4xxjFiyBOCGeMe2ge8t1p3qJ9DrKwespynh845xgn4Xeg5AfcQBMFqWSVJkuflfL4khHRdVxTVwcGBDInqVFNrgjuMmsViVRZ11ynfjw3e9haQ/0ERbnAG8BFG9zjsFh3kM7ngtgP2zhDMKAOykvfOUIICyWGvFkWRZdnBwcHV1ZW1dmdnZzyeQtp3587dBw8eHRwcHR3dkTL8wz/8HkzvYIyhDsVxLIS4vr4Ow/Dhw4fWbLLGxWKFMYbWLLAnCCH4oDzPQdMEGgibukMIr1dVU3dKKecFaJmdnJwghN577z2oOLq+RLu9/tt+dPgKqwG6SGiY1Nszs0yvJLi9VgihoX3I9bNmYbeAGYQuF/g53AuiZPjb3hAhhDzgB9CaNZ1Oi6IAyl7nDLwnADbWWiEipVQYpEAsAHoUIQQj7h2tqgZtJswSKWNKJSUcIcRi0XUNIYRQpHXnHFot10oppRug+AoBcoybZCYMIu+Qs9471LUKurlWy7Vu13XdJnEHsU4Sj4xGCBFGxwNsADx8gN8JIUEQACgCzeK4by6H3nQZUCk545jSQAiR18ApUW1rgiDgPHBegzW21ljr20Zh7IOQYUyNQWkWNE3DmReC5+uyzss0TeMkwZgwGmEfOCuxDygVWtm2bQ8ODuq6brWxDkEQHKWZ1ho7wG4t5zIMDTA2mqbp1Aah7PW/CEjrBAGD6YpllTtnEbKEMGMs50ypjhCSpilsYxCZYQOEMqTSsAWtc1CQ55xbi7TWTaO01pwFtzcVpdzbYDyKKQ7y0jHirXVxnMClaIXnt4U1NBAjQlrQcHDOEepHo6xpqqbNnaVlWQEBT8pQdf7Bx+fvdQ+oZO/88gFGsipV25qbm5vz88d3Tvan06lSyloNHFRoi6KUVrVer4q6bhlj63UeyIhRUXY5wRhOL8GWEOIdhoYWSlxRFKDVAAxAaOhsG9N1HQhFWWu9xwVpc99o06lSnxwevfjiy1EUXV5drctilKYG66aq67qFTLTr9Gwyuv/M3de/8HpRFLfLBfAVXYcQQpQxpRtCfcAIwgwhY6wljDDK66Yqq+LhowcffPj+bDYDti1C6P133r25uVnc3HZ1g51fL5bYecbY2ufrVS6FqOtaH99ZLVYXFxeqVY5quBHCmUfoz3/+s9PTc2v9alkCR4CzECODEVdKtY0y2DZNxajIRilEV5xJKSSn1NkOI08IJoQhTxFiGFFCHEh4eu/bptVaQ7ubVVY3yjmXBGmcpU67+e1yfjWXSreNqqqaEBaFGSNUME4xOTrYT9N4lGbr3NblOo5ScbRfFtWiKJRuCeXOudublbVOK5/neUzGxriuM0oZrU2Zr5sKXV9WIuy8RwCGV1VjjCIYE0q7pjYWj8ax9369XiNPOZdNrTxqMcbW+DjmhBDvDEbUGt9UrUcb9jUhhDPBBTMmoYR1XVdVDaFYCAUtRlD1TNNUK/v48eMib8fjsVY2z/O9ye7QSBrHCXgUay0XFNBaQjauF2Hftq3yGqKBwTBBBtC0JSEkiqIsyyil0Ks2AKHQ40R62Z2madIsVcwhRKxxTdPl67IsK6NdGmSDQ4U3B9MPdnkb9HJ9b/F2BWo7tP+MJ4avYRBA2WLIC6Mo2t3d/St/5bcvLy/Pzs6stUdHR9fX10+ePLm5ufnv//u/N5vNfv/3f58Q8sUvftF7//bbbz/zzDPj8VipFhhwhGYnJyef+9yrdV1jTP78z/+8LKvxeBwEQdu2QkgoxOBeLBA00eCfy+U8CAKY3hqFCcIOY2JMF0YSHFWapgihJEmcc1EUcSYHCJ1szbGGSg3equl+ZhnRlpAZYwy4SPgp0X3zzSBSSHqN/WGpSd9yBm8I/4sIuZ1RDe9D3FPpytlsBpOgsiwjQtIt6f4hLADOmh+Qdu+FEITyKr/FBFPKGWM7szQIQH+GQm8VtB60Xa1UW9f1arWIRQzYtTGGsYhSYq2t65pwWVUNfGLbKu+xEFIpkyYJMN3CMAyCJI4yoxHnkmALWS9cZ1EUG6TXKuccEKoPDg4A4S+K4vH5OUKIUhJFUZJECFvvrXNuNBo5hyipEKqBnEio8N7COFEZMOs65ClnIcbYWYQpK+um6dRkMuEhtYhqZxulivwqTabT8fFstpvEM86CpmnKsrx4lMdx7OqmqlvnXF3XyjqM8eLmFvcMMtRLzcCRdFsSrcNT01qDri0hRKkNUC+EMEanaUY2A6Z8liVa68ePnzzNgIfHvNln/axE16tRGqOttVmWrddufq3brkEIJYn1yNSV//nP3gQUN0mSrusuL24GKT6EiDHOuk4INp1l19d1lkW6gxZJjDxVHdwGIlh2jcrz/Oz0uq40QfHOdLJa60411gullEcOE7BEvixb733TOmu9ECIMI6Od1ppzqbXGfVQLfeKoH2bcdI3WllJGCHDrFWNOCG2M3U4LkGda+bZtETaxDCajSSjCUIT37927vL7I6zIeh2uliqKSNAyEjKLo/v37r7/++b3dvYODg7wql8ulMlo7K4RgnBvvvHceOe83M6KbWreNslIAvlE3bdN2UFw5PDwslraqKuzR3s5uEASM0GKde+/nfmmUxhiv5ov333+/qqq6KO/cubPMV0KI0WTcKtV13WK1jNMkGU2vrp8YY73fqI1SSjkX1rqDo+P5fB4EIgozjGjb1dai5XKdJjvOeu8xwZwSjjH1DnlPpQy7TmttnWs3oozae6905eu6VUpZhe0IqVo3Zau1jjAzxrSNCwKiOg1lHkrx5eV5nkfG6qJY100ppWQcO9RMp6OiKIIgUEpr7TCiUSTCsK6XoOG+qW8ZY4qiQojIqGUMUxZTSrqubtqK4I5SwTmFBh6l1Gq1JlgIHta1CkJKKTVGM2YpRW1rYD+0NdJaMcYow5RihEgYSmc9wdQYUF/CbaMJxYwRzqUMSNu2RV5p7bVC3m0SF6Vr55VHCCNEKZIB44K2bYsx8951Xdd1jjHCOccEGWM8Q9sGevB20EMMDwuwPtXPHVrMV0mSJHGW5znyJJBRvi4Pj3aEcFIEhAhnkbOYYCHE5nFvJ2Hg78H0k74teDj7kIdtZ7rwTyhhbrtkeD1z98QYU5Yl8MMJ9lEo0yT62te+9u677+7u7kKOOB6PAYU+OrpzeHj45S9/FTQIf/nLX373u9/90Y9+sru7W9ellHJvb8cjO5vNTk5Osixbrdbvv/9+U3dZNoYVALd3dHQESCB4PpiPAkkV0KExppPJDPD8QCYikIDxgmc9PDyE6w+DGNIXSHcgWoI8DP8KowpceJ+BbcZ4hGG4jVJ8JnwhW41McMDLsqzrGnBUqOWDAQTf44X4C9c5orQoipubm6Io4PyOx+P79+8TEcFlQ214QDvWRTGAz2B+gyBIssn7v1xiRCnhjMosm0wmE2cRIUQbUHUmGHulYm26ssydc4vlFTx6a6HzikEX8qps21Z57xljGJMkyUCIsa5vOZdpmibxSMqYs0ArL2VIiRuo+K4f0oMxNr6F4BKKPvAQoV4AzzqO48lkbGzXdU1RFONozLkMZMxYDjFoGIooCrynhFSMI6UcQp5zCan8etV4R0W4Kd/WdWt0I0Q0HsWU0rou2+aUkluMOIwzIpqC+wSlitv5sjMWY+y0GoIneFiAQjtvfD+wYTi8WutOdd5jIYQ13nuklAWCqmmqfF3DrRndNLWu6/r6+ppt14eGA4kQYnzTeI4wVCVATIC2+hYhbg2ryjod23vP7eYrcnFWEhI459pWVdUNY4Ix1nU2kBFPEKW0KEqETZpGUnJC0N7+7uJGgS6oc8h7DPQKKQLO+Gic1ZVer6rJOE3TlAt/ef0oCay1ljMpBKNEIE+butPKGu/CMLTWCSEIdm2rnOso5aqzlDLoIsWYeI+MMW3bmU7fu3cPBgqdnp4iTyjh1vg+ityUWAjhGDOEqGrt7iQ5ObkXiAB7tL+/75y7ubp0bOq9Y1RQyihlQRBOp5Od3SmkAqPRaDi3nHPKmGetge7Fp1p0GCGnVSmEoFw0TYOKklK6Ksq6e+RbvlqtnHM7OztSyrquoWttkdehkGEYtsZK57VHMk5qpYtam7yplCuqUimFKZ3sZYhSKUJjTNdqa1utNcB31vhHDx/nec4FWy7XlOIsS6SUXdetV3ldt11rOQsEp8gT55A1DoB6YwxG3hiHEHYWKaVN5Z1FqnGLdtWU2lpvlMdeVGtFKaVeRCLlnNam5gFlJFkul4wQZD0n/Gjv6Jl7J4TgvZ3J48vbTjGtdVnWUoSgWmetNW7NGEPEeOc88sYqhBkmIggkoY5zJiTJRhHjBCOKMUvG+84b6KCjlOXruigq1TlCQlC6pUQz5utaY4yVMoGMvfeUEimkRxsT7JwpCyDRcGt12yrOKcimGqOrqrLWJknW1Ga5yL3DaZp2qsIEM0K0Vto0ziuErPeGc04ot9Yq1bqebIUxRvwp62fIkLz3SZKAcR8SVvi1MGTOedhp1jpjDOfCObdcrJxzSjmMFELYe8y5JJgFUqBekQpsBzhgsPtDyeppvovdZzDYbTrIdoYH3+/vzKqqQtZEUnDOobbNCf6n//SfAlTQdd0Pf/jDxWJBCLl79+6/+df/Vmu9WCxOTk7W63XTNKNscn19vV6vEXIgB1E35ZMnT95//72u63Z2ds/Pz1VnsmzsvT85OYFGpqIoEEKD84PUeblcVuVKSglqTYDVc86zbMwlg2WEK9zf3we3ZPQmOgG/Ag3cAIdu3+m2Q7XWNk2zWq2A4Qx6FDCnb3u54J9PQ/menmN7ETdwQjs7O6gHtK21hrLtgGnIiyLOnHOLxUL1o702+mvaUeIx8t5hghlCCARYCGMIEfg00I6Wsl2v10ZD3O+7zsRRK0VbljU4DqVbhKBeowkhnVJKGcjkIPVarVaE4NFoBPQFQkhZllprQFMh2/OcQ988oxI0mS2BOegFOI6heg2hDMMMY9x1HZg1Smnbtre3tzKOhzCUMeaRsdZWVdUVVsrQGlSWVV3XVYWjWHJOA5m2rWIGdapjHBntnPdtq9rSJkkkZOg87pTJi7quTBh4TpLcNG1T1pW2FqAUb612jaeUWoQ7Zay1lAlPqDGGIEUp9ciDogh21iOHsOnabghkBwcKFaj1qpRSykBQItvGOFuozmrrQHQhSZKmbqqq0lob4xn9dKY7nD0hhFKdMcajjZTMplcyaSWPKQplIF58ZfLb/9VXzp6sv/fdt1dLAhNjzs4uKEFJnC6X68o0L774fFWXeb5yznpklWrLqkizKI7TtlVad1GUSBHABJ62VTyQcZQV5e1oNBE8uL6+2d3LxuMx8dhoEgQCcFGMadeartXaq+l0plRdVy3GtCxLoDX4nvoPeS2kO13XhUK8/PLL9+7de/vtty8uLiBwxhj3082I994YpzqDPLEGT6fT3dner3/l17/5ja9WVfnBR+9TQqIoqqqKeG6tzau8JjROjo6Pj1999dUs2bXWPjk/U0o1XUsFp5Q677VpnfXOGWOsMY4QIkUohCCk/fa3vv3666+/+eabP/jBD5q63ts9ODk5qZfdw4cPl8uld85oXVcVqI/WTWesbbWySsdpIqSUQpRlmVdtURSecCpC7EijusWqVEqNImGMU2ojvBUECgA9R721Fil0c3PjvcX4iBDSNqqp66bRzmIcghQa8h4755bLZddqsCdKGUopJVwrn8+LKIokC7uua4rOGIBhqVEUcYIQo0QwRjFuAJKAzvqqqooij+NQCEGoj5JJ3ipCyHIBcxQk6vWhXvnc3TRNGWPeY+RJ13VCBDs7O8vl3LouScMgZF3XdJ3GiDuLZJwyToDhZa17/70HH7z/wHvUNgpIs4IHjiOjHaXUWVRVVdd1YRiEYei8g4zTWu0sg6ZAmNkHY1G6VjXdMgzDLJXOkbrSYRhiRJ1Dd+6dQKS/XhcE0yxLRuNYBhT4QVJKY5QxCiBo55xnyGwG1280g+AYwhBP1sspQ3xtjBGCcs4BLgvDsKqqsixns5nWGuJdjBjBLI49owFjLGAUMFLUaxqDuR8YPZ9xqKCS4bfKnGBYQYX7Mw4GIdRVBfyv0Wg0nU6Bti2EMN4zxl555RVwGFDomc/n77zzzs7OjlLq9vYWHNLOzs50OkXYwbRThFxCkzAMjdHr9fqdd945Pj4W02AymVZVNZ3uFHnlnFOmA0MEwCAsFDhXuP4wDKMo0doyKuI4pgKV5VMaCigChWF4cz2HKxziEtKLag3Z//b3sFBQJoAWfyj1FUXxmYyZ9FJubkt5aqgUAmIJJUDobIGvNElALw/0f4bK4MoYaPgGcBFA8uvr61YTeFtI4qGy0LZtazV4dAzjgRECTRjpMQRjgFsgRG5vb41xYcjbtjVWAcAZBMIjC+OHnXPQYhtGMggkyENCZcTAqGYhwHEKIaBb/ebm5uZ60bYmjjJrMELEO2W3BnQO7cKebLJ2SDph17l+Fpn3Ls+zJImUboqiWCwWAkWUVtagdpPIOKUbjH2aoKaphKSdqjgnWZZ4ZOqqNYi2TFmrZcCECOI4beuybc3p4xXBzBrSddZZRBlGyBirhafWWhnFhJCmaQSmnIumaTg1EBsbo7331m6EZhHCQyC7HatxHjZN07ZKyhBjBMBHVTWjnene3khKWZZlXSshIinxarViiArvnEcOYU+2GPlt28D54Yy3bWsMTDd0UXy4d+DiUf6MwAcHwc314smj9XKRV7mcTtnBcTRfnNsuLpYhwS2TRasWzmtCbSBCjMQv3vyEc/mLN55IGXrvewGwghAiA4YQIkQXq7X3oq6M5qUNSZ3P21aPYOCo4UIIQonWOpQSey9sXMxBDgZ5r6ljzjlnLGNUa4UxklJ47xmjQSARQseMTwnF2mqPa2OjJLK6nSRxRUQURVdXV8cHh0WXm6raG43mda0rt7+7E6WSBphatHuw6zQeh7O6uEUep8F4cjCLoiiMJNPMllYj4wmaX8/PLs53Zzu2UvmiSYKIxaPr22tKKca8yHMpZTSVxPN8VVKXCj8hXfbs7iuzSapVFXpx9+h4KjJldGvsw/Pzm2WrjPcEO+JYwJz3OGQt0lzy3DQk5iOKnnnlXhiGxrjzs1zZEoDMVUFB0kWEmcMCYUxFPIpGvqtmx/dB1Q9jzBGfhnua+TvP+3xdekeVssi386t1FGVJkrhYIgGaR9Y6VdQlQi4IgngnXCzmzrnJZMIYLcuGOBdEfGcvhBg2jgXnPBghrTXn47PzT1jUjUajuy88E8dx5yvqqdZ4lIk0GR8eZAgds35MkPceptENBximUBhcIuGyeFyW5aqsRqMR4aKqqiAIqqoxxnDOMe6stYeH+7u7s8Vi8fjx44ODAyGEtbYoCibo/v5+GIbvvP3xaDyD+CwMIwgs0jS9vrkIQlFVFWNEawy1tLqpVEmCIFjcFozycTy20gNvK0vHy+VSKTVK90Ay98UXXoXEC/zZfD631k4mE78RhhTOOcjU27bOixVIhoUhNcZUVeUsFiLgLLK6q0rddmtwMBTRtnMyYEHI267ai7MgCKlDdd1eX93MZrthGEsR7u3ugnfnm+E5pigKQIxHo9FoNGK9QiTU4dI0BabxkydPHPa6MwcHB5xzPhWAkQK9HyBfa20pwtbcUEd5mPEwCxmLgGMPMh0OEyoZYh4xrXU2mhm7WKzmSZJgihihTFDrjUdetR2kWeCHoATjLI/C8WpZS2m19oSQR48eYYwBpCn7nH4ogsZRZMwmUoFRzZRiIUnd5MIG2JOmajnn2JNGt96humwoNaNRwHkqhLC2Pj1dAN5+eHAPQGOlVFVVkIoRQhh3QRAEAR6PQyEAOqZal1k6rarKWV0WNWMMuFdxHF/dnAJxeqh/UUp3dlKEEMb+/PzBxcXDAbqEj4ZFAM89JFXWPC0HPH5UgKM6bwrvKYQgQ80CggPGGGg5EEIYxt77ul5ja7GUjGKMseCirldVtYTMRGs0eBHOiDXGWiuYbFpPCSU4NNpZzRrrmzqPoqherxFCiZTxzg5yzjQNJwRp7Rmvyq5rK6098jRf11o7a/x4EjuPjTZaN0OO57133iKEtG6G6WTOIoKlaQxs2vVtjg1K03gUTSYvTh89uBnmdvvN0CHMOZ8vzoUQzVrXdS2EoCRI05SiSdXdLJfLyWQyGgXrZYkQimJ5eXn53L27GNGybOp2XVaNMchZjBARTGKMUb0yG0HKBcRSQjDOOdQdoCcQgHQgdsARgxQfb6ZLKag0OecIYVGYbjrEFBIRjgObRPxgb99bsVqoLsebJl336e5AhBDC/Ur1lSoIpaPEHx3v8qBr2sX56eqtn/7w9so0FSYMlZX9+KPrpumIr5Rq0xFTytxcr4QQAPQ1/UQOEObtQ3sB+A9MUGcMJF4ZwRxqJ4CO1XUNaA/sM8hUnHNSbKC2gdQANhpbAiEVIYRzgRAy2iCElPNRFMVxDFp62CNGCPTbaN0JRqq6CEN5fHiUpumz9+/eLG5XqxWcDSiKgArP7u7+eDTd3T3Y2z3AGK/WC865lGFTrmUcTcc7k2z/k0/ORmn2zMndvZ3dbGf6la98ZXd311r7xhtvvPPOO8vlEmOMvb64uHg0eXRzc7PK12HEBWOUsXc+/ikmREaxJgbzOh75EDOPCCUZSPiCWYf4nTHGyDPGGOeQ4DKOkuvrW0q5UioMuXMjaPOArbBhAiOWJIEQWRzHVVVFUfTyyy+XZRkkOs9LY1y+rlTnrq/nlHDGhEwE2cgeYW1U29abOlNlm2aCEIL+TtDEkVKGoxjgJtbPtIe9NJuNh4up6xrqIpDbbaVfiJANHHpxvrC9VDLqu0EIIaozZdEAftW1G3wvCDqlHJghAP8nkyjLxkmSZdl4MpnA44Px4JTyum5Ho5H3vixqAJ+lDIgg1mkuaFmWVVXA1NKmqaBxXoqAUt4TmCnnGEpxuC/mDdEDmJXxeAwbBgBGhFAEw6oasJubOQ3Wwe5yUhpCmDFIq65pmo5o1Zm2bXd2d6DwOehM9Q1+TzMnAEWFCDAi8Imo5z9DhOH76jKUUeGhwJFfrVaQaUFvCRwxiFdQX9+CUwDHqmka2ADee1AKAy/SKfXUeVhrN8KfGx7JUDMecKmBqzFYHvjbvhbggB0Gl0H6tunPOGDnHOebNZdSCiHKsgRsQ6nl9s6EzYYxruoKHhDsKFguxtiDBw/gMob0FC4sTvjQWu173pbWerkojDFpmgJADW05bdtGsYDf9D2zFdZ/8EDD9/CC8jDp6WCon1bbNhv4GvdVXrhfCEzhNaTgcEC2gUzU97mBnwPjOewEOHcDkwjeBC6M9bUPiEWstUp3RVEgZEB9DPd65tDjW5ZrY6xWoCVgVeeUstbaulkDlOJ6Shc8R0w82aKhwU2pzWzjIAwlY6Sua627ONnwwGFBtjeztZZQPRDj4YnUdc0Yg95xeL7Deu7s7KyWuZRSCDkajYz2TaO981obTj+FDA1gxrDyYFLwMC8kkENlYXvfbgpMPQQCb8UYWy6Xxjad5lwgSrizuqqUMYZ5ZDHBnMF8bGuM0dpYayFf3D63GGNjzOMnnxDWJKnkXMyvi7PTteSZEIwLZK2r8i4KU2tdvl7PxJFX4WpZMdbFSUQpy7JESl4URVVVhCBYHaj+gnninBNsOeecSYK599jZzQaiUnprddcBIuCM8dZ655xWun1qlazqrOqstYQzgpmzJpDR3t6O1vry8rKu6/HJ/f29vXAyIYSAivLGTFg9v7n+zd/8zf/T/+H/+Owzzzx48ODq/OLv/J2/86/+1b/6/h//Z0YIdn40ym4ub6IgqIvKWntzM1/Mi6vLeRiGGPuTkzve+65eWatn472//tf+9nJVfO1rX71390i1tXXtyy+/PB6NPfJlWc7n848++uj73//+n/zJ96ANdzKZcc7vnRwmsZABb9htFEUyCIumFWN0YGYI087o1fUiDHkUMedc0xStcgDBqdpXVUUJOz4+wZgKEQQyShMynlHIWoa4HmMcBIGkoIPNw5DnRa20zYub1Wq1fnJjjGEsaOqW81AIKgT3HrVtTSlF2CJMEXKEII+M8yiMeJJmWmtKHReOG1c3lW3qm/Xaew8y+iC7CKc9X1mgBdp+vi/UtObz+QDG0l7Q31rb1C1kDxB+bSF4ArwRYyxfd737NGD24X4ZY1oZqIws5su22YB7A4+xKAopICnBURRFUeScW69XNzfXXADtAgHZGyEHG4wziTGmhGEMtCDBmQS+oesHSIDPALT25uYGDiScTEjy1us1QhQhRCmhlEI8CcT+1SpHiJjN9EBYZ0sp2UgQU0oIiaJIKQUJwdHetFfI8ZQI8IjWmtVqtW1KwPzBMYEIdXB7ECSB/xBC6H4e39XV1fn5eZwktO8eMRuxGgoZGfwmaLxsBsUIgfpiNhgg2zONwzAE9BuAa3j6zrkkjm3PyoZLxf00ZTDc4PWH9wQv6HtoFz9lFz8dJAPx+kbLXRmgaLmNNLHrDeumJWxwq27TL1QOiemQjCKE6nrz5hB2AH7QNA3nm0ERWmvAuiHirOty8Gqob6qmvfrp4POGsAOAXMiDwWfAkXEOQRwwfC58FmP1Zxwq3MtfuJjgJGA9oRLnvQfkA65ke2XgejAhgMdD/ZFSyhGnlFZVA6PYYMNLKRkTCJGmVs4hpYxWRmuPEAkCSQhdLG5A0hVthr70y74ZhblRHRmY0lJK74H2RWUgMKaqc0aXcBdDMEd6kRNMsRAsCARA7k1bGavCMIxFKqWEpA4QICjhEeuNsVEY+IgtSYm8oZSpzm3HMUBUhLNW1yVkFAMbcVPJEgJvAcZDsDKUQrZjJoyx85hzLkWIiW1btVwsV4umqS2TUtpesx4sXRRFnPO6roYN7XuBDmst9+z8dEkp3t3baWo0nYyfeeaF66vbi4vrqkLOsjiOtK4oI95jwcbJPm3bmjPedQ3nPE0DhAq4dPhoAL7gU0ajESVuNBp5h5eL3Dk/Go0Y43VdZ1EEJwpscSAkdBBh5ChBVPK+rUiUFCulgiiENGs2mz333DNt27Z1qdp6NpkGQUAwFozt7+9LirtynYYBE9E3vvbVv/I7v/PiC88RQkzXPnr4yZ/84Ptf/epXP/zoXWvtfD7Pi9UHH3ywu7vLmWAUdZ3mLNDaLhYX43EipdTKNtWaGRzJ9PXXvnZ+cSvk+Kc/ffuXv3gjlPqtN94E1d/Dw8M7d+6kcXL3zslPmBSMH+wf3b/37HKxqOv8/Y8/fHL6YHbC1su6qdtlvm5aRblwCCllsEJ11RSiBFsG5iPPc0FSrS3npCiqIq+urq5hYvzNvIE2O1g610vkj+IAhAuklFVVTafT25sPLy4u+mROlEXNuVRKY0TruhZxuGmkoRicnHMGISQIhmY+ay3gb9B/lVcIYwxaSMvlMkmSJEnyPO9aPeTuYJtMP2J9MKy4Hw/nNmMxofV+U0KDAxwGYrVoEEJhyLVWG4DIeutbsDWUYmv1YrFarXIwvl2nQd0CYwwzd6U0i/mSMQbdliD4MF/c3N7eHh5NZzu7YRhqrbtWAZColKFWW2uNcSBZLDhGvtHaNk0FEvYQg/epPAPSEGRUCKE8z9GmXQEIWWBkjdKt954xonEDpTVCiNbWmBaSUS6w97aqSq019BMLwbJsFxI4rfXt7a1Wbr0uYIzgNjd3CM/h0A1rOxgySikcLkIISA0D2Ku1RtfXw9l3fbsLY0wKsQ1+QizVtq3f8oLbkGPTNJAmQqaO+s5awflgfIbnDu4nyzIICID1tm3gtpOV/r42EC7kZ+v1Gs6ac2i5XMLmHEAgQggIpAxJ5+BrCWHDWg0v7z3nmwEDlFIhNFhh0EWAxzokQ4BDFEUx+Fe/BTHGsfa/wrnpXb4CpSogUmgNo5mYtQ5KbAB5eO+t9Xm+GI/HMOIear3bidfwxIf1gblwcOhwX5a21sLc+wFBHfYMhFzee6gFCSEiGVFKozAG/oFzLgzDOEooEV1rmkYbA97XEsLiKBqPp3Ecd109RAC45zoMn0V7cvsQpgjB+kTZMcYM8arrrLVBEG0HE+AFwjBMsmyAZIb0GvVCKKAAs7e3B7UJa+0L959rWwW+vOu0cygIpLOI9uw52r/YRne9M73+2sDGH3Jfu8WY237WQww3nD7gBoZhYIyyRreN8t5nWcZg3DfGCGOY02Ta1inVUUoH2If0jfmEkHF6x3m7Xs/1iEwnsyCkX/i1ZyfT13/vX/7k4YMnbjNfnWTppMhbRpHSBcI+TgKEhfcWlolzDvqyvp91iPqpD8iYvdlOEmfLUZ4mo89//tfSJLu5uWmbGsIZQkgQBBAxtW1blQpSZ6DqVFW1XC7rur5/9x44+CzLTk5O2rY93j9cr9d349H+zi5J0heff+Hu/ftxwLtiHQnO4/Cll16a397+8//PP6uLMgpC59wnH7738UcPCMJWm7PT06oqlovFf/2/+2tam3feeZsxPp3sPXz4+Lvf/W5dl0VRPnr0JJFYUNmqerWqHz08++CDjx49/LCpltkIP3r0qOu6u3fvlmX5xhtv1HW9Xq+jKLm+vv3BD37gnK+aSkiidWMRPr1YtV23XudFUTiPKeWIEuQJ0dQYw7nBm/FhiDHW1tQxJYSgRFZlu1gs66plNDC6bbtKCA2IPQRxCKEyd5d+RSktioIQMh6Pw/Dg8vJyPjd4k27SuvZxTK0hCKGqQHWnMcYIGYQcxh6TPsrzPoo2iV0QKMZYXeu2bcMoxYQgx52xyHFGQskTwSwN/SZCNMgiZPopoTs7O2BAQTTUe+Qcdg4jJJB33mFrqMPYGIcQ8g4TbLsOBrZgpZy1SAjqHImibKgfW2thODYkZ6BR5cnmkDjrjEYY8a5V0JKBEBKS7exMg0AQ1lHqpaQIOTiA1nrO8WqxUgrCcExwI4QgBBILNYSwQ3IG6Sbs84EP1Z9J4r0HB+y9NVZhjIVgCjXWekhlgJUqBOOcYuwx9lEUeC8RQkopIdhkMoqllFJqvSiKgmCulEGIpAmuq2qwpIN1gEQfPAeYiQEtr6qKEALRGEyqAQqI6jFY1POSNsFTj0YMphNvxs/5IVvd9mTQNQRo/NB2ghBq+6oe7jt2huxwyJyGXixKKfzVtmvEG8S4A2yjLEtIhuCOoCcEQjcg+0AwofUmFNvyfwBly894396ZbUwt7FLUowtu0xHbjsfj/f395XJ5dXU1mGzwGcOtQSDymcBo8Jfwtrx/bXI+7QihgjNIdi2ylFLBAzZiMIx2Pp9fXl7C3w5lMr+FQsPnQgM02prmC0cP1nM76oVbDjm3DqqTG9RdG+ycG49mEFtyTsMwJoTl+WZEhHPOGGetZRRbaaEbcGdnByo+uAdy3aZcuFEGxT3Z0G5K+z6KAoyp1rosa2NySjnnPI4p1EeGFB+ggjTdhVPWtk0QSABahmBuiHUApsYYx3HatvO6bttGA9AiRegsEZwOx2RIfxFCSZKA5YTQAa5hMKS/+jJbw8s/fRm4aZq6Ka21GNEkGccRSZKMKd3CRqEMe0Qo24QAzm6U0uDD4DgJIZbzdjobcV5i4oOQ3sxP333f/6W/9F/MZpOLiydNUyLCKcVShlV1m6ScS1TXzTrvKGVRmHjvKeVaW0Iw+F2Y9wL7r6qqV557ZjaZKmXKvPAWqbbjYxZH0ThNh42FtrC1INgMzwKAHmowxhjJAJezhBCCHKf45Pjw3smxulh46wjCHNY+4AFBAcarpvjk4w9Xq9VLzz83m05122mtkyQ5fXz71S99+c7x/sXlkyovsjh54dnnzs8vvv71rxvtoyhzlhzsH01n49l0t2ma2e5x2bmHT07Pr1acE6ddQEg2mt5/aR9qyUKI+c3t5eXl9fV1WZacS4xXlxc3nTLOmyCWVDhjtGNa8AD7iFNqjDOdscZh7JHDjIXesaZtq6rDeAOvKVpL6ZyrvcNFUVnrtLZFUWFErfbOUeQD5DhgUMVay0BnWcYF1Vo7bxgnVV1o0zEk3UYnr9F6g4VW9SogKcYYYYDguJAMIaS18xYbq5w3zpumraSUMDLZoQ4h0mmvTOdQp23ddFiZyig+BOCDxQnD2FoPIf+QnMHJiaPMO4M8cCWQNch7j7w3utHKIk60stZ477F32FkUBCGkWeAO67qBOYYYE+c8lIb7jM11nYLd2HUdLr1HZjod7+xM9w92budP6qbwyAoeSCm1Ms7ZLBvPL9ZVVRHCtLLWWs6l95CZoWF/Dh4FaLdg5gZVZzicQoTeg1YWQ8gZC/IazFGH8abeirEPoyCOI85p12mMcZpO4zjO8/zq6gph77wtiqIsK1DK3d/bK8t6sVi1jaJ9+9BnHDDqg57B5w1uDNwzUG2jKHry5Eld17wfhDc4DLgd3AvhwrvBAZRSuk9TSQYDBCkjBCIAHkIYvVouyZZUxbBuUIcegEHUCzEOudRg4OAFABvqs2Qw9JA5vfjii0mSPHr06PT0lBACT4RzuX3vAA4BBrAduAwr0wPUmwUEn8G5ZGwThUyn0xdeeKEoCillURRdp/tkfZPGoF7VZLBdeCs5hpW01iJEKAWZDuPcBjoesOU+BReYcCh8gtIy7sUiBs89fAqs6s7ODhSnfV+npFvTrwcY4DMGVgghJYfh2doopVSRN1p776i2vrANQg1sACEkwZ4SP/hUENs/PDwEZ48QAtcI1wbqN9srPGwDY4z31hjjPYbWhq5nD2CMAfvtGWS6beswDBkjYSgppWmaUkqbpoGeH6B9wBMHld+iKKqysRY5S6QIvKcIEUqZlJtrQz1tArarlHzYY0AvgMy702o7eNraLZ+1A71rdkopEH8cjSacofW6qKqKDabQWiulnM1mx8fHs9nsh3/6I9g3YDggkJdSFkXZqSrNAiG9sU3T1D/76YdPHp97PYuyNpu5ndns6ryZ3y5ne/wb33ru5OTkvXc/ePPNt9umIQQrpTDmzm40leAQwqaBxzabzfI8Pz+/PH1yEQSR4FFZVlEUdVU1HAB4ZlAlanhdVdUgFDfUWtbWoi14E9aAMZYpaowJKC3X+dXilmPPkUVaa2o557rriHNnpzLgoqnq1WrVdfTi8smbb+H54qpt6zQdffD+J5eXVzyQRjvOw8V83XWqrus///M/71SzaKxHeL5cSya//rVvpAGdhLLO87MnT2az2fPPP399fX1zdUUQApNTVVUUJabTnVKY0apuVVkr2waB2J0lIpTIUSqJsyhfr6uqIoLAeYPH4foyHrJedUZrDUM3OQulCIFCOSAZuC8jlWWptF3npTEGY1LVrdJWaYswtcYao5wzzjlCMXYIe8c4brsaTBNlmCNECHPOWKvrykDcTQhxzlMmwkgY69tGU0pVZ7XWzuKuNc7WWltKxK9szadTZrcNMWRCw24e8g/4vmlLhL1HVpvOI0cZRdh5ZJu601qDagHn3DvMqAjDsCgKghnGGKgZ3mFrneqMs5CeCoRQVVWc4yDkARbHdw7LsiRYqM6CCqzWXgiTZWNrPcEMbgcUtr3DzpltQ4Z66OiFF15YLBbn5+dQyWvbNssyKSXQXWENnDPWgen3cZwIwTHxWnt4Cl3XaI12dg6ur69hEiVUf0FctzUVQiiKosND+dKLr5yfX3qPGRVDZok+nb+6rcEPg2vxPTkLYzwajYYu1aIotDEQNIDjHG7Nb0mIQB1k826fnukyXAPo84BNhwcNc1jbphm4RRAzDYAkPMfBOsMtkP7lt8rAhBATXTRqAADr10lEQVSYwQwEHOB1QtE6y7I4jrMsA5Fq1Us6J3E2JNyDw+66Tul2m4WAeo6rsxumJ7hVsCpCiE5VkKg0TXNxcREEwdHR0dXV1WpZwvtrtEljIAsfjNi2mUYIBUEAwOZwVBElWFDOxZBJg0oBPIi8WJ6dnS0Wi+EnsEQ9dvL0yKMtQZUhZce9Vhf9FbFSWN6267zDQogoCkEkThvlvbfGE8KEIPApGGMpwyTJerxjI+kKbqVTDSHHrJ+zC7AlbDbK+LDIuC+sYowR9qpTXaehksIZM8ZCuR0gcUhGh/O1WCyg1gamA/aY69uZRqOREALY7Aihuq6LptLaYkwIFoyJtjFa1d6jBtltfHtYk6pSfUzgoYQBVAnr3a+SsFCvNLddX4C3CgIhRKCUq8padRuV8q7rGEJOCBbHIQSwWZYBA22IBOHpwupyzqOYV/ViZ3/n4HCcjYKvf+MrtzerP/mTPxuP/Jde+9zugTw+fP4P/+Cd7/3hj4/u3PnNv/Q5b2OEddNWTW2byl1fLTEixjguNpQEQjaMTVjZn//0Z13XIUSyJJUyPHtyenF2IYRAzg77Y9Br9N7XVTMcBoQQnDGE0DhJgfc4uGqgAHzpmVfuPPssSdLz8/O333sXe5NIZtuWpUy3HSHkwccfrZfLNE05ZRhjZ0KlahkQLrBzhjGRr+vRaHw5v6FEYsS7TimliiK/ubmyrmv4ZDabhEmwWiwvLx5S7RIaTfcOXv2NVx8/ftwTN/jOzg5U8qUI43TcKl2UtaNeO1U2nhjSNbnzhliHvU3iJA4i6l2Vr73X1nYAygkhMPZ1XXnv75/ctdbWdWuM67q8aRrGuFIqjFjT1sPGoiyjlDqvBIlWy5xSmiSJ0Qh5yVlCiXHeWuMxIggR5Ll31juGPHfOY0QJpdhjgiVEpkYTwVOtKkZDznnXdchLggPvaqcF8cw656wQnFPEkSUMe0wUbFyMcRAEECQBNjgkQKQn5YGZgv8DjXcIbUbxaK0BWhwyHjiQWTZumqbroObNgRpljAuCiBCmlKLUwNwCQhyl3GiHEWWMeq/rurK2wwQFgXhucrCzs8OoOD29qOta8JBSxpnc2Qm998gTjClClZSBNd5736ly23CTvlZ6cHAAAROkv4vFAkq8lALBGArbGNuNnCzMfgkCSQPsvSXUe2+VsmVZXl1dgfQBRMyAJAdB4D0SQiBkgCqSZdlsuvv40SO31aSIeoh1yL22MzDnHNRrMMbAH4a3Ojo6Wq5W0LE6AMJwBpu6Nr3SIciGtG1b13UUx0Mqg/uinfd+d3cXhGXgNwczN+j22Z5sNSCNg8EdqGFw6gcHPBgESik0xQ0pJohdgDs/Pz/P8zxJkmeeeSbP8zzPpZSBjIY3AesBnjjCASDAgwOGf66WOQDLYOsHamoY8cEKP3jwYHd39/j4OAiCJNmIkYEJgi5kt/WynyZhkX4Ix/DDnjz8FMzfdqiz2QxqWIMWNKzVkPJuB7gQXNJeRmPwFttBwAAtwL411lq14b1jvJnhgRBarVawIEP5HJ4y8tQ5bYzxHhy8R9ghj1arFWhPDo0P8L0MNpwm11MXQWWMi4ALxjnX2ndtZ0yLEWWMBYEAtwqbBxZfCFHVBcBvQIsDVqaUMoojkB7rug7CFErparViThDCGOUgb9A0jdZO8KCpNzV7+HOwLQih+XzBGANEbeBPBEEQROFgo+Dgw+rxreFXQ1JBKSUUweLXdet9EUXBeDwOAsE4zaxtSzWXITo6eZ5i/MtfvKcVCjiOZaCUurm4xBhTQkzbLdqb1uvpLrv/4vQr37z/+Pz9yd3u5NX7a3tVzW8Oj5I7J3uCYMFuXn5Z7oy7P/7P//Z3/tpvieDhs88ryXcffFhcPFa65ZJPiIvaer27j7/y68+lWfDRhw+uL6s02UlT9PjBI4zpOIus8m3TIIsp1a+88trZ2VlZliDXrvpB6FdnZ0EQUMK0BrnODCPqnGOSUroLB9v1UnyUUh6Mg91Jp4q9cYCfP0qSWCm1WNyOxintp4gHQdA0jXNuPB7jNuqMxiHx1LZtzr2LKfadfv4LzxEi3n3no7PTG8QJj8nO/ljrZr3C1c31/v5ecXP9vlf/3d/+b9u2effdtz/4dw/v37+jbEOEPjyZ1pWa2V3Kw2wUjMbj5XI5mkrCWdM0b79z1dWNo64sc23aMJRXq9w7Mh7tsTgmRDSNVkpb67TuGGNSxgih69vC9VPkjEWekKptKKVd6ygJ8AYHQzANxnurnC/bbjIbN0gTRtk0zD+pFi4XmnDJmRAIoWVRwh5iQdwUS2PUdDr13tdVqzrTj+sx1nbLZRnHcZqmGNuqWlPqQ4GMabwxyDnrCUWCcs4oddZHXDrKm6bRXcsYE5QyisfxeLVatc2G62u19dZzyo2xQBcANhbaIJ90gNoAUjbGBEGQZdl6DYp9XCmT5yWcEGtbzrkQRMqwadq2VWEYIoQIYYzrrjPWEu9pFMy6rvvo/eudnR0p18656XQaheM6MG3bSokwVek47BAlmNcmj1hY5A2lIknG3drwMHTOQYbaKrUzHtd1/YM//hFs1OPj47feemuU7SCE4jjWaKMMA82j8D2lVAaOUoo8kjLoutYak6YpgG8HBweU0qqqwjAcjUYHBwd5nq+VuXPnbmTI/PH5H/7xn8VRduf4mThOzeNzKmiWpvAn1lpOKTRogQskfVkLxo+HnGGMX3vtNSHE22+/fXl1a4zdP5hls/033ngjHc0mk8nNzQ3EPdhhjygXHPxB3WxmP8ggjuMY4H3GKELYWgc51Wq+0sZKKa1FnSZRFCEaL9ZrSYWUsXPOmE4IuUmjHHPeW4cpZQiz9Xolpdzb25vP54wx67w2dqgFem8QQm3dbLjols5RLqXsWre/v58X1XJZ3dysX3rpJaXM5eWCMaYU8qgbPJD3vqxBFgoFSUqkvFksoGqAEOLcWFv6DXNN570EUh+LoK7rJpPJdDZ79OjRBw+eaMQoFYvl9XYOVNUd/L7B3hgD3qtt2729vd3d3QcPHnRFuZ0Z+6ciD58tSMNLiODevXtCiEePHvmuA8gHIRQw6rdeg4N3ytAt/hpkh3fv3n1ycQYDiQEDQP2QR8jkFvOCMTYajQBdWC7Xx8fHq9VKKU2I9d5Pp1NK6dnZ2VBL3nY/3vssnXWdub1dDqhGEARKtatVLqXknBKKwjBMkiiOpTFh3S6iMEYIpVmoFAcuW9uWyyU4Pzc8d4xxXbfeMZsGqsaMWykDxgJOaRymBKPOW6980awDGpRFi6nEKlHGUUotQdZqqF065+qmEEJ67xhjHqGm1YwHYRAbY0bj3bquEfZCSkyId44yZCzu2k1o0hfjOujrsbSTAXeNatvWIWptN0pGB4f75WpRVivrmiDElJkklTs7e3EcM+CyMhaotjs/nRNSFEVBibDKbGUhT8kOu3uTnX3RqfrJk0frcp3lqzTeee0Lr9S3J4SiQGYPPnncqu4b3/ySQzkXjTHm8OBOHM7aBt2OinTSFivtvR7Pkvmiub5ev/eeeeXVZ3/rO7/OGHv08Iku2ChOrXKvv/7lr/zaV53By+WaE6bNpn1iSHfgmyQKgiDgXHq3wRIJYc65IOZA2hqSeDg2lIo8X1FKv/Gt1wlFTdNg7KMoats6TVPIxuDMwL3LIGuqmoAoIPGMc0RJ3VaSxet19S/+l3/TNn9+e3sbx/Ezzzzz8OFHzinv/YcffsgFQwi99dZbzz77TBjGdw6Pd3cnlLnl6gbsKVTaVKdWq3y9LgijHmNjDGMijqlyRMqQUiIER95o7YBwVxTroYoG30CuoJuWQu2IMIycdRZ7RxBpdIMxppRwzglFwBXy3sbMT5JsHMSc4nE2OuLJVBFqRU692YyPJECZAf5Cmo6ANwgmGNLKKAo450IE3sPQZe+cARCC2E1cP/TFQnDQti2MNBgKHwC9rNdrsDhN0yRJMh6Py7K8vr4W0UZ0EH6Z9aPBtuFNiD2NMVD7QVvtc0NKNOQiEOmDvYCSvO1nkcIFb+jQTaeU0sqMRiPvUJGXOjCUMO91XbfId3VdO0uttd6bpqkgOs6yrOu6MAyllBcXF2maOm3X67UQ4vj4eOjiLcuShVJrDVqGQBuEfEIGCCjckYms04Rg7zDG+OryGjIYZ32aplIEbdMJLp31A0fJe5/n+TyYOwdw+maHQNrB+om2Q0RP+yG+GOPHjx/v7OxAjrVYLC4vL6EmhblYLBa4J7TD8lpribPbfmhITEejUVEUYNNpr3FNCLFKGes459YhRBkwnJ1z1/Nb4AcNzxTSVsowBFVBEEBaA59yfX3tt5DbIb83Sg/1JijUwb1D06O1FqbbwuxCrbVHTy3b9hven84IIcYYEH+FuwDAZvBew97z3o9GKcwUhyZgSNGCIMjzfBuHH77XyA2gN1AXAXjXnya7+adk2qck2+3XQBajveofPFzTdxtvZ8AYY8wIosT19tx55Cl25CmcQPphPHiLXAZ7Aw4LHB/AMAa0dvDZQ1HjMw4YLNWQeQ+mFd4ZTBPw44JASCld7QkhgYym0ymlfLlcr9frtukQ3myk7UeGEPIIrDqlFHHOCfUgbgMAoQxoXZdVVVmLwoCHYVgWld+gPsPUSOK3gKLPvKCFxPTzpwffjzaZAOqxN0QpFkJYa6IoAr2d5XIJXQ9RFAWMlmXZtVoIw5gwxl1eXrZNx7ggXecxFlrZ66sCgALEkXcbofDtu8UYC4lfevn+yTMBC6vWBPP5UnUfcxav8pJTdBmudnfuEvzRW7/8xde/+fzJ/eliveY0Wyy7uql2jsRXvn34+MH69PHi8WlxcHB0ePjMar788Q/fG49mL7x0rN3y3/2rP1HKfOsb3/76l7/64nMvlXn1wjPPLuerZVlba9fr9Xw+Z5YdHBxAV8MojQMZCSEQIggRSqmz3hhDAhTEHHrdjDHr9bqqKm98uVjnee6R/fDjj05Pn7RtzTnvVDMZ7+7v76dpCoTq6XQ6SmPOOaZlGgbMIaRx03bKaEM4CoNRNMnzuusayjxlPoqC2Wz27rtvCyEoDZzXYSibpn3v3Q+m0+nx8Z0P3n1QlqvxJDEWoNF6Pp9LGXJOYUKICGTbt5Q0TUOE18pa55lBGDPBmeBBmo602hy2pu2cawAvwphQ77w20AaLnGMYE0wowjgIANmz1hprtd4QGVzTCUpVWbfOxDIsiqJqG+2sNdg5TzgRPKCEq84Y7bzA2m5EyaFO0XVdnucAEkI1aADKIHCBlh5o+wNYBmwTCMZCzmeMgSA0CAJKBWOsruvb21uYcYYQiuPYkY3ABfDnAf8ghCi98a+DVwYqJvBoyGaUNYNzBf57ICTjXtjB9yTeIRR4CsGZVmub5/MwjIUIuk5Tyr3Hda0IpoQKIaTqnBCCMcmZqJunGcxyuYRvVqvV/nQH7hTmmeOt8a4wRy8MQ9OPUi/L0joo6WEQMqIMO+edRdZ6KUUUJc45KcMoclVVJUlS1zVj666zUsoo8qtlAXxUWHmIpcDKw+fCbUKFDPAxkPMtiqLrurfeeiuO4/Pzc+iTXq1WUTbq2hbqqXZDU7daa4YG7HezpPBPMLVA1Bq4o865gHPnkTGmU4YHIUDcwN+BixwUJCB4QngD/7pPN4Bus3bhKW+YO0oPfz6UFcHWD1cOrhSWhbKndbvBRw5hxAD2Du/jPj0JeNjt4HtYP8gZ7itJkqG91fdQ+QaKxE87RH1fvgWx9+ETh6jl0270U6/BQ8PtPy3P40/Nd3/6noR4jP2QZOONxP9nHDDuidOu5/PDo9G9/MgAJoNohu1bswYH8asOGGjztO90Ghyw7xFau7FLPgiCV1991WiX53lVNZQaYwxGUHd/+tBRTwpGCHlM4YEijIyhFCGMN/VpzhnngGZb6OYnRPdLZ4cRtPC21rrP+GC4figYDVeO+sIE8OPA2TvnEPIQBmDqF4sFUDSGCKaqKuodJTyOY2Nc03Rdt/IOGWNYEIq2bQliFAdKK8yZENgjG4YR7il/phcZIIRcXJyfXwRBmmBel3VlXLu4rRhjGb/zi7ff++lP3v21179xddU9+KR8/oVuMo3jeCTo1OhVWZbPvjD+wpe+0DXsycPlxx+oD947q0v3/P1fL4r8P/2HX/7wT38eJf43vvmd9955py27Jm+aoqmKepTwpqziJHTOtV3FBQkCkY3iJImapqGcI4qMd95bSjnBzBPvMKpKM5/Pr66uLi8vP/7444cPH3ZdF0XR4c7zzz//rPf+z370p5988tHBwUEUBY8fP/7k41NYryzLZrPZ/v7+ycnJ4eHhF798J4vi3fF0nIziWDBrWm2d1ctu+eabb87nt1kWI2QByiaElFXOGDs83K+qqigKrfnjR6evvz6bzjKgggUyJoSU5dmjxw+iKJIitt557z0iRVVRSrW2q1XOJIzXIxhZhIjq2qpwy+WqHx9GhjoZWLqD0XQTUHtkwdLp1hhDIqmU8t5xzhF2xiiw7zvhGFHiGTLI+EjUzPtJXGEVEOG911pDq5/tBQGquu0jd9F1umk67zE0vXiPvccwrcE5Z4wjhJZlCXTBPM9Xq9V4PP785z//wgsv/O7v/u7e3h6U67z3wEQIggBjNpvNvPc///nPf+/3fu8HP/hBnudxHHd2I5gMJ2Fz2D4djcLPwUxAJor6stbQqwr51nYQDX842H2wRGC+27a1deOcu71dp0kZhmFdaYxMwVvnuyCICGacybqqrPWEGGMxuFLosanr+u7du3/zb/7NX/7ylz/9sx9D34KUEnTQoPZPJAfGEOlFvsB8E4IIwRhhjKn31llitFOdpUR6RzkLjTGqcwQLoyuIxlAvoQMPKAgCmOiwXRofXoMnGGwl/OZ0Oi3L8vLyEvLg3d1dhNBoNIpH47Av08KlQtEXGT284fYCDkovw6eD84vjuO2Ucw5hSjkf3BLgDX6LQbkx9FYRQqAaB88XrCrwBnBP8R3uhWIC7mHIlSHMAoDdORf2L2BpgQP+1ResIWwYWNtBROJXrT/GmDEybE5ou+CcTyYT8MEQOw6sacaY8na7GA9vCJzwbQcwODBr9V94nfAmw9McYotAym3/NzhF7R1CCKM+lULeY2T9Uybd4ERpT3HCWyRt3Cs6ASwxHLEBU9l29tsXYHu182GTwJv0f/KUGW6tbZomCk8KU+R5qdQCY+rsRnXHmKeM9+EROOc8AkkyY2Dip8PWYkIIoUgpRagLgoAQZs0GIesjQg8RFPh0jDEEOts4B9rCfV3PVN/+IcRpfcDnrcXWWiYpFJ5JPwS667rT09OQgYjKRg+HYCqECIKIYewZJ1EYca6LwmKMCEXWOro1pGH4eELI3s7+xx99Uiu2e5ASKgmT43EWxfz9Nx+8++718eHsvffOypzv7hz+4q3rjz96EmTvvPryl5nglPHzi2tPuqOjk2dfPEgzG4T4l29cf//73yc4IFQz2YSx/+/+L//n7/zmX/noo0+WiyqQqZK+qdujw5PKt3meD1wM2O5hGNaNYpgQRp1FddOtVtcXFxc3Nzd/8mfvPX78+Pz83DkHNMiDg+P9/f27Ryd7h0da6y/82pe++OUv7+3tEYrKsvzk49PlcrlcLiFv+/jho5/87Ofr9Xpnb7K7O3v+hWdfe+3V11598e7RURzwlDA6np6dnXWq8khr06zWtx99ZMMw3tsLoOURNlZd12dnV8fHq5deeuH6+rptlTGOMYYx3d2d7e7uWsOTNE2SJIjC2+UiTVNjbZ7n49l0NE4ZQ4yTtlE3N8v5TX57u0DYPHr06Pb2FpoQMIZeBQJCiZDx037iShiGKOAIISlFkiRCMu+hsYGYxjvn0jTmgsZhdOfO0UGSvf/+++99dBZFUdu2q9UKYwQjd5qmTeIMwHnvcL4uvfdpMoK9GEjmHUYeaWWVUl2ngiDI4hjUCU5OTr7+9a//xm/8xquvvjqbzcCIQ1THGJtOp4SQJEmCQGiNKEX37x//zu/8zg9+8IN/8S/+xfe+9z1HMPjIof1gwDYHF+L6hndrLaTUYEfA9oGJMYP24ZbjAf8BBBkwDVD7r+uaMcJ5QIlUnWPUcxZyFmrljbWUOOUUpTwMQ0o4cFOXy/Wg83BwcPC3/tbf+gf/4B+8++67/9P/9f/+/vvvAy5NKR32RlvXAJPqXqQTUoo+p7TeEe+R9U5r33XaOpfnBecCY7xareM4Rgg3TZskSRzHTa2LoqiqjmAObCl4K/ZpjUywL5C4QLSB+owTlLaAPwymEGKa/SSBpHbwdhtWpu4lfvoXrCeIg8In9iAqIoS0bdu0HSRDDtqCMeWcO7Ux30OWOcQE28noYIsGFzW8+fD7uCcu2V4eASqO0CIByFbPgKPOm7/QscG2HAy97dtRhmLc8Oo3EgY2HCA01tpBHme45uF6MMbaatQPGoFfhsoabO/P+DCEUNf9xSmw1hvYaXutUM9I91tyEJsb0RpjjHCPtTqPnHdmw8oevqI+8yZb7Jkh9YRnBOsDq+p7Epzpx+VuH0x4BIMnxn03F7wDIQTajWDjeW+LonjjjbcQQnXdCiEoIb3IP95+oS06t+0TWcaJEAJhq7Xy3suAa620IUkSea+7TjW10VoLLoH8+BlHO9z7gG3Aa4hv3FbPG6UUY9C288bCtImNWCTGeH9/fzweQ2kJRM2stTQkTdN1nTbGCC6FCLz3bauY1loIlo0CpYjShTEdxBqDeq3dardHCKmWXi/QM8+Pjg+fv74uTx/feBuFQbpc1cfHUynCsiyrqimr1WR2KIT/4Z899Ojtl19+NUqzjz66PD0rfu2L2Ww2pqK+cy9eLITWBXJOKc9ZeOfozv/wP/yP3/zmNw/29vPKLlZNEo2dcNoYxqV3BCMmRYQ8rasuid14PCbEaq0X83yxWC7mq5ub+dnZ2fX1tdJx3fhOkfF4+uKLLx4dHQHDMEyRdoXxarYXh5E0pqraNkqD17/8nO9F4Z1z6/X6Jz/5yfe+973VMihWpx++/eF/+vf/69Hh3uc+/+JXv/bFz33ulazQV1dX3luErZA0DCXn/LlnX2i6LooiSniSZKenp3/6p39WFvWDTx4dHo6aplktS8ZEEARZOv7GN75xcLh7sPdcGEWcc4f85c31eDwG8b8km6RZzAWRkksZGu21wtagDz/65Xe/+93vf//7y+WSUjrKNmXLq0ePnnnm2c9//vNHR0dg78D3sCgwxgyDrTAGo2D8LHTKTMIw8jgh/EhzgUe2le96zLlUyljrEcKUcowdIWwoUg7nyhhTluVkMgGYZdgtlNIkSY4O9v/yX/7L3/rWt15//XVIqgaYGuBNiPDA4gsBM+M25yGOxW//9ne+9rWvLRaLf/j/+J8//PDDDz74AHazc05KmSRJUa6Gcw65hfceGqKG/nXwarSXkEW9vKXvpVVRr50L3AJKKYiy1XUdhYkQ3jta5E1dqbYxGCmE1GQaa+UXizlCRCnFqHDOK6WkDI0x4/G4KIovfvGLv/M7v8MYe/XVV//G3/gb/+Sf/BOofIN+ZJIkxhhlNUJoe7istbYsyzCAcYHYGOe9RchrZVXnslFa1zXoiK1XBUYUIdTUTad0EETg2ITwgm8E4IbQhGw1BG9nRQPACI8SurOiKBqPx6A0DtAieBdYTFioDRCCNgnEUIDocwIyQJRgNza5zqZxlmPCOmOVUlwY3OtUDFc75GGQcUL1d/j5kHhtB17w8lsQ4pChQpwHPgCwazjd3ntwwIM7H76BLeR7yvFg+gCzGT5xWIohFRsCKXiHwW0PDngDrhgF52hop4Fn9Kl72brN/43XYJyHPyT9tKXhNXhEhjBGmJINYICtI857bYYwlGzVgAdnPESE1j7tZoZAv21biNIgiPwLr3DwuLAlhqullCIEXWQb58c5N8YbY5rGMCa899Y4i4wxBujK29sYfboMTAjhnAYhS5LYeV1VmzXXWmNC4DhXZde1jlI+RCfDzYLDhTB62ELDRwBeAj0CsL3hJ1Bh8N4qTa21lGIAiZggcRyPRiPU8+c3EXBnOZeMia5VWtu6rkF+gDmHGCMi8JT7sRNdR8pcI8S83ZZn22BNxpj8to4T+spLX9rbnZ0/+bhY4TojZWHzVXdwOFvMb46P7k9n2c/+/DIZsekseOH5pKrzq+vHyMWfvF9Zi/dnztv2T/74+7/9X/7Xv/7rB4x8wOl4b/fk/Ozqgw8+CuPdP/zeT5y1v/+f/vjfv/AH3/lLv/Wtb31rlKQU073do8ODE+cczHVpas1o2xp3fX37ySefnD45V0qHYTie7o+n+56n+0c7p6enSinM3O3yahOl6t3j46PZbCYlARshpaSUEbLhoDOGGWOHh3vT6ejOncM//Ge/d2c02Y3G0hqTu/mfvvm/vPEGniTH9z9/fvGEcY+xFYJnozRLJ2EYrYv84GD/1Vc/d/fkftua46N7f/zHP6jrZj6/CcPUaNR1drlcC0EOj3a6rglkeHV1fX5+bpxdF0UURUzwKIo85pxTYxVCPgwjRgOMWBimbbfc39//23/7b0+n0yAIbm9vHzx4cH19/coLz6dpGibJssgHubEwDHmHrbVAJxmN08PD/dFoRAgaZ7sCU2w06dQkTCZheLu3F8rgyWwkhABtnaE+lySJcyYMw9PT0/U6n06nnAtjTJqStu0oZRgT5yxsaSnleDz5u3/37yZJAt1WVVWxvj0RTDOUckGTNgxDa73pp75QCsMY0GSSTCbJ/+v/+T+/8+6HP/nJT87OznQ/WYhS+uDhR7C5wTQAVokxXq/X8LZANSqKAshEkJdAigwPnRAC2i9RFG10YgmMOxSU0q41Q7Tedd1oNIZE+bnn72utT09PEULLxRr1DBStHdR0gT7685///Mc//vFsNjs/Px8G4R0fH08mEzDHte4QQlEU1XUN/UWj0chay6h0znpvkCfeO++RMVZrI0TAuYTxutb6tgVejDZuU0Qfj8dBYLwjQ0L5q2nQdkoKqwd+DtIX4BBNJhOlFOTBUEiGFNn2LzBSxtnBWwyeyfe9uXABoLEDRT5OiOwUQqjtNiAWIMa+hyK27T7GmFgyODC01dI6ZHiDg4GfG2uH1OozJgvuDgKdp9W0XjhleIfPOG/cN5DEcUwpBcaJ66Fj2Dl1XWP8tBY+uCtoDRqcKNlqH8I9YAv5wAD/mi398P9tvzu8XA9uD4/4VxO4pw7YekoJQphhSgjxSFPrkTKf+Ti8BTD0wbHouq4sS7OR8ESoH8AwDOQAAt1n3mrw64DMgwzIACQM0fx2XSkIgtE4s9aulmtwvdZ6xpx3mDCy7TsH78sYRxttGe+co2yjeIWwwzgg1IEXjCLqbGeMM94YA9kFIYQgv6ngDDHQ9i0Ma0i3COSMMSklqLhbq51nlFIhGKUYIWS9Vkqt1+sBlsAYp2m6bFaMMUa50bYsa6UMxpgSzhgVmChjG8b9ZBZZQ5CvVYsJfaoGMhwzY0wg9yajuK70n/zxT9/4+QPrRZqmdbtslS+KMsnCm/nDJEpHOwjR/PNffJnHyeXNB1T4SEy8Gy1vu/PTrqjXxB4G/Gjv6FA1SV3ZJNpPwqO92YvLxc3l2fn5+emT0+vTJ5f/+Y9+8My9k29/+9t//a//l9AE2TTNo0ePzs7OMMbj8bjufNM063Xetm0QRIFMGGPW+sY1e0ez0SxZLBa3t7dVm1NKk3F4drpuaopQPJ1OreFCsCiKtOmMaQfeStMUUtZxnL722te+8bf8uMOTlR15htP4F93i9y8++OX66o/+6I9efuWF0SjySEdRNJtNsnTWtm2er956a5WmWZFXX/nK1//e3/t7zvnVKn/mmdmLL7yqFVqvq8vLyyQJvvD6K8vVjenk2dnZT37yEyY45ZxzXtYV55yJREruvcXEBzJyjnStkSL2uAZrAl3OqBckCkK2KNaLYo374l/nTKVahoHC4Bhj0Hiwt7eHkBNLO5lOG9V0up0d7Flvlt18eRB9bfL1w8NDGBg1mUyAu5QkCaFutVr943/8j//gD/4AHDNkdRAP4h4chlQSY/wP/+E/lFKOx+O9vb29vb1+pq+HvsDRaCSlhKbY4+NjKeX5+VVd11EUHR4eMsbm8zm8//7x0XK5hCG4x8fH4CwXi8Urr7wCjg3S4jAMBzIRBB8wWQH4XECmhTAWfgLjS9u2nU6nQojb21vda2WDUMZ6VVdVBcYXah+bgIYTIcRisQjDcLlcBkFwfHx8dHS0XOYPHjwYqDRxHE+n0+l0+tu/9Z2///f/fp7ns9msaRop5Wq1SpJE+Y1W0X/8j//xH/2jf3R5eQmwleChtVapjjFhDLJeO4eMMcvlOk3T+XwJmZPW0EVK9vf3R6NRU2vVWaWcdRvxHNqLCQzuYUhxhiieUjqkmKbvIgXO+WDpIDMe3Cru54KbthlyRNRTgUg/qn3Q7Ynj2HsP4tjgZpqmMR71TDcz4KiQtQzvCdzJ4W2Hn2/nhdv5K1w8EL8hYwajOawD7gFqeCtj1fC3285jcMNDL4DrhQzN1lga1LeuCrEJCOyWROIQmgwXPJjQIeNEvawYxD2Dxd++r8E//epL601Wvb0mGGMgYQ2I9/CVeE88whhzQgkhGhPsEbIOkb/w7ZExJoqiNE2HDgVAPkhftAZOH6wq6pPjIc4Y3gfcle/BksHJkX76Mtxg13Wc0ziO1+s1RsQ5B+RHYwzyxOiK9PwMv1WWRghxwb33dV21nWeMxEkACauxynuHsAnDcDxGBItze3NzM2eUQ17ZR3sY409d/HALvof6tgGMbT+9/UNCCNC5YaoVbBjY+c450APRyhRt2TQdQiSKIoyotZZJ6ZXuCMZ1VQjBkiT71rdfLsv6T7//54wkBAtlGoQ7LjD1EfIBtrfNUn7/f32vKArOkywMn7x1K6XUrhKTLCS8aqvR0bjrUFlN/vN/uvjk9KOXXrp39qg6ffAG6qKUBDfvF8987Qv3npvdfuRl66b8YG+HEcyvisVrz9/7T997Esfx5z//hXv37t29exfaCtu2/eU756+++rJ25pNPHt3e3laVu7leXly8fbS/J6NwMpmE0RghFCbpcrn86Rs//9zdu2kUt6s1W60POe8CstINJf7O3sxiVJZry721NlWBxJR7lDcmyyawFSgJGWOBjJxz7Gv/xTogi7rAHzyQDx573N5/MV1SnTzZodRRRG9ulvdef3Fvutc03Wpxu5feJ4TMz6v1dfe5lzXbFQ8ePFosFl97/WvnWLqM2FX+8z/94Re+8eU33nn37T/7cR2bqmzGJ7FWriqVMo4FYdvpNi8nk8lqVVhr09SB+JGUkhIBdcqrqysQTAAbilkKIepQ8TLGSCnThLRtCwXIyeS06TJCrn/3d383Oiis94fjOwihvMq/+wd/8KMf/agoiojyLPkKxRkj7Ytf/RzY6LqunbHjWD5/7/iDoz0pJca4aRpCCObjR48eTSaTujJBGCcxWy6XZ6c3ulOcu3VuHj66sfatgSUks9gYc+/evWefffb09HR/f//BxS8mkwmE2IvFR4eHN0mSQAi5XC4PD580TXN5eQnm+8UXX7y6ulJK5Xk5mUwODg7Ozs5g04/H4yzLinVeFAV0WDLGoHXVOXf//n3O+YMHD+Bcgd+dz+df/uZvHBwcXF9f39zcQPr73HPPjcdjiSRCgVpbhCxCAcKBMkgV3ivVuUom4QcfPLZOjZP48Pjuzs5ukk0urq60tev1ejqdPnry5OrmJkmSv/ztb82mu+NRwhiLQuG9JzgbjUZ1W7Vta4zam44jwe/sHzZlnUYR47jrLMPYe8U4Ho12CSFJIANJDg4OFpeXQoimaZJeFNfWKL8pwiBeXS+stZRyr+pYzARxnFHiFDIm5NhgZIzCyHvkGTKIINtVVAjqnWnbQAgdhhvDGoWOUy+Y8YbEAbE4oDKNU+ZpFqa2NZxyp53FyGOEMXLeOwSOmVHGeBi1pmBBSClttHFlxRirOxUJjjAyznJBA0pVW1rdJCFdK8w4sdZapxF2AzfKO11XRSCnnGFKvFZNVa45w0YB1xeTLbki7732TggQhvNhGASBXK9XjDGHnSceIaSdZpIpqzjhnHGEPlX4HMw68S3HIXUo4mHbtg7pcEKta5q83t3dvb6+5lHUNM16vTadDlmAvPHOm7aLRyNVNxwTZKzXBhPPGeu6zlojpYQyEGMs5iGoRRHjBAzIKmviHHH2Vx2A995upWR468X6Ic3g3jjngOdpo8FQ+J6BDCRHg5XHnlLa2tYb76knhKzrtacMe2+1dsZATGaMgYKx1Ro5JzmPgoBirKwlCFFii3w+GcdRyKTARtd15eOIq67EGDPKjDGq6zjngvOuU95pZ1UgmdGYUYQEtaYjGCHvCLaUUuyRMzYMIyFEUzfIEmOtYNIo3dZNHMdBIDCSTaM555SxruuwR4GUgKyEAdFak0gQQoyyVd5hjBFqo1hSSr0nZ4+gv7ExynLKkGcEeYScs87Y3ncybKyCDMEYDcUZrVtjDCVxFAprOuSRjEJCiPfO6BYm6jrnCMLeurbu4AHFInM1Wlfl0uXWWm4DY8zZx5dQY9JaY48I8t4ahC3BiE2mKaERE91yfVbVyHt/eTG/vFgQFGAkGAsQQtZ7Z613xjkSh6lSymjtLEWMO0utIZ13Io6TeOZ8ZzT2TrStXueXGLEgi7TyFxc3dd3eO7y/vm6W+XK+WHz7279T12U2isBVPHl8dXFxtZiXn/vc56+vr0ej0Ze+9KXRaHR6emqtOzg4vL2+fvf9d6JYBIE8unN0fX1zdX2LMJ7szIQQRVFgSl5++eUojj/55JOHH3/yV7/9m3s7u/lieXt9gyk5v72+ulgjbR8XXVGW9Fxkk7H3vikrYj2jVOtNkamXIgpgvSTDN/lt4PWRRtOq2d3Pur1EIJOm9Lnnnp9MJjfX8+eff/HVV191Dj1+/PjqbH3vmfsHBweLxaJuipvryzAUTVPqiNZe6c5a1xXM/eDtn6+K1eriWnVlkmRSBnu7By+/9ELX2tVqvb8XySAjhJz4vaGJCEBU5DeVy+deOBqSBmPMulIDwIX7eR3ee6cNBGtd1905Obx77/iHP/zh//g//d+ef/YYZrMD6+Tx48dNRcbZ8c5oQ95BCD158oQxBk2NVpskSf7qX/2r3/nOd7IsgyxzNBr9v/+//+af//N/DgMHAZcjhBwcHKwWS+/9hnTjHOh/McaQ4G3bOusX8+VyseJMVFXFmcCYOOud9dY4rUzbdIQQo621XimjlMHYeu+NcQgRjCn0e0AitZFY4RyozoCUQKcpAGh5npdlube3B9zUQS5nML6U0slkkuc5wNfGmFEy+gszAx5zZRTiGGNc13W+mBfL5TtvvSmi+I/+6I9AwXhnZ+fs7ExKeXJy8qd/+AdJkgghIKqAnGA2m33y8ENjzPHxSVN3QtCTkzsgMgA94gPqGwSBECLLsqZeU0phljDwkMHsMo6CIIiiKMsy7z3ncjqdzmaz3d1doF7TvhNmKOJC0AaNkgghaFvilARBwDmPw2iajgijcRCO45RzGkWBc6Ysc++9ECxJYiHEPF9sI6u+L5oO7cWsFxz2vfgwpA68n4IF2xW08CDldf34eoQQwRvte6AUDPnlgIKiLQB5yMPgU5qmgXgOIYS2hPURQmJreDP6tALUcNnwQYzxyWTCOT042FO6DuU4DGXb1saAmKWxVltrozgYsF/ci+65oeCNMWC5cIOMMbyFb5Oexea9l6EYbsptvTbs5T5HHxwzuB/fKwPC53rvgQA/lCHgwjjnyH9KdXL4v0TIASOB1XZ9jy9CqCw3QxVhmpkQwiPtvc+ybNhXcNlQ9aT9qD44jNCvMSwyMNjJpvGvA9syGAfY2MvlHDLIYcMAYBOGG3Q9jkPaq1gDCDwA/nZLGc0YhbeImRB2R1FkzdMGM7yF+QN0hLakMeHKYU4BpO/Ah4dCGEzTGp7XUKOBIR9wbUCJ3WTqnHddBwPohtoWpZRdXF7u7KXpJDg4HivVGq3OLs4ffrKUKELIUKK5YJzF3mvMKA0ChK3zmlHGBbFONa32yGGC2xrVpa+bpsx9XdmudXXTea/yes0RioPR/nP3psl+UzwxS3V1e3N+eYOx087u7+/u7O3Fyc7R8XMY01VVZeMxIWRdFA8ePXr33XdhmN3OJJtM0vEkHY8z59zt7QJjf+/+ycnd+3fv3v3www/ffPPNn9dvUkrnt4svf/ErH3zwwdXF5c5stru/l1clY2x3MvWUdASfPPeMUfrjDz48PT11GBlnl/k6Y7uMsSzLQDAvTVPQHBB7YbFc7I9Hwd0jZPR7q+vy7Mak4ku/9uWmaX7x9vuTyYQw4RC9uLp4/8NPnjx88vji0c7ODmPsowcfJEkiOH7l5ec/+tnPUBJMdqa7QfSVF159srgsL69fObpXIHdwcHB5eVkUlfdem+Z2fjVDM+vdfD4/OjoiFDdNMxqNopghhNpGRVGk9eacwzxB7/2RYECjHUadbLavYbaf3/Laa6994bWX3nzjx2/8/K0P332/bVvwmtA5wxjb39//7f/97wohZrMZlH+CINjd3Q3DMA4j8KyD5CdY0q9+9atvvPFGWZYw9G02m0G2fXR0BO8MGujA4Yrj+OH5WVVV4/HYWssEp5wZZ2UYPHz4ECbYBFHYaXW7mMPJzMbZze3i/OKKUhqGYVHW67xsmqZpGudxFKdFWcMAHMZlGCUPHjyC3W+ME0KAxkVRFGEYeo8fPXoCNdokSUaj0fn55Resb1vVNB0hpK7bxWJxcHBkjLs+u/kLHXAUROkoHe9OgiBQOsCchVIShPb29qAPKk1TOLTOuXv37l0/UfP5fDQaTadHTVOsVqvRaDQaxQhbTFwQsNvb67YrF8trwQPWS6z4XmwEoG8wi957qJ3DyhNCwjD0SIM/hrHHlPI4juM4BtYh0KHxVnMFCHQMLVuEkH4k+wb1zZL4+PDA96WvJA1P7h5hjMGYAoEOY39wcLAN3lproVeYMTFgkoNIGSFEEDyAuttguFIKkoMBqNx8NPG6Hx04Ho9Rr+vuf4WaNFjSoQ5dlqWxKowkcL4YwYyxJArTONrbmYHrYowM0CLeatlaLG8pkZzznZ3dZ5555oUXnvv2b3xjMk29o+fn5//sn/2zhw8fOueCkKdZxBiDrlOIFTDGEPNBSZ71CpGDE2KMUWIHGHz7FlRPY/pVB7ztfYefU7rZFeDG2GZ2ns6SeMjsad8JHQQBdk/5Vn6rMu2Ql4Ybs8mYB7Kb6SWPoJQZhMOIzA6qucC6GNr84CGCAwZGPWwnxjb1KVicwclpDQKTASzREK+AI4c/gZSDUiqlFALDRgWSP2wSIUTb+kHCc9ghzjnGuBASY2yMRWjDtwiCwJqnDWxkaxwWZU/bFPE2FR9j+FvnNlqn/UBrPQR8sPl7dVg7BFiQHpCtueAYY8gBoDLNGGNFpYqH551NPveFO8+9eNg16J1fXDYt0quoaTpjDCaYeu88Qsh61hHaEaoxMaSnCHrvjWmNDa4u8rYrPOWrRdu1djweY4yvLi5vLtfPP/fcwe7R4iZ3vpvsjqum/Hf//t8nacQ5e+WVl775zW+/8vLns2x6e7OslQYNmqIonEPPPfcCaAh87SuvHxzuMI617m5vb/cODttGx9HoX//r3/vGN74BwcXV1ZVW6vj4+Ld+67fe/PGPHz05zbJxuJd99PCRUub5Z18wxiQHO8V8qcqaHJ64vD67vuSCHe0fNGstAzIaR21XUCpOTg5AOufFb3w5v75OGH/tlZeiWLz11s+Lxx/vBuPnnn/55ubm0eML58kvfvnug4dn6/V6sVhR6q9uLi+vzpMkCbgAxYMsSYtHV3VdT0fjxWRqOGLOn0wPXnn+xS995ztBEPzLf/kvfu/f/uur86s4DpVq00je3BTvvvtu8WJDKa2q6s6dO4DinpzcYywIguTq6qosS4RQ09yEYTiZJdfX17u7u/lyAR3PXdft7+83bQGynVEUXV48/qM/LIyu/6u/8h1nN/2yYOPAoc5mM4j1GGMgpTuE8GC2oEcriiIpJXB6EUK/9Vu/9dprrw1H5cGDB++99x4VGy4uWO3FYtG2rXZ2MpkFQZSm6Xq9juNUyhAhwphYr4u+JZdgTL3HWlvvcRxny2XOmKSUZtkkDBMhyqZRXaeMsd4jjIn3QCWlQRBOZzvQkZVmI4xxfX5RVjWhLBuNKePrvNgE1FHMuECYwLEkvYA7xO8IobrXJvzMqywqmYSccyYFWvsoCMdpujMegZOA/E8pBeNXpZSv/9prb7zxxsHBwTe/9fWLi4uzs7Pd3d3XXnstTLhS6vDwcJ2vuq4B2DBJEsFTOMlwziEjt9bWVQmFc1hVsI9d1zGOBqYS/Fz1L9SXHskWxWk0GtF++DljDNp2hRBV1cAbqrabjieMUoxxURRc4PEk0VorXYdRLAMKv28RH0jvoh/Q5pxrmg72xkAnBvsVcgY0KKhfDLLPkKcOCe5QVKPEG2Ourq5AvGXQw9omPQ3pIFwSMN6VUre3txhjeLLOEkj6GWN7O7v3797DGHddF8ViqCnirSmwR8cHUZi1jRYi2N/fn06nzz777P1n7nDOHzyYHh7tVvUackGIgDESzjm4NTgalNKdnZ3nnntuG8kYAuL/P3F/FmvZnt6HYd/3H9a4x7PPfGq+VXXr3tu3+/ZAkRIpUma3TcZJBNEOkMRGIjCG8pAHA37Lg94TJ4CB5DFADFgJEkeEpNiS7MhSU2yS3U123x7vPNRcdeY97zX+pzx8a629zqlTlOgIyEJhY9c+a/3Xf/zm7/cZnbBW+lZDqR34DTNoOLFzzrK1V7UtfOR5peHRbFhryU7gsUoWIUZFzCYIAoYX6vZAbev2vKpsVKM7Eo+k4ETS22hiSRDknFPpLWstzXATb0GTQFqBECIMQ2utEF57+FBndknJbR3cTlsFEVerVb/fpUaIpNu6OEe/3ycgOZJvWA0bonXUeHBpYinYlosK8aYZLwmmnPnQMuY3whDjkqJJSGAlGuj7vtHa1ukApMHXxFDRCtL6kp3PWluWeVuQovPr6jgJOim8nTZmNGZ5OZuunHOdrnzj7u7B/q2338r+0d/7gXV5lucOuAOKAbPWWqUs5x7VT2WMMWTWWa1M3O2ulhkXcmtnSLAmB9e2jS1M4ebz5dHz8/k4zbI08PywG47HU6PC3b2twaAHaN9//0cffPDh7s6NstCLTGVZFobh/v7+rdtvvPng7W63OxqNvve9fz6eTblwDx7ce/OtdxaL5Lv/4nuffPIDg/jhx58IxvrD4f7uvjFm2O+Hwn/7ra8URfHWV94ZDoeWceZgtLFxfHj0xz/6/nI85cZJhyM/3rz7wHA8nU3KHR3H8c7OwAtMr9d78803p9Ppcrl87/5bL2XQ8YLbt+4Odzd3rt18+NFHjz/8dLXMBA878UCVeDoZD4fW8/xuZ7C509Naz6ezPMv8jj/o9T0ufN8P3oi9ZfnWzTu93a2yH71cjI+Ojow2n33y+XDY58h3t/ek5EII8ijE4a7VcjbJaCMKFhNL8OVQ68ne3t6jLw+ttfv7+y+ePR8Oh0mSPHz4UH41ev78+Xw+v379+tnZGcdAq9X7778fRdHf/Jt/8+tf/9pkMinKdDI1UdgNgqAsS+uMKo111jpZKrFcMiqBqWsQJUIitNoQcaEMY631fD53zt24cSPP83feeWdrK7IWfvKTj1++fCmEMJZQoipTGBl+rbW4zPww7vV6THhRpxdFUaltpze4e/9Bg3js+37U6ZEJ3Q/j/nBEeDdxHEs/jDo9YEL4IowiJoUXBl2GACAD34ALolBbY4xRRjvnlNEWHEMMotAL/LjbIZrlBT4TXPpenpU6tuCYKhU41u30Az9SSkXdzpUMWBvLhSiUklIOBoO90ajrebEnAeDWrVu0daWU9+7dI43/6OjhZDKhwukUsbW9vd3r9d59993VajUajc7PJ+PzSRx3CS7/5YvzxWLR5IY65zzPo8g1EqRIhaXJLIoiCAUi+l6uKwxCJObXBpZqVCJSmnVV9g7SNCW7xWAwuHb7uu/7ztjN4YYUIgrCOAhXq5XfC2/cuKGUOj8/p2eJzh6fzaj6AskKFKtijCGoATK10QYgK5ytERuakC6oKlGGDcqSa4UyEXo5gQoR+BrZzDlH0h5YXbGD7qdAd5IhyBVCnggChyEOMdzo7+xuAUCe50HgNdwOW87XvCyisGe6AMBonxNBJ2bAOR+NRrdu3SLukuc5wZES7abwfgAYDAa3b982dQ4SJYPS9yisfIdNTDUR5VJdCGJaX7zCdbqkqc9mi0YQofZpLKaozFqdToc0NhIE2Tphex2fBQCMQVsKaVRzihuy1q5WK2JFJDkZY6IoWiwWtL1pCGT0ovMLUFUdILh1EhRI2yMprfaOGeJ2zjkSW+kLYxUoBym7pB74vk8lUx0wBwaZCyPfVUVF16JbYz1yzoHjZaEBABzzZAAADIXRzo9EM5+N+MIYM4WiQ9cE0lNToq6o0QAh8woGuIJ7qw0SnBhzljHiykQ/mzBDwt+lxWovpbj31sHpqVRm8fjps9wevvXWm04PXxyumEjjng67zBowGlXJAC3nLk3YxsYQ6+rNy8VKCNGJt5A5bYq4293f35snJ2Hcv3l7c744/+SnC8GD2SSbjBfdnheEbL7Ml8lCxp2sWG0FA4fm0y8+evni5OaNOwcHN1Mler1eJDra2SCOdnd3AeB0fP7zn3307NkTQPP7v/+/2N+7mQkYny9Ojie379359OOPz05O4yBE65LFkiMb9Hq7u1t71w6+fPp4Pp8rpXwmFueT58+ejXY233nrrW7cWc7mm5ubb7/7FQvuk88+e7E8unXr1oMHD0h1GAwGi8Uiy7K97dt73e7+7m4QRcenJ1u9TXH3nV/++S//+m/+9o9+9H4QdsMw6vU2kySZzROllObq8MVLX0oBrBN2uC25z/Zu7JsygfH5+PTDhz5T14cZx9Fw0zGXZMu8SKI4/NVf/VWj7XQ6LYpiNBqdz+zGxhbnnnMqjnuIoixNv99//uzlfD4Hx46PTgeDQeBH89nSk8FykZ4enSe3stl4MZ3ORoOt8en0sHsc+LpIs36nO+j2ulE8n0wPdvdGo9HLk+fdfk+pNRoUYyyKqsBRCucjUMwXL15YayfnY1LRyFVD0R/37t2jbIT5fL61Fc1mxYcffvjhhx8OBoOo35UIYNFa6xCCKAwgtNbKTh8R4zgebAxpl/eHg83Nzd39PUqKJafgcLRBe9RZ3N7ZI1slGdOGG5tSSmSGFI6N0RaJusTm+70hjYh+3N2/5pwjA/jm5mbU6QkhyIAmpfSCaLFYBkFIAnS/P5BSUuVg+4qpky7uyflqmZSpJ/nOzs5bd94oVst8sZBS/tZv/RbZwegoMsY6nc57v/c/oBqxW1tb5CMgbrS5vZllWeCHqoTpZLG3d/Di+aGUcjH/MTFFVqOd93q9+XxO/IZQVqIoosBUW8M0mjpN0zkkckmQT5XfvWWnJTHO1MU6iZFba2+8eWdrY7Q5GqmiRG0Dzxt0eoh47eadJEmowgSBNhO/TGuEAWNMlmWz2ez09HQ+n//85780xqxWq+VySao8Wa0jTxKzaezMUJs6dV2+vsm50FpbUxLFb9tLnXPWGucYokB0ABbRATjOmdYlgHUOnDOcY5YlZdmJ41ByoayRnBlwgmHgSWst+h7BMjb2cFfBE9ooihDQGG1MpZrTJIdBt99zgd/hbOl7sScD5xxDT2tD9lWoQ4JNjQOja4RRqE0RZVkKQclgxtqG+gtEHkUhdaOWY3T9ajA1AihxMjLYhmFIen9jxyJmBoLTihAgOUEyOecsON1iPM3EZunC1VWAiLVTH2SrsJLneUKwoiApBEgiYYxRLAgBsPf7fXoXq8Ob6S2rVdpYmEk2qnzzYMl03PhoSY8ndxJNArbcwM1xAIAoivr9PiLmeT7WU6IYDfIBEajT03PbqrzpnDMmL0tNOQWNgsEaMDVWawi1OYTkEpKGkiQh+Zj0b8/zCFSfyg24OjSBTDuNoNM0RSSoERyhBiQAAPGb33nwwx+kz5/NHbDlqjg8Onv85cM/+ednX30w7A86UeQlK3tymEwnqVZKG7Wzt2NMdnx83u2Gm5ubhSrTdMFlzpzHhXNQIlNByMI43tgMcq2SZdrrxL6IDOTSgzDy/IhzGQgrvnzyxeHZ0+3tTWMcSns+O0vyrDe41e8PjXHHx6eIXEp/uVx+8skn/f4W4OFiMT06Hv/5j3724vnx4ycvNzf3syLPy5JLwRibTsanL4/QuXEQHh8fPj88PJtOJrPp3s7uKOoybTf7G2GvoyV7OR9rsP2u/9HTh87aN99+8Hb/67u7u9evX6co0yRJtreVECKW/v61XT8Knz56+vCzzzth1wv8zt4el8Hh8QmXQX84QuQnH35igd1+4/7J9MUXXz55580Hwg9Ojsdnh8fT8/Fbb731K3cPokfjyThbbARBfD93Zv/a3cHGxrmal6Xe6Pecw8U8+eCDj86Op0Vio9HGg7feIO8slSKZTE/CSJSFlhkg01EsPR+zfGFs7gcsSQo/YEk6c1B6PjJuolhOZ6fd0NOldsahQ8mlYAIdjs/GaZpvbYkgkE1EFdHH3eEwDMNer0c4w71ejzwCo3sbi8WCYpqm02m3293f39/a2vri8ekPf/jDDz74oN/vn56efvzxx1mW3blz5+72pta6zLJGrankaC9kjDmL5PJExM3RNmc8Cv3AjxoS7MkqtqUslef5YRg2OM/0Xy6AZoYQqZoNHYedIAjIfouIw+FICEGpR91ul/6bpikNZDgcWccoQ4mCp+jARFEEEF7JgEtrtVFJkmhPzBicnp7OTk6SyaRbZOT6JVM8UYEsy3w/7veHNdCdZIxbC9YCchFHPQDmyWg2XW1vYZoWo1GHeoI1ui91m5QYSs+lUkhkfvB93/craCpeQRZDowc0alZjp8U6lbYxERNSo9b6//p/+y92dnbefOPuyyfP8iTlgIGQoR+88cY7h4eHWuvz83Ni50SAvLhKbiaWs1gsxuPxYrE4OxtDbaYjAuecWy6XGIWkGLk6VJBuIILl1biqawruKtCGxjVAPEObErUjpGjb1OtlcrVcVuqgKhmHvEizPOmaGAFUURjyNRpD9XTQOacVMuYs2jpBiOZK+ARcU+Z5mSQJoiMKu5gnjHGGEkFYg6tlRgpQGFVg/TQc2qUEUkGyDjEA+tRah36MYMEZJr3GEOosLhYLV4fz6BZEtmXYMGBqh2yYYRiTqEe8B2o3fCgr8MuGMdNEaacaeathwM45p/NqbzAnkAGC1qosy1WyII9SHMd+IBFBF2VRZoP+ZhRFhFfDaje/tZaKshOPpDgjOq15XjR9I6cVKeVxHJJ/mi5XY5gQXjotN+UNkiqc5xVj8zyvLIskWfG6vGMzb6ouaEGz51o5Y6YOK6O9pGt4FqjTOLnwSIKnSW68KoRh0GxFsoE758ghTZPp6iBHOlbQyv8WNaoaIhISamMkJ6AFMZ5/amB6+41r7371/nz1FBzrd7cfvB3k+fP9brS721vObbLUyUoxbriQ/9u/+x/98Ic//O53/+X9+we/+7u/O5/PP/jgg+l0+snHZ1Hsa50vllOUWc/zLWRZPr176+752VJrhwzTNLn5xv7tW3cXM/WzH/0cmQtDzxhdFIXnBaR77O7vWXDLZOX7/jJZPXz8aLVazZeLKOq9ef8dP+DvvP218/PzL798/MXnj3d39yFQyySVKEajra2Nrf2tPVsqBtgZRAZc2O++0/1Kr9M1q2wUd9976ysnLN092P/+T3707PhwcPuAa2eS/Ku9zoO3vnZ8fPz+jz6g1DdK6JRSvsgn/rBXzNzp+bGUcjaZJM52Drb/4T/8f/+zf/bPGRNhGA4Ho5OT0263W5b61s03Ptz46NqN25PTs/H5KeceOD4+nXzoZ2/p4GCju/HuG51vvfuDD37xdH5+7pRRS4KrnM+SItfPnh6dnJwFQfTtb769t7fn+/5yueSc//KXv0yzaZoFeV4al2fFTHjGuHQyOwpjdu3GVp75na7f64fINpVS+wdbo83ebDYb9UbWwt7eXq83SJLs/HyCyIfDwel0bDRoraQotdYYCd8XDCUAUAIu7arBYLC1tTWdTgPPbwA0wjB85513rl27BgDHx8d/+Id/KIS4d+9elmXT6XRnZ+fmzZtnZ2ez2YyiKIkYSSl7vd43/+pvWYCiLBDRMbTWEmvJllX0oAOHpEAYY5X2vDDPc2WccSj9sFIsmMjL1AJ4QeBrjRSNQoA1RUkchTJ9SSonpx0dORKTyVQYRZF1ojb6IQV3UM4xk1cnSDKAwAu9QKI1q/nizDst5gvBOcWsJUlC4JqU0RQEgSpN4IMqrecxzjgBdvo+L5STUiil47gbx7293WunJ+Ned0AklVfgHoqsBWEYlsWKDG4Ej0An3/O8IJCNfw4ou8JaV8cP8xrGqLLLNUjLWlNgGuFXz+fzpU7CbKnBLLKlKnLucFlSDeDhs2fPrLWTyYRoCunWqUqamJd2sMlsNmOMDYdDslcT+1ytVh4bUX8afZfVYVNNqHxjl1NKCe6JGleSBk7sv1Ql1HAZpsZtJl8yq0N8yfhhK5+rUqqg0GVjlDGqkW8u8KH6MsZ4XhT4cZJknuc1ehIi9zyfCnJoTVnCjnNJ3JroOxF94jSNNsnquiBQxeygtQjAGat8lsYYrQ3V3XOtkFp6Nfc928LWIA7KGNO6crWS7EJjX61WLo4oRLFphLqhjGpMpu2BW1Uz4FZqU5Zlw+GQ9Gzy8tKO6vV6nXiglDo5OaHaJyTDcc7n8zm2Io9MK6W7UjFrGwxt4NVqQZI9MSSavcVi4ZwFgMbrbOvQ/Sj2G0UZEelc09ub15GdnObf84LG9G2MAShpOBR9XZGaljtcaU2xbDRSsr4Qq6Zgxoatts9mLfXaRrjhNUa9a5WWQkTKSmgMJFAb6sX+tVFRJlubB/PZ2aC3V5bl3/j23XffO/nH/+XzNJtv77w1GJZpfoZeWhbma1/7+o13suG1d9/9lYPnzw9PF59aB3u3Bi9PX86XaWQ0Y7CcpqPNYXLOfvpH8+nU92TgB8v54sTzpCsQs2Do7y3yF1u7w+2dDSHg+ORl2ONpdtrb2nnzzXtmxQHAGVOsVi8Xi0bGOZs9FELE/tYHP/3RYrGYnj4f9bnKTg6fLa5fv3737u29/Z2dnc2Da3t7ezu9XmfU6zTPtn0nkkdKuWdPnr//x39249v/w9/93d/N83w+nz9//HFRFE4Vy+lSBYHnec66MjWcsdXRGWMMlsuiXKzKRVEUW4PBf/5//wMC+rGqHJ8dMbCrxfiDX5zv7x588ytfv7V/Y3J8XpbaatPf2jLInr2czPv9Ozf3bg4D9/GXbK5O0mfb2zvxnb0nj1788qNPSEEc3Rg++Ob9PM85ivPTMUl5SZI4A2/cvjudTlXhJmeLyJ8dH52TC202Xv34z34W+Xa5XK6Gw8PDQyHEN95976233lJKqSKNol+XUsaRPHzxeLUYB77PQN3Y2t3q9IlK0unlwDsy2GMb89VSShwM+8h5xx/evtn3/COdpt3rQxpyHMdSSpU7a61nZ/+zv/XbiyQdbGwz6SmL2jo/DOzqlHMVRez4+JRwtbrd7mgU+0K9fPnyzp07RVEsFueDwWA6PUTEjZ1RWVhrjeTeyclJf9B1TksPnbaBRFUsfCk5B2NKjyNYHUiM+v08Tz3uPI8F0jPGWJUFQVwUBSl2ZCUjmbfIda/fBbB5kXS6kXMGkVuDHlfgGJO8sOAJvkxWQRAg58Zexv5tzqozDoEDcAy8l8sSeAgAq5MZR9fr9XpMDrrdqAvWKMbYl8+eEMSVUur27dtlVsaRrwE8TxjjPE/cunXtP/lP/mNE/PZ3fsM5eOvBvb/7d//u8+fPiUP8zu/8zrvvvvvg/v3/7D/7392+fRvBduJQq8JZba1Nk+VS50EQGFnwDlQOXektzZHxs7PJRCAb9gcW7Gq5uH3r1uHh4d0bN7rDwU8/PDyaPWcr3uv0N/sbZpltZEH5dP7j598naz+V8BNCPPr8ObSCdxBxNkcAoPhVYnK6trM559ABA7SFyu3CORtHgfSlKMVm37e2zJcLz/MKrQPeLwtrrQUWcBBYYuCFXc/LdbFKU+1Ko30DNitdoTEr3XxVCGGCIODOMnCB55lauweJvgyENavJFJEhcAB2Y/uOc7AR7ShEx5aTeRJFQaHZZJGQFzPkG0Egs3yBzChVWIthOByPJwVTq9VLMvujB5ubm2lZFhqzcumECbp+boqkTAM/Ws4WiGhsStQ8LfPCKGttt98trU64SrgCAIbWGCOZ5JynXJki8TwPEMgK6pyroo1kVpFvdKUrueROuNVqVU4r6arhppGMvNDL5oXn+ZxzrSwiYygAII66wEXYEblyKIJcOce8tDCe5yUpaZCMMVHLatYaY7UHAN1eTym1nCshRFk63++jFWA4OiaYtNqUZcEYC4KgLJIgCHxPnBzNPSEHg41eL2TAjVGDfteURZosgKFzOFkslXaDWDIGShVnZ+Nup9+J+0EQJElGqJBakzRAxh6Mok5ZaMZY4PeMMUYbzr0wDH3PN8UsXy273f7OaNMYY40bjbaiKBqvzsvCqIJL7jjnkmGazUAVidXciv296/PpYrVaDDYGmc5cgB2/RyqBUpkDbMSLCIWpI/mtRSEcgMvzMuzvIWPpcu448zzP80QY+ZM07flOGVsUhfR8GQZJovNceZ6nMyOEQMEdBaBY54BxzmerIop4xAVyiZKB5c4YiyjOj7x0EWWh7XSire2hJ2N00fHLfHd7P8tX7//4J1zYwTDe3jsAsHfv9Zxlg/7wl9Mn3/uj7wsJQeCrkj15MgvryLSiUPPZsixLBybLsp1hXJY6CAKK/Do7O/vjP/7TslSjzWs7wzt7B/ujjaM0T7IiHWwMFqswmczIhkPQE2RkN8Z0fK6UiuNn+/v7/X6/OxxFvYEQwgVfDDZj7qMBYxwD9LnoCDksc59zLjhQBqAxUGTOGHN6/ggAkixdJqsf/NkP58sFyfXpctYILM0FACT+E35vA1hTavu1b3yzkeyIvJKZKMlWFkyaJ8LjQRyUWV6WRWmd5MUqTQ6PX2Z5nufleDx2Drvd7l8d/LvLRcqZ14m7u7u7u7u7Ozs7iEgmuEYqv3FzvywfKKVUaabT6Wg0Oj4+bnSOIAh0XozH4263u7d3oLX2/XCxWCFi4HMu0Dpdqjwv0lLljEOp2PbWRhR6AIahjcKAoqYX88nTZ8+7/d5wt+eF1i7naW7Cfvfg5tDDTRo7JxA/sA4cGHP99p1/O4wYY0mSnZydUgBOmqYEoBiGUZpmN27c9H3/zp07nU7nk08+OTs7e/DgAQCMx+OyLI+Ojoqi+Ebv61HU+/KLx1rbDz74ANGFkTcYdN558PWHDx9SRjL5cff394+Pj0uVE0m6fft2HMfPnz/XWodhyNDb3NyUUh4fH5OTzBhz/fp1GXjz+dzYrCyLxWIxHG54Xufs9LwTCqUU4xIAwk6MiMYo4xx/jQb8umu1Wjmj0jRVZb7q9Zxzi/l0uVyGsip21O/3P/nk0zfeeINCTrgzlNNF5rLz8/M0TTc2Nk5PTynSjRT3zc3Nvb29/f393/zN3zR1yDGFBBMDCocrpdRgEAohoqDknA+HXpYcDWMmrO+c8wKNiFGnd+3OFg/1PJkwg/2t8H7vutFOF9raVZZNAIbuInZxw18b7tuIIKSCNCY43qqtVFDVWF0IjpxzBN3vxv1BHDjd6XZUIMnCHPuiLEvgLANTFGVa5ryUAFAaxZgNfW5L6yx3ZYo6d2UKKpQijCSWyoWhLwRDdEVhrHWe1/V96fkCMfT9ME2zNMm7vWhnZ+/+/fsnkxmi6/c7W9ujW7dvaJNnWTKbzcbjF2WZa5PHcSSEEEIqXWRZWmbJZDI5PDwMw3A+n5MLJkmSIJTGKmPLUiVpNjc2n8xOjDFRz2OMCRDW2sLmWmuujFcC41bwoiiKQmtjTFlnBHGI82IJAEIIZKjKslSZscVqviCfAu0lsmlrrY3ynCGVV1cZqNY5Y52tYM4a8wOpa/TsarUi7DkAIAdBUSaNCEWPcM6FkIPhPqmhel0UwQFAki57vV4UBVEU5Hlm63yn1SrRdd2Fsq5GulqtAJixUFrUwNGhA0DkQsAqN5EvfT/q9kyv15NcWOvSdDUYdk0dhsZrNEqllCqXjce3Uc2ttcZgtz/q9frAuCcDo90yybgMg3C4tz/yRWCMef706dnpYdTr5GU66kdlok6OnwcyOtjbcQzUqsiTvHAlIoJzvA62KstSlaUfxFjnT1MQHymssV6i4A5y4AjOuhIKk2arlfIiz/OKnM1mWb8fxN2RQ3+xWHTiThWQIcDjzBjDOJce15lqXAOkElQhGv/kH/yYy/w3fuurb3/l5snp4XSSHr1Y/uD7j37jVwff/s5fC0Lviy8/Virb3Rteu763u7cdBoNHX5x88dmLNDGbW/1+r3vz5ht/7dd6/8+/9/2yLI3RqoSFzuaLGZlfluMvoygcbW4sFrM47ly7diPPtBAyXalPP3m4TN1wc7sfXYMk4cHAykBGqXDO79h+a68wxtLlWNc1QSdJTra4UPjf/Ctfy7NyMpl8+tkXi0VqtGXoIfKIXwhCafwo89XTGzdunJ2d5aV6+PjJsxcvKfH3+sEBARbSVrZ1TB2hBIernBaGdvnJ+ezeO+81RhWsQ9KstavFGTgnQrG5vdHphLTTfd9nLpNSxlE3CAJjXFEoAPBkkGYa0Nvc2hdCaMOms2SxfCqEuLY/ci2U3cbYEoZBnudxHF+7vkf+QrohEPHp6SnV2SXTEDGkfHWGDgDAGeuMNUoXLjdKb3Q6Zb4SQnDGwJZ5qp8/f/7xxx+/KzpeFCbz6Z10oT3e3+h5DBUg2HUJsOZUOOdKraTv+Z6wTu9ubXQ68Ww2e/70aa/XE4Q48ejRzZs3O53ON7/5TUQ8m6w4n127duP8/DzPy26XlaXOsqIsy729CvvixYsXdET39rbee1eenJw8efKEfNKMsVu3bj158gSZI1PbaDTSWn/yyScUJFwW+r333guC4Gc/+wkd4MVi8Zu/+Zs7Owc//OH3V8nMGJ2m6Te+8c3dnWvf//4PnUrLUsfdzsH+9XffizhnQggZ+HktbL2qAV/5u+f5unTGmCRJJGNZln326cefffbZ7miLqkLdunXr+9///u/93u99+OGHAPA/+b1/N4qinZ2dJnzm8PDwww8/1EptbY863YgizhiHVbLY2NgY9vpnZ2edTpcQKwWy4XC4t7f39OXns9lMa82R721skM8pK7PrO8EyWqZ5zgQHycMoCjo98CZFkc2V8nrdYbSfJfn46MTliiNHKfFiBVzdgqFta8B0tU2+NAN0j/SYEIKBZeiE4IBaSByNNuJ0fn2j5+pkzW63S4Fyc22fHB6fTscKEADKIuNWBwIPtm7sb+8/uHXQ6/UODg4ox0YIIboR+SCLokiSRCm1sbHBObdff5sQ/spCF4VijFnrgiAY7e3s7m0BWMbA9/nBtR3G8PT0dLY4cioRnnMIeeFsyrP0bDJZHNy8dfPG9SdPnmwMB1LKIs9+8v6P37hzO97orpIFQyW45ryIIh53tFJqlU8558II51xWZEopx1fcz8syp/Aiyp4ihud53nKyopWN44EQoizTLJtkWZaryqtNMRac89FotLGx8fTJMc1z418MsiAIAqaryGQKZSKvR5IkZDZXZb5czJxz3W43jkJrvaPjKa8rWVF/SLHWpixVDgBCijiOfd9nHJRSDFkcB71eNwgCymIjw+xsNqf65cRIqMPn5+e94aC0WBgoLXLOjTOI6AmOIjTGamBxd9Dv94zRDLBUHdoJ7ckheuL5VUADb+XpImKhAi+IuoNRHHU5l+PxWJX6zf1rnz56+vnDj+6/cfdv/+2//eknH/yf/0//qZDuzu3r8+zUQzY9mUgEhp2yVIHvo2Taun6/HwRBnmbL2VwrxTnvxLE20Hi1iar7vh8EgTp7aktUaSp83487lkkNWBpME92DwKGn9Wo5m0vn+kEwCP1MMypHCNoBWmsts5qhJxDQGl3k1lqjFEP0OAs8KQJfzheLzz75wrnsZz//qNvlu9vXv/2dN3a3yq9947YUwXhy/POf/VKVeLB336rOh7/8/Hv/8ieff3qILpqO8zQp9vfeiALJmWeNQhDOcm2NVg4A/CgAZ6IoRuBa6/l8/uzpi7I0ziIX1jhmpJYdf9DpeNBLLXKHYRBaa6lEBSBSfUREtF7kRYLssctsqbWVzuSg/ADm8/T0bHZ2PlutEvJ2gWODXpVXx2vYFFrO0c6+454f967fvruxve37/sb2HkUM1gX+Klhjki63hSAxn+xyq9UqWyyytPjBn/+YxFhKsa1gbhCtTWaz2dPDZ2fHJ2maSi4k451Ox9mypt0MgAxlAACHM62U2t7epvNAKlGv1/v0488aszmNgoSJMBIA4Ps+6eVKKfIIdqJ8maQoZLfb7Q6GxIaHGxsm4hQBL6UMw9iYSozY2hoRpKVS5WIxM8asVgvGQAbxbLWaf/qF9ryD2zcDHoDBIsm63Q2HYKyzxtrKm8gAYBD7tkiklKzT6XQ63d6ASX++yjtzhcCdRd8Lz07Hk/HMk0G322WMP3367Hvf++Ojo6PT09O9vf00zc7Pxx99+GGRaV0q3w/TVWKMXs4XvW6V3kAel/l8Tsk8y+VSemusHDrDZIrI8iQIPc8Tq2RBxOjw6EVepEVRPH78UOmcczw7O7t37961A3Z+fu4xk6ZpXhYbGxtCMGSijtL8y11FUYA1dIAp1x4AJpPJqLcxmcystZzLzz//0hh3eHjsnKN7ut04CAIh+HA49DzvX/yLfyE4futb3+h2u43F5ejoZVFkW1tbcRzfuHFjc3OzLMuPP/642+2+9957y/nCFZKgN4fD4dnZ2enpaS+IuyLuj/ZAcI3u5dnJbJYZt5rPIIdeNndeEHZ7I3Arla+gUD7bzEwVtkNDaPIa28y1YcAAQOzZ1qULmku5NAgCgYyhk1I4q7UuOceYs+1e1zlHXDNiiM7GgnvIX+aZXsxkr7u5uenhgBWF58wqnadzz0Odo56dYTKTJHMvGSLi4eEhTY5zLgzD2WzWjwOockztxsZGGIZlWY42tgrLjo+PpZQOzMnpYVFknPPnz5/v7PXznNRxI0WQpfbk5FGWFUKI4+Pju3fvfuc733n69Ckl9X322WebW99cLGYONOPaukz6vvS1hdwXljHgHIwxXJQOtPS055t0OZNSCswtlAKlVVYXFm0ATErBhGcsZFlh8nJeqEWhsmThiOOmaVqkmTHGKp2tEsmQiuYyZ9Ea55zTypS4WM4bBYPsqESg+v1+FEV7+9sUFLlK5nmRJEkynY4JL93zYs9bA0EsJmdFkVCgkxBgDPnLTX/od7oe4zbLl9poP5CMsSxPfN9fLBYUHdL4d8mKWxaqKE1pmIeolWHW+IIxGWQ6MdoFkS88DxXEccg4HB0dkXVT1jB2pNt0OhWIDdnIG3nXoe+H3bg7zLMiTZMs04wx43jUGW1u8k5/My/N7t7B3/jOtxeL0zCU1/14Pkn3RlvJvFRFKmSgtSrTzHFhlNZMqbwoikIr5fu+YJxCNUkoJDMA0Zz/4Pf/Nw+fPvvRT35yNJ650vfjXjTod7r7MB2XZc5QbI22mS1NnhgrR8NBBjzoSO4XVpcAjqGzVmtdBn5grdVKO+ekINg+wdCJd7625dzmdHa+XKxu395588Gt7Z3hnTdu6FXx8MsnX37xYny+SBN3omcfffTpT37ys9PJ5MnDyWLKGAaez9Mk/eiDL4viE6PRGmAcjbGMsSCIKNqt0xnM59OTk8Pdve1er8eZ3N3Z4VzmZtIfjCaL9Ge/eH9rb3Jw+03ph1xKpTJkCIxjU8kSAMCBEBrAIYbdbm9jQ9bF5hCYF/hbu+HG1j7nKKvQDeZ7F+qNN5r0oL+zXC5PT0+11nEcU7J5p9PJM9XoN65V8UprLah8WAR+ZxD18+5GlmXZZDan+ItsuRrPF7YuxmfMbLVaEcK61UZyoZTqhFGpcuecVoRpLqT0EdFox8INpZQyliztJMn2+/0iMeT8b2CP6Or2/MY+Q0DZxIYHvZCYcRzHhEFD7ah03Ov1CJrHOce4F/uRc04DB+FHQQAAGsZlWd6+t/eV976563llWRZKbW5vhZ0YGAJgN+6CA0QQHAGZo4PBGCDsbmyM+gOU3mdfPv38i0cGjuer7Oj0bLlYTafT+XxeFOrRo4+NMT/72S8ODg7e/fo3z8/P/+k//afn5+d37tyx1p6fnz969ChLZuOT6fXrtzhwMLbf7eZ5ovIKGJKk+9VqRYmnzjlKTyQ9jExnZIHIsowiTagAVOM5Wy7ndLyD0JtMzxGd7/tB4DmdIQNjlFKFc8ZaV5S5dhbwahP06zTgUikGFbui/mxubu7s7HS7cRyHUsqdna3t7c2trdHOzpa1dnd3l5xh5+fnGxsbQoiNjY2vf/3rX37xGSXOEnWj9N8oiiQXg14/9INhf+Cc+8PDoz/+o+99+vEn//6//zvvv38eRd5bb12Poqjf52+/fWN7eztkW1En5lI8Pzr8R//0H//yg09KaxCxu7uZ57kfGF8k6SJJVjkUyhpelhXwSGMYdDWC4JUMWNTZHQ0PrjSVbEUisAOntdaqYA6Wy2VcFkZbz/OiMDaeCYLAGseZ2Aqig8GmA97f2dm/dhAJIcpSglkyTtFeZFQ4PT0dj8da66lxAHB6emqtpVh9zvnx8bEp8m4vplTUr3zlK3t7O6PR6Df++q9lSvz9v//3Pc/b3z84OzsdDAZ3797d3d0dbft5nkopF4uV70Vnp4vnz44ZBg8//8xaewTuT7/3R9evX//8k4+fPX50+8b1PzXJ+fjs5PClLgtVZMwN0BqwOpBULgK1BY3AOQulCKWYgxOchYEf+B5J1UVRSMG9IKRYp9l4QigNnTCKg3AxPQv9IA6jIsvBOo6MAZZ54YkKzxKsQwfWWo4MHTittNEqzxCxrMGhdJHPxsqU3cFgEEgBRquyVACT83PrygI02FIVSaOOc86d1UWZZVmWF7IoszAMh8Nht9vtdoHg/KbTeQ336OV5rlRGoD3DwWgymSRJYowLwxDRWeOsAc6l4JwxxdEOA34yH4dBwJjNlnN0JWH4nJyf0Nm0dR4d1sgkFJVCMretcdMQ8b1vfHN3Z280Gh0fnyZJtrGx4ckgCILuaM+XHoWpXtvf+p3f+Z3vf/+7v/jFT3y52Bru/o9/72998cnT/+6f/UtWGpBs0OvnqwzSosyV0zr0fPQDC04ZHXiBaBUtbc4CjG55uR8dFKE/Uchlp7d5/VYYd9Knnx+9fFEWSX/YjzyxmJ4l8+nzeRn0NuPAQ2fTZG51IQVTKktWqtvtNpAmlEdA50v0evbNN9/6+c9+eXJycvvOtW7szWeHZRGdvpTf/9MPH375vN/vbGxsvPX2rXtv7j959pnG/nKGL56ecSzfffed07OXH3/4NMugG+4AWsaEUqUfyF6vl+ep1trrBtvb28cnypPB17769W9/+9/+tV/99SQp+tsbT548/3/9wT/6+Qefo5OoeaayMGCuhmZtSBsdfs4q2HTiu5St65wrXODQ83wmJDJuAQygZQyWKSWQ8bop45x2zp2cPwYArW2n03OM5drOk8VslUoZN7HprIaqMTUeiqP0EhF4sS+jnkjTwfYumbV1XemdKJFSU2ttkWYA4Kz1uEjT1JeeQ0DkAMCZlNLzfZ9ziYgWvdPT08PDw/TsDKhipxTK6EJbZYusXBfapIHYl9o5R1AM5LilLTvoVjXOGpOUcy4IAs4NZcRTsKK1lgKAHz196fs+wSMnibYWRjvDG3fuKT3uE4YcF8s8V+cnxOmN5s1yNAGrjLEsLTgXWb78s/c/+ckvftEfbKL0Tk/Pvv7uG91udzabfe1rXyMVZDweHxwcdPqbf+2v/oa1djabXb9+vdvpXzu4EQYxuIyiYxhjN2/e3BgNFotptxeSytvpdMhg2+l0VquV7/vL1ZxQu12r6GwURZ1ODOC0VlIKrZUxptOJOWeeJ/xAKqUYt51O5HleqXLO0TkMw5DVwLbIKdARjb2Sz772iuMYrG7iITudzo0bN4wx/TjY3dvc2Nj4lV/5FS7c7/zut+/eu0WPWGs///zzL7/88v79+8fHx1rre/fulUUymUyWy2W3Gw8GA9qEGxsbBxujo6Ojjz/86NnjJ/fv3+9G8eZww5Tq3v2v/fmPPiiK4uR0+fDhz5fL5d27d8/H6fZwyaVgUhRl2e16D+7e1M76vn84OS1NlsyWL7NZmas0XUkLUkrp1tAWRIBoLKLGRm5Wn45nk+tZ6ytV/ARnvjXMoKMoNoYMked5WXAvtTzqDLc3NqhUFIUKRyiu3fvKLC94FEkpyyKzRSbRnhZqsVgcHp2dnp6enJwcHx9nWSaEWNV4h84551gYdrIsS9NCZRljUms9GAxuXL/1xt3bo9HowYMHItj62c8++PrXv/buu+/8w3/4Dx89/vL09Pzx46effrZcLhf37r+BiNasjo/GJ8dng8HmoN/94osvfE88evjF6cmRNer+vXdevnj27NkXeZ4ZZQe9jX6nuzHYVoUpisKBbkJhM5mRWDDsDfOlaqJtpZSmhoPthlskV52ZM5XbJsr39u3bBOO6XFZOUNJQs2xJ0higpX/GKqeNJ8kRYKy1RjvDHSIyNM6axXzM0GwMu5zZTuxLKcsiKRUCgNFlqooqwNj4UkrOQUqG6FMYfxiG+/s7W1tbaXYURoJz4SWCfJZS+nEcf/rJF+T+j+P4/Pz8+PjYGBfHsQBVGMgNen7YCXybLwKXAyu/fufN4Wh0Ppv97INfvHy52tzZRU88fPasw6sIc4oa4TUG9dHRS1cnLmJdektKubUxSlfL5XzGGOcAZ8cnlZ0y9PO8dNqkaWq/+bXbt3aTRRIIv0iNtxF8/avf6gc7P/vxh8s0UdbEoXSny77fCcNoUWSTxWxZ5sAQGTM2AYBG9hVCdLvdTqfzX/+z73EpUothf6jSfLZYspOTME56/b3QeSxLEwYlOrbd8/p5liSxD1LyPFuukmy5mEjmBHdal6vlnKaRMabKnNeVtsWXnz2Nw95o1O31xPbuIE2Wp6fn6VJvDXdv39nf3Bycn0+yfCk8M9jw7wYHpZ6pPHz0+SpPRRhsxGEZhy4OWbIqhOCez8sylzIYjfqLJUwmkziOf+VXvnl49OynP/1xURTvvff1WzfuTGazzmDn0eNJFI7eeeurnh8Izzs/nxRl5jh7NeKDhJEmRoA8K5SjptLUgeOSc0mQJdY5EEJQnrtzDHGd+GytjTse5zxJkrxQZVl2Oh3GZRR3ZsuyTkhziFXsibVgEJhjZVlyA4xZ0ksyZUPJqf4nthBlEdFq7vv+arnkyKy1cRDmVMVIUPUuzlA454yxAIxzHkU+gDs+PpJSEKAM7T/JqcPrPE5Xob1IpRQXolTK2AKZKVUKAKtUqRr6sckadM6h4GSJJVx+ROx2uwAQyqAxHyGi7/u3np0fnq68OA7DMMkyKaW2hglOOAxOVbBKlMzQOAiFFxd5Xub5F599Ph8nve5W5Im+lJ9//mWe50EQFIXa3Nz2fb/b7cdxnJXmrbfeoS4xxjiX7777NcYYc6lSbjjY1MpujTY9XxRlKiVG3Y1f/dVfffDgAckZVDH+137t1/IipahFktOpnpIQ4saNa0HgWWtv3Lhm67rcnic8z9vZ2V4lMyGY7/ueLxaLOec8z7WUknFpjFa68HgoJQ/DcJXkfykG7OqcfRIQhRA3btzY2trqxcw5t7W1devWrTtvXB8NR9dv7Bpjnj96xhg7Pz8/PDx84403KEXSGNMfdFfJogPR3t5ev99fLpdJkihdEPz98+fPybB0//79mzdvTqfTD375fLngANHxUf7k8ez09PTxo+lqtVJmQjrEcDjUWnf6PepbfzhA6cbpbL5cOIfWsNJYLrARYhqltglxgNeYoJvoB5oBYjY+iwBAMHSojTGelJ70s7R8WqyWH3zCOaek7TAMKUWNc57mWmlwgIVWaZpokwsJs2WVc0XrPk/KotCcV3k4VK5Y8KDbGR4fH+eZ7kVDo8EaazSkaWE0Jqvso48+uXHbv3njTicejMdzSmXc3Ny4dnDzxYvjf/7P/xnH7r17d621o43x+VkS+NEqmf3mb/4mSbFbW1tElPv9vh9wygEly+TBwX6/u2uMWYxPyTkKdY4p1WPvRCP6L/FX55zxTFmWZeEANEN/d+f6/t5NiszSWiMXVBP61o0b1/b3p9MpHbRhb0D82LUqagCAaOWYAUCTQcQYy/N8NBrdu3cvigOK29Km9DwJdd1GCnahHO6iTMh3E8cxrfX+we7m5uaTp4erZMaZlB5GUVAWSilFkpO1Vilz9+7dKIqePXvx8OHjs7OzO3sbzFkuvF6/1+9GrOAdzPc2ut/4ym3meY9Y+azjz1eLosiCODq4cfPFp59DnU6WJEnj6/UDFEJ4F1LGGRf4/MnDoihOTs52dva2tram4ykA833/xfFDAJat8qOjo/Hxs3t3b6XZPBQBF4Ofv//xf/5/+S88EaFjcRAaZjuhZxIdhlZyY1fZYjKbFyn6UoQ+S4sGXpTV8GScc7s88cOwjw49EZsyg3zTS3ohP1kuYuGiDl8ul/M0jeM4iiPkzJQrjiyI4s2dXcFdnsykYINeXBYq9CR40lprjC7LwjnHnBObG7devjh97xt33/7KTUBzfDTtd/fPT5defH5rNIiCg+dPz3/5yw8/+OWHxydP44785LOj7Y237t2797P3H//4Rz8VgsdxvJgn1mkpfCm5Us735cZoCGgWi9mzZ89+9Vd/ZX9//4c/VOPx9OTkBJxYrdIX5x9Mp9NOJ/B9vlgsuoEf7XWsteHGAZkgyEPQBF5FUUR4YKIuQGuMWS6XgQcIwCXjXFilrRWIPueh5nNA59A6JNkcuZQAcHp+2uv1lNHImQWnrcmSVZKlXA4RpZBeS6IHKViapshMnivGqmS7IOBKQ7lYET9r7qe4gUWSjqTvgCETDCwKCVgaC3mmnAPGDIKhHH9jnBCiVMssy45OT5RSTApbFpzzLMviAJE7zsHjXNRmKGOMJ+M0Tbvd0EEpJTADWpeMMWuEVoZzLqS0xjkLZFFRyCwKZY0tDYDRWqeFVkpx8Mm96uq8yZ9/+MXGD34y6H4liMJ5sgLJFTqUYpklQRTZVYVha2qYHqLOOegsmW/2Ik/nqJZcq4DbMl25QcfzvO3t7dlsRp6tKrtahIwxwtAgrkMYOgBWSu/4+FiV5vr16+RtsrakSNRer0dhQQRxsL29LT0eRRGl/AdB8Ou//uuuCsicEyzzwcEBlQyiIvNpWnz7298OQoHo5vN5GMaCB3/lV13scyn9NM+sgY2Njbwo0rTMixReVyj19VdjOCEk824nCsNwPHkWBIHSnfHkZDQanU2OhsOhdebGjRvkcPJ9f3d3lxA9Pc8D6Jyfn4/H4+fPnz9+/JiSkgeDwTIznPOT4+MPP/zwT/74j8uyfOONN87OzmZ54vv+YDDY29v4+l/5PVK2ACDPPK31YjbP0/TFixeekIvpLEmSRbKI0M+F1JgwKZUrk2SlnTMuoQAI0m9Ie2vsOq/KxGRlae9/MmwmWeGcYygdonEOkavSUc7x/PicYLopirBCr/S40+AsF0wiZxqMFQZK25GdUmdGA2jQGgrLFAhg0pMiSRKGErkY9Ef7e9cX84ThuTXo+/7maFtIeP7spVIKEX70ox/1Rz8NguBHP3p/sZj9yq9863d+93c7nU4Q+MeHy3/53R9kiXvjzoPbt29aC77sP3r0OAxvEM3Z2dl58uRJr9cDZ/IsmU6SstRxHGdpkWWFymE6nQshfOdJEfgYCiGELUpX+hhKF26Prs1mM/IrlVCSCyzPc8YkoVh0u91ut0sM2Dm3zBZSyuFweOPGjd3d3dlsRiSlLFSTbWFbyCqScQK4btneFFlup9NpHMfXrl3LktRau7m5eePa9TDy2qEk0EQdm5IcNxTjyTm/ffv29vZ2UR7O50sEORptM/Rm06Vz2OsNtrf2tNbLZfLNb/zKarV6+vT5H/7hHz18+FBlK6XRSWDoPM6EwJixXiBOnnyWlnpeqFsHe8OdPez0/q3f/k7Y7f7pf/PfEjltMmhpiozNiPlRrwiPzzl39PL5/fv3j16+/OXP39/a3CHtZblczYsThlLyoBeHZ6fHZ8cvbt+6dv36NW9zND5effzh56PBKFkuS1M+ePfBb/yNv/bl8s9Lq+cq7wfR/TtvmFAWzOVG5bOUiBu5pZt64cXsyAihTRkEnrBW5qnRJ8nE63S2lVLAuEQd8NLlabZU59NZN97c3BjcvHF7Z2uQLsZHLx4X+aobR74XkM2/LMvVakWwqZ7n4X/4H9+8e+eN4WCUp2k3joxLz86ebozio+O03+8PN0ePHj02Rigj3v/RB0HYWy2LXrStCu/saJEsCiml5GCMOp8t/MAb9nt5umIobt24+7WvfvPJo2f/09//X/7BH/zBT3/6006n8+DBg29/+9tvv/12kiRZWVnbG15LNH2yyhvFha7KUuGC12ge69pSjfxure2GUfMdWtGbiGv/bvsCIa9sX9RADURhm3iupS7WLdbCqbWW28uFrujZwlaQNG17tXMuOX9hrXVGlWWuylLlWakKq43gVXZTAyRb2WSg+6pq4pwLoqiekAu47dKLauf0ukwHIqaOMFzAGrCWMRRSekJ4bPNbzT3tMNeyTBsGQxJ9lQKRa+eMdQacYphxXnBZMK5vxFVwI02aqMFlVpmtwi+1Jj8CwUG8/eD+L3/5y8PDw+3tbYL4oEhLpdTW1hbW8P2TyYRqGISRaCLbm85wzrNUHx4eBkGwu7vbRGbNZrPAj2Rdso0EOyJwVMWFDN2kuVIoadnKSWscIs45cbHguavDevthFSxGBaCoGCIiHuz0PM/rdruDwaDf73tBAIhgLQCo1erzTz/76Be/XI1n3TDigKvl8m/+e7/33e9+90++/6deEHDOD4+PmOCdTifz+GqxnE6n6XJllKaNbowBowEYcMZQCM8Po6jT6fpReP3mDUpYCluXlJISfG0NEF0UxWw2Wy6XJ5MTGtTZ2RmVfLDWjsdj4B5Fx7Q9dsYYxquK6LYF5c8YS+aLJm+VomR5DagZxzEiEmwTyUZkVW4f2+ZcIAjaZnQD+c8AQHgsSRJK7x4MBg8ePNjZ2bl3794vvvx0uVzeu3fv7bffzrLsH//jf3xycvJ3/s7f2d3d7Xd7/9Uf/IMf/eCH/+H//D/4/f/ofxXEoQP4/PGX/8f//X/6nd/+dp6mu5vbVus/+8EPv/rVrybpXKkSudVaO4bTWfLi+TEyL8Z0Y2NzsDGUfgiAxtpCG6XUKBbn5+fT6fT+/fuDwWA2m/m+v1qtkK0L1ZHLjPaq50c0UbaOGqloCAvhIio1fXrIoRWb0szPLF/2+31EPp/Py0JrbZ89e/bpp58zLQAsF9DrR/sH21tbGw7MYjEbdrcZY91uFxFPT0+plLiUcpEr3/fDyBeC6v3ZMPKjKOrv769WK6XU/v6+c+7JkyekXsdepyyybhgMOp2z0/PpMj2bLr73x9/fRq2YyIGVqDs9HvPV7/zm1/76r733D/7LD0rr7r/z1Xi4waRYLmeegEG/m6Z5W9RrCGxhdBiGAKwoCgRurTs8PHz8+On50+d7B/tnZ2eHx0fdQf+rX/1qFMd/9md/BiCUUkmyNEa98cYbv/4bf21vb2c+n5syIen29PSUNNqbN292u13BdeNkYS1UyLwAEp0XiwWFMVPQyS9+cURfnHM0Y7SmhO5OMQeuBu8Mw/DeG73z8/Pt7e1f//Vf397ePjs7A4Dr169P0ykigmPkX5bSC4PY932xsdFfrOYff/TpeDx+76tf2d4aJGnJGAC6l4dPS5vfunUd0Hv67HR7Z8NY0euOnj48Wc6tz3t0niWHIPCE18mLIikUF36pzOHp2fXFYnNv/9PPv/CC8KvvfZ1M6mfjyUeffJplWa8/agbfHG8AUIpgyVwdPlWlaQseXsk4yfTbBKw30rqpBXcHtHcBnEOEUmXQsqRVXxA5F20q0HBuydbOwOpFGhGxMKphhA0Fcc5xXPtKaQzNs1CjqLQZ/Khzy5BRt8yNLi2FOyIyhEtHlxqcn0+azrfeC4t02n5R895FsmjC+hHROme0s9Z6UUR1h8AxRCaE58lASqn5qi09NFPRlevSXVbY+l0KI8cYEyg449aBNVprq1UR+AOqokH5iLrGXx2MKrtZnudFIRoGbK2RUkRR6HnSWqOUyrKUjkRZFmQUcc4R3J3vezCpdo6tkdDpeGRZkecZgEuSVTNLSbKKooj8Z8aYUlXQhtZxvSqllGHkd7ud+XzunPUDKaUwupJgGl5bLSu4tjRGe9QYUxRLRIzjMAzDKAqk5EIwRDw/P2+kH9Yq42OMytPs/OT05PCoSFIPuTNWFcWH/4fPZ4v5fD4P46jQ6uzszPP9VZ6JbidJkjxJ8zTTWoNzaJ211velRWatzVVWLlf27IyCwv/4T/+E7KiNLEXzQ1JIw5tJi2KMyVA2fseNjQ3KCEiSJO70m53cmHycc2m6bHSyBuCQMXZ+dtZYR8hkBQBBELi6MkQTZE7CZTOH7daMMb4XNQEZSqnKFK+UA10KgVCdamuMKss0Scz5wtM6yAxf5LGDO8MduSrTl2czJsrpcjPqfuvNr2zIcPzoeRjHxpiTP/nJN4Ltuzp8fnL+/KP3jw+PFuPxw7NUHQyQGT/0nTOltscn548ePiu1zlaLjY2N69evX7t2LY5D5xw6J7h4fnQ+m80+/fSzF8fja9eukU9kc3PTuhIROaIIMGxHtNj14W3rBg4vHN71WdOmfaKbp4ZsBxFPT8+PT85mswUCX65SLmTgh1pr6WHc6Xl+qLTTRgFyP4yDIBgOh8aY8XQ+X56mJ2fGmM6oG7koLZzW2g9kHIfJZDZ7NJ2+/1MKZiQXDyWpb2xs/H/+m/+q4/s39ve2t0bHx6fHJ2NlEZjwPekMgDVZki6mizfvbA76Wz95/5fA2PnZxH/+fJexvf390dYWs7os04P9643xHGqoSCHEy9NDRFTKeDIIw5D0r/Pz84Pr13zft+Bol44nk+lsFve66TLXWgdBgBgSpNLm5qYxBhg3DqQf3Ll7b2dnpyKGiwVzZcMj2lQ07g6NMRYwyXLj0qwoV2m2SrPhKIg62O2LRpSkI7BalmHk+YFodrVzzjpljet1+9a4x4+e+F5w7+59ytp3ErXWAExKyRhPVtnz58/PzyfiwVfu/uz9X3z5+LDfkdbqz774PM+S+7/1W9qlp6fHk8k5Iq6S4uR0sbU9ODoeA8RCCIBytVoVKdW2xOVyOdy+l2UJcqtN6Tg3TFjhbV+7dnY273ZHW1sHUso8z4+PJ/N5hogn58tGS7vAO2Xg1kHIiEwwdIyDDDqXGCTdb8warbutrKj8Qh5nw7AJMgZbF1T1OBvkI4aMcQaMFsmsb6sJMFjnhPTa7TRjAWOhQoWHirdTbY0aiw4usn+mLQIHxjgXYA2i48iQOQ5ri1P7oKob82ZQ7alYJQUxJKJrjfU+9mMiuLzGqk3TtCzNYn7OGCOfNGPceR5zIQMvjs4aLR/q2mEWrGjV/CKYRuobhiHnXDLBGbPWaO10CdqwUutCqbwsPaUsEQ4AC9DtxqyVOU2UnTGmVBFFwe7u9vb2du1nWtdIKYqiKbnjVeXoq5m3dcGZsiyLQuV5aq12zpBlnriC54kXL543GjCpdFCX8wyCoNfrSSlOTo4JZZ5zrmrLStvswRhj9bq4GkCYWvOgJDmS0kIaFd/qpPpSZxkSw8vLzPf9OIoCT0qMkuVqPp2mSfL02bPRaORHYZ4ni8UiU0Uceug0TGdlWaKDKAwBAK0zSmutE505i1rrQmllnBf43U4cx3HQiQmeVyISmnSWZbPFgqgVFVYjtbJSXmW1wZryf77v53k+GmxBbTjx6mr2zrmt7Y22jYeoJ3C+t7dHMIFtKNAoiqKoYqhN0mdj12nsorTWdHHmUbwo5eI/ffr0yZMn0+l0OR1zC1EUKen7wktmi3S+XIyn2fFYKfUkN5PHL6SU6XwO8/SL939x+qd/Csp4BnrC//Bf/uDo5592Oh0uxbCEXuYe/+gXWVHs72xt3+1l1/I/+/GPPnv8GaCOOiFjAFxkuR6PZ4B8WUpRyvOFSh8dSe44OF0WWZa9961vfeP+e+O5+u53v+t5v6Tq16vVandv2Bh+KGGXDAPDusoW/VU2xem8mtBcJE1eXVwZWhUUnHOlDbWyR8enT58djscTIQQCtw4dCuMMB2EcW6V6mUy1KRGRwVQIQQVjXrw4PD4+I4tCb2eQ5kmapmWZd3ux9Lc9X8bdzkcPHxFE19MnL6nDm5ubg8Gg1x0ev3z56Msve3HkLK6yknuxQ6EYBGEkBLcAqdPOipOjxePPP9s5+Obx+ecvp/PRy6N7b94/2Nvd2R5J6Z+fn5P9SdRoybQNdnb2tNZpmhrtPM83JqPj8/zF4fb29v0Hb//2d/6d22/cmS0Xn3322cHNW3s71x49ejQen708fP742XMDbpWmxhgGGgDIsR1Fj4wxFATTCcJmbl0rrKGnGOcckPf6wyjuNtYL4NDYKlzL0qZLn7Jpzs7OiqLwfZ8wjJPZ0Te+8Y2bN2+uVqssy0ptpANtnXZggUspo05PCK/UkzTXJ2dj8aMf/zBdma3NTlmWn3zxqSmL4WDz/DQTYRpFnZPzMSIqpc7OTrY29xeLaZEWUTRQhXc4GavCDQaDKJC+L9968BXLzHR69vLwealU2B/OC/X8bBIHsQg85VyelcY4ADC58n2/WOWN1CxbNSLQrrMwa7aHACAcfUFEhgiMYc1QJdTut/bGBX/9S6MpWmu9YG2qbbimc84Ze+UBKPOizYArdugchUZDy9jb9LrdcvMsF2tTdiPGAoAxCISG6zmwpsKgt64oCgDugCFHipGp6H9pmkbY2hDgel6V98xaSc+IaLKiSZNVSlGdiaIoxpNle6RSVBn92xucqEaVpVBb1ynMhGgiGTNpgz6ZTLV2RW7ytMjTxJapVrmxxZdPPqGguYb0VC5kXanXjX2bqPBX3n6QJAljLMuTxbIiNz7zGWPalMhcEHqMA2M+57ws863NvSb6lDIgqanNrY1ON6JYrSbKzBjDWbXHyAdDhqYG/Z8x4Byt1cYo348QUQgJF9QOpbR1znU6HUCHjHQw5hzXmhnDAybG4/F0NgWATqdD3CtJEq3StsTdrEvQizi6Qqssz5eLxfR8PB6PV4vlcDiUvRg5z5JVycHrd0QYaACXr7VMROQcJRfW2jjsaW3TIsdV6vLSImhrlbNe4Kd5ZpwVCMKTnu8XihLwGXIGDB1VyLGVdt7xQxJHSHOFWkOdnn7eaPwkOtCEKJU3Z9bWMRCMMRH69LhX15CmPxH5a/Lam71KpWyqNWjh2vteVdmCAv5nsxkVCgu5AOl5jCOzTun5eJIkydHzFz3mpWk6GY9JbqMqh5PxWKGzebnbHQ6HW6vkPHlxujEYbmxsZMz1h4O5ykUn2HzjxmB7U4P7ZHq0/MlPjNFZkVtrgTEHUpWGcX7zza/eOLgmuDt6/lRnq41epEp9eHg0/ZP3d3dffPL581xLg2JxNHPOSSkXj49cywXWkILdUb/xerZPgfQvTEtDN4LWuW6zDe53Aj8siuLsbLJapUIIzqRSplCptVZYUzo4X6yMUc4ZRFwuq4UmKbzQILzI87zxJDfGCCHjTk8IbzZXQYBRNNja3CcQb1MX5kIQ81m6u7sPBhaeL7kQQoS5kmF3Y2tv8fgz7dhstjo8PBptdFUhFgv7b/323/rgi2PwpDYwnq/yjz779NNPR4NumWfO2CAIut0u+YCa0r+FLRkKrbVSmjGhlHrx/PDJk6eDTv/lyXn45eO49/Hu/h5jbLFcXrt2zZOzVZokWa6NY5znhVqsVnEcp6mRUhYKjFEvj55Np1MhRKfTUblptIvmQHHODVSQII1ASXvSjyrbYRPHTrTRl72yLAnDMc9zZcpC5c65dDEXH31+dDolSG3P8yjj37AKrToIIkS2XCST6cJYFEL6G6PO9YONNFu8fPE5BkF3MHz06HBjS3ieGJ8v7tx+c2+3//NffD4ez6UMEq1FIJxTzjmSo4UQBwd7o81BpxNtb2/0Bt28tJtbe1E88GSYa8uqQAPm+QEiamuNcmDRWnTOcUA0wByxN0BYm3zb7M1CdpHPVcSRMVHfScwPSOtkQrb5qLUWrEXnCBfwEtd0znW8yL1yAQACb0tMjd7GeF3IutZBsaoi6V1izPQ7mTRbyn3dAZQcnAFg4BDQAXdOO3DM77g6sNYBWABwgBaB9auhkmBSty9x2Z4xB0Av8PyQ1SW3pBeEUac/2LDWXrvBa9ai28rZ7kaVjUD1fMhkSpeuUbeI7eV5XhRu/2CrKHSyKlaL1BNQeExraZ3e6HFsQXDXo7bjs5Qsk43uRedhcn5ELsPGTQsAUsrNzc00TZtkMIreXK1W3e6gaZ96Ti9SWmqtrVXOVcU7KcQsjjtYu2yRmSAUQkbWBqSvzBdjZCYvVozDYNiRUmaFoejWZhKImJJnurFJNNKxThfOWa0J6x/KsiA3UuDztqih6hosw52RMeb50eHhy5cUcSMZdwIny/kiSxjnSilgKHxvkSWlUhteh+bNKo0OWnBBEhhngsswUIBlWS7S1SpPGVC5dQ8AZrMZ7WGqT0eBbPQLxVIxxrJ8RcsKAGTtJwHLF37DRWik9F/Gqmy0S6eSpChaQZpA51ySJOPxmPziSZKQmaGJOG3OVEMNGWOC+42PkOaZGDmTgmJzdF0ptsrz5lCAEQ41GKtUwcEY41QuHUqHaZqmftrzAqetKZVkfL6aR53Y8zwLMJ7PjC8UWC8KaFNR5l6pdakgz/M0W4ztF8vlUoA7P37JnbL7O5KhVvbHP/tlp/PIGBP1hgBQ2oQxxj0PUDjn0Dls5WghYlY6paxStonJoK1l5pXQ2aZaiGhMculH2ktZ8azX61FNJOuY1sygNYZpZaTHrcXVbGUtpUiBcy7PJmRDIrHYWqeSFCBNnxkA8Dzh+77WZVFmUsper+tRaS8egtOMMcGFKlVRFJ8vHzHndK6YK+K4qy3Pk0KGWck8RHZw7Ybwg63NwWo2+d6f/kJ4g8eHLw2K4dZmrz9gjCXzuTUMHD58+KjJOXbOUbAVIoJgnuchMtLWrAHGRL8/DKOOS1MRhMtVOv/8S+7JLMuOz8cdLwAAZM7zgoOD60oVD7987PlCyJCMxhWDL3Q6XcDZREJwJQMGaRobqmlhrBqlm5gGIlnEgK2tSlGRM4t8almW7W7vnU8W4+myNm8Uq7T0PC8tlojoLMXQWKWMUspoJ7RhTx4+68TJwcFo/2Cn348HnYMvPj07PUp7/fjlswVzn25u7zCIPdEN+h7arB8PVgtiDI5EhjzPBc8Y4uYw6g/uL5Y58CjPmfQCZQvJJZPonDOADJlFsh4bQObAWYfGAFriTCDZhZLUDUdRumjvY8YY7UYU69vwwrUOIGqzPVW6WqBs2kFEZNK7ksHzuNPe981VGt2YH5uzhIhQC7L0SGMqL/OiaZNeSzcoo7XVRmljFVrDALlADmgJchkB2QWrtUrXXLY9WucUXHUpMGABHaKpPNBccskYAlWM0VprYzWAFYJxzjVIdEI4IZxgIAErxNTFfEVjEUJIKRhjKAR3vjWOSYjjjid6qqu0yp0prDNWnbqWot9MxWh4QBrApaCwMk+bYDHSvQCAQqK0KY1VtAEArQNjrDo6euFeidxxzuVF6pxrvDXNoYrCdXEOUsjIvMk5j6Ko1+vt7e36vvfy5ctHjx6enp6maUZlGSl6SNZIjVG309ijiHNQnCAUJWOs3++XdW12TXC+1rS3DYWpCyHOz8+ttdPp9Hw8nk6nNBVa62Hcpexb46xjiIxRJknGEgBgQLm2qIwCo9C6PFEMBXKGyB0yEfqcCeTMlhf2gwOgcIgwjtoWeIdQqNIY40lOZnMhBElCFdIvOuucdQ5rAxS5Eow1jDGGDBki441pLltVlZhJEyUZnbYrWcLp1NACGWOoGqaqy8SS9UUIEfgxocE3jhWip7bMiVI75wRDtMaCA2sKsAatQIsetxZTp5GjEFIX2hPScEydjjzOfbni9lylMi+nL46dYJrBbDwRUbDIkpcvX1prrCsBAsaAC5SIjIPS+fzwcTo98qVg6AJPnJwcScG01QRMHcehtTZJkigK6hKikb18OQCXOGctOpQovbaxSuUXgkWaL7osSKUACh+tqZAfMxCecmiRW0SHnFaDOycpJ0pZbR1yybl01naGmzzLkiSRnhd3OsYYCsfzQRIXmS1Ta63nxcbx6VyX5yck9TZl6mn+g8gHdKWy+WplNON+VBi1WuVBtzudTjvILWNJbtDraK6+fDF30vc6HeXcbJWpojx89jgUDKxezCdUbdA516RfImKmSmsd5SAwFEqZ1Wq1WKxKBdY5JmxpodQ65FIGcV5qnS+CIABwnifCMMyKfD6fSik7Pa6UyvOcwv08z9OWIaJWClG3bQlEP5NiBbU5FupSWpxzp0AIQjatHL2cK85zZVaXuDgAGGMmn33Z7/e73S5i2ZQvC4KAC6eUUqUhTzDpVtaAmM9S67zJeJnls+1d/s1vvd2NDz78xfOPfvHw7t03rI5ePJuVpR/6m57ol8pwXi4WC8bYaDTKE03DmM1mjz77iQXWH4yGW3uFkmHcRSskxtrnjHPGmFKqKEspue9Htg41akvQ9F9jlCM1Fly12QAAwGi6n+qpIX0CANXToItYKiJDRGDcrVkmtU/VLh3tZwbUTqVKGmUaet22iUlxAQmo6SovS9MC4miezcuiedzV5bXJ0Xglg2RSGmMsN8ZqsIaj45xzZIu0qMUE1rbaybCKwm3vHgCQ2Lu6/XV1LGcArENmGTrk6AOAddwAM44hc4AMGBsnwLkVWSGl5bwyMwKAs1i7bBXtyCqGM+5bwwCcY9oxBQytRQtKiI5SisrAtRghJOmScy494TOJraA5yS/4ZrCWknhd9bOKzfF9IQS1XFnGancyzTOBbFOzbb1hOp2XZZllJVVqgzqKCgCklEVRvHj5bLVaEcZhmqaCybYlAGuknlyrZubbmjEURSNZ67pOHwAJMOvT3pj3nVFCiCgM79+7R5XStdbKmgh4URRciJxiWxGyPPd9P0mySn5Chs4ZVQkxvU5fa1uoUmtj0YFD68A5jHyfXLyMMVLiyY9OfeY1LDAiclpHq2ibkXOBoFWllEpfSAvGOu9I1sUqqpl3TjtrLZD/m+5XSlH4KHH02WwmhCDRCuoiifSnRuegpdFa93sbRPrzPCdZjdwZabZEbx1db6zVtio35BCyIkcqq2esEMITHBgrHOQSE26NSRkgg/zwLOnmhjGmwCpnpw8X0+WCCe6HQX/QyXILaLTR2jghgyCQns/6XFu9MJYxKYsck9XUOcMY29i6dnJyUhbe9va24G48HiPone3ReDylDSyEbJuUlV27vSrBEQAApc+a35tPAPBDv00nm7MchKGzBNDBeWUEJLoHhjFwjPuRZcYhWia4lKWy2oA24EojS2OttY4JKbW2yJkvvSCmfrqiyPI8B8e1clKgs4yh9GTgnAuC4PDsaHtjY3trN40SCjWxIIOol9uF4uxstVSWZdp50h9de2Oc2vnyhQPGhR+F4ElJmH8CXK87cM4Z7YpcSeEDoLNoq4PsAIChkLIGYzAmzQovDGbLFReCe16hjB/KMA5kJQabrFSFVtbaIOoIIYx1YRRLz+ecL5dLxq02lnMedzttg2Wzn3vBgKxTld+tLLU22lhfegZMVRuNAzjQTiulGJfaOsaY8AQA0GFEFHE3dMim8wVxX1Znjni+rIJmgDEm6mNnBLJwPjtJVsXNeOD7crI4F2xw/ea1j3/xoshhc+MgjHxkbDw5X851EHbSPP30w8eD3saD+187P5k9f/5csGBzc4NBkSapNqUBFHJjZ7tb+D5HjzFnnWMokCGg4yIQMiiKgtJaGiHC1dZIcvE654hq0XcAcHiZYdPvF7TPdjmjulK0bUUwEQdv7+ZGRfPCAAAcgLFgLEn5AACGX8bba+bUGGu0tcY5B7VjmiPjrLYOOucAtQN0YOIgdlcFkWlrGXLhMQ88BOecAWMdmE63d+nIOeesddwDax3aKlLcNshEep2u0L6IUJKQUb3ROXBQGgS0AMxabp1hDhEFovDDDiJaxMKBU64Zu+/Fpi6Pwyy5o7i1Nh+X1jqjSbDXCJZxjhycCtF5koco1jGu1loeNOkrujkJjDGjK3dsM9XN6pD72RhlrS1LpxQaY8KIsNzKtvVScJQyanZUwxEBYGtri2TYS0tAMu9kMrl+/Xqe58Nhn9ZOFbYJDkLERjsv7RoMAVsm6NV43LRPTI7OZJ7lZPQjxY7EYSklaFWWJVrnR6HneYDo+34QRyxXFCdVlKUy2oAjA3XhHLm601VSZoVRGhFR8FWaWAvOOeRSCg84M8YarQtbICKFH5sa7Y/McfQLaerErjjnYIxzjoKWKVGVwFu0Y80hYi2nL9eVN9o1yGiAgIA1ExV1tRl6b/NScgo0bbo6gKuJD6c7z87OqEwsZc40Mo3n+1UfXJUC4QcBIjIHjDFKCyEoVmstR6Z9XC0TLoS05Xi6dAgoRVYW0hdpnp1PJt1+T6ObpfMgjkKn9pdlkqyCUgKAYxgAWFdqrWy54pxbjWluATn3JAIrVPn86aMgCNDpwxdPGWOB54HTp8cvA79b0xuwqrXr/AoABwAALdT7H01eMd1KJK1Ys+Nr3bfa2OAcuFWqnUPGmCd94XnOOdra4DArC8oQ5JyVZems5QEu0wwRUUgmhGNcaaOsY5J3h/5isdBlGQSBtjZNV4yxziBC5adpSokSnDPOZZqmxmTD4ahUarpYotFhEGtg82Uxncwg0lGvn6yWYeB1ev3FKumG3XyVImNSBqWGtMittUmae2g7gUfQjJVSISWhSTvnpAkchUkqq7UuCkV8MYjCTqczmU6DIIi6nZOz00KVg41htlhaazudiJR1xEqeLo31laHwKId8ONoiofPs6JjObMMQiKxx31PGMcbCICKCQ3Lq2fFzWrdG+qTT1ImHSpXOaSuRMQaOe9ILgiDPc13J6Mw5q1SFD++cE1xyjyNya8FaC44xFPg3/71bVPWPYiNv3bp1/fr1o6Oj//a7H+ZF2h+K22/sbI52/ugP/3xzO/z9//X/6PEXyy+++Gw6HY9Go+fPjp89mb7z9jfu3H5Tm/Hp+aEXbL1x729wb+t8uUTeYbiZ5MecMymlLyQ6tJaZ0mrtLEuwZQFueEyb5TRcqjn8jUWxYd5NRGVjGIQa8AWuulRdSJnXANGNz6mhyKS8kqWO1cGKTb6auRiZ3HSYHjeuUvjoR2xqy6iKatOrG5pOhrhauVxrGOSla2S05kLpQUt8bqYI2XpLtW+AWuGAllgNrbC1Ntt2zmHdkyZ0q5le4iJYY3HYVhRJ0+1GEwXUl15aLa69usqQtRd8/02X0FxdGgExufJ35vSrLwUAj1+tYRibY61qNxcior7aYmHZ6srfnSqbbdAMARHLPCOWQwyY15X7wFQ2ZyqJQSZuY4wC29jhG65Tc6VKUW70ReecAGwfE3opY0wDbw+2+UL70F2UBQGgrIPF2pvKORdK3vxozBqXrcxFM4fYupw0l1aQvsfeOi9f15e1VorgwjauL2su+0Rf3dvtUduWoaXRjxGxLBJWh481BNRaW6bJ/fv3//pf/+v/5J/8k/F4TEFbxhgrsWkTaug3pZRgPbh40i9tpEuXcvaSLQ2rbIjwyvubfOim5fp3r31IL91wadERq+PSJq3NQK58b1muz0v7s41/0F5Q5slLv9BnEMor908UKESkFDLP84qioFoON/Y2aMkI0JAwIK21QRzRhNcGrYLCibPiQpgtq0PSmnA2EnObKH0pQlcLN000qBBiNj9v7//mwHoyoPAIcp0QaIEQQpuyubmh/HSObI0/QzfX3MFhDZbQpKIg4re+9S1jzNOnT5tSdURLxcZg/9HkUZ7BoDeYT+f/9IPvbW4Otre34+BguXhsbK7s2SorOz25Wpr/x9/77waDHmPgQE9np1yqN9/euX4rPjz5SDBPazcIB05L7ZjH/Fxp4xLfixlYZ0xhCoIOoPSJMI7adL+52hqtaKXu6Fdq1NDmIPnItZj0X3zRSl86G9Za8kxDi1phi81fOht4UdGstiYj47C7pNnTOpEusqZT9eYgRaRN2uhqovMvvd1eTGRaE0F2QXZBrAohs6u6CgCcrwlrWyOULY5rjCHhlJAjnXMUnkOPUwwCrVfTOF+nil72wdMX8xpfNedXr11L+r/4u7vss6+uinA3L10ziXrtKvtK9V/wGo8EOO4ss+TGh6vfS3VYr/gdJel/nENbRozDDvnSKJ6rUfUIRt8YQyZWXsMKHp2fU+yOcwjA6gQuZKwS5shE3LyXtXYNtDgW8ypC3/yJPpv85kuXrQUXd5HBcFdVSbrEdbSyzf1tyqjgakHKFhU26iVxOU3z5qXNI4jImbfe89Wr68pLCMhcE4HIKvcbHSj6ByTnIMJgMIIW92oExG7kc8FWybI/6HV7nSaqf1lkzTBpRYiMZkkFXOMcpWDQdxcEVzNU9EQznPYowF0tUJaqbIsZzWxbpXHtwcFq+M2ZXsdyIjnTeBW9D3XgJlCwprGvqfFFeZYXjIgMAEBdSH8HAOcsAKzSWUPu2uuel2vXz3qwAEWmCAYAAJzjiI6CMpvqKc45ooG0MZIyb1z+tk5wyPNciG5tyEMKtoUqzFA61xwN0dAfzrGJ37VWK+UoJE2ptUJCgyPKY6xC5qTHhSTCZfJC2czGcUTniXMmxFqoXS5XFASLrILpphiLOK4scFprzlFrbitkdY0IYehLySmwnyiw+NGPPyU8v6KcJkkynoA2KWCel6wolCrdfLbM0qLb7RgtHn75otM92dkdFGUyHPY9P+Acga2Ozz69efCVrh9tb247hWmach+cTrlAtL7WWuvSgWUMGAPuaSYv2IGhRSaiKLqSMbSlSKid5FAz5obkXb3JWhcZH5rHm70ieJVWdIErW0vF/mhCmz3adHt9Yloic/tdjVJe5Kq5sxkUjZfe2JAGuofko1cZcGnXEkDTGURk/EJaMDaFiosLDLv5Ymqw6FaYMwCA0YXfUiCadoCzsiyVNgAgpRSexyp/p2ozAOeqFB2j9ZrvwpoBILuAQ9I6DJeN59Xlrv4dzWvu57WPljpTv9e6y/utup8hIDpEC4RTg+gQEZm7WmNA5l/5O6sFhWbSaN4Cn9cRYcJarjXTmuaBAyIAMuk5ZhwdWndhEduz6lwVu9cQ4ooOmvVt7Q7Y1rq2h+zE+tn2fk6zVf0i1whnAIDu4v5o2oSy3cOmNc9evS4yXp/NC8pHLai1GTAAcC4bOtC2OV06d00QU57neFGwpt8Fv2yjoivwfMbYKltsbA16vR6duzzPp6usfVtjisiyElpkqvnyqmJAV6mq6mokN1hrES2AY/zq+RGtBEKoZQVrrapiU9YA9c0subal2gECggMpLuuyxIS1uVrwpaqOr54+n0skGeYiCdK2ip93jjFkCMiQOQBez3P7ZgBQKkPmEU83ttCmtK504E7OT2mnBUEQoQsq351YrZYNJXRVXniptRLCNtwXkQHQf9fzby0jrzxWdo7KQnbpvPt+lV54yUKAyAEcsXDegoUpy7y937CWVTqdmMbI6vBDaifPK8heZOD5XHoVYzofnzDGijIFAO7AgVZaGWPEwy8nw2HHWphNJ0EQbAy3GGPj86Lkp1EcSN7NVpkSEIVRvy/j/oYqKQ5bfOWd95bL5Cc/+clqqYyGwQbz/XBjMzg/XibLSciYYMX2VrhY2hI0GKMdcPSk53GOgLYsoD0vzTQ1E4p1kgn9t73R23PacKxL7Op1BL3RLLEFY2svoR21GBh5xfCVq2H57fcCQBRF7WAcEuWcc1L4RBRsDeOALYnBtUzfDWW51CXqpFa6/fv6CzDOOENHhYabjhWqQtK5tOEYv0yy67+FZHKHVtoJAHh+IGTpBxXQBKOouqLgQrqWwNvMia1Jw6X14q9hqG0WcuH7lXcDOHY1Y2BW0JS4Ws2l/9q6pUoaaBpG1mjZ1iFRMQAQcDUDFq/BiEbRCG0OgCzMDsCBRUTHmGXswgYOpGkOOVmV6ZPK8loDzqKzCI6BcwhQ1CnLnCOtJL3IGer72nDqqp+vthgREE2zXs0nZ/LSndVVBw1dOlBchO6irlztK3mhhTXD0BpbckNDoxum0ublAPAai2mrwYvwO4TnX0/ROg+eDCvNsWJ14J4ng7IstS3jbtgbdAgwRNuy2+02kwO1KtPwA7i4mdtyw6VL2wsuoWaAr2PYYRhiS55oJIY0zdqPN9SDhKRX5/9169i2VLWvoszgKohc1LatdTsH1jprLQ+9V4lha8FoNYlTAgB4YqPtvFPKi2IfAPI0oT47tMqUUDq6xw+FtcxaXss3wgu4Uj64ih7iRd5Zlo3LwzLW7LHqlDZ0fj1XYJFsI8hoD1XzxpnWuqgRkZtX5Pna5dQ+Aoiy2cBYru8XgmG9xwCAsaoaPSHHITOcc8a1ZM45x4wTve7AWaaV4iwK/K4qNeHmY6x2t28w7oJADIZBntnJZLJ3sEE5nEUORSaXMzx6Ufa6KgxHy/QFk0Njz+bLo6PDiT/XInT9XjEa3Slym2a8yJlxnrNCV2tTXtoicMFOiFcO+9WrzQKhpdFyfjWBtq1wkqYD7feupxUREdsH5tWd1yzVeiwMmwisJknJOaqUWa1K0wdEbDn51qJ9+3WXOtkIyO3hAJBljNZ6DeMMANqTV3Y7CILG7NMmIp2wB2u64wAYGU7JbGKtJYMqAGRZRuNo978hiG19pU2OrXmNRtUmcLh+8DVleYHB1Zq0w3WZvPar0TYE6IJpGnC9BZ1b/+zwNRqwfZ0Gz5xzDhnlbteEAJuYA8ZcmzHkRd7MW2PnbAhgI8/AKyrIJU7AzAUG2YyX+ZdjIKrtilf4hgHAWte+s/lOvsl2O/RfwS/4bpunuMz/AkZ16ag655RSlxqnR4xV8MqJu9xnB+CqdAouKLvBco6MkbGNIYLkXjMo3qoL7ixSwhUAUFY65zzPcyciYEgwdowxDsClsNZqU7aHv57/11jdmkzr9ro453p+dOX9Db1qHqHPqIXxfski6FpX8yzhXrVfTV9eJygg9pt91VwA4FR5ibjRexvD06VdEXnreb7wxVUcCGp3YRV7j6IttUMtFOYmaw9qHfSg1pPTZsCXLKPNPU0cQHsIjoB0rrIIauXKsqQCVlgHCSHibD52r5hjnXNZWjZSLwAZ0YAxBFSAzFjlahsGvUIIobVhjDkwxlZVPhkHYawz1iDjzrlSaa210sYPmFU9o728GA+2zf6N4dlx8fjRIkvY5q4zms1n6Q+///M0MSr3lOflaV4q3R/uDIYYRmmhXk6Pz2SAka9vBR1npcBIs9BpUNY54xxDXHOOC4XP2r7JZhkaxvPqdWl+r7ynfbVNLhdOiNXNKtpWQEf7ve1la5u+oXXAkiyltXe1w6kaIDSViaumqHEyf7XfCDVEdntjrScE1r/AhWOwHn5bvPCD6MoNB8iBLEwMGbac08AQkQtR10+s06vyXGurlMJSZ3lJM6C1Vdq2u2GdQ2sRkfJfX+2q4K9hnGAqh1a1jhWbfB0HtlfzcWBrBn+B0Tau20vz5uCyZlD10139XvMazdi1XOGsZcOXLSYCBPmL4MCVBkxdc9gYKA1oAwAMLm7jZgP4XgiXCQ2dnTWzb4+uTXCbG5xzruUUXys4UM39q/skL3WjzdQz5gBAW2IALRoEiIha5/UyXjBFetyDi/uZ4hmEuGCsah6RtYXj0nrhVQGbiNi4bC5RXga8vQ+bY6UUMsaMRaWdXpGWaaxj2ppGVuAIjDHH0AEiyHqYF66yFeTYvqKw0x5UQ7tfp4lSodVmUM0qNKb15heikJcYcLNe5Mu/xKWwJZFfuhyUAOT3vXCDcOsYAmgtnG2Z9NtL42q62t5CABBGXUsJ3NbmuYNapCsLA6w2KFej4wDQuH6aV1Qk1F6BFIaITXgdtAyZjDHnLKsjKyvKVm2DCwvYjEtxIz0vimWzhagP/WHQsNILtvHSNCfOtXQPbYrmde3QWorNplW21lLlMUQUuc4oyma1SnKdRVGEEjKVCgZnp2Ptpr2RmEwmUvaiKDo/m96+e8doyBJ2cjwrC9PthcIzKksQutev3bx+sDcbu2dPWVHm3MnVbP7s0UMp+0JsAqK2YJAjR0Dr7AVu1MxskiTNYNoHqS0pt08stA5n89fX7TYAIGieZlc1BiujLxTHgBohpYEsaL/L1akXLQW0urzAZ2uzRnVUENH3wka6vLRNHcEz1ZHbJPS19337pDkums5cbIeiFtEYZ2vzFwBIeZnhOQeIWJZr3+2FeXCaIQpR5YnSNtLGrLIKAaq9qxBRu0vBGnV+FB2vtkaLAC3ksleuy8FuNAOWu6tvfw0hc9y1CW7zyS6p13XfHNj2zQDVCbX/Gqby9tUIHIiIzjLHGEEsM+vsejjrx7WlauqMMWutKg2F76FjQFzSEUurZ0eyppGqm7Tuem1NgYb1IhTmsqBZPfsazT5N1gS0bVWSQQitndb8Xls4qvlq/uR0BFetI4O1ZcJVDAmcc8Y6gHX8v6sFzYv8Zd1Ou5HmvQDAeaVqcG7bdMMTvKWpOABDzlQDntYl59yCsMZyzpVSwouM1XjRKk7fxWuqpeFrBERXF1EAIEGXIVrnHBdX7//lMsFXBBEA8L0IWyEFzSo3t9WvqC5R52e3KQy8ft+WNV29fL9S7irXEmMcruyAWwfPXrBKojZWAXLnnLGFc84BL8tSyJgetM5aZ11tgOHeWiIkuzcnxew1DJjEuJrgO1els4KxBtBaZxqdveqqu3p+GBfIyK3jrKuSoLTWQlxMQsFqZ4ZRReddLewSs8+LNaKWazFm5xygDkOPogq8GnlUeJ5YLhPPyxGRc2attlb7fiiC+XJeOMvOT2CxOLxzO97ZGxRqOp+tkqQocss5RrEMQmRcD0bxo8/HX/96Pugl8/lsNpuslqtO3J1PkkKdB6ELo0h6kUGnwYFnuXPS9ZuJaJ+lxhTjag2S/tuW1psL8XIORnP2XidpNgEdtsY6IRnKVsGA68gpmtC2uRgunvymzTbhaACYmiWndoyuEsiaftZkyBJCAiISYAL5Vsn0hK8wYMYqlIP6PDR7UbRF7NZmXXeyPQ++7zf2Zxoy3d/rRoR+4Fp5tPW25ryFDt0WMBuJp5H0ff+yL4o+dXG1D4y9pkwk41czDGuvDipZq3iXbc0A9WZrb7m26RVay2pfQ7DsaxhYO4S93ZR2eXPO24wBGDqE5h8wBEAmeDtIvOnteix1+6zOyqt8Wq+MsZ2Ge4HQ4OXyf7ReBF/VbKfmyyovm4PZ6j4qm7R3FGOMHGsCKdofnLNQIaLSyjY7Gax1zSlklQmRUdky5ywB8GhdRdXSmBpO36wtIrQ7TCIsqT6cN44kKO0F3zMiUpdkILMsZ4xzLhAtY0zrPAhCZQgl1wJAtUYA1jlr1oNtT7g2r9knpcGWT5exyhutdH7l/VL42NJ01+EXjgGgs0iSSnuDvcp9kawsa2ljffPrTNBNrEDTMn0GrYIZ0III1UXRDB8vMmyoN7ltD0QrpRThuniewCpRwtm62Enz0prWqab99gZrU872RDWkqWGERFpflxZVFhcw/1vtXChTyBgDcJwzpcr2Oaq3KxaFcu4CA6Y96Xlr5F3a5M6hc8z3fSGY5wmtwVpNWxQRcDDqtJlKQ1I9Tyi9EtIxxhHk9Zvb73x1b3sv+PkHp48fP57Pp1E32NnbTTN3ff+dONx5+PwfbG51v/Pv/Pr5+CRZ6k8+epktw72de0H/1412BGMFDIFrZMaiMUW6Mbgt2cgaQJHmxVwp5XsRwaC0aUS1QVuA/lhBzAjO+XI1ay9VcwNhpzXctH0DtKhS+13tLdV8oXD5xjPP6irll7ZOQ54oKJha5jVSMee8LrNomyw3qADu1ykrNPmNxt/EoLV9CVpX2KTUlLWWXkGg1I2FpNlbJZU9r1lmky1XFJq1MiabOTRm7Ztv71QhfFb7cmwdOkRttgXSZq8bdA2rblOK5iA168jqGgnNfLYJgW0BDruWCi4uhmet55xBu511a9CKym6bzuzVBJHZqwW412neQuj2fmiugHs1lzPOGfJNMsa4NdZarWl1lK3ooDXqNekirxE4XqfRCu65qzSYJo2qTd0AAPg6bebCF7za1t+2DLXPi3X5a+bZXLkuSl/GeKeLOXvl/aDLS2+kLxSMwy5eiOiFFXBH1Wzzu4zpJDZTRFsr1xdxe+rLvSa6+3VBVYxfYKjNWrxOYAVXZUlUx6eWUIzNr1iUi3SMtTROIfxL5w5b4gI13pw7RCzKVXulmnlmr7hmqvHmSfvx5n6Da82+/caAr7H0230oYB1UhS1G3tRTv3S/NlfjB7Qpc5sWyTC8cv+0kRPbXa0hii/5ZdbEvH1enHOBt1YR2yROeuLKdTfmQrR580W0X9YetlKmVIYxiSCzTB2+GDOunr9wnVH/2o0BP8qt41ubO1G3c+3aqNMVub1+fn7y8YdPtbZgfTSj/Z0b1w8eZBgy5imD2gAiWjAGLBcOec+XnuC5dUqZFeM6YN1Abi2Sl818tXckVVNpgpsI59M5R9G8bapdH8iyLeA3Y25QTpr7m4PhLoaK0BZvgOmbFlytgrTpyxpc167L9rka0R4R6exjreI3ngmt1+kNrrZsIyLpxKz2JcPF/Ch2ERLEGEOz1eaR9DtliLMaZx/rJPHm2Tb7BIBXITNpgOTrau9RYt6NT719ABhj1lV9bu9drEGRmu6Rsd3V0aHtM0OPNBPVfrVzjhAH2i23l+PSqXNurRi3b/s3euHF79W/ZoDWWQBXhS47Z7Vq5qHV59fE/v7lr+YEVR26OD//v19togn1uWtPOLxCs+DiuriLJsFLV6PFNiJdJVlaeik6R2eQeoEVtNQr1lqC4m76bE2Fn6XBUqg5OEa58sgcAmf2QhDTmj2wq03Q7nVpcq8oavR5KTi0OePOkm2psefRCeNCrk2gtmXtayI6m9mgHdgYwBhb+yzcKz7jhtRQVHxd5doh1mkCr8kbFtxrTwtj1b4iAOpXGQwZsJr7my6xGlCovStoRq98L3uNIEiGBUREQHDoLDhwiFWsz6XOIOLrosSlbK11KxS3saS2mSMiKlXAxXDa6nFsVPkLQ7OWmm2monqXaO6+dJaAceO4cUKwyGGxSuDZsxVgEY9Ot3cGURRyPtge3Q9iL0nPjse/GJ+dL+ardAEM47OT5PxE7Qw2mYsR/cCPmXagNOdonOJMh6Hc2e2dnS9W88IhoEApPGvZKpnEcdxonO18rBpsExslkgYvKrxQ21rCSnN1r6hxuLbPQDM7bcm0vSrN420Th7uYJtTcaeu8Rr7W0bF2llElmcq60DxFB4AW8tUDr5Rpt4w1w2unJ1EPKc4WcR17cuHB2lbZ3lvWWmPW6V5tsjWZLHmrxFDTZ88L6mk3ABUdcc5KWVkaylK1xRQ/jq6k9VmWtd/bite/GqmqkUgutYNt8+xfSOirH/Hyyl7ZvX/l9WpP/uKr0ZBcbY+tjnTle7u8G/97dOnKy74m6hhfk0b1l70urResZ5VWhH7D1l+rz/Y/eP18ci7qPWzqzqOjKtv0D4kXV0iNTKzrc9OhJSambTvAEACqLDQgARTWTBsAmHPSralw+zy+LnbhdaZdZLI9+bVtuMKxv0SsENG66mA25KiK5WxtZqpAVTPgq2M7jK4VXETAdfnUOp+tykt21Uw46V2OvcAqWO/qy1UJ79X6NYnCVr9q6qfRieo2qDwp1HKb8RPXrxg/mnp5a4ZNvX+ND/7C2W+OkwMwbcNPCyWipTi1V4Fz2e55i3FePRMVEDdcxmsjS9urVMi20mUbEo2Ia0fRpTlHBHCsLCyCYigYMqO4c+L8KO3GftyNhoMbkXeduXA6Lr98utLF3KiyzIteZzjshVuD/q2b109PJrlkDI3SkKUpCg5cIbO+F25ul6vlLF1wZ3pWSysdyNTylXO79iJWJ+m77ZG4OoNbSgm49um2J7Shzm3xBC9KNOtZa918aXUb/tResPYRbTaBbQGGNLPfNGWMrbAWLkZHv07p4bzacKxODq7bMY0NnNUJP7au4tc2tdEBLuuiDpVDl7JTHRijLg2QbiCm26SWNyZfzwOty7IsrLWcc2OqhGYSdBAd58hb5qY2Qln7s1nZCyfn9fmUBKN6aTdD64S/SisuzXz77a/+99/YRcFTQKxmrQFbq1objZGzGFozj4iI3FZ9Rvs6AJC/ZHcaweUSQcGLPmN8Df/7V16NBQguTmmtETYKN1y6p72Izjl8jWZDKGBQsS5gDGnqKAiofXihImpr1LzmdwAwUIFF4MWD6SwAMIKLc2teDkKuSWL78/WM9i8ClnEXZUTEy2p9i3AzB4BMIFhG51EIxlipNABiDWgnXrPtq/kkHZaGQyOiSPBaciHRuf0shYbhmjlSr+B1gpqtcUWaYbIKAvOCa2k9dZXCQG9fn01dXghVoYcQUTvtWg9UjBlfewDcK9H+dAm+VjzaRhGtLdTqfjPe9gK1P9uE91L71nLEZj9TFh+1cDkst26ctWTQtahwYbe1L+0yL+RKmWU6Z4xJ4TMbh2GvH2+qcpnnKwflZHo+6N/d3XzP6sCwP14sVt2eL0SpXYZglumzk/OXN96604lTVUijSmN8AF9iIFU4O3uERm2OthiGk2mZFGXoi9HGVpFdDvYjBtPUNXM1UjHh62b5yl0EqqX+NybT9VK1RM5mSZq/mqbudK23EqumAjLt4KP22rCWnkt9Y2wNvN6+hzNBwlTDfUk0E1K0u9d8Nqbyhl3RRb5SW0evNM9SFakWmeAA1jmWl0UdTcbZBa1ljXbU3jGNdbq2nK+T9Bunb+OEbqK126Y2uopXMKib1WzP26Wd+uplW/nE0JaQ3AVgoBZBv7KZCwTRXaU6/2ter+dYrD5UFxhwi/liG1YTZQUZ6EjKdsy9Xgr5N3g1J+gvHMu/1nVpJvEVIf7iiytEjAv6LyVOX3W1XRINGYVac2o6sB4Frm2d7S8c1z659jmicpztbUA9Et7VvszXBf3BawBhwDUiSJvbYRP9dpkBI0PORI1T1tBALoL2482XS+eC/uCca4IZrXNA9IeMVdpA65w2rRlb1O1c2Ayv0/irRW/3n7I8qv18kaMCGL3+DpVeR/Nfm9BbJg0AQHDtx2vET8dfgyBmW/ni7S90/yUiAwCVHeUVS4xWTSJo3REAAKQs86opt26wfVTbjBZbGAatpccmWt5VaSLVPVczYOdc0GXDweZisZpMTuNOIISzupBhl/uztBiDNCgWq+x5EHX6wxt7uzePjiNmc7DKuUVRnCYKEadBxAX/qTF9q3tOiTyJo2A38mKp5eOPT5bZxI+fb2xdC7ubBiNTBpr3OM+gFeRZ7wbWVE2AmodRtTVS+RtFrRkzMez22tNfbSvjdr3MFw9Deyp4K6eTuE6bkTRT17IqOEQHQPnOjuYdkQG6GjsUODKsK8Agrk9pu/+NqbnxerZDsS6p9YwxQMM5k2wdg2etNVa3owFaAeBWygCg5hGMOTAOnHV2tVqxVmWC5uEG6tIBK5UFtU6Xam/KJirBC7vt+W8Pbd3nV7byq7uxjYzWdjNrs47ehItXm6rCVZJs+87XxVr9m7rYGiigErHpkpw4LkmN6FpV6q5s5y/LKl+ddqgIt2vf0Hz/y0oil5pdt2OqNJW69eZ1tv7vRU0Lr14A2/aQAGnAgIjALwCJQB2vXiXbO0DAxtKDiMgEYlNQCCsgZefAVcFQFVFYm45aPsJ2f+B1DPg1Jn3d8Jr1uoMD6xRcRW+ryOHaxwS1TC+8teKxNvI5QOSXSRWdZlbdWqmGiI5ohVkTE7rq2Sux5byH+rwQDMCrF7ZqRqx/RER7RawGAGDNCC9tSClieMUuAgDsYtDWeg5fs08awas5WvUQGuxu115J1hKY2vNnHQKgc2gtND9XokLNjBGx/gRroDXYNYsxVtVaNTadAqj2+SU6f4EBXzr5g6G/szMwNlUW33p7LwiCZ0/GRbaQ4aIb+nHU3RhuL5fqfPbZdPFYKfPiy/PF6mS+Nx+O5OZWf3t7t8gAwX/62fsAgSdGZRkYHW109famz9jy+Zfnz48/T9Tk1p23bt75q57fXa6s1orJtOlJQ6MRsW26tK3w5l4/brZmm5S3Czm4Ruxcpz3U87jWXKsKSHDxeFOZmrUJtzYCV8t20e5NvzXSQ8PUm9aoKdvCv6ww018xk2ItWODFurN4UX1s2sQ6vLYZF/2pibpsTyYiGtOYRivUNnqk1+s1LbeHtlzOoXVU2pHVeJE1IqIQrPm9ffCcc00Guqsj1BpjQ7Ne7RPYjL09220KcmnrvkKULvyOF9OQ/ntcr2ufaAVN2yUNuNqZWBnqaVo8wY0xWl+KpPs3pgFjS9uD1wz/9WP5V1+XWmgdqOrvcNEggfia6O7XBGFBnV7cNI6VpCuJBRGfcc1/wAE0OHHrRxyZ/uqD1ex5YxznjMqIQq3+ISLCZY22pgNXM6TXGi3WfOqC4EVpqY2U3LqBXJWMulKPCyjtEKrRrde0Jdhd0P+sNQ4cMsdZfX4dOAeCrRHxaH2IQwvuXexs1R/Orl4vFBdsimuCoNdOQyJxtcVirRlDrdECAAJ3DVR7SxVF3upk/Rp4/WltGyBcbcYABw3m9uVN7hhUJ5P+XA0E+AVF4tJstJuiEyTlhWC01t1rAKKGADLGjFHtRprP16EigPAdcJ0WCybt3Qf7g8Fgtpg/eXR+fTPe6F83KlZ5PBkfHZ5+PJmcA4CbR/1hx5PRZHKkzMIP2HyW+143HUcAzB+IXiS9wL75Fr7zFcG4/emfj8tiMptOzjqLjZH1JDJQYceW6kImYvOZZZlrRSNLKavS33CFJoQXITIaAteYstu/2ypv1Xct72zDURrEK+ccMXVqirfKIDZqMSJae8H03ayL51FVDWw/BQCcu0v9r774kqzB0Ip/bvrQbr9aSCGcc8TPGhbFGDMXAk3WxG65XLWbdbUEUBZrCL1G7EBEwDVSWDPJlzZfe88BF23LYXMPlYhvPM1NHdBmZeEiQaERVTjJLdEnvGi6b/fKXdR3XUsM+v/LVQ+9qvPAWohvWNs26o33uhITf+mrZodrp0wtDLlmftxrDAP/moNqpvoSTXl1/gEAkcYLbSWY/v4X9B9e2erAmgLd1kJTF9sBgW4T3XcOnKvdpuvoDeopYwiA1tKXqnbWBeZ0cZj05XXlTV+XhuTM5XNRXRabPQAX67JATZSgdV60bs5F03mAOpYCXsF4t9a0PU2NabDtI2/ea631A95+XUMH2GvS23QL5AdIuKw9Yg3RaHcpV1VUG1ZdqrRSVWYXpqU5+BcVpBZdvVpQE4K7i1fVf3lBQGk+L1m8mglpGw4r66FtPH3VCEgbpu9huEYKa5iLtbbtYsdWeqq1uj0/a10F0RmjEZGQE5RSjIHvewGXo37nNPI3N69/+eE0S49OTuaxFwh98PTL6fHRpwcH14vcdP3BLFsZY0CaVW6OT2zcOSgy/0d/fnz9xt69Nx9sD1cvXrwocmGS/mQ69eKfbV+f7+4Pf+2vHpycfr43uhOx6+nUjW7FnnVByMYCAAEZUpkaU8MICYla67xQ6zOvoM1ssBUnjHVoUjM1zSwnSUIl9siIbYwhd3KD2dsgGDSPUOPGGPIrVxXlrEHnOALjDPhaC0zXZVUdY4yLKpoxTVPHGKFyeEFdVNxaLpxSiupm1wvDAECbDBkKRhTNOFcF1zURm7Z2wdKQhfDbI21mo/ElX7q2RtvtMKtGt4ZawrBVTBkwBogg/Ki9xdt7yF1Mp6HZ42gRHENGxQ2sq4O5EKzRqsxKErRrIBTBWdvF3uxshgKc484xBMGZq5UAzxf11gdrySzhgFTISsQHqG2SAGDMZdsGfUF2dd1fh8WlO6v9cME8tW4NLdZqH/EFR7aNSHIuKF6JWWu1tuTFXyzOq2FqZXSJYDljnItksbiSQKC5GvLQ1haO9qQ55wBeAUywRIaqfB36Z51BROeAOcpTd67yz5HgxVHUkbR16gttDyEb0+haP3HOoZSN2dC17EMMWKPutG2zZPu4QIIRAcAPKnwCYy5EWdo6eIehYJxc5w4AXCuKtU3THVQaD2tRYQfgx8I516BvY80y2EWfbsvQdLWvV3qBbV1NB9bh1PVgDZmUw2FrjQA5CnKppKl162hhrA2b9R6r37f2KlbOc7NmlJUpvnnj/7ezL1uW7DgOy8yqs/Ry79w7gwGGGMwMAEEKibakoMSgJNMOhxUK2fKLwo7wh+kf/OBHPfhND7YfHdpoQpQpUhRJEMBg9rv0cpaqSj/kqTx5TnePQFdMdPT0PUtVVu6VSx4IgFxMSnICETMiuO3+ZqaFD/yqDfZHBSkzE6Fzg2ru/PC6ruuGg7cEUrpT2AMVS50ccz6GA5CjbctpeTja82Y1Zg+M5W3HyfSkA0E+HFVMD1v0Pyl2iEhuXNGwRyNiTDSAGHKpYARAJmJxznfdtbTPcs6VZYngQkghtFV1Yek0MqeYmNmrzcRGmQ0hQLq4fhOefrF58yr0fUBwbdvV9fLN600IXFUrhKJp9jFQWdTry/PA3W6/3Ww2XY+L5f3Vas2MT798/oO//ctf+ZWPfvXXHr/4Kvz002f/9Nlnt7fXf/zHf/zoo3/x29/uX71yiO+5an29v900LW1dyJ5RmHoXi5K0+IPFJNFMZ0ofM2ttWMwnPbrHallC9nBqV2cyQ+YgFYIycqirkPfbDZlUdEXTlJ3GKlqEbWkXJuEpmLXXvm+smavEAMbI0KUxsygKkMUkM2tRDjYJ+Pq0mciBjPSr5ZhKaCegeau6KBlalD9lb79ccHFxYbUcRTLxWNjf5U+bzcbOR/dosVrqiuw8y6LWJdgppW04yqCth2O28MOBiG/xbs0w8O2PxUFHZkTt1zqyQt1ufWbhV2kovhMTYgogjbLdQRtBhf/RGfYHTraZJLO/AIAEBymccToGBZ+Bh+xzRhgLDKHxSLF5ss5WwWVXbSF5+IszTQjsn2yNZSUoOEhLUwK0DNeuVwXqBAjHnNuzC77mSOash0zq7WySKefuQ6aR2WW2cpn9PZ4o/HJqMJNuhCWZNA0yUNQqyxqNG4aZJZbG1kWwz1F+qHxGpmpL/FrABp5sq5nAJIhMx0zOjes61Z/7BP3yMe9Oxuojww14gmYFhAitRpGlaeSmKTUKBkSYHYcKVR4UzWhJQAHot9vtYrGoqiqEID25pOTF3//dz+7cufPqRXfv3jpG9K7k6PdbePrla+9918abor16s62qlCJ5V4UQEIgT9l1q9m2IYb9/9uUXX717d1Uv+Xb35YtX+3vv3Nk173/6ty+5/clvfufdon7iFz3jJZarfYzoi0S8KmvdSOaxHm7kSETajVwxXrqOQMbyqG3dYnTOSTIrZomVUqqqSg8vpaW8gEksRftq+XJ1dXVI8IorwhRUorOpdEO586CU8tBa1vZ2REQaE+eVxdiF4/TEzibgK1snIq0kpVxSd9rSjxLGzc2VlffyIxEVRaWPtffudjurIihA+mnNWMon31KJDHNtLJ3VgwcP7O36/C4XptAEreHQnQmOkZnPtZGtQmA3TtE9/w6HP8LbGC4efU6cNsnQ72hSJTjLYzhIB1IPlXMAERImREfk0UGMkFIosqJjdw1GBjEf8SCk2dL5oVBxzqvyZPFK9yjDnFJKCjS7WafgJr/00zPRUbwxWkjaZ86+QGZPMzy3CzzkfXBwJjp8P4j7tWwUp5bN7MlfZ6RpWIYqgodzti4iS57yWU67Cf2z0zgteOZ5vXAAZHvvzIrgUYQM3a7UspchfZrzb8zSFnhoU21zFubVQ2e7IPRlYUKmTtEROJ9abzwZNjHDKIvthwNz9vN4mWzSpHKlYQU5ym/yCgDvSkfFuC5ARCAHROpYHdwiwiq9CCGRWHqwGkK4c+eSiIrCx8BN09W1K4saAPbbDUDXdR3Ctu/AEccYb2/3AdoYeblakwt9h1fXNzGFGMOHDz+sF8X5ecEJnzz+9dXy7G/+6kcY733/7zZ1fblrOvTLgso2xKIumVObNpwVB4uvBS1VSFgZLEE9ikaKMX3fW7+cDqv7K+idc5reoySUGeWRMxJ9F5rCUpBFMpqgZdUr1SJXtBv2N3ue9UaZgC8mpTN0WJFJ5qxlxqdmRH6I6ISTaEO9RfKPDx8oXVlmDIuzYmF5EGT3OGaXvi5Kga+0oaAWy95yCvlTDEfOngFA4UMm5A2mp572XcxB4cZTGXxqIM5lsH3mIfR4zFKQK0eo2gfK59D8NyRk9q5E52PsY3TIkwpfcIxp2qHbcTCZiRNF/2oPDmaryNtLCE70OgACNymopA6S4kS6joRzzyZz9LtdnX7X/zpTE17fzsbkstshjwaDtyPqHnUDmPnM4HM4w7ePwweq7TjDEMql8Wbzl3EoeDBrbEffm04Ff0EBB/yKTXqSXDQSYAiIILlEkKMTnHNyjMLTyFYcgmGtTgZDU40Y2TjGdP6+KvWNFhrOUTIFfZW3nGzWcmK5CU/VhD9uAZ/yJGHKwZKDqT0wNOEzdisz4aTDTWRmlwXtQTjRpNSrwt9fXl7udrvNZuOcu3fv3p07d+S/v/LRe/v9fr2tUmz7sKc+FSUhokuLGCMhMaP3JZGPkdu2pZK7LiwW1WJ1VlUeoUboCOkXn718593VJ7/6uHuEq+V6tTr74ovzz3+6Jb5/ef6+wwao9EW5adrFsgJCwGamdg1EkndLFqa/i+sDDE/MlZtKCy/dZlkp5egqzJaWurzkIeI9tg5hu4vMTFBY0lXrUA04eZT0H5X9UDeaNgnWG2diO+WgBjgQwKIo6JSOcKJjuHj4XzdYkCNeD+d/OJ4VkSlPvV6vVZ+wBwGcq/bYFOrT3AE2m82MOwyrcPOgicyYjjN6dTnMPk8JYH0CT2XSKXZrLWb75ZcdlnSt6ckppRSZgdAR6lEWRVNzxkLpZM3hqecGMpSURmbrFUVHsM7COcONY4wIiWiIoWMjpXT+FhpfU3Sdgl4ywZKHqzgE5lte8Zbn41Trms3f8tZTrzg1fxWr9mlkmsHMBD+acbgu+xad6qn3Hv1d6FcxX7/TtBSrfknY58mMIeKILsTeTkb1Hm16YfmSReyZwCYDGTaMUXpgAEQhQRrjPY8rHKeyvfCEZD48qph9mQ1GJ3nTg68bkZFAlBLUNDYxc5mBCXMCM4AJ42ZGrTaJQ6g5OXTO9uEGg3Veiv5Lm+IYo/DH1Wr11bPPOSFi9IVbrWsA6LpdjJFwIa7dGDjEPoROvK0cKPQJsSh87V3pqEoJUsTPf775xvu3zT4h0JdPP1uvz6uaqto58h54WWDkgJCW1JeMmHCfCBiRySk9MABAgqG2p5sOqQg9M1sBQAXGrFiEChXM57Xyy3q9VhxSDkVENzc3GWOGM125pi4LFZaFSUJXwWBpAAC0tjOYKh8AUPpRzOuJqTVzZ7QkDgA2FrA8RwxNnb+OU7Jwu72dUYus5WxNCkkawrsGXqzButbJNmvYrnPQZhh2tqKOHLJaRHSFt85n5fhH01SYue32MwhzFsB6jcV4qS0MB7z41FDhNOPaM35qp5Q/2Z5XJdNMArJlDwCESOQRmTgxp5hijCzGxGwOw40nSuLNJnCUv9hVhNArCeh8DPkAABB6IumFBTEyTb24g6I5XddbGBwfc91bkXN0I4TRqzzTOYylPY0gGbiiWawMZuZTFZ1OlDj9/xu6rUqVyUQ12gmTiVbRP6lXz/6JjQfucJyaOQIhjrWdAYbSEEQTIh2fXxRKa5aLdt2o8BERE+cgelLrcCh1yQmAXfaUMI10DVOdRgGOiBJ/nnU8+QVhbAd8sC46ITiPXz7x4dlx6gwYyTEAuqGeXZ7WqMAp6EbuxeMadYQ47HtKnBICOJR/UW4f6VQe6TebTV3Xi8UipbTb7a6vr5fL5fn5+dVujwgxYuh7AEpJmii5ELuyLBFd1zcx9oi8WNZFSbumX6/X795/kDhcvbnuWn7/4ZO7dy/uLi8+/GR1ef7+7e32qy+fOre7f/dXP/n43ZtdLOkNFl3fh5QYAan3hK6/2dqtUr0jru4KfqBx8ogpOXBw4ysGE2evJCFkfH5+rpRgbVwZKWem6hxEkICJOh6OmatS3y66m8ib1WqlW6UaQEpJCmeK+NFbiCjExs4WsoahDGi2wWU51piVK+V3OR2fBUOp3qorVRqT69NBSUs0Tv6U+xvisS5GFsU1jlrXrrDS+aTc+3ZGG3JBUZXShxEAyrIUnYaZQz+2pbOytp82sdA/2bO0qaA9IUpPELC1gO2N5CaaLEzYmdIlZPYHfbClKMe3pQhEDilh4pQgBU482u6zi5n5MD/V/nUmxizrNywPAADckd6aYOSWuKCJ3CHflOsPvx++1+4UZwFsZ6Kfs4fotNO00I3O81BwDq+Y1r7Wx5KpnW6/JFMS4GAff4kx88RwlsQpe+xmMtgd4M9sLUc/D8dJCxjmIM3/tcsUfNbjkiNfxGWa344AJNHU2ZWKmUAGTW7mLFSEb01R4RnHsNcrktCJymgnS2OeMDBOHlWcGJpipJAbMBdHQgAA5jSmMo/4yfqPE4PUzwLnnVfLHkI/23QZvizLruu6rpO2Oc65vu+3223TxKIokGuEUJZV38UudOSqohqc2py4qgpf4GpVl2W53Xf377/78OHDX3z+86++el7X5e/+zre/+93vlnF5s//JzdXLtqWz1Teqqrp/76PU3nv8WLw0UvbZuaImLL0vODZWNGZA8F997oVBS8Ryys34XK5grIaaXL/djv1KFQoyuq4LIWi/Aak1raYtGoGNpna0vAI1kbfvUo4DtL/f3Ny4XEvZbNsQfaczZ9OxVek25Sa7RVG0XWuZlA5pSqHkbaldA9A4G6/GsTNa0lnSD/8QSatDpARa8lN1AnmgoIflsLp8zgVMwKQnLRYLNDa6PieEQDkPWCHD2bIXBztqBFbOv1QQKUNfLM8tWJLxPCvMLeGF0Cow306KR4eVwXZTpq87kMQAMbvsFKXlCX0IzjnnhbUFZkZw5DhNLX4jOU7kZZ6Y8CkBXJVHgg0pn6M7JyVUfD6JIMrdzlUbEyxloxBYGTZRMsx+6RfL5Nh4FGZfDFRHZNPnzHQCANAjKst2Zw+cSXQ+HRH29UeaCv5koggzTU0UU0vOYBgxfj3HzNcZs4dYXJ0RBTNzVvR1ztm3OE+gmMHcrpFMYXAwbgDMDmVdo5JA24hCZp4p8ClO2rRHfz0lgN2solb+csqjIPnKZNYouFuUk/xvRWnkOSvIMAHI4l/dtEQUmhP7fvHeHX263RiXXdlserwTUbEs5aF93wKksirELflH/+Y7Tz589NlP/+nnn/300cPH6/r8/Pzy9779r169eAlTEpXP1XphWZgC6+zsDJGdp6Jw9cIvFlVdV0Xprruiabqb6/3Vm931VbO5bfe7EPp0U1GMHENq2hjZV/Xa+xKBAL6MMRL5qlwxQ9emlIDI792WmYlcWSzLsnZUMmNKCborUUQgV7+S9Nz33rkvUu3Bgwer1erm5kYu2/awWCwktGq9Xt/c3NR1/ebNG06kpjmbdCAqKJl87Rla6K7o5X3fWpLGfJzchSE/NZpKkERU0vEoSknvUb6gZFOXlSgiRVGsVisJAg8hvLm+ITNA6S0NiKXmvigu6/U6xth1nehDeuOi1mjJcTBzWSzA1BZFxBBCCIEpKoIqlJi5qhZH4SbBd0oVlvFZjLLXHCW8dKLtmlYim4l28RyoSNC3OMAY+xQjpkROEp/7GGPo9naxujqfAoAmc7IULmWIJSQ+dqSC1XHGJLXrZ4QNAITzIwnZl3Sq1IeHlBInlMuJvKOCiHyplQTGLpYAICUAR26lSXHl2QSMI/yDBaZFpNlDbBiE8i+9xjlnoxBQa72VYwN2+/ayXswmM0ypn7Pm4Yv3FvIqS06dwbdtq9qkoiiaPuJp1tA+jBWRpvg5OUHQCdhSrHb+p+R06jp3rI84wJhemMyRLdGYrolGY0aMerHFRmtZWo08xgkr09GZfVSGxge+k3H+psa1AoGnLnQ7tHTobB/pRLOQeCKfXmE7h3PyumTlupYXzZ7PJ/oox3bvclYO5dSbGOOQK2JRXADU98HOhojkZnBD3FNKLsakCTwff/zxN95/7+bN68+/cIvF4sMnH4bAP/nJTy7vXMywWTasa2c2EzlyiNj3LTNzM0TtOyoG03PdEnpP5b1Ld2d91uzrto19F14m/+L5q+tme7E+AyrarsEYY2IuVk3fdF2TUpNSCqFzzpVlGT1WVYXguq7b7/dS2QIA0v5WCEnssLIs7969u16vu31TVZUI4+12e3t7u1qtlsslRhI4tG273+/Fhm7bVnQ+JPBkfV9skRUMYVthY6CBXTceRbvcQtg5lxpRkwESQkJJeQHABBOhrugo0ctgvNyC/bvN4OrX9DPZ+uX6TPZL410Vt+wkxwfeRiuQINdViMH2Kx2dk9InOIYQYm9Nq5AmDcnZuCLEV2EXBSYq2/ICZu66bvZeXeZRwjglgLXAjv6iYJTvbhYeby7j3L1dxYMFgtzY3FwhIiZEGk7pmBmAYurtI9ViiCeKVsu9M+6D2QaiqZc1pcQnSj+mKOsioiEWhnBi+PK0zXthmgQwMyHLISBMXb4jPP0gwm1pMztnMAzXcvnZLgiRqhpk5wDZSaqEg4jhBK+3FeUs9OIUCXVWNnrWXi/KOkx1ICKSoEvMQRiWx9qhe3domSnRHb7X/j4TM5j7qdj5ICLz5ChHP2dHSwoQW6FPiVfhMGMIAEB0pFTnTBgf/WU2jm4WIp7yAJ26naZn7frelI4LfhubotBj5sIvOauwbE76LRzsFpxaHmUPon0+IvqUvbiCAUpj9qG6K4joi6Isy/1+75wDSCH04sT+4Q9/eOfi7NGjR9c3b+q6Xq/XAO71i+vyfsnTZglpOMctM0RAThSYGRFCbAEgBgwhxQAAybtUFOi6G+cK55yjAtGVHgtCrrEuVhc1Xt3WVbnabLvXb268h82u2ac75Fy9rJ1DpJi4JwLvabeDZb0koqbdtb0E8nBKaeFK8X8uFovLy8vlcomIXddJ3nDbtpvNZrvd9n1/fn6+WCxCm4qi6LquaRrrXk5TjU8l02FDe/nStm06dnarFl4ysccAkGJOmCOgosDs6OjanUVBRcSu61wuEWBD0iCxVAQTZiFecURsmsYaIvqo9bpmDnqZ4vd+3+BouI+c6yaf5ZPx5yNiiJ2igTUii7KeecudCVaHrBpqkrd9LJnzsEPpC1+D7A+HtRJ045Qc9L+qfDjVt6Y0OWP0agnVd+9lYu9jjCH2KfYppRSU0SiOECL28Xi6hTcQs/NMaTR8LR6+Zb0Zb0WiECexPCadsDXmTgSwhc8Aan8qOncQYzPPwaxxug49I7TMx0Jeox/kgUU5eiasgeLLGnSGQ1CnnF7Oeb19ERhTJOWjlsNrZBrK3KzeoNDGLM4PVUCe5JefiHI/SMRQpn8oTZnZGT0JjdTXrkGzz1MC3jmeLdau2sKHB53p6KYPXmb42jSIx7LCmBne2sd6Ru84LUU8ffvx58QoFyDAJBc5xSNSFU2+shWUAMAnXOWc5xaH+QAAAoJPpp4+GIy3mp0gdNd1MUaqnAikui69933oYoxN03z66acPP/jGt37rN8/vrPfbZr1eF0Vd+eWhOJcRw2gLOgdEBA4Q4fxiDQApQdeGrgspMSE7H0q4y4E5cEREZEQgQiLg9vW98+XCVc77i6V793JRVauvnj774eveF1iUhfdEBIlL6cV7Z7msqoohct9QVZFLAKnv+8ovLi4u5AQ0hNA0jRheKaWmabbbrbCnxWJxdnaGudLTUEWSeb1ei2K+3+8BCIeeSCP0pKG0klzKMSB6OK2uCBk8lAYcS4sI3M5Xd+2+QPZu8QGBDV9CLw+0ah0aiYjGmANjfDhjyiBiTE1MIXGQeWpwaYiJiAAdghsieACZQaLK4YBTIEZ5Q4zQ9zGlKIJJNAOdiSJkMsE46rS0HByntoVNJ5vRzFHCyIQ3HymODgD7kJkDbcaG7O/yX8LJWazesihqhphDk7qUUsIEAAlHBkFECRFQVneccdDB8ZsMzgLYTgYRTzU/QJ4lCIB4Zha+TiaeaGTHIJJ4OOpWHrLtdnwgLQSiin52njP+QGawMQEVHzTv3C6N5UyOIcWUpi4l6SZk5yM3amGcGclArlgHxpEAOSrbzly+S0yGqAvuIBPPkmr+nBcqkS+1cZXbWdmoXUtKaXr2PJK8CXZTzTulJBQjd9h9hGl6kq73VJs/u67DjZj9CQBofNFkCW8Z9glWiflnL7ZfZoWP9PZTZ8BgdtaOtulhurqZV2k2N8QTHqaxC9lgag74qbNko2wSEfJYJEXpJMa42WzUCkHkoijOz8/v3LlzXsEXX3zx3jv3Pvzo8eUdard90zRd13dpwu7HieY+YJy4DyPz6gJ5T1VVVXW5Pl/UdVkvyqJwV8+BCLx3ziMRMMeUEkPC/TVC16a9B1ytVylSAr53p/7Vc2Lm0Ke27du2a5s+9TGE0EDoO4/Efd8l7gpflFW1XJRnq/uCrG3bipcMEb33u/1eSlmJvbhcLsuyvL293Ww20RRBLIpiaNvgAIQPpN5KoPVyZUHN02IjCnYdu1xUGvKJqQBwvRwq1PR934tsBgiIRT06aS1ykB89pSpTiSiFKIYvGlGXUlo4j1P9Tra+bQfLGHLWhPwJoWAp9EysJ3ZErixKMGWllc8ql2dmiYAbaIzGGLqMsinGWNdjDWqVuwAQTdHKNI1zOfqFjqrop8dMb5j9ydpYlgEhSoFl5hxVaQWz3sXMu7DNvyfAxMBAjpAQJlhhnvzPzN8SF0wNRMtQTglgYlI9hpmlEr31Ods1IqJUsp0hMJi0tNmnStNknGHMLPkXKlHYeIzYKDc6f9sUQX4Reun2jdyOAB4Jffb869kqT76EOGn+oZ+h69R9fYq5g9GkZ0kTkCswHIou+bHrRk+G3WXnvAWmncMMhhajcKpJA0DKzU70CdmbNSnao3tdlvO+TPlzYnnPvsw2fbYjE4jlHw/p6OsMfVo6EcMxm8ZsPm+5cjasC9p6v7RblN6utAzH4AMnEqMij/YVGIB7Zb6i4nE2PmLXc2bZcpvwzevdDTPXtejFvFwtLy8vHzx4QP3mxctnn376aVG6i/PLdtt3XUw9rhZL3bNpcA1Cdlyo6MHBRYlIUBS4Whd1XZYVEeH6UvW1KKErHhkA7/jzEJJD73wVevynz36x3TcfPHx0jxpEFwveQ9yGsOXmdr/rdruuXLc7lsIq5IBSVSDWi8V2u5UGw0LkIgLfvHmzrGrn3Hq9lmqdIrRE+qpXWRa13W6bpkGaW0VyzcyVqqwtmdrRcosQKuWobIWMXHx9/XrY0Rg17IiIKM75hXxqfi0AiA4hOLQ4r8V8z0bYwByDqTyl7DKlVNc1Exd+bM0kfyqKhS5Toj+E+Jvdlo0/cBTAkgFLjoiKonBu+N0XlV6pbCLlGO94UAbcudE1epTAZpzilAA+6fqb6vWztyj9WN53dBxyrsGGhiGTcjBtEQAYMJIrwDrAAcSjcFqBeBtj0nkaiXJ8qpK+EqN0z5LyRgAATdNY9AOtwMoTCKeULZ6qsDJjnOWBU1T+qoxvRjLDrKawxenRu33OTJTqetUROfwpP+rwTFc+u1wIZSbYZhWULB460w+DjfNmtlgZReFnD8mPmoh2ZdbWA2SBgydGmh4563zE8J5BCQC8n1QcMyxrnp9pJ2x/5+HACGezgsFzdkQ5fsuwPBMMOZ9Kw2MYazLbW1RRm6PiCQVULF04IFhpv2iXkBH+uIsbTwSLMRAiAdLg0GLmlACyALbxcqJAhRDBpM8XRVFVVVEUybG4ZyUteLlcSgQstO1+v3/z5s2zZ88I3LJcn5+vYgfI4ymmChtEJD/Uaq6qarFYSD1q731drcRXDAAMqeu6Vze7pmkef/hIGTQIF6CCiBztEF29WDP4ro2fff78yy9+fvfyvYcfrOt6KT7k0CcJodput5819dOnT1+/fl346mx1XhQFJ9xv2+dvXso0AKBpGumaJ9Qu7ZKcc7vdLqUkR+CIXjsVitzabrdd1xXlkXBzAN7v9+a/I4fVoJJZzepoqn0xcwhhCNLud5aqM0tyu93xyjtlXcXcs0FWIa+oqqosy7qupXeHEmoXxmqRdtR1rdc4029KghQ4W5lqBDscLcVpYAEpjomolnf1sev7XmLZrOtMzwidaVSlYLECWH7sj+UNv2WcugAnvWhGmrQqqb2XmREHC5iHmmKAiGwchmBcWN5VQ3Ud5JQCM6UUgB06eR0CD2XsZcnuVDH61NiFjOzenEHKBVnwn3DFpwgAKAouIpEXJanve0Eb3coc3DAEu0lOpG5EjKcqeXVWrqh42263ODXyBFaSxqaT1zVaA8KiVjH1EIzisyghSy80Dgk6ETeggtbSr85ktijO6jIaX7oVP2BIXoYIYItXPCgiBRvHslqx2616SiazjQcFJezbydTnouGICo6+d+bi1u8pHeEDCslDuNlVK4NCRPrnjObDVdiV8uiXPeU6Ph58SieCsDidqKketaTupL1Ysu0Xjffrl/WoleXYJIaHsjGECF7kR8qBBspftLBDzDkwghPvnL/z9OlTIkoJRCQ/f/58t9v5uNs3W0zx2bNn6+XZxTfuErnrzbVDUqkptaYle+fibmUZsUggibECKIh8WSwLX6cEu12z3zXeY1EUZVFV1cK5QvqQpZQcbUJi78quT6uze2+umr/8q//zg7/7v9/+5r8vS+8LAmDnuSwJ6X4I4cftvb/567/d77d1vXzw4IFzxetXV1dXN48fP27bVtj9crlcr9eSZqMB/WLyCrj6vgc/COCyLGWBuS3BaHJZpOwDqyPBIoe4mvWylOOMNpsbEczK/iQNel0JAxqNQgFjwuUhFiJiSEPiZlVVuq0ppZcvXxZF4ZyTKOgYY1mWEu8NhvuQer+BmBMLuxUZKh/gIEcYICAwccLEg2WjNrp+F9clAHjvBX+ICAC999HUVBEDV7oDWREyscgNX1BoHy1BCm+rnXv8d4QhOtSyIeUI6qJX2oEDzqLbCsb+UwXldrtDRKKhaxsSgxyf56hU3cFhnIjW5oOVQva4zNyYQi90wpU9BD2lpI0IpeVc7ILlBqqmMwQepgfMzBATp5TS6vw+ZxPBTiyl8hSIpvxuhCcYSWllnu6LEIV4caQ7DeU0+rEwgCg5MH7KiyOm2Xw4e4msHqCbaN3mdmkada9cTv1AkCnaGtMSO3JsRaPItHhi4/+tJNA9nc2nNO6KaMoEcV6jrmu499gJCwB03d7+V3dkZtybIP+5BTyb6mzTjyLhbH/1y9tlNhzgFUwjtO0STrUvlAJKdmsUjXXJbCo1afMeO8O3TNWX5SBPM54MMKIlnJ+fVVXVdZ2US8x20tBpQGpVSlBuCOGsXpOL79w/a/vr7XbLqdhtYl3duXexrevlt37rW/ffeZegqMtFjLwoanC7sixXy/XZ2Z316qKqFgjEjG25VsO3LEvvveQFPX78TbE1mWOIXUpBMk197CKnlFKfotBoAgaAIpVilQqPePny5Z/92Z/dvXv3v/zHP7p3/10gYqSb3f7O5UUCTMAvt2+efvXi6dMX19ftbs9dy4BVWdY/ffUckCExInuC0hdV4ZxzsXS31zeY4m57UxK+/413HfJus33ZlES0XC5TSovFwjl3dXXlvd/c7i1PGTkgBCEqmLrjbq63ViqztotwwTp7eayt4YXpKGaIcrBen1MuaGUFs2h2M0KVX7S0iEoXRESYBx8Ngq1YCk8XjiBZvyI1JbcEADTLDRFvtxsyQwnSpWZI/GV2uWIJIu7j6OOyDGVRnymDm7jccTjOUAEjj6XsUrP0DwAIQ9tKuymIKJBMJrRkEPOhsdfrLbFtZGJkEgdCCMiTylyKA4cVxAZhk2t6MyQJ2RsmFpqjDBr4RFs6nASJ6BcHJ0r14shlLK8si5WFjD6evGPTq05ZjLQPByBmBiY116mq0QhUw8t8zEU8dNPtDs6ut2dybHQsO20wAlvPgyy0IZ9xWhSSW+rqjI8Nv5Acy2RBJLgtHhrIgTyCb6rwzYYNArJbiUYokmk4FsJYUlcHM1fVyuWBxutzs9vJiZIeXQmIaHrkr9cnGsGrcZ0ppVVVgxHt+sXOR34ctiweP8Muq7MZnst/m4M0J52YvtG+V1IiZ/iQUiqyBam/D3DuTniwTghCS49gqGwWc6pftPb+jI50gbNb0tjWffIKnLGj/F+/XKxCn5r9bUqpKIqqrJh5v2ur2lnJr7hY1v3du3dj5BfPdoh09+66qvquu2WK9cJFaJFCWZRFBReLs/Ozi7M751VVlWXtqECkwi+Wy2VdL4vzd9S4zCjIiP0//ujH2+0WMH388cdnZ6ubm6vt7cZ5bPqQMjKL1pZkYqnruu5meyMhygnTYr1Yni2/9/1PHz16VCyWgK6LAYuirBYJ+MG9B3fP73/8qL++aV5f3T57+vqLp1+9ev4LTyDGmXOu9NVqtVgsFkVRbfs+rdg5V5WlA/DFstlvb/c9YKneAu2Rycx3712qoTY43qP8t9eNsYjLUlGUwI1FoT0zk6/RGC7ZgEOxZdWQ1b03CvokTagsSz7G0DWTB3HiM1/U824qSrTKFFIOiRfT3GKYnijbMxjbY5hiE3M2lDMlw7rpwZXyyr67mbEquSzFVhFaET2ltN+OXZt0AEBZVArzQ3Frf5H32vQhmMZ5HZI3IqprF6dCAk3qEeRgi5RSqUAGZk4AQ51OOqglLp/ul/N4Teap0AMArXCkF6jmB1OWKkM9InZF+Y8EAAhOiwLplWD4hlABESryKLQ5B1sdTvvm5ma2jyIAJGzQMj65XfIXLIpmrnKkFKJz7vClMOV1bMwaABBFDUxJDdE+Bc/1vfrYWXtBHaEZFDvI2rbcSzR6m1TtA4DdrlO0VOgxs7oMLf0Ks1Cg6QQQsQsThQCzEjCLCtYlKJz1OdmD1eNUUcOs/uoT7KevJ1HoOvS9M7Ka0R3m8Ptw0BUNBmSbX2+ncXQcoPHJsyqeerYspejvh5+HQLCvnn33En0nXkZRqWKMZMoSydVqUb2+elYU3rvV/XsfxNRvt6/PLuCDJ3c3r692zfZHP/6HxWLxe9/+jffuP3DOhy6u7rxfluWiXi0Wy6IoiqKSs9ubfRzc8YzeOe99WSzrav1f//t/K0p37969d965e3a2cM4BJuccmRJ6yZz97F6/qKrKl46ZU2h3m2tIPXJ4fXV17/57i6Jo+yYmJu/KumpD329ivahXZ2fni/DevXc+fP/9Fy8fvHjx6udPv9h33XbX9JElhDIkTn0XeojROfJEC+/JlWcuYFlz2wZR0kUAq0CKpryAmqSQoy4BpKb56FXzvkLjcdLt6fNZLCI58oUfbtntb20tFc6GrJzZcFaE9flHsw9hKhfBGAfAY2UchTYzp0iWt+qE5dRWLZ5x7d4p/7KMg8AxgMvnqS4fAxfoVdOHbFbGGPf7VhmKzhYRCb01s1L2/kFus6izoulpTTLhJACT4CaldgAoislZ4/iKA0gOAKFcuSPH78jv4qqyoDi2HQww1JvjYzVy5SXwyww7N8sX2Jxtg+1y088P6gY8gUnk1PicIS2KJM4VBgt4bBU6w6tBW841U/VFKlfGnT1mACm2E414aP0ZyZyyYz4EBVNhCo0mhIgxzHm0Irz+VycguKpA0IgWnZXeooqCnt1adm//a7eYsyv7UAZfXFzMmJ6819e1EkXKZeqZ2RlvgcUESmNetZ2M1NvgA4EhXeEtPcrYbhqdmx4PMQ+9QlBDfJQEDlzoCkOYoHee50Hec773iExFxEH7PTBe04kjp5nlOn3F/DzCwmr2nBme2IewGXYXdNMtf/B9369Wq8ViQblIMhGtVqu22+gkwAjgyzv3maFpN+fn533ofOzv3ru7PqtvXi0c4O1t3zZUFmd37nzj/QfvV1XlFu92Xa8VgBFd0zTtrkEqNd4SgImAGQGoropvfvObDx68e3lxnmKsSk+EXdf1toReYkiAEYBhuSiqqtCtfQ2hKimGplicLxZVWZb79rYf0qb6tm19wLbfA+wZky+Ld+5U9y4e/sqTd38Pf+P5y9c/+/zLL5+9vLrd7ft2v2tjgsRV37bc+xgDYtW1abdPbTeAT2pKQ+4wmFLabm/B8BEi8p4AoCgXVoPGnB5Q+CrLpyChpDi4gAa+I0IKMqHKoamVeVnbHRiZvjcb4sfzDlerlUxAkUaWsNttKB/MW5TSsyjK1alkqimlo671lFHNHuICQGyH4l9gIkgBYNt2FrOVFUqD6sL0bJHfHTkFo7XSzs/XMwqR0fcjo7R/mvkSIFvAIu5nlDOD4UQA5zAly2UAQAq5qNcdczgFt61AjyQhbxpUPHvXIev5mmPGmwCgi5N+w4IwzAwnokzNIR9kRE0ppYJoKPqGDhiRUEIDYmLmwR8DAJJDh7njjbJX9Sioq9nOGRElz0JJRidgKxDh9HRgtjvyZb837nfjWBaf+UzhmPFZy0mVobPRJtlosSqTrGV5CP+QcxyUeGGw/CowHN/g0qSkq0pQjc6Z/dUXRzxYs+WgGXBw1Jr5z6TUogpgbRkwi2XxVMKxI552WlBFvxwNlhQ+w8cUMudHT54FaYoTp8shGszGZO0GJjM1ffacw08r4O277I7Y19lp6y4ws/cFJu5DJAcOMAJGAEACqVmjDEVvu73ms3OMfHuzvXr4wTt/9Lv/blGv/uIv/uIffvjq0cPHdX322c+v/vzP/+flxad/+G//8Pd//w9Wq3VdQ4yxD23XB+bofH1eL/s+iiNIZUBKqe/7X/+1T37/O99e3zm7vbrabm8B2Xvf7rdJKg0xEAAyuMTIwMx1Xe33+7Zt5ei629yuywJCXzogiJg6DzFS8pAIouPe0bLv2gTRe0p9t+kiAKDH1IfLdXn3X/7ab//mN6+3+198+fwff/bZ06+eI0OILXPPkcFR2+23u9uuDa72zCwH5FIPS+BOGtUPMSVW8eccKjdhNgK4KFKKIQ6V+VRJV8YNkELolAYWy9Ie8WKuJel9qTtlEWKWN2mJynIfzMlXwJUSGBojONcfnSRQ6aww96LQJUSe1PJVjtMnjomlTpPUHpZJmfkPCq9z5NxQWEOnocI74ljqT4ohDOKtmOvynF3up6jr6FAWIEMtKjAKjdIYEWndFVmFmiaWOYLJ6IuIIMlUgOZoaTRQDmd0aqqnhuVK+p14tCAnf+WxOptezEYFmT05IQ0NZAHJeUCURBHKmKUoKsqTeGJmIgHNYaFlMgpe+xDKWa3JhBGpTNInW4Azs9Q0VnapEqIsVkfBBdOwOx2aFjFz28ZcpFMmpkqtXYjFw8oUvbHP13Q4+yMAMI+FTazwaA8KdAzLXCzmOwuAiDHNPQ0yKjep1Ka3SN4wa+xkhnNdj2f8aDz2LitSohDrFsQpR9Ivbzk752MCmNwYJa5baSFgv7yFrq1yYEHnjhXo4APRfpo8hyFCTYGj7+IDVUPW4perom3bzXYnocjkkJkTh7KsNNInb0kCAMcL74vVcu3L3d13Fu8/vNztuu3u+vqKQ/+08ssvP7/iwATFDz792f/6H3/53T/8o8ePP/joo4/W67N9s99ub1OIBFXft8xiY2U6RgZIq9XCOQxtu9ttur5NKYhOtKQmhRjarm+71PWh6zlGSPxluxUjfrlcPnv27Ac/+MH+zauzszMO22bzisPCk/Mleew8lKuS+u1tH3ogLKhKnLquTSm4soCYUtdF3jFi4fzj9y7fu3vehf7zz19d3Wxubm5eX10ztLENsd0QEmIRc/kbEcBidBbl6Iq0GxzjmOojhctlD3a7SQKDbjxDw8yASnvgEJBQvBTi7hYzVKK1z85KNBZGvmt4pGUBMiQac2ZhAIAQGEzV3pQSwg5N5QF1TLlpF0i9scsVuGYGSlE4lHJZiOQc5kPfRT1niJD95FbR1rfINMhUE5NXdN28YhGRaPST6GL9rswCptqrpGtaiM1u1MkcEjOZI4DdbmflEGc1gqZ1b3Qv8ATD4rcWIjg1yRmz4GxhgNEVZPQ8MSh17U3XZjBO4tE6mT4iknQmd0gEQB7HcDlA6RzrxD1gwaugs9OY7TKbJB/ODm0LZ7u0U7W+paaxZbszW2c21HWkVCnzlChURWnI+oHFfzvsWibUd1APQOirbXeHmw5ZUM0sSwDwxmGu82Fm7nswep6cExMRdu3h9BBRTQSLMIhosww4e/4BgHDC1nRdiSd1h9iIz6Nw1i5n+ot8t33T7cQOjyoEc7wbY00s2E+999BfIjdamPMBtzwcFl3txUcXjlMXmh0eqT87ryRHRfJwqrJcrVbNDrVKkTNZgMs6bLdNAqiYX7+6/d73vndxufrT//zv4v4ff/ZPP321uVrVzfnqDJz/ux98/4f/8Pf/+6+//8knH3/nO9/+1u/89uPHj9brJTlg5lAAUWLmEIbEwbZtm6ZZ1ou6rBgiAjskZoihC32/u/qy67pms21ut81m2zVt6nqO6UXTdV335MmTd9999/lnP3/xi8/urVZPHn2QuCmgpwjLep0Q0v6mDQ04Qr8uHEbgLjWJmYmRCgZyhecYMUZOkWKsiRY1IvqH3/r112+un7969fSr512I230b2puUUoMYY/TeLxYLCY+UA+C+n2j6ihYhDBV2kjmDRMS+32EOiECElEKMnFLqQkvmyMo5R458QX1HZVlaRiBhVszj8cnMAWIRS+dT5+CIZPzGRMSps6xBXeuOek2RtMlRllmDyRRCN2cZMqqq1jfa2G8N+rDPSblQufIFPWGSfgdozqJkaU078VDpA93U8gBDsRZc5r80u1g+T50BK9Bwao3FHOymbxzgqX1SafIoS6gz8fnLjkOeAjBUJuIDI9hN98uyDMuFRwnN8jAAJsz9GxCRnEu58bOFjJ0S57MSNp7J2cJFX1HBw8ySBy8C6RCxJYNfSUbnud/f2j2CKRUcAopyqIHa3zK0/YPijCTQ60vtgSgzyxnwDPgAoO3/0EhQMHnPZAYiAoxHwgo6Zl4tl+oMUCKKMbb5vVb3VXmAUy2HeTi8PdwFMRjApCTIBd6hVVDGueEYtKVbAADpVN/iYwal/vcI6uKow4E5ffBurLxmd5ZPCDw0Aw7obsYZ7JhdOYOYfqaDQyilertwFc++abbvvffkyZMnKaWf/exnTbNdLs8ePXr/pz95oXtGplgH0I4BQl+FAETtze0Pv/HB4k//0x+///D+i5dfOt8Spp6b0hcAqa7px//wo5/8+Eff/97ffvdf/8Gf/Ml/+J3f/a2zs1Xbta4AIogxISbmRITeo/d4e3sLmIhc27ZNsyOixOH29tZff9m3XbvZtdtdt29S26MUk+vds1/8ArquJlo499HDh5988smTJ0+uty+LqkyAi9V633d15frQI7lt3FZV5dD1fUhIZblAxD4GRF9674gcsCjxkBIzv7l54SG9/875vcs1+fr69na1KHZN949f7ZjZe1/Xtcb09n0vJ3rRjAGDT6QheTe6fJlZkn1DCAk75xyD1/5Cck27J62nEXOFjaIo+n4sCAD5zB4RhTHxwUgmrFePJyGnNcc4ZlXKbNerMzmuk3BEidHITnKArFrGGMVxsl6vLTXqu5quBchNnAiBhImDd4UVpcPJLsc+jJWY2FhLZVWlafJ6VhTGtnSJR97hC8fHxlEXvZKPpSv57gY/5fxUOL9qwgtSjqa2DEtgFXPQDQJM6iSftrl/qXGEhQEAQDrokyOY4GjiWtQF2vaL+XScEDFRiQAIhIRJ1iTe6LzdqtbMHDw8VRBnebcqNnRnJTI0paQ1udS8m/FQmAp4eaCeGcsv2o5ptTzuAlXWmcypASJut9uUixmIBgxZcXS5HwOYKHcwMsbi/267tfPXT+nsrH9SOEgUtE5J57/OcSecrT3ZHW+c82AMvgCjkg0GRWs/WqIWgetc2lafJgBpm51do87W5ywDJZYBXJn/zLAxmprVCnZmFg+cCh1FHobRM6GAIiJgZ1/KRtt7y/5aSpcv8SD7QHcfDqTv7Hd7V8xpZlbGc2abaBQs+e//Axmb7ZJmG54PAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image.\n",
+ "PIL.Image.fromarray(img_array)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly flip an image.\n",
+ "def random_flip_left_right(image):\n",
+ " return tf.image.random_flip_left_right(image)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display randomly flipped image.\n",
+ "PIL.Image.fromarray(random_flip_left_right(img_array).numpy())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image contrast.\n",
+ "def random_contrast(image, minval=0.6, maxval=1.4):\n",
+ " r = tf.random.uniform([], minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_contrast(image, contrast_factor=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different contrast.\n",
+ "PIL.Image.fromarray(random_contrast(img_array).numpy())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image brightness\n",
+ "def random_brightness(image, minval=0., maxval=.2):\n",
+ " r = tf.random.uniform([], minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_brightness(image, delta=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different brightness.\n",
+ "PIL.Image.fromarray(random_brightness(img_array).numpy())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image saturation\n",
+ "def random_saturation(image, minval=0.4, maxval=2.):\n",
+ " r = tf.random.uniform((), minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_saturation(image, saturation_factor=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different staturation.\n",
+ "PIL.Image.fromarray(random_saturation(img_array).numpy())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Randomly change an image hue.\n",
+ "def random_hue(image, minval=-0.04, maxval=0.08):\n",
+ " r = tf.random.uniform((), minval=minval, maxval=maxval)\n",
+ " image = tf.image.adjust_hue(image, delta=r)\n",
+ " return tf.cast(image, tf.uint8)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display image with different hue.\n",
+ "PIL.Image.fromarray(random_hue(img_array).numpy())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Distort an image by cropping it with a different aspect ratio.\n",
+ "def distorted_random_crop(image,\n",
+ " min_object_covered=0.1,\n",
+ " aspect_ratio_range=(3./4., 4./3.),\n",
+ " area_range=(0.06, 1.0),\n",
+ " max_attempts=100,\n",
+ " scope=None):\n",
+ "\n",
+ " cropbox = tf.constant([0.0, 0.0, 1.0, 1.0], dtype=tf.float32, shape=[1, 1, 4])\n",
+ " sample_distorted_bounding_box = tf.image.sample_distorted_bounding_box(\n",
+ " tf.shape(image),\n",
+ " bounding_boxes=cropbox,\n",
+ " min_object_covered=min_object_covered,\n",
+ " aspect_ratio_range=aspect_ratio_range,\n",
+ " area_range=area_range,\n",
+ " max_attempts=max_attempts,\n",
+ " use_image_if_no_bounding_boxes=True)\n",
+ " bbox_begin, bbox_size, distort_bbox = sample_distorted_bounding_box\n",
+ "\n",
+ " # Crop the image to the specified bounding box.\n",
+ " cropped_image = tf.slice(image, bbox_begin, bbox_size)\n",
+ " return cropped_image"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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ZyeKp02djE/zV3/0lIp48MxeH3WDQLHN5ZibXDU7cuz2cf7u8OBNttjpFpfqpdaoP//p51Ys+cn3vZ4wvNM6Nt8YxngZjTFJkx/O8bDZLREQUBEEYhidPntza2rp//34QBL1eb3p6+vLly8Jzvvc3P77x6c25qXwhi51WdzA0AT3bquhfZYyNWC83nrX7RGttSzTGZDIZ18lTsGuMCYLAdd1Op1ssli9cuOB5XrVY+Na3fqvd2v3gw/92EFCpUJ2qWp7teyprO2Vwuhi+HG6el84d9auW1ElDuuj4ZUYd4wWClDKOYymloxx/SMxsjPGH4YcffBz40W69CQBTb9SGg4AJc+V8JVfLu0WJg6yjC7nKgw4xDjwY27GeCcYc+OXGs+YYQghEjqJIh2HGpqRspVJqOPRdL9ftdqMonpqaarfbP/vZz8qlQibrbdS3Oth1VVZKadtKm8iWiC9Jg++XngO/8n6zMY4EKSVRbIzp9Xpe1jiWJYRwXZcZb9++u7Ly8A/++E+UUn/7V/9BkCmXCo2txiAc5CdPdfpmeW3HQK5ULIHtmOB5X8krii9rxMIUHMvkxvhCpN3/Y3wuxhhm7na7QRDYtp0Q8Pz8fBybTCZbqVT6/X4QhLlcwbKs9s7u1SunvvbOa50Brqx1NEaIg7jv/wbmeSx40ebzhRiL0GM8DYnGCwBhGMaxZVlZRBRShmH4ta99rVid+OCDD4bD4dmzZ4UQWutBszMzU7Y9a7cdnspUZdELHjZzljcuS/mMoAAeM/Efda/hFD8ni6MNlOY2Tt/80vzDR+xjmer2PppsQni0rTCt3jWmhgoefl1H9SejOFqFdUuGJoyRxJkz5+LebS8vYAfXHraVG//Od7/5o//TP7z30/eXlpaWFmcLNRdM8OZ3v/3//e9/WZtuzZ5YyMhcr96ruFYbXAWHnzdNNRZ0NP982jhIx6MSiiOu57TgUZZp9z8lL/qLTjT2A4/xNGitEdGyZC6XkVI2m02tdaGY8zzv/v371Wr1T/7kT86dO5fJZM6fP//Hf/zH7XY7n88pi8O463pYKRcAOYrGyQzPCmMReoynwWgGIm3iTCZjsvl+b9MYIyX2ewPN29vbdd833W53YWEqny9mM7npianqtGWkBMRCAUMlTBTaVvF5X8crizEBj/E0CGEb43e7zbJlZbO5/tCNsD8Y9KNIP7hxy7bc27dvO44zMz33wx/83ZXL54IgaA+aPeOXq+VBvyELRQbjWLbRX61grDTV79h9PGMCHuNpsC0v8DtDv1vf1bUMWZZt2w5DbFlWo9HY3Gx8+9vftm17bW0FaVgueKsPVvo6NAodRz1cWzl5cTHjOlvDoW0f0TYxxq+GsQ48xtNgWQ4iAnCr1RwMfGBl23Y+nwUQnU4viuK5uQUprbW1dWPYdTPbm2uz0zNff+vd2akT6ytbg77v2g7yV4v9wm/QHTUm4DGeBgQZxaGygFhbluPYWWZ2XOW52Uwm981v/tatm7fv3rl35cobvd7AttxmcyeXyVYr05YqdBqhjkAI4bpjQe9ZYUzAYzwNzBAEASI7jlUsFrPZrI5Ja+153r/6V/9qa2vr2rVrvV6v1WqdPn261WrNTE8i4tZ6fdAJ8rlqtTKlhDAUP+/reGXx5etCH/69SXF3pSr3xyZcHH7i9Pmn1SVOuy2HS4PiuErApJyWUsdJud7Up3q0eWrdQxDzs+e769eGnbrtRsNuHcAoO87nighy6dT0YDCIQn3m9LmTSwVp/ZPv/+iD5nBz8eLlkzMlv35tbuK1T5qmaKfVTz58lpTShzntvqUtH05LQz7i80q//2kFN4+63lL8+V+UhzzmwGM8DV4mK6XUcSgEhnHU6faVZWWzWdu219fXAaBYLNZqtZmZmUKhcPXqVcN6eqr229/+pm2JTMZdWjqxvbNeyHnP+zpeWTwr5eRFDh/9TeJlvw/9fj8KfDTx5EQVQ+g3eoSi1+ttbGz0B0673W73dgeDweuX3vR9fzgcKgszrpysZuv9ztDvZXJeMW/MVk+ldeRIwct+335jGFsXDkf6Ano+C+tZL+iniaY6HHR3vQwgcQwqky10g342m/34k1vT09OEked5J0+e/PDDDycnZL3RyHjWjc/e72pRKc08XH9YLM7r1Y6yq890/s8az+v+fyF+0xz4q5au+CrcB6MH7V0nRttzlJf3APrNTaVUo9FYXr3+x//kD5RSN27c2N1evXu3dPvu3fMnTvaaO151znGcO/fve3PFvOfERwvBfiXu228EYw58OF4WDnxc6zl1fCKgmMMgUujlc9K1OAillN1uN5PJKKXK5fJgMFhfX/dsMTk52R98urK8+tqFq6WF89fu3xn68ekFV1H8spuhn9f9/0KMjVhjPA3ZbFZJlKBNHLGQBqU2VKlUtNZCiD/8wz+8du3a+++/f/ny5Xq9LoRw7CxprpUr+Wyu0+4bVvl80URH5L9j/MoYc+AxnoZ+v6/DIJ/NVMrZ0tRUs9Nu9QZ5is+cOZMvLP3wxz+/eecGIk7V5i5durSxsRFE5htvvLG5ttnf6JbKE66X7/f8jOdFX7lYrN8QFD/hyErJtxQpjtrj6rBOdDRZQKQWUE7DcW1VR4vpTe+TfDh+Rbf8ARxeLI7oeDL4pAlzU2XHfXvz9rWpia1cf2swCBt+01Lu7GzBy1gnT821Wq219Qff/sbXT5+aqOWKn93UP7u7NnFu9ur0UtGysioihWkO2bSnnn7fjvYcpTyudZK2Ax31eR0P9uloLEKP8TQIIWIdKYmOY7W6nd1GC6WoVCpxHO/s7MaxUUqdPXt2YWHR98O333574cTS2traH/z+78zUandu3Vycmy7nbQ66z/s6Xlm8KCL0q+r3e17XdVzn7ff7rcbuXD4/PTXB8WAQamUkxPHubvP6zY04jq/fuDkYDH7rG7+Xy+Xi2HQD/823vhZwLCGen6n1mjsLs5XFauaz9nHN/9VcJ782nhUHflmKmI3xdHiZXNDv9Bq7oT/s9ofCztiZvDGm3x9ub+9YyvE8TylVrUz4fvDjH//k9v2VfD63tnI/HHbiKLh39+ZUpSDC9vO+jlcWYw78bPGyc2DLsmLfb7WbOccWrlOayHM/bO92C4VCt9PvDhuvv3b1xIkTg675xc/fc37r8p2VlYorXcX3Hy7PVa1CqXD77i2Kj2zCGnPgXxFjHXiMpyEIAqMDHfZsCfliOVuqkZDMDCw2NzcHg8H09Cwz3rx5c3t7O+PlHMfZ2FjzHLW4uLh49nw3hut3HpQmpp73dbyyeHFioY9Y9e8lCcg56n04tsbcx8X5EbMZVwVdgWyYw0iDkGfOnOn1+qVS5dS5C0KI69evG0O12qRl2dPTk3c/+ujMhfkr3/jGykN9b6Nx7u23tHKPb/6v5jr5tTHmwGM8DZ1OR6Eo5LPVajWbzQZhHAZxpVLJZrPvvPPO3NzcjRs3e73+7OysUqpQKDx8+HB6aqJcLi0vL7eHofLy9d4QrHE20rOC+lyh4KPm6x6teFcqh0nJa02DSPErpo3PKXWej5qve9S+wcfFAI6cV5xWdzqlTjIiHjwFIiaZqLEeTJ35xubdD4P6zhtn57r9u/X2+vXQ/V/8T5amZ07/13/x152Iun6c7Q8uXTwbBe1SoXLmzdc++vDe8sPW+StfP710OuOWMW6TdpRSUtkAoIkMIwCgUDKl/3N6K6XD14lI6fOMR6zvzZxWvzqtid8zTnJIqeO9/6heFCPWGC8mXMeWHHi2Ew6irfpOGIa5XM6yLESxub1VLBSGNJiYrC7UFrZWbi0tvT23dO6/+m//nda5E0unbNvOZR0Xw5LlJhsNM7+q1srnhTEBj/E0xP22kLpSKffiVrPdHgZB3rMAaX1j6+HqxoMHD6ycCHS8tbU1OTE9MTkthCjlc+WZCyBLa1u7lk3VxeJcQQghHqNhfpLnj/Hr4VXTgV9VP/NxXddRx9HDdne37jpWNl8IojiOYyIycbyx02h1OxK4Vd95/2c/3dnc8HLZX3706dbaw9OnluI4rLeb0hasfRdiKxpIKQ+e5RV4Ii8Ixhx4jKch58iVjc2cFXMcC2m5XhbAsImDMLpz597swonO6nYu656/cG5tbWNjvbdVLQXs7PZgsx1OTs+FoV5fX5+buCilZGZiYOZkFxmz32PBmAO/HHheHNjhyO+0u51WGJtSpVqbmmbmYOhni6XlB6vXPv3s/OlT/+yf/hM2dPvOPYOi3uw+WHlYrhQ4HgbDTrZUelhv7w6TRuHIzAfpdkzDXx6vGgGPcbwIh12FxpJKa+3YXj6fl1K6np3JFi3LiqJgbna6VMzfunVjMBjk8uXF0+fbve6g05ys5U8uzRdrE80Ab20P93XgBK/GrvoiYEzAYzwNFAW5XDaby/i+3+514zh2HWt2emZ9fV0o+Y/+8A+DYPjzn/+0Ui5PTk/lcjnlZvv94ebGwyuvXTx3/vRn129sNvvFmdNjcn1G+PJ1oZ8PyBy+9aTV701D2sJKX3CHV1dkOLxoDKZVYzyqP/m48q5TjpcoiCgxESceYGOMMSbK10SU32n4Fy+erxXtW9dvhFotzE/UPPMv/vSfarv045//Q7fL71xZLGbqw/ryrpMt1pbefOedRrtx98HqZHEezcAOuxcd99MehVbZlRpMSErG2rgiMuLw/OqjkjunxhEcteH14c8rjdExHrFYUIq/Om09fOHGN+bAYzzC5yXbXCY/Pz8fRUEQ9put+vbGOrBavr/+5ptvzs7P3b1zx3GcMAxty0IpcrlcxtKnT53Y2W19/NntnUbfdTKzMxP+cBdHjcgf30DSyq6P8SvjVbNCPy9RLfW8aYFnx9TJ4cjzScNhjllE1DHbCixFzdZmD3xlyXy+GPqGGMIwrNWqQd3/+jtvrqw8ODVXXlyaXTq39LNfrH5ya1t5NTdXGfjR3HS5kuVgyEISIh+k4VdArj76JaRF+P2az3e8BY4B8PhCPGiazmWySObkyQV/2KzvrJeLhWAYSeHW281mp722et+RyHFYLefbva6Ty5xZmgiDnutmzp69mslPNpvdyO9mHRaCcPRiFLx3hvHy+7IYc+DDcVw6Z2ro9wvJgeFzlByHQwSRy7oCWcexBIxirQB6/eGDBw8Q+cHyrXq9/ubrX5+ZqgyGwaDbq5QKhdq8D44fxJVKCchkHFsqECLhwLw3uNiTq19iPGsO/IXr4VUj4DG+PBJZOlki9x/cmK5MD7pDW7iVQk1rKmRzWnc367s3b9969+u/tb1zH0wUR+Hcwvzyw7uCBhvrQ6/krWxu9gOT96r36t3FxaLIVIRkRAKifSkaUUJK8sAYvyLGBPx88KzVvyNz7L0o5Sf48HC42xLCkuBZbjFfNEMYdNsAfU0mioIPPvjlldcuLy7MLy1dvHfvzsr69cnKdza26hPsUNTUw9AtVIzI3V/dnb58CpERGcUo4QdBAnNadtEYT8dYBx7jSXye5hFRWby9s+laNpPI58sz03ONRkMJ8rwsCGw26rEOf/f3vnPzxrVffvD+YOC72UqswbVlKSfjYWNqsnrh4us3bj8EABRPSoOvgBHruUP9ijfxqPf6yPmrR9Q5pUo5Pr0x7pHOm9qXNc1/yyn1olOnk1J/O+W8R9aZ9xJq93+YfNApfkuJQmsjEDKeEwchAlmu3NjYspvDpde/NmAatgZWT0ZB1y26OdGC0Aw6/jvf+Ga2lPvs1v0wVnm3NuzsuBLy2fyd2/dnJ5z/2b/4Zz5M/Dc//HRQXAKXyk5x0HGMii3biNBnsgIpj14H+3AwHT5Oaj5t6no7Wh3po9vh0sY/Wr76PsYi9KuK/YUyIuBkJaQ1IhcCpRTISdAyIzAzg6GJucX+MPAKmcUzixDjTj0uTs+fnp7rdJtnz56emZ7drK/V641yYbpayn/22ZqJom63ky9VVU7d3agbqYSlpitFAQyYaL8CQQICIgLi8ZU8+IpCvGJB/2MkeOKB8h5QwKEvqdBSQllgCbSUUEpYEgHN0rkrPT/SwbCcUVFnZ2ttpdntbnfD+YWpq1dfd91crxss31+LorhYLExMFgK/Nzc3d+HKG6HyfvrpvQfbzWKxWMwqxZFgnXAZRmCUQgg5VuC+NF6conbPBy/aPI/LXXTQQ8PMyVHMnFaKSAlkFBLRthBYKYECWUnM12adlQcm7oed3XjYdS1luZl+FF+5eqHfv7+83CqXpqYm+1pTrMPXXr/g2GpqutDpdbfbwz56GZK1SqmQUxZrGzQyMSJBktmAEkX8glmhX7r1MObAryYS+TR5CYHJS0ohkA99STRKkCWFsqRrS89Vtq2UwEEUTc/O5TLZ+tZm0O+UK8ViocxCImK/32+1Wrlc7uzZs6VSiZknJyevXr0yUS1+8vEHWutzly4RqsGgJ3ToCa2QJTLwKJIjOe/zvk8vPcYNvl9ZHHQIPfI6pAT9I7AQAgVJNChASTTGEMedZqNarvSotb3Siv3IVUUYstK9lQeb21s7YeQvP7jFjIVM2VaivtMqFEtL89ZctRBnnGzG6XQCIUmHPUeUXGGS/YNAAJBgHivAXx5fdSPWi7bRHF+EltnPTUhycZMjVarVNEREicBGG6ONYB0FoT+gbku6IiYmZVuurSxHCch59s52a21tI1eo3ltZbTRaJ+cvXDi31Ov2P7r2qfHlmYWJtU5r/f5NO7dULuQDf8OVpJClAAABQKM0BjYvmiPzuLwtx4UvXA9fdQJ+5TGKOd6jYfU5Z+wIhgUQMxIRGa2RoigKgkDosLFbDwYdlLalLEBJJkCM/WG0vr751tyJYim3U9/0g0GhUDIat3d273xyZ2qixkF/c607eaLcZNPYWZbfOqdwNAceGdV+szfiFYVSqImREICR8dfoT3s40vq7phtdjimGOb2g8JGQuvPh4fmimOofTqtXnOI3PmJeqIUZIs1khAApSCIQaTIxCZRCKiUty1JK7RfEcCBgRmJmRk1smJiRALSakEJTHESsAvJcUDrc6e9s1x98MDV/Ol9wG5GZny6t3rpna67OlH227m21M7fWzs3MzOatzMz8xmDjs/c/+Md/+qfl829EYSh6jO32IO9nvPw7X/v6//DjBxfesWG348FrsSsDObStzMA0Lcwefh9SkCqJqDT/aorbjFLytI+4raQ996NKTL+25PVIuHrK0WO8sBCShUQhQEiSUlgWOq70PMezhKvQkWAhSdZoItAhx4ExhojM49BaG2PiONZaJ5+TDwCgMmzZWN9uLs5dLObnJydO1Bvb0gosSzqOMxwOM1727Jnzw2Hw6afXBoNBp347m82tbvhDLWbn8hNVvnjx8uaWYpEjdFHYjIRgBLJksMxYAPyyUEIIpiQU9nnP5TjwzA3packkqZUfnnXMs0EkEAYFS4WWhUrZUgjU/p7kDMyGEjAxK2ZiZiImYko4MHNMMUKMRhsETUIix3EspXSquUw+0+343d1h4AQETrFSzhZkr9PK57ITE1PZfIFY+8MwGIYmiidy1Gx0W74ahMNLZ8tz55YGIFc2ee5kmSHLIiIDAFoBSA2SVPxiqcAvHL5wPSshBAMYerHccWP8iiDWxAbAMAMgC2HbjrKkyLAFe4+fiIwBY5iIQ5DMCEQAIICZgQgEIhvWRitgYgIQRKS1dhzHdmb6/fi1C+c09Rjl6vLDU2cuup7ud5rVavni5csUt3/50YeYL77++tV7H3+Yh3JdC1nIWWE2l8sh8XZz28cI1CxhRihAZgQWCMKwYCs+cuji0Vr5PC/8xjyySSw0IyK/cDfh18HLwoGPS1sxxjATAhOxMZwwWpDCs9W+csTMieRMRKQtZhRExjAQAxkh0DCDSSo2AyIKFImZKZPJCDz12Sc/qXpi6XTp3urGyvpqrXgRWZ5acjYanMnlm2tbaxv12bOVxfnFqL67fntw6ndPt9dWi2qq0e7fXV8unbpSm9WJHi6lTGqHCSHGbVZ+FXwxBx4d9CoQ71cRTAggmQEE6RhioaWUAmRSS29k9WVGRGOMEAIN7ruXEJPU39GRzCykMEk4NFBCwF5+cnL6YaO+OTVlbt+9UazOKivred4337lw9+Fwc3Mz7AdTswsC7WEvmJuapj4XsvZkxe43eg/X+tX51zuDYKomLQoVBpZEBGkAQQgClqmWp1Skc+AXawX/xtyTYv9840islxGIFqIl0AaWTFLHEMcUhSY2OnlFOj74/oTtah/MnFSlTIZN/rRte6uxNTs7LQzev7UGlC0UJpvd9vrGfceWlqV6/aEBmJiatV0vinTWy73+9VlLdmXkD1r+bp8nTr7+cKOtYttRAyl8W5IAYJYsZSxIy7Hi9mXxmA1hTMAvHRCUQCmEEmgDIJEwGo3hSMf7rzCO9l8Jucafwz4BH4SUkq2wUM6WS5Ot3fD1y98KIuz12sKJVlaX4zjO5/O25ZKBjJctFouIuHQ5f2KxtLu+nffKYGU2W+0gEKZnWyJQGAk0yIJBMgiDoNWYgL8sVKw1AEjExAFsBCX6EiImDakSr4PCozVZPy5/8tFxZKnsSEhrB8sp/yFS5kMpIh9SSp3klLxWQf3RB4FSjry+KCUhxIbDUPsxhRpjVhoQADlK5nPg6SAAQmS0sm2wrTCICbSLMfuNVv1BrTLLSq6HUY/4s1sfX3jrmzk1LVr3r9/ZHbTWG43GzZs3FxYWmDknzlQqld1VVVvsXTxZsLA8mRVh9N7M5RlVnPO2f3bmwlzgdNdp2c1dGuy2ihk5DB0l027o4R4mA9Gh3ys84npLC2hJQepzNyl+3ZRMq7TT/tq888mEfuQkoxwREFkgoIBxyPmLi6RpGHyupHNsWBsyhskAERED8N6zPQxCCE7CO/Zip40x3W7XcvM7vW6v06mUctL1es2dXtSeFINeT25vb9dqtQsXLrRaLUTMZDLVavXO8meBuDLso1KNrc0HudK8Vyitb9yeisJe37ecLCoZBaExMRFK2wJztAL3YzwBldgDYU+9ZgJgRBAICIwACAziqNvbGL8poFC4bxpBQYyGgIGD2JCByEBkjDFIQMSC2MiU2GMhhNF08E+tdaPRiAO/WJ30XBuNP1Eoa4wa7R1Vlp7nDQaDkydPZrPZer1+4cKFmZmZnZ0dHtaLPdNqBfmSDsJ284Hl9NwWdF3X3Wz1oFxCwCiKbJUSCPWF1/uCaXnPfT4iwf7+jYSCRfJCQjCjbzAFz3f2Lw6e4/3Z338TZSdRcf2I/dgEMWmDhhInMIFJ1S+SUj77zDwh4H6/X8l7p04uVqtVE/sFR9Cg2Vx7YIFutVr1ev2jjz7qdDoXL16cnZ39+7//+7/9279ttv1Wp/XZ9c/qO+1isTocNvv95vmzF3xwttoD35AxRgBlMx4iRtHh8vAYvzqeFKEFJkIU7lsy9o/8zU9ujC+EJoJ9DpyQHxEAECMRMoMhJCIAHIXapctS+ysBEZNoLcuyJNNnn322+XDZGm5XM7hWr/dbdcELSqkgCG7evDkxMXH16tX19fX333//1KlTg74aRq0bdz7wBxcvnj07PZOdWJqenT238qDRj0QOHZSGmYQAkxIt/3Sk7onPSc177oElj8gy4RhC4oHwHUpyEhCRXrC0uzES7Im9B7uiMAAQCAA52oJRAJuniwOJl3jf+GxMhIi1Wm1+YbazsluZnou3uo3des5W1dOLAFAqlSzLevPNN0+ePLm8vDwcDr/97W9LKaOBzhZcbaLl+w+Lbv7db19YunDqzupO1yh288rLKicIfY6CAJEs24ZxCOCXgzhoAkFEz1EZ1/Ic5drSVmhJSF5jPB3PS4Tep9snThqzMCSIEVAiohBKgpTp8zHG7DsOEvlZSjkzM3NveQUtZ3rhJCg1GAwcS83MzJRrE7u7u6VS6cqVK/1+/yc/+cnm5ubJkyfX1tY2th8oWcrnp0rVTHUi47kl1qrX29bSs7NlFpZApSxBOv71bs6Lpso99/k8xoEBwHEVIjKz1gwoIDaQtH0YaysvJlDy4ybopAIWExAioJCQ/BchPl4p63EQEaJI8nQRkYiEEJVK5d5nH06cn88VSq6Xl7GztrYWxsGVi3/Y7DTfeuut3d3dv/iLv2Bm3/dzuZzjOFtbdyxZLBfnF+btK2+c6bW5c2NVWlq5E8r1wigmIsdx0DAixHHsjAvbfTkoCWwLtpW0lJAI0w4BAKOINMRSaMsmYEQZ5UKtKYpNREAsCSSxNAQk5RNBPCMJ/JiycI5LRE+t83zU86bUH4bU/rQph6dt0mnBSWn+w5Fj8cB0EQBAHZjmSMpOqmHQ4QNlUYARsSXI5iDsZRyr55SdiZqY3N5euz/l7Zx7fe6DD83DrezGnfWrX7/x53/6r/7Lf/P/+t73/sbJKFtZu1u9z8y9P/tn3x34w+vX/92E17l04ndWt9qcmyhMfe3e/WuXz2WL/TAXB9N2dGO4YueXIAbmMP0OHa2ec2qFy5TrTfPDp9blPnz09HzdlF+kRsyn5p+nHL93WpVVZElhK7AtIYRQUiOiYXYUCgAhGViAAI5jKYWjbBaSWEYxDQMdmohkbv/0Y334ZUaSU6owWTJs4jiMo0CgU8pNbKxvWFZ88ezrk4Xg9md/A+TlPLdaLJ87c971WEqnWY96vcE//OyDd9752ne+ffmDn17/7NNrXT1487fOdps7u/Wt8+fnWbddT8mhcEWODQGzQgU89gN/KaiShxJZSbKEEYIUGhCoEA2BkGAZkeT8KyEZhRAShU0MvgCL2GfTetyUiHthAOnZOUfDy7IppHLUVKPpi3VdjEAja4hE1qxN7PcHfXHx3KW4t3X/+gOjuycXK5OVatC8Z2Fme21rd7NeLVSyZUdrsbR0Ulr2g7VbC5MTtUplemb+1s2tyZJbzjm3N7amq3kz1CGtFguu8nOuKISGFRqBthkTMAAcff3sf60KDiTZoQgERIAgUI48wwxGsBASEW0rQ0TGMHNMgEKx48qcctr9R7x3n3p/Exf2nHDU+aQdf9SrSj3+2AZiAAQQiCRAchwHfqfXDk/MV+vd2LZVYMz62vLsJNQmimTiB3fu29I2jnywvBzEeGKpPDkzNzm3WMrndEzSzp06dzFXYMEBxGZpaTYeanC65ZK268yRMhSgDDUZ6R5NtTmu9fC8xjn21axsJYxJ3AfEApnZMDEJAtBEzMjAQqCQkogNETMjC4mACpS0oP/oMg4G4o058Oj7tB+8aNclmBGAGVkJjo2O/H6nH3VuB0PudTKuFCjW1q53Gjs2twyV7t5bsZxMrpS5+/BO34+6/d6c41y+dOZn3/tv+ua1O8t+szHIDwbAXWkvhtFwd6ftFTvhcCBFEUhLKT3X1ZE0L5gk8rzw63PgiJhBEgJIiYi+DoUQwEjAsUnsH0YghKCBGBEtqaQQQGwYKNaIFow58NGPP+oGd1wcOE10JyQACSAQEBkpjsJBpzcMVezXvKwUrhC2HwYbW8su9fPvzu4Oop9/8PE3f+vbkzPT93/2i2JpZnqi0O/s3L59Z+LsySFmsrWSzRvra7t2aSJoCxROEFqrq33p2SxDy3aU5RCZl52Anz8H9jUYAEAJoECgFccIkhEMo44pJsMgEE1XxwLBlsqxhSWFACBD9HgLvJeFW36VkWrt3Ht0EhEZ2OjYHwL3TswsecIKg165NF0oTMbD+2G771kF4YWr2zunms1SpXz1jcuTtdk4bG2s3Gbh2rlqOTuNWvJw2GjfCborJTn31tfe1mu4suxX3/SEHYQg434Ym9h1j1aV8kUToZ87VEQYMzAAAYHArLEQ0QAbTZHmSAMAMcKQARlCaUITO5ayBSLIz4dnPWLCY1oGgBcv9C8VSAQgGBN3ExFpE3PkA9s7W20Z6sX5OTvj9Nq6EUaDHm03WvNLp1fWHjqZ8F/883/24N7G/+f//X8vFMB0EJUrZWHtwUbFMScWT6ri2cWvvW5J2ByK7Y1G9S3pZIxAj0O0RWjG8QVfDmrChUiLWJOOSRPEGSupV2gQDAoWTARMTJhlNhQZRkKthSVsCQo56zraGK0pJkMEgIIRESXS8VgX0wggre50Go7qB04fP61u8+HjH9XfeFSk8ZHU+YsUkZ6znmVZltXvdsoFd+1+x8fs0snT8zPVe7pP9tyGnNi5/RBjSSokpSvZYOP+L6ampt55/Wvt7fX11Q3Pm0CLrXg5NwwCajTb/mo7OJmjb13OWdnBL+84103p7OVaJmyajhy4sWOJ1jAqSedY7kMqUq73qDg2zp/ir0ZOqaOeMs5+ZqgCkTh8EQQgsjFJzVHYy2QQAASAoLUAEmBspVxHZWypJEjARnwgguBVEUu+miCiKIqSMCwiKhaLmUymUd+dmZzqhf78zIwHor9Dk6XzJLDb7iydPPOt3/odL6+u331AmLny+pvN9trE4iQ5yhHqzJn5zWUfwpDIZc4J3c+5tpRIIGwngyhZR1klXzhJ5GWDMihICEAAxWg4phhYMDMxshAMBCARwGGDiEpKz5KuI22lFAIgJWkrMBKbf3NP41lvFl/BzSjJRpRCEFEcx7VaLZvN3Pnww9/6zruTtWIc9NYertgQzdWq0yemtlfuLS2eXTh16cHmyvJmf2ZiYmZu0fOgE2zbOVsiDHU0WSvmyI0oX6+DCdvlwqRl6YjYcjxhBIdRxnV0/HLc5+e13r7QriRiEhFhDBAzx0kaGjCjAIEohJBKWkooK2OrjK08S9lKSkBjjB+Fw0FwMOXwYERuWpD3ceEY790YsFeVkoiS+q9xHBcKBdu2EWW/0y45oruzGYb+zPxCd+gHUfj7v/d7c/NL281Bs0/FyRPKLYShmahWVx6sCxPJsDNsPqxV8uXp2fWeXulSOOwUC55rKxOHUkpbKskkzVcuFenYCUH5McWGDSXtJBES2ZrFnj93/0+dVCEl4EgTM2sTU6yJk5Iu+1T1G6KtZ03DX7U9QgiRJCQppQSaKIqk9AB44fTpOBxur93vt3uxP6zvNlub29H52vk3r/zkZ/fXlpeNJTzPC4bB9nYAVTFfncroOI77lhkYKrdj3h7oKFuwomHFlnbMwoRSRBI8EiLSBtNqYr1geGHXg/IjNkyagAho1GRlT+9N6r2DAGAyo8RgyVIIZAZthOG9jFMY0fvYkfSSIiFgy7KYGQUmpSodW00tnggad+7e+ixbmABDt27cKUjfFXasNXA8U6vIjGp3+uh5k+W8EoOvv3n15MwkQ/SweW959X51ainjVTrdpm3ZxFpxULA8D0JpQpROGPM4UzVB2gbxhSK0Cg0RIxGZxG6lYUS9kFCyADAAAinJMQLBKAQSCENgCPf9IYgISYHDA0EdLw6O6qM+6vxfdh94IkIrpaLAtx1JREEQFL0iZL1gJ+z1G/lc4fTSaUKrs/7hoNH+5Yfva+MXLdPYXW83mvnsrG9TbDoTp6ZylUwhU8zc2zC7bUdwxoTt7sCrVQa+n6P+dKHQ9Glz6KOVYekAPCUh6QXCca3ntHFSA7HS/yP5VxGjAWDExBhFxhygXgYwzAhAtrKSVpSaAQkNgzGgCWxMBOjHTvmSL+avInCvgUMURWQ5zKy1Vkotrz+kTrtSKW5urNul3Nfe+gY17lSy+dW1uxnPDv32/RsfRtoMMsHDhyvCjgtl3O3mLLtUqZVPccEEcW/n4Xx+Msrnu0HEGJSzVjZmjiO0smBnQL8cBPzCQoXxvgMKEdDsp/jv0yQCAISJnDz60gCCVCBBkkHYC4RHAECQAIBs0uqnpfjl0uoqHxXPeqc86vFH7RObdvxROfxR/cxhJPI5jyAkiS7rGdPVO62O5Ufd/NcmT65/eOtUbWJLmt2gudnZKOQX7v1ixZa1hfnTljuzufrA6u6eWJz6H//Lf/zXf/vT95Vz9crM8pput4dFV9UHO46rwug8r9yMczvbvTLbWS9f3m4PporcT/EjcYpf/bjwvCTENH8vI+EBA/D+u0irH44jlTYRkg++xvgqQikVx/FgMEi6rvi+3+/3fd+vVOW9tTu5yYnZpUXQ/sqta6VMrj/Q01OLP/vphxsbm5cuXZiZmapUKn/2p//8+rV73W63UqloraNQZ3J5aVkmjhFg0NwolAvgVT64tszGuEiVUiHAZ1uF/yVCumh9OMQe1JOcL2WjT+cAqSc+fJy0UcZF8543mFkIkc9nMR72+/1w2M9rjdze6tbdah68fKUYXL9+08lbAp12MwS22u12pWafOXvq3Jk3f/mLTwwHUeAP+11DMDE1dfPOim2GQsDWxsbJt0/PV2Z62/bK6rW5ywL8NqlaB6IsPONIrBcM6Zz/sYI2+4c9pcNJcoz6nOz6chDMcYm4zxovyzy11pYEKaXneUGvqbUulUpzc3NrayvZfGWt3S/2w3Iln7PCzbX72eLvdzvh6VMXcrlct9f+7nd//2//+hcPHjzUZlCqGK11vV6PyNvY3FG6t7gwf27xdPXEhGF1o63BmbGV9MA0Iu3UcthNCbl9Zd2ET6Ovg9Q7EqFTVKGkiBUiCobHXsc1zTTWf1zHj3G8EEIQURiGYRh2Oh3XdWdnZ0ulUtYpVcvzllV0ssV6q12erIAIBQ4bjcb29rbjOL/7u7/73nvvaa3n5+fz+fzO1lYhl220O0M/tjPZ+s7ug5X7F8+emSqV/Giw3eyXJ5favXYmY5sQ+YgNil4BpK3z/dX+BAdOO5L2IAzwwVfaiTkFv5nL/jyOa4N41hvHcc3zuOaTBtu2kxgsIUQURfl83nGcW7duzc2eUqguLJ2YmZ6787Dh1RZml04Hg67t8ORU+Q/+4Pc/+fiz3d0GsZ6crJbKWVsyABVLpVPnzueLJTebQTKtZr3Xp8Gwa9nSzWa229tWNs/oRoP+s76uNBx1PRwXvnBW8Dj1Pv14ZlZP1r0b87wXEs+ahpN67p7nWZYVhmGhUMhmvfdv3zm5eAmj7sz0RK/VRm8yN33FiUNX5spV9923f+enP/1pq7MTBnFA3aCUmz9R9sQpgZjJF7zKhB/qy5dfn58sKIn3V1vtYX1uchJZawXkZLLZipID1F/g5/yK4PNEi3v9FZ5+vGCEg68xvpoIwzBRq3zf73a7mUxmfn6+XC7XdzcED8lv3vj0o/lTr5WmzxsqVQuz/8l/+i9/8g8/WF1dUco2hq9fv/5g5U4mK40xnuf5vr+xsaGNqdZqcRRtb2zGxhXAp09MK8l23msPQh2jGLdlSME+faZJvo+s0OIJU35KX9b0wsRfMINfcRxKeZZpebZpSDvvU4wBh35/1P7GR81PPuo8zTOO+8eMVLHlY6Cou5jhXK72i4dbp8+86ep1y/ZubG1geeHsuXP91nqvecPLVWOcLJVcpdRg0KtVy5MTJQHW9ppeOnUxX5vsbK7VpPPdNxf9oby7vjUxbXEBby/r/ER/sijMFtrVRjc7XLOylThtRmmc5/Dnkt4CN8XvmuZf5bT1dvg4qesKo2Q0RCkBkRERkYWGEB4XlRM9NDIshVAISrAUoICRDCAZOz8qWHcAAEB78xw7fscAACDSgT+M49hxHCFEEAylxGq1GkWRJTGfsVwO/OZ6v7kVhcEgjDY214qlHCJcunShkC9961vfvnz5NTI4PzMzVS3lPbdWLU+US0yRrSDrqEGvMVmpCBDhoF8syHJRsg5tOFrX+JcIjFIIJaQlpUQUkJSLJCKEpO1n8r7/UlIKAUJCUhCWATgpekO03zjhUKvTi9JzMJ1jvxzuhGetoz7r8ZMOBkk1rNAf2paxLCUAG7tNcsO43+jHTdKWPxxGod/z47t37wHodqc5vOlvbtSLxcrC/Mlez8+6jmtZkk3es7oyDAZN1yIJYae+NrtwRrE1HHROVAuOF5ggclwPMaWmzhElu/S7kzZQ2tfHsw4RFSMKSGoEMjITMABJ+agI5N6RAAAKAUVydaP/YhCEI8nu89T7SAc+0rS+PH4969wYzxoSOZfxXFsN+v1GvR6FPgNtb216GTcK/HDYduIBdDepu+MqFE5mfeOhlPLcuTPNZtNxnHarW6tNfv2dd+ubG4369qDfDvqd7e2H3dZu1lOdTj2jtA2wvba1vbkRBE3bjjwplH7pBcCnWZyJiYjJIBMiWAptRyolpEQpUQhIXsmfUpAATgInmVkza+b4gOT8ROui/ZOMOfCYAwMAGBMp5SghAxM3GnVm1xYTURAUFPajyJKqVCj0B4Neo27bQax5Y30rjvjcuQu+78cRl8s1x5Fexr5/d3N+cVpr3e1219cfdrvt6lRhe23Hqsx12rtbW7seDuq7zfJ8VCpW+6Hho9ZDfkk4sEXAzMAGkSWCLYVSSkkREzIDMxDtEyQAAI/YMhMRgdjr98yw5yp/onLz/n17UQh4jOcL0ibQATmUcWwdh+2mXy2X8467+3Az6LWnq9nqxHS3t9Ft71YqDqEQ6HXaw53txvT07Orq6unTS83W9v3lOyoKwpgsOxMYE4Rx1x/0/WEYB1v37s2fyc8tTBfdSr35ILvRsXMzisP4FU1GckViJkv6FqFlgW2BlJwQcNJ5OwmlShAbaRJOi0ijvHwAkLCX/PCEi3i/eeBvmoCPzkmOh/McV1ZQGo6LQz6v2BglBcfaREYyW1LlMjKb86hvOBwys5UtOMUai6ZlOcVi0fOcVnNoWcq2GufOnTl79iyRvn371vbO5pm5+ZgwNBzEbHmZ3XYHVh7k8o7RODFVmZw/AeHgkwcPcrvkFhVhGyBzpHm+aBw4bT4ZCUIKhVIqVhKUICFIIGiR5N4TIRFRQr1CiABtzaiNYCIGBkBKkosogj2B+eCHfafHS6+EjHEscBzHdV0i8v2hlGJqaqpcKHa7XUsBM/sRtwdRazAMIk1EvXaHyYoj2Nra3t3dvXr19WvXP7l95zNEM/Djvh91BkM/DJXrttrd5dVV5TlvvPm1E0uLGkyz1et0wLIrrpftB43nfd3PCq4lskrkXKvgOnlXerZwBCmIHQmOBFuwhWQL3n8pS9hSKTmCQCWEwsd9VIcq2uoJh6dJiS0XMiVvk464BaSnIx3+dQpHSqu3nIZ0BpnGmV+sfNRjkxRS8lEzsb8b2+VSbdB84OWdwtR8LjdRmQ5F9fXejY8uXX6XSyfrt1u5hdj1AtuyBsNWEA2/+wffOXV26Qc/+ZGTrUwtXAWWOmfPlnObhtY2B+dOn3v7t+GHf/+LT/7+43/5r/Jn3fm7q+onK9o/+4bMdiaDDTc8I7xUR3DK9R5utUZpH7wh+7dFEB9kX/vHaKBDDagS5UGj0SNjr5AwYneMQMiQeIaHXBDIEklCKCH2bM55tuvIqmgCCGDBDMxIRhARM8QQCEQbAS15cFbK9IxAg6ANxKhiYwwDMYK3Pz0+uFY1SWZmemGMWGM8X7jZTE67QsDu7m6lUgniaO3mzclaqdkeJOUp76w+OHli0QtkTTT9/kAb/uZvfWfhxLnt7dbWdndiYnp6Lnfjxs3tzQ0lpNZ6enre6CjruYY0Cmmr6c1OFFvkyUG1crrbq5tJR9qd4xKh2TyuK8KIMk0SssGAB7qFMAMj76ugj4+jEVHgvig9OsZg0k2IAUCMKsAJBMhCoARKoS1hLCTXYk8ZG0EqFwCQk1qfgAASJDMLhAPFH5NmgIyIIKRijA0CAhskBDaIhJwSQGIJAQBGfk4HPi7OcGQcTVV58br7veTodHvGkSjkoNd949z53c5gdf3GqYWZNkCukIvjcH1988z5C9FW3WJpjH7tjaunTp8ndIVgywrDWM3OT525gHevtyrVck/LITjZjHKVuHj+3HxWE0w+7CFznJX9xVppZ213CNJyurE+HgImHlWoANw/jBFRoDwopIw+IzLuxUs8kcRnIiWVUhIAtNZEBAyIgoiRR/5YSvLpUaIQBRhYUtkKLSUciUqyrUBJQGElYyKxEEwIKJmZbeT9SzjwARBtIpYGUTMAE+8z+pSIQInMjPzScuBn7VZ5Xlkdz9wdlXJdjJZjWUihRM4XSmuNLgD4wy6QjqJoe2PTkhj4/ubDh7Lgn1h499LrenOzHmtZKU8Jkdupt/KldnWiUnj9slIq0ub9j9//8z/6jiv5zTeu2IN6a+hH2UKv3cgpUbDDhm3aw25WZTvmaNebFrq4n5g4usDkT2apJOwFQhw8Xh0IYzwoS+ddaVkqqc4ZhiaKDBEhI6DNwAzMAhAkSBYChUAFoAQrJS0LpRISkZFjIiKByFKgQikEK0FIBgHVY9PfJ2ZmRgOY5PkaBAuBkQwypVipkAwjAP3KHPiolTSOjDEHfq5QTgYAQr8nBba63Yjg3LkLoKNms5mlIZOcWXxte3trc2t9IVM8ffLUR/ea66vr+VxNACuJJ+bnPdvpd3sXT8zFQXj95u3rt279+Xe/OTddW+ua5ZXVwrRfXvjm7u72fKEYhPVSMdLDppepdI44z7T1phQe1H4f6cAcH8wBOGD9YWYGBGZGQAQUKBCxZJPjgG0jM0SWiCJBBIgYo2BmbUgTazLERGCAIASIgaOIFAvbJOMCs1AYSIGWFI4iR6ItWCqUiJ+3QYw2EdACQDIikwLQQBIQAUyKzSI5O3Bq6sKLjpedAx/VrXXUcY4KP4yEMSL08xmv2xt4mUIp57YefMqkbUsqhEqxtLK+QXFkWzIIhqB1KedNTpejSOsYa5N5Y/SgP7DQrlbL0nbOnj3LFF84vfjZ3/6i1enKipwwPQ4CrFW6w0HFHWSE6LA4+nNMu2+j0Ib9gKXkzkgKD1KvSIRfRIHEwKMUFAaBQoBAwKIV2wptBVJKdiSRA6OHIgxRZEwQc6RNoE0UGyIIWLKh0BBqKZARk+hlzFpGCXQVIaNEtASgAATiA+tqtNck/mJjgBgYFKJBtAUiMwkEPjyJRQpkZjIvrQg9RoIj2yzS/JmW7ShpOXbg2kEY25Vqs7nbrG/PTk3CsEVE3W6nUix1HMdxrNUH9+vrD00ctOoPCLjfa9e371tOJp8vKqRSqXTixKLTHLhKTlaKjqVqkxO2ZQWt5Zw7NN50YFS1t332ZO7j3hCgcBy3YWTESuxPCYkmd8ZFsxf2NCoEl9QtkHspPgkVCSGklIhYsntKsSXJsqxkHABABEGaATWLmDDU0o8pik1M1DJOHJs40sZoAARCQAGMsRYgUQvQoz6BgESAZNiGR2LCgf2XNIIQzAKEJQWikBIMo+DDrfRCWIaZPm/EGuOrCSEUABuKB4NezKLgZesPlzOuV6vlNm5v9v3ecHPzxKlTG46T8zLtdru5U69MFpuNjSAeNtudtYc7s7OnyvlCLuN2u11N9ODBA3x9no3O5XKDlud5+WFruZjPsg0EpahjTlQKn/a6ANPHMn9jYhzVapRCgBAjMs7bzr4CnFCpSrytrA+6i5L/EkIUUAqBUrBCkgKFwITSBfgoFAiLhRWBiAkjDZqMiiw/jAIfo5iZBaMCRgKMtSAYZeoyG0469iLvi8RP5CcgkABgHBWaZEQBUjICH+7XlUoxs/68Dpzm7021hqXV9T2yfzJl/BQGI48rQitlmKPm96YjxQiRmsB6PP7t1OFTfpB1mQLtNzoPb342O1+uPwxmJkrDyProH/5dbW6yXC2eOVMJB73GZrP2j7+jFe9sr7GCYvXktQ8+8n207PLi/PRrp+fe+4cfgzI07GfAuvHQrDRv2MHDghjGG2trulo8fzXe2FGNn9xtP1x589J8wbtXD0gIQptRAoBEVqgls8THFjrs581GUgIKIaSApD9mcqVCkhLoWODalLONZyvHYilQUngwhmmfM4c6PpgekFCvECKvJCIKgYiUPKPkMEt4CSUzB5LIZWbBjKyFVXBIS22MOWgSU/BI396TCBQAKiP2LirhwKNrjPaqcwoAgaSQkk7UGY4PnT/RABGNeGl14DGOF1EUKRCImFSHdnPlXq/XrNeVUkaz7wfAYnV1NYnWAsBWP7C6Q2F1MhLDODx5cumtd775g7/53vmlEoJstRpnzpze3d2aUplmq533KkNFVk+GnU1LedliuTZZfLC6ka1UHTUdMxmIiVkIoQQpZMm8H140MvHA6N1VIAUKwRKFRE6csQBkC0ciWBIcBY4C12JLgkSWgvd8uYm3BkbuJSkO8pgkMQiRJTIiIJBAMdpM8UludFBt8RQSIQlpDOwbyYQQCOZQwtPwZHpg8k4pjRCSaMv9cWBvBxZSMjLAWAdOwfEZyZ5TltURj5dSurbT1zoIgji2c0oFfhAEweTERIwYRhhF1GjUZ2YnpJRRFLX8aPv6jX/6J0vzsxOXLpw+sXjy/spqLG1/QFFMnW7rzXdO/M33flibOr272+5JLM2VB2trk4XWN99+S0q59fD+e+//4s/+8XcLgkPNodEMpKSylFDAgrX1qOvZY0FUrmQhQAALaRQKkaS+M9jKEghKgIUkhbHQCCQUrMS+m3f/hQCgxH5fPoAReQAACxYHSe4R6SIhjtTW5JX4m3MSiZBZJBLbPr9VBySvg2vJT4K5HmO/wMyQIvHpWBwcZH8oBEFIjKCekTn36MM+H79r2mmfV1LB88JwOLQzqtlsAkChUHBdd6fRIaIwjNHOZDOl7a3dVquVFXGztRv5xsqUGEQUht/6+tuWZf27//g3W81urlTrDeJhEPpBEIbB9u7GJTrJaF2/fvdS5c2luanXzi1kZdjVXii8QmXCRlPyRBhrPzYMyrbBtlgBsAFlPZY9t/8hq8JE2FUIAjXulcCxkQFAokFgiUYgCWQAsmw8lAPbApM43b0HzcwEAMY8xjBh5G6CvZI6vDfIiLZzwhzcCBKzFyJIIQ93a6mE8+MeDY/kbpkSwhw8WoePubIZQCIy0pgDH46vGgd2HCebzTLz6dOnL148pbOleBiVOGptbEzX5ueXLt+8dc+yZa9dD0PfU9ba+rojQCo7iKL7Dx7sNlqTU3NWJpcvWFGkY+LVtYeMchj4tYnJT355X9mubcJyVikwjiU367sn50+Eka4VwVfgK2QA2wbbQgUgCGnEgHmfNyIiAOeUQSSJQghQAgUyACAxcoCc+HNZAqMwAhCQbSXhc3IsIlr4pDEpIQ/NB6h3RDTMe86cJ9ggAFjikZvn4DYh9wj/CWkZhdgjfjzIh9OW236uwZ7aPBqHDDEyjPOBx0hgjOn1eltbW7Oe1Wq1+l1fSikdZ6I2Wa1O5bLlOKbJyQnOw8REze+2FOLXv/7O5atX3/vJ3/u+/8bbb6Ow641WvpCJtM5kC4z2yVPnw5gnJmrFSnGyWlq7fWNnZ+dMbUHZXtjvZE9Nd6OwYhtHgKcEI1oWKMEKWALHuM+BH6tE4SIKCQpBCBBIAhCQhBjFMCfF44RExJEk7EgBh6XjiUcUk9iE9opOgYQDJJq4mhDRPJZP/2gceUDXPTi+FHhAQoZ9ohUITxB28qdJ2XI14d7B8GiOAJoIAUnwkyL0cYmOL7sI/exP8GJxYNd1TWiklDMzMw/Xb3fAunjmQrez6zgOgrWz09QxRfHw5OxEqVRq7WxevXjmG+++c2d5te2bcnmqMwgunz/R3NmMjPCylYnaTLU8a6lSENZL5cLC0gyG/aWlJSdbXF/fbPRXzi/NnDp1avnerWmMlQJHSYMghLGQFRiBYD+KMXxsQVoSETHhwBJBACUNLy1nRLEsktyAhJBIaYGIwKP0hoRBAgBhfJDTJo0p9k+2FxPCDAx7MVvJfyQ/2vMQg8DHkooe3f89FRoPxGwCABDui+Wj9KKkM3NK9putkv2FmYHwEQ2jlIjIYsyBxwAAgCiKUHO5XD59euHu/U97UeC67oNms+xox3ZDY1erE598evPCyXOlcqFWm/yjPzzxH//2ezFY+fLE2tZup7FdzmfyWTeK/VK5MAyVVF4c+ShUPp+dm58Kes2J6cVcoexmStv1m1PzC0RkF6qStRBSALNgACOBJZJCEHIUwwyPe5IQ7X3qlYAoBDIBgmtbjICIhJBQbyIiozncGgwC9zkpAABz4vLFA8akgxT4KMLr8XEOBHs8TqgCAQD3VOX9+Bk0e6M9bsgSKVuuxESCSLI1MPEPcpLeKJiF+FWNWGmHHZuxB59Pje90/pjmlz58npxyPKfEsqbOJ9V/e7T7g6l9mA8/gWXX4uYHGafdz17ZjCavnp679cufBmbYxdJnG5vZ0nRmatF52J4+8c5Hn338n/1P/+B/97/9PzfrG5cvX97aWu51OrZSNz778N133wW/PTsx5fcbEMioF1p2b762sJGR85d+f2PlXn177a1vLH123+350ULUneMWtgaFuXM9kY8AhAl10BW2iqQdxiOrDiImxl2AhA4MMDEDghQCUIISFiKAiBOpWO3roYko68E+G2dm2vsgwIakNtVjDwilfESHzCxlIgljUsLqkSi+F0BgeJSl+MSDPhgBeZB2krLW+LgCDIAQH57nbAsCAEZmcVCXBuJACMli7EYaAwAAkEmbCJFXlu/Pzc0oAa5tdXthrTS/trWZzxUlD10V1zdWZ6sZ7ccLCwunTp2K41gpNTMzE0XR9PT0+vr6n/zeu1PTkzdur+fzQlo0GPayucz8/Ey73fJ9P1P2dhstrbWXzbU63aDRnDs5E+sgRBuUDQCIEtgyeuSmQUTm0TuMKGFEGXtGHSCihMaTI2HUan7vzwPGpGO5UYdIxXvfH/xAj3u/DtLw5+fziM9/DsnO9YTCzMxMo9DRL+tG+pI/f4GRFuJ0NJ322CSUZwwEGva6TKa+s7W0eLazegdIK+CZ6sTq8h2OmmEnyKjhyr3PTtbO3bt9PwzDer1erVYty8pms1JKx3FmZmYWl+Zs2261GlK1/KAdBEPXdRdOzFz78fVg0MlnMzs7O5lsfmpmNu7Wles5jgy0H5BQosgG0EhSdhgbOXLiPGYfAgYQBh4t6BELRQSSjIgM/IiCkz8JkkfzeJID/hrP5fNEiPhI4t6PqUr+1KMDEs/wI4mAST8xyP5Qh540qQTyBPUCAGuNKPjFKSv7quKoG1zq0ce0UabNRyEMez0IfC+fzzr2Zr837PcEQmd7J+w0ojx2fD8r3V5jt5h/88G9hxMTE77vZ7NZ3/d3d3fr9Xo+n3/ttdcazR3Dend3tzu4tr29PT2R84eBZQsv40BstVqtjs8iP73baOlBD4NQ2qApDuOIZKQMoAFp0GgprS9WPZiZiAUmwqU4yIGZR8TzRDrePoGJAwT8qzyjz1Pv3odHHPLgB6JHUVlwQHN+gvF+4RyklAdH3h9fCAGA8Ktz4LQda8yBn378y8KBBRvSQTDoLEyfaDXrriWGOhz025trywXPKjqiu9N0s0UTDCyp7m1u3lzeXlhY6PV6vV7P9/18Pv/d734XEa9f/6xWOzEY+Bs7d4bD4fkz76w93LFtvbn2kHU8HA4LUzhdWbi3sgZhj/qtM+drpCA2xkTaZhZaK4sBhcTDI5CEEIm/F5J7y5xw4Njsl6c5aJxiAU/aDkZD7bHOfUvVr76SH3+mI/a+H5Wx7z0a7SXEAliIva3lcSPZoZ8/P+H9M+5L78lWxWM/8LPG8+LAR95wSYOOB71OFPi9bq+Wy/iOvbMz8AEnp4rVYqHfLnRbA62JgPvhsNlsnjp1KpfLffLJJ4j4ne98R0r5/vvvTxYMmWIUstaB6ypLZW7dfDA9nSFjLIHD4dDf3s5Nna63+3lLmJi2t1redEUIWxtWUgCCAWO5lmL/CQVy9C6EYEAcicqw38qAUqzNe7rigaGS+AeCxxnjkTjZI4ranwUDEz+iZATg0W7CkOwyCADW55JVnn7eJ3j7/p84qhzwzPzAY7xcIBP3e91Bp9vvdYBcf+DbSk5WK9Gg0+mybYlivry52vKyeS+fyxZzrVbrvffe+8Y3vpHP513XlVL+9Kc/3d7ePvG101HI3U4wOT+RyWR63XB95WGtdtb3B2jbSqnlh+u1k4PZuYWFyQpGg3v3PzlbOSVcFwgty0KMEclxpNSPtqy9oEYAABBCMADQiIBxZAQmA4eGTPLIepyM8GixGzb4OPbO9cVkfJCGE+fT5//34Gc6sIlIpP2NJtk19t8PPVfSlfLzRqyk4iy/vBU5xjheIJl2uxlGvomjXL60c+deVkSLSyd2Hi43W3XS5sTcmeEgKhSLIFAj53K53d3dzc3NP/zDP4zj+Ac/+MHOzk6lUsnnyv2ebLd6l95YKhaLD++2m42epbz79++fXlw8derUgLemp6cXz5wL++2d3cb29u5SBDJrIbC0hACFioSN8sCiP0hdhPIROR9Y9Dopagf46IUIe37dg2x2XwplfkxN3T/Fr3K7DtCbQEx8SKOY6uTbR4IyP1amy5YHuPeBeK+0E+03N4MDZDz6DQPA55IZ0oqGHRUvPSfHNCNKirk/pfzn8QVcHdtzOSg37ie1x92Vra2d03Mnz5w689ndtYbKrbX9kj9ga+obv/3O9//dv13fHcycmoGo2+oGD7tFV8wMu/eYNs+fzfzlv//JvbsrtYnprUan02gaic3+/XsPS985e/Hj7//ctrINM2FXSm//+f/85z//5ORJ5/XZKIxu5yZP3l+zFt/901gPi7CjVMEE4CFq348s5YILAPt9dZPUXBQsdfSIngUCiMTjHcURo2BiSiKjmSmJcNLWQYLB/WwhGe7fByFg//usoGTkfRkVGJiZ9roKIgMy457HXh/w3yY7R0JBKooBgBFAIDAQjspfDiiGUcKTHJ0UJABYFBCwJiBgAkGIIAUigkHmJF/C8EjsTxzT2eSkYw781cJBFpT8uW8mdRzn9OkzU5MzDzZ2bXsqf2Jm5fanr79+0RKxdHNufmLhzPm85VcqlUoh+9PVO29947e/+e1v/l//y/+uXJm9eOWNdtf3lGNZdqwj28oszJ+8d3flzJlzOa9UKJTOnTmfyxXyuVy4u9Ft94qz5eGgP2jsnDxxxsZAAduWJJ2wVzRsiAEFMyU0zIiY/Cl5398L+wakhB5Ge+UjM3MSY8z7Cb2J1J1QpGDFe+3F9ip4ICLGoA8K1Qc4ngEWB5IJRjOgVGOnhJGgjwBAMIr8YLQBgRiBxN5gBACKBAtkECMCBjaaGdAGtXctCpD2tjPUGmAsQn8F8QT17nOe5bt35+cWhO188tmnnuN6Hlqgi+WKJaVlq8LkQs/YMj9x/kx1bnbaev+D05dPX7r6zQ8+ra/tCJmzZk6eKAUUBgQcC7QvXnx9ZvrE/dWN6cmFfLa0vr557tyFzm5TMWYyeWbJBnrtxlypMFHJR+1dBVrZKgRhMQppEYNhjYSAlJiBEBgJAVkckBnxQLCEEIIRyCTuYtozCDPyKH0PAICTmERGxAjUvvSByEKwlCAECn7Ur2j/nsHIzmwEABMaYmZK6MqklHQxkHBsAAOUxG0x0J7qSwREZAyQYSLDDALtUfy2QANMREmvM0cigAQgABLCEjIJw0aIRpz/yxZ2H+PFxFOs0Pv/xcxiD63mzplzZwXAjU8+e/PNt+I4HAwGJBSy8bLF4sSMhIIPzma9dXq+YlHwnd/71iefPnyw0jt3+Tvt/kY/NmfPXQz6QN0Pi8Vytjy1sV7PeMUwNK5tNjc3v/nu7/30kzVX4skTS44r67udB8ub55eWco5qmgjYKIkGhRQSBURSaE2YhGNAUvZ1T3SEkdUKEQ/2W0CUI0syE4DYi5tEQ4lbmPftzEIgAGiSRKg1EzEASwlKoRCIRDiqrfWYXVoKSnYEQ4IJiTCxjqVlEYVGwR7XNXvKOuHI1WQMkxHGGGOIKHkQkhH2Ss2DASACZhQ6SmYhBAhJUspko7H3YjXHHHgMAADPUp7nEYGynTj0+71WHJn6bvPcYq3b7XZ6/qk33pYQfvbZj7752tzVS+d+/POP3vv7n/6T/9F/trazXW91GaKTC6fZQCbrnDy19IuPb33w2d2zF14X0jKxnpmZoLAfdHczTimbzRpBMpMF1cxnsnEcktZaazRGs9IoAcCAJTgCBhSjViQIDAZQsDZPWoz33plHMYa4947MbEbUC8l/IyKYxA4sjWFjRpU0JAgDKGVCtok4PSL1BAqJGJmFJtQGNTGxHLmLDsNAIwBwQr0MjGCAASDWBhLiTHYBkkzAzFJJZgY2zAaAUIBISv/EAEkbJ8FSokwKkgg2YpT2+Kw48EtvxHpFcfC57NuxmFkKzmRy69s7UllKYNDra4TT5y9tbm9mJDXq2/N+V5gg6vcqhSxQZWt59WtXzs5Ouz0fuj1ZLuQVhfmMM1eZOHN26d/+5d9EUdRoNCq1aqPZunjpjGfpMycmtbb7/rA31MUTM5Gdub+xNeuVotjEmqIgDo0FAgg5tJG0RMFAgAgoGFEgMhBYe6ESiZEZ9lasAmIUzEDENKrkigCoaS8J4HHbL43kWGRO/DGCWRChSATZxHZ2wC6JBAbAEBjCyIjYYNJ8jFLIJdBJRDQzswFOevEZ5ljDnk4reKQGCwCwABgIiYENCrYQAEEgCkvBvu1KAgtkgYQQ7YWEPysOPBbFny/SNlB+POooIWAAyGVcZdthTBNTM5YtA7+Xr05++7e/85f/3f9N2OgqMWhsoR7kXQwH3Qf3l+dLtdr8VOw/uHi+rEQt72Y9iCfyzukzJ2xHZrPexYuzyslFOnQcpWlgo1fKyq3dfgzUCEww1OTlnYLbbPVchIjADyJNjkGIQWt08jECIIr9iGJGREBCsU+HyfsoMAOBGQ1TQjOJnZiBBe3l3/H+PUl0YNIAwKMeSUgCQQAL0PuhXLCfZsTMTEYaRkMYEUZGRISG0DBQirciplEIJDEbJrMXcGKSChss9vwTgpM9QMRJwJYSSgpSgqUARHaEhJHWwwCEyCgIEcmMst/G/YG/WtjnRfvWLCIyxniuff/+fWI+f/7i5traxtqaZVlRpFGoTqfjWJh3ZdGzcrZqNRv9QZf8+Id/8xdZL2jU74TD1uq9e/dufrZ856Op6VqrVZ+ZnVxcXDhz9lQUhycWZ6NoWCtnLWECv5PNejHizQcPd/v+5NyJvu8bFgZVGJkgIj82/SDyY4ojiCOKQ9Ax6xh0LLQGHYtEM0z8u/vvzEh7SCRnZgYWAGCYCcAwf+5lCEY9tFEiSgQBjIkFWBjG5KUJkldEGBEERgQGA4O+FgMjfC2HER76ig1qEmFC8IQRYWggJDRgGbAMWhqkBkuzZVBpUMyGkYVCy0qaM0kpQQpWghWiRBKgBRByjKyBYgJJIA0L9USB4qPmr6YjbWs4fPzj4thpfuwkouXLI22e6SrD8dyHo6okSV7r5xGwyNke+ToG0tI4nswyNFZW4p6xXTU5OXH7k0+ifv/04hyG/R/9zV/kqLezfbdWLs/XnI8/vlmyucuFDx+Ec+drby387srdPhn0tGp0192F04sXL/zN372HstRqx4Pd5anp1nRVDnc3rF4+uHp2Ml/atts3bn4mYu+sKEJB3Fx9LyPPB6s/+dbSm5903WXtEWb8qCOF3YhDKYQSZAtwkG3JowpYmAEkwQxIyBqBAFgAdW0rcQvxqK4GMxsAiChGlIACAImRjDCGmNmTic8WhRASZOJIQkSzV12ORhmMo2AvHUaGUZOJCEKSEYuIBQGwcQCIEUbF9USiFZMdP4q1VCD3Bd3IHN5pgSgR/jkWSW8JK1nJAWoAkKPiX4TAEhCQbBkAAOLYiPUVAyKS0YC0V5wJAUCH0Y3rH565/GYYZKYmy1uDzdX7yydOn9tudQvQu3jx4u7u7kcffWRZ1tmzpxCx2+3mWA+H/sb6zsTE1PXr10+fPnnhwsX/8Jff+51vXRz4Q23ixYX5MOrv7u5ePnOpWqjduHY/HPL6zk7MYb/fCnE4PXFxu0G31z48mxt2g8DNetyJhoFmaTxXmShGEgZYAwkBSEhAMrFmAQKwREYQcq9AhdGPalDBgZxBHFW0wD13MQqBRKMmRUyjlETBgDRKSDz0thlGSiiWkTlRoRMDthlJ60kqIwFjUkPr8Ptv0rKOCBGRCYlBjBo3MSIGFCPDqGD1KAg8MY+PrutZlZVND0FKiWR6xjrz8xv/qN8fdfyjQQowxigUlhRBFEiwkWkw7MdRr7GzarloS/L7jcla8fLF0+76zoNPfy7nqxMTE3c3Wru7u9+4crZWqxljNtYbMzNTc/O4svJg6eTM73/3Oz/76fsPV3eGV5e6fTYxShQ7OzutVsfN5mJQH330wYVzV223mMtnuv69eyu3qTS7FeenqkWU8Ue3H6q5CkCGhQ0Cg6EPZBkExUAMRBwLsBAAyNKMggUwCpTIAgQmJdhj2KdbOJD9izLxQ8GeYpzEroBmmWi5SChGLipGHLUd/TwYJCXe2FHPbsZEm93r3kC0H6oBTxGYOEUiI6T9nyZbyeh5EUlAFEzAco9wESBMOpnwmAN/xSCQwRhEa+QjQWJj+t1esWB3e7sn3TPd5nYU+2++dhGYWo1GJpPZ3d2tVqsTExP9fj+KIillPp9fWb6NiHPztdpE6Y/+6I++99c/aDYGZBBRFvOZKPa319dNGExOTPUG0dbmvUFj493a792u+00f0KmAtVsoZ8qVK/MTor1x59M7Nxa9wJ5Qkq2YIR7GEm0JSMgSWQNKAQGyACFFLBERQQqQKIRMMvlRjljek+SHo1JSMDJj0T55jfKHmYEM7xv1AB5z/z6y9qFgYCBAwZLRQgA0yMhoAIAQBPPIKG2QP9fMYR+couLtGcP3ZrEnCCiZXB+AEIAsEBBRIvsm+dXnspGOD68mB35KgETamY/0/dHHPxxP0ZkRSAAhkEQWAHEcDvrdRrt14tTFMA7WNtZdqZTlrKyutzv9U1NT3a3lTqfjVedPnDjhOM79+/f7/b4Q4s6dO1Lp/9X/+r/4N//m32xt1Qd9PTExYVmWEm7YbzTbrdMXTk3NzW9s9Zcf1m1q9uN+aBRBxfXcyYnuwnxRljzU0I28IZctWcraXnuoAa2ssqMkCoOAEQXQSE4FUAIQWQmQhEKSAiERULBNKddLeNDcsGfWxr184/1fPQpuecJQn0Dint2bUQAJQEsQMxrQAGAAmdAwEwMjEoCRKTXVUp8LHjjk0WTIsiQyIzIwoyAhJLIB0JxkKY058FcNRkspQTMbspRQAvwwGAx65dr0b3/3D2/dXQGZKVerG9vd3U4wNXs6Y3eur60ppaZzE2EY9no9Y8ytW7fyPKzVKu+++42//Pd/HUfs+4Ex3O40lLIb9catG9eEUpeunDeGI8O58tTKzQ+2GzuL517r0/TyzfcVQRYG4XANVLUz1JnSHOg4I2ILYxTSAwB5IJ/nwKInZgGoCVAyclKumZHQwCPT+mO0pwWPcvpHvVGS0FH7kTvqMUI1B7KX9qkYR5HWqImYwQhhFDELw6yRmIAZDQlDrEkkAVtBinvJUIqR9WBm0qMpoTasAQSSBNSCJI7Cq3kkbn8uG+l5BWCMA0h+M2DSSioCQ4aUoxAhCsI4CGulWrMTRGydv/TmbDnX3t31qTl/5rKp/0JrXS6XC4VCq9UCgKRxro4Gf/pn//y9f/jFtWs3rl696jo5IYb1+iYZaLfbzd36lStXBMPK6urE3OVMybn2YakXxufnMtRBMlHBsXIinsjbTTOIeXhi8aQOdizOlAtZja4Kh0K5AJCk4SQJA4mPN0mnlbgXmzgyaZmDOcOIB0VfCSwACBARk4Bngciu2K/IkbyPiHUQP0bAe5keYDEzQkL2zGj2qmpFRMRIRIZYE5JhQwkRHr4OIzrcG2LQPjifR98nnJaAEZCAgARgEpsFADgOpfyqIYl/NqzBsCVkIkIbik+eufjezz8sT87OnT5BFGZy5eFqcxiYqVLp4sWLcRzbtv3GG2+cmq92u93XXnvtrfO/fffunU8++cyxM/2ef+rUmcGwWa7koihSwqpVq++88w5ZeH9z9+q7CzsNLcW8sjLSiaQ1OHtmthaHMAiM6rfDpjbDpTNzzXsbjurlbQttVENo6sSMDIYw6ftHjMxgYpaAiIBgBAMgJelIIB4R4mMftBg5ShEQkzhEEEJK1PtH7R3LiChGPcr2X6MiAWqPYe/FVMDIDmxiZiQhjQYNaAAImRijFDeh/iI+9YQQkUjPIEYFDBiQk1r2e0kX6gmOflz5wOl4xuOncfKU79O83kedZRrnp5R+v2mFvI86z7Q+xmnzt1D4cegV84PBAKKoWMj+4he/OHX5gjU9a9/Zlu06d7ERcaOlh4OWDO66mdyNlvVb//Q/f3B3DRqd77xTLU/YMv/OD77/05///ONT514n0nd36nHGe+21t9bX1+MoQKWvvHtlub5dqM1OL57LFXO37n30B9+pZExQC/TW8k8unTrjh3OZXFkIq/Hxg6/PlU7imu3Rzv3VK++eWtttxygmrRBAEEvNypAMDcdaEEFs7duZZEJhSYqPIQOQNGoABJKQuJsoVhqRJaBAlhIViiTNVkqV2I8FADIlxwBQyXvUi+hR1jyAxSO3zUFdFRE1CQKMgUmiBoiADYIhptgRApQgS4ASJJJIDGTpmUebEYnYMBETI4R+wvBF8ra3DGx+rHB8IhYAgANdRJRSjjnwVwuWZQVhHMexkCCFjKLIkpjPeFGoY8PTCzP1xjYrb22jsTg3PzldXr953XPsmcka+3r1w093doqXXz+zunHr/s3rimKMIxMHkqKNB/elCbPZrJSlCxfOZ4vVH/74p+WJmSjws55ldJS1bCnl2trqnTu3cvm870eDfvitb/32zz/6TAgYBlGpVCK0TRRmsm4vZGDDIBgkgzCMTGCSxCEA2AsI3f/AzCwEADFIAZREYEoAAJF0IEkIWCROJwREjDUAkAAUEgQKhYIFCEApzUEb0v47PV64fy8qE4gtw6wJyGASjKEJmUCikQASQACPrIaj0gB7uY0jhxYiAjJ69pNN2BJW6srHRO59wlasxgT8KiDNdpAmqUllcRDFcawESsTQ7wvkbMa7/WC5NjkxPTf/i5/fjHFw9uy5c6cWl+/+4tpHP5s8dfHkbC0HuPrzQb+z61kXBMGZE9O9cnbp5Hwch7dv+71eJ+fAidnqW29dmZic/dsf/KjX6966eW1y5sS1jz8cdHYny7aJoygKdBw+WL7XavctlVlcXCqX8lLKnd3diXJRSdjZXpf5yUym3B9GBECAhkTMEBEZRs0gYJ9D7uUDAwKAIUKRiJkioVjGhLYNACapwQRsIHEZsTGEyBJRItpSGBAgcMRiHzmBRpHYzGzwiVYvyRw41GhYGIaY2SSpwsTM6CChYIkgBEtkgQYP8PPkwSGglAIAGQTKx6JckxxPRPSseO96HxPl0CRdVn/l1iqvKo4nzOLZj592/FGNdkQEQiEiMyGT3+8J0hwHxpipqZl2u0ms/TD+5re+hTr86/9wW1ksaPDD//Bv2/Uu6mE+5zy4e7u9szNR9DxpMBpOV8oz33yr3W4KIbIKq9Xq5FSNOD5/ZunT67ev7+5e+/TjU2fOMWHgR1ffuEgc3bhxy2gSQt69fYNjOn35YhAED1eW0ejTl+cGUu30+kJlNYEhjgzExDGAZtBMNj8qN3uQQ8bIQKCQEVGCYGAhpGCKtUZEQhCAiGxGdi8SgEIIkgAEMSBIIE2IqA6M+Zg7ByQ/Aoyq7QCGSacXHJWplUlYCYArYkRO2D4AQxL2gcQHek0gokCBKBiEkpSEUibNEMXotwL3SosczKwAADGqYjuuyPGS46gcOIxNYkZmHbAxw36b48DvNl+/fK63WV95cNsSMFkp9jq7JhzmPXtoU7+13WoMw244kQscZT798JfBILuzsTY7O9vvdx52Gq5n7+xs+b5/6dJFZnP39q3tzfVhEL9+6dxWvSWEFHq4vlqfnJmcqJVd79zq6srUVBHR7XXb2WxWAHmZnG3bxUy2VsjVt3tubqbnS01gmGLDEUGUpO8B0r52f0CcBgBmEEBGCIGkCBBRclIOLnEg79scBLNhAqke87sak8RZAe91foDHCRilxZ8DjAq4S9xrm0iJAZxFBpJYZWTxaBBmICESHTh5Srz/EA/Q5/7gzAxJYYAD3yQflAiJaMyBj41DvizuK8OglCURiIRkHfR7HIex3y/n3E44kBAOe425uZkPfvrjqVol62LX+ECmViihnfO723HQXXv4IO+dqlZKlhKFfL7f7z64f69ULp4/dyWbzf7dj354+tQZZGo363fu3C4Vq14212w2bcHVWqG+vSksIYCI9ObGsu/HF86ee/jwoZUp+r6flXHkd3WklWUPu5oINHFEbBh0kpyLyHu9gpLL2VcpiZlQCmJEQcgCWTNIYFtaKFgJKQUggkiil5ktYYQAJYSQoJATBRWI97w8T3RgQSF1EmuZcN/9OluuJQEMjioTUVIfD5GtUafwZNNhSizqAISKCEZl6hJezgSImpBZEI9CNWHErUHskTo8vsYkBokMMubAx4OjcsLjEqGPeryUEgCIyLKUzeQPB2RiJUVja7XgihBMvdcMe636RoeHzW5z+8TidKve23pwx0ZHyXY+58T+cHnt7ukLJ1ut1tbWhpBQLFe+9tabROav/uqvfu+73wLkfD57tfbarTt3337r691u9wc/WJ2anZUCrl37dHJmMvAHxvBuYycMzN2bscxVrJyur2/s6u7MzMzkxMKHKyuxNUvMScUbI4ABWCAIeTCSaZ8dAQCKUds/Tiz/TAjIwBYzskBEgTLpyAksmI0rSQhQAqVCiSgAiBiI470SG08wYVs8iq8+eHelBZC4nUAjotiLxLT2S7qj0AAEwhBJZi2UMUx7Ra9MsgEhaFDMwCAIRrYuHtX6edRBYv+0iKiUGrmRjrgwxni5YVkWEZExGUspoDgMEMhzrDjol13v0/UHEuLdnTU07trqfVd13enCwvx0a60lWFSq+XKlSCZubLftrLp48eKNGzd2d3f+0R/9wfz8/Mcff1woFMvlYhQFV66+Phz4uVzOdeRr33w3joJSsRLrcH39YamcZzbFYv7iufOMVntr4+OPP86Up775tdfC+oPbN67nz+aFlYk1J6m8CfsCucfa9pTPfYvPSCeUCpCAE38wMUsEYhBaR1JKgywSa1fyeyZls0ShFNpKSQRAQlLMhvcS5Z8gYAvNI9/yHhBRyESpTrp/UlJdWABJtACAQTACjkLHkAAIBI98u0kKRELAqEf2OGSBREkyEjEziPhzbiRkgEcE/Mz9vi82UrN1U/yraUhTRFIiYo8scqc+pSOyZhkNA02u62LQr7jR4OEt6ndv3bl/omTtIFUK3s5mfXXjYxBYqU0WCxPrNzdOnDgxd2Lmxo0bhakl4ZxrhgWs8tr2ppVx508uLpxaqk3P/fu/+r4xJjSikK92OvHK+urp8xciGXca3ekZ/3d/9zt/8f/7a62j+YWZfCb/2vmLUjq5bDGbzffp6j/8zX8sZ02xOvsPq+325s43ligyw4Bdx3FMbBiE47gxmUhrpRTt5XU/CtkQAgBsJoEkbBYCCUEb0jEYEiismCHUiIaEEIiJW1WVLE3IBuMQjGCWiChRAks5QEQJEgCQhUiKWtKo0TaM+irQXnAIWURJTY+9x5rsLIhsMUKSeIgMwjAzIyECIbPFKISSFgGIJD8pA2QAiMgQaABjDAlkBjQjv3dSjFKgSBjxqD4ejSOxvmJQSgnSQoism+21G1tbW8w8VywWJ4qffvS+A2ZqZs6YuN1phmGYcezsxESj0Wg0dguFXLlcBgBm02w2+51+tTZ56dKlQqHwd3/3dzdu3LBtezAYlEsTP/zRj/76+39XmfxZoVB46+qVfn/w0QcfXrt+/fUrly9curiwMPfhhx+26pulYjQtLTuT8TzP9nK+Ua1BxCzz2UxoY6dna5KaiJmYSDIoIvm5XfUJljhSK+ERlzaw1/QMgPfz9RBDLRNmJhEFsNyLx2ISiEmJDkREYk7svUoIGMWMjCKxUDAAHgy6OLgpEzAwUlJVj4CADCMxGRilEzMzgKCkhxIIQCOSutMIMknbJ2AAg6NTJtmKzEmxTggNAOCYgFPxqtr2ksuK41i4dr3RMMYsLS29/fbba2trjX5k0RCKjuV6sis4Dov5zMrmaqfTqVar5fJiFId3796enJycnJwMA01EAz8oVaqa+PLrV4bD4dbWluNk/GEc+Pre3Qe2bZ9aOLn2cOvnP3+/Xm/YllsslH3fv3bt2mef3rSUOzs7/9qbl8vVqlOsbbYHWrqZDAwHPSap1CyDEYhMMRhQiMRs0agK5BPxhog4KsSRWHof2XGT2pTJkUj0KFh6ENmQyNWjrCwEJGRUYEtEIUBJlogoWAIDsgsEDKOEf9z7AKOCAbBvZKbELEWaAYAJgRiIQRMaJgYwxMysefR9EppCyIoTamXByAgKBAsGQM0imfQoxXAv0zBxa8HnW6uMkeBlsSofFUSklDLGaK0bjUapVKrVakopku7Zi6/f+uRnD1bWczYFgc8matV3Tpw4cePGNSEgk/Waa/V79+4JAVprZVvdbnd9c2O32bBdZ2JiotfrlauVv/vhj8MwfvfdbwwCvb6+HoZRvz+cnJi+eXe50W7ttpozM1OT07Pe8sPl+6trmzsawj/6g3/UF+61lTXLy+aU2t1a98pVy7G0AduSBkEC20ICCIUQHyDaJz7AnlbJe+WXYa8yDu6ZcfcP7mtr1CSNJQIjsgAJQDYLhSgVWoqVIKnAIAPjXrZQktiX7B8EAMjywKkpqdjOLOLRXiOSElxEYBiYhWYgFkRkSJhRrKYABgF6T09K9qa9rYEkP66QJ+/hKCpNjDnw4XhV9zUmdl2PiLT2G41GrVbr9/vf//73q9Nz+XyOtAmDYVZIx7Jq1WK/1xGsW62WHwwZ9Pb2dj6fdT270+lkM2UpcGKi1mq1TizMR1FkW0pKeePGjWK5Mj+/QGhJKYMg2NraKpVK8wsLQRTfun1HWmpyeub0mbPtznDQ94vFYqGQH/RY+362nMlYxhF0cm5ydysAHbq5HKEiMpZSOg6FGNmCP0+9T5Ax7DlXR26nvYAt2GvLEsQIB2pNCeCRVouoBSsNBKgVKs0CEYDiRxZgkRS6RJR7gm1yUmAWxjARMkPIBICMBlgQCA1EJAiSfEPWiThNMMpzFlKwgJFujZDYulAAgIYR+33cdAc6ac80diN9BZHY53zf73Q6r51cqtfrG/eXl+Zn++3dUtaazkz7/SYpmc1mdxsNMtHs3EylUsrn82HoM5jFxUUA2lnf7ja345wz6OxKjrrdLiI2m80Ts3NSyc3NDSebLZayrlI6GKBwr1x5A4C2tnYc13Ycp1AonVw6bVlOqVy5deNmJ1KKSkErrge79kzF7y8Mm5EhLnuCBEZEjMok9eeMfoJoR+8wMs/uYz+ceIRHgR8AAEaQANRMIx8SgkQEQIMGk9pTgIrAcOIiEn1IIqwFjPaEJMlpryjsiICBSCQlMoGTLUEQMjEQYWLG0syGiAg0YZJ3yIBgKOmllPRGAkZCkRjXifdbKPFBDmxGSVFf+UCO54XnJaJLKQfDoeM4pHWv16tWq4PBIJfL7a7e2l5fsSHOOmhnvYlK3nVdZTnnzixWKiXLsrJZ7+Kls9ls9urV16WUDlOn0xFC7O7urq+vDwYDpVQQBJZy/DC8dutuu9MAAHLsoN9p7G7a+UnHVWE0iEyUyWSIQNpWtTapHGu3vh3GwilKJj/qN1r1aGtjbXdNC2nVSi5aTqwBbaWZUOB+JfUn1GAhRkm/ic127/9Gif5PgJktNAAgRy2FWY2SCoBljICEKFAYQMOIBgDABwSTbBGIyPsGLaMfTYOZmUUiQiswLBIRIBGewTAzoWEwgMSQFLsFBgOAOIowI0JCYEJGQcwAmPSZGE1778rhkfNh7Af+isGyrLg/zGQy0rJ83/d9v16vdzqdTL83aNcnS7luu1sqZGrV2vZuvVStbW6uA1Cn0wmCoR8MhsP+nTu3PM+byXvFYjGKoqWlpcLZU7VardfrSSndXN5xc6/dubfdaDabzbznWsjtVr01kNlcZnPzYa/farfbCBaiJYS4v7xih73GbmeA6+XKROy3NtahR6IdZC0nGwdzCovaAGovBsK99fp5rpOYqfa8eSMRelSfPfnq8UQCAC2TwGkEiSwECiREZGmARZKlOGogSAgAIQnYa04GCCP5GVDrg1vJyIfEzAgEBkAwseCkhwMjA5ukqCUAMzElVUKAGBkkABAgETODIWBEZhztH58Djq6R8f/wH4bHtzweIaVyyHODSHHrHtc8+bgGSnlgafNPg1FeFPhZz2HSpDUI4QeRm8l1wmAyJ63uw1vv/dXtn/8d6EEmkwkinfVsy7Js20bEKIr6/X632x0Oh77vA4BSqtvtMnOlUjHGBEGgiDKZjFJKa23bdqlUymaziDhRytVqtWq1atu2EMJ13Wz2/8/efwZJlmXngeA5996nn2sPrSMjI3VmVZau6qrqLnRXCwBEAyA5ZJOgxnKX5KzZ7I7ZLpfYHVujzQyNZpgd4+wuORwOaLZkDwmAAk0A3SBal+rSInVmqAytXPvT74r98SI8o7LTMZNEVVd1oY5di3T3dH/ivnvuUd85xzEMg0KUXZhSSgiRedGklMC9oaEhAMj2Ec/zut1uFEUqV3UGpoemTltuZXt7X7BcefriTmTo7N7LVe9TAaOfpnNXSZ3ejiAO6wSgyroTKTx8CwCEAEWgSNhhJUuh6F2nyN46Rp+E/vTeCq8iVCklsgr1CnjmzFaYtSJVMsNjEqWyABXhhGWYkE8l8CeTlOBSSs6TLLLJKFUa1VGYyK++9cbOtVe9zRsq9HImcywrl2NpmnDOfd8PDylJEiFEkiSappmmWSgUEDHzS2maFocRFTKRaRAEQnQanW7GzEREWbJEmqYAYJqmZVmMsUrR0TTNtu1cLpfP513XzT4frjhUt0zTtNyCruuapgEAYyxIu0a+2opUHHn5MbrneWF3wdCrCvIfyPz0kiLucm6xA7cREJQkQ0Nm1a3wIEvxQGQqBFAEkMg7hdoPkSUAAKRPgwStT7E7CRIQiBIZdoMcCGqZFdtUBxUplQAkCgFVluakfrwm1gdFHzfL+j4Lddw3fdyCToh4UM5QKkqBqJjyME08C6LtxUsr196uGHK4UmAglUgBZL1ej+M4E7lJkgAAIYRSqusMQBECmqZTSqWUmkZt2zbtXBaOUlQjhOi6nqZp2O3mLJcQIoRQBBCRK9IN4jT1ao06HPUPH6IC8w5zXVfX9WyPsCxL13XHcaZGSpTpQRRXq9Wh0QmjUmppehdlLbr3/fab/37Lu3cl6v21AShmWEhEAERJQGUZyAKzFmuAKqtQqbLoEkPRu5ejL7Q+bQspu7eGJXu9FImUCnnWFg2RK5plMkuhuAKCMpPGIsOBfNqZ4YOiD2wf7JcUcZ+H1xnhoCEqRAoyjYN20NiPwm7ekGbaHsqbgzndRN5u7HmeJ6Xcb3V7Da/pEdJ1FoahYRiUUiGEaZqaplFKw27IiMaoJkERQnTDYLoGBGUSU03T9IPE2kwhTxV3nUKmPGfnOLwp9CLZ9jvZlqHrehzHaZpalmWCYerEtQzTtjyuilOnH/rCLxcnT/wRE9fn8z6qdS+8dOiYgl7a4UHJdkURCBBERQ45ExWQgwrskiACoMHuKoJ34EWjfYpfsb7VZoVSKOCAPyVVSqJElSiqJEgAiUglCKVk1ioNUSkp4UPrzPCpBP5oSYqUICgATdMSr9va2ezsroWdhk884tdsKjrN2na76XfbnHPOuSQ005B7tSCyhWFaOqDMF1ylVLfbNUyNMStJEl3XbdvWNC0IgjRNEVHXdUqpSHVN0xAxTVPOOSKajDFd101DStnrad0TgEzTgXNKDw5opmmSJJZlBR71ZdRtR8pTwsxTWk70sqAO9GlxJfpIPK2Pa0IeRn2PptfDIQQSAAkSCSqLISlEigggCUKWFoWKACgCoDMGRxj4Dif3q4VG7t0bCZWSoKgCRQ6L+BEEyJRlpRRyVJRIIUEiKgUpKAlKyU9t4A+IPm4SmKfpAQSesTjwt9eWOpuLImhtdzaTKI6iwOu2/U5X06mmaZxL/TC7JdOcM0JE2zZ1nRECnAvXtXM5RwjBGOESGJU8DUAltqWZpsE570aBRqjOkBBCkUqGhBClFOdE0TuJ6Ue9PoxonHNESiklhGWFmZOE6wVDcNbYjSZmzz371a8Nz52X1ApTH8i9bWCF/ZyIf1RTO3VYUgsP63ukih7U60BCs/8nigAakKnKWRszpAQOcgzYQS0rOKI/H3F+/xiRPs9XKgSCCBIUOchYQgAweNaxHAjKzDUtiFIKadaY8VMs9CeVNIrpYWq412mtryx5Gzc07sfdnThNhUIhAXSTWZbGNAGBxlSPezORyRijlBIiKKXNZjOXy128eFEp9c4778Rx7Fh2uVyyLCsIgiAIEJGYWt42hBBKqTRNlZSMImOUcy6FoJqVXVjGKj02Jqj1MuOyk2qaxhgDk4JyqGHPnH9kZP5htCvcD/O63uH3vt9+3mbswzCyJ7HVAWYrY5hYIVEMUVFFpFKEAlGICAZkzZcOUo8IAXIQ+Mm8TACHaM3soHdXez2kfk3PtIPU/V6qRKZqE4ISFSiiiERBQIBiikhQlEqlFJfyUwb+ZJJhGMhlKqVSyvf9vd1tf2fTgcjSkigIBVLNdAhBLhVICUy37cMiaYxlbJwxlee1AKDZbIyMDD/77DN7e3vf/e53dnZ2CrY1PvLUyfljGxsbr7xyfX9/f3x8fG5u7tTps81mc3t7O6sCb5omAERRJNHMLiyztA/0dilNXUdEokAIoVOGDHXKKKXE0PZ2a0ZheGTsDJLBKKQG6iz2j3ZsOEryPjUUdQQXfZSEIlnGoFJKIaUKJCoEVEoRQCASkdCD+HLWc+wIhPNIexfsE9bqJ5oVwkH9ejzsUIoEABhIQCIBJFFUZno8EECkQimFCIz0y1j949HHLAzcNzGXqPu70n7hXvygkFX9FmKf6++XtxzHIWNM12maxlMnz/3pyf/H66+//uK3vjXFl81iM4k9qkjJKllmQmlCkChqIWIcx67txHFMAOu1epIkwnCooKaW91vrU4PGD7/5xpmZOUi6f+rn/+zu7u7O1q7fDarlgauXr02MTV584KFHHz+xs1P7+r+8evXy1TBKFcGHH754/oEL27c3bty4lW0QQdiePTY+NT1eq+9222nKeaWYa7Y6hZJTqzXcXD5JkihWA3Y4Nq0NT1eIS8XWjubK0CJMOPe8X9GnN1LaZyVmSnBG6shfkpXYABCZtDxUwJlmA9yjPDen91bRTXHvByn6rB+zb9Oze98Xjw/O+7FjtE/pAyGlFOe8F4wdGRl55JFHPv/Vr4ZhqgiWB4rVgYJmAKGo67qmW5QyShnnol5v1OsN3w/SlEdRzBjpdjpJFB0/flxKefPm9Wq1+ou/+Ivb29vLy8tKqVqtNjU19fzzz3/hC194+eWXoyD45je/WalUjh07ZjvmF7/wMxOT46+//jrn/Ny5M2maXr9+tdvtVqvVL37xy3/rb/0d28q/+urry8uLjmtMz0w899xn19bWG/V2FEUT0zMXLjxYytmR180XXEI10U8B/fApkXjPIcW9RyLh3kPce8Rc3ddIBGbjUxX6p5v6Oc+QkCxsA4fFK4aHhw3D2PyPY6lY00ypKRXLhFmMURJ4ouXXMzBzkiSEEDefM21LIciUG4amEZF37UazJoSYnpoYHCl+63e/LaVMwqDdqNuG/tWf/7k/+IM/WFpcrFYrfqe9sLTx7DM/83M/9/OXrlx+7+138qW8Ar61vXnu3JlczilXSkrh//w///O/+Tf/+sjw+DPPfPYHP/jOuQuno8jzveDC+QcvXbo2OTt8bG5ifGwSc3an1TXz1TCKCWrqI+puGfXxhWl9vEhc9Glu1ucy74nZhp5N/eOfH87Dp8kM93f7H3Y46n4P1Nd5c0iZKO50upRS27ZL5eH9xq5mCI1oScKFUl6Y7u93U0gy9xVhOmNMAuEShELFE8swTYqmbriWeebUiTRNr169emxuamtry7K1KPaOzU1JlaQ8TNIgjZNWs7l+eyX3s7njc8e+851vX7t25anPPIGorl+/Krj88pe/bJj6b/7m17e2V//iX/yaECqfK37ta19DppZvL585dbFYdBH0+QdOlR3c26tPjUQlg0VpkEqim5rsA0X8sCntE6Yi/N46LO+zrvq2yFH9vOV9beaDC+jzs0/pp4N+PALZC2b0/MmapmU+G8exhobHiGaEiex0o/1Gt90NEq4MJyeEiqKEUk3TDF0301QkCWdMNwwt8HwlebFYKBWLpq6//MIPX33l5WqldOH8Wcc2n3n6qb3d7f/l6/9i7tjM8blZU2eua//iV39hf3f7n/2zfzo6MvTUk4+3Gk3D1KIoYBrVdb3b7UopKWWrq+ulcv726vIXv/hFBCa4Gh4eTdJoZnZ6ZnaCmbnbK2uy06hayvc7kmg87V8arP88fEDzTO85hMJ7DknoPUe/4yi4vyEJy8anEviDkcAfPygHAEAW1OkRIZArVaNEen5oannLGrBzukwTpqFuGEmSmJYVRREgJmkqlTINgxIpDOE4es6xJE+rlUq5VJiYqnqd5kMPPWQYRpIk//LFH6ysrAwNlJ947OEkib70/BcuX7rxzW/9QaPZfeqZp6cmJqcmx9M0mj8xd/z4sVd+9HK73T537sLe/sDK8trzzz9/5do7b731nu+lY6OzW1s7lDLPr0dJFMRSSgwb24VCVQFF3Yi6HjO0Pvf64S7jfl5l6ON86tcksP/yubds7sueh+GxT23gD4Y+bCDH/R8GEZFzLoRgjAFAmqZhmG7t7HheMjg4MjV2kko9DPc3N5Z5wsvVASnlyMjI7u4u51xxDkRIQItRp1IqurRUKEolZmenxyemDRvTNA2C4IEHHnjppZf+xt/4a6urq7quP/LIQ6ZhPPrwI6+/9k6pVJqdndtYux3F3iOPPOS45vnzF1584UdvvPFOmnDP886dO9VotAaHCqdOz1+/diuOcXhsXGMmV5FpYafT2m+E+VzR298ZmDlu29UQiELtjzAZ7vn5B5V3TfswWL/npfqoxP2yylQf5bovIuTw658y8CeTlFJZODfL6ZNSJkmilGp3O5abm5yaGypNbm/u7+13pYTpY7N7O+uWZZXLZd/3s9BUHMeUUltTsRd7XtdxLc/zNjY2TMOJ9jvV6uCVS5dDPygXS0mSPPrwI/V6vdNqj4wU1tfX/tyf+3N/5S87zbbvBX4UBchw7vhMq9ltNrqWlbNMO06iOI7PnT9LmfzSl55/643/odXkXO6apjkxPWhaGAHU6s3ZaiXo1hhyyzbagbRNmwv/I5lP7BOuk9q9OYj0CWv1swF4XwncR8L3vvDffj/pc8z3Ub9AObnPDe5+j3O/Afr+1LcC9L0/7Zt/e78dhfv0773P+8U+C6IfJZqpokiDiGosAi2O+GjZufSjH33vf/mH58+dqdVqIIVtGhsbG7ZlzMzM1DcWstTfLMs3DMM4jgGA+2khp1t6+l/+n/6mktF+vUaooZtOq75VLpfTVHTaAUHKOXTaHuf82Wemtzbatb0AKUMmFZFK0jQBg8VZ2nC2m2RmebvdLg6M5fP5jY2NTqdTr9eHhoZGR0cNw7i8uh60TUxUKR9OTM36+txlz0iGCqT94eAWDul+JfkHp3n9UZDPP4I+lcCfTFIcsgZ82Vtd15Ig3tnaYBSbzWZ9f8/QdENjtmWYmh6HftZyhXMeRVGG6Mh0b8YYZYwQkSQJo2gYVqcbtrpRpVje22+7rmvZTqvVqlYHR8aGFxaWOJeUam6+oJACpoShAhpHSqZGnMh6I5EyStM0g096ntcO+GOPPWYYBiIODw9zzldWVsbGxnKWXbRdEYZp2AGZFnOkIGGzHZiQ+0jn9WNHnzLwvan/zvrBfN732x9QmEpJQKIopYlSgOCaulfbWlu6OTI0aBm6ZeimYRBUBGSaRLvbW7aW5Z8eeG4PgMqElAdLadgtlktjo+Otzn6j2Tbt3PzUsTSIDL2FiOVycWoKGo1aGPqzxyZKlWLgt4XCOEmjONYoRUqBoG6iEIIQohFiu45lWZqmJUlSb9bW1jakhEKh1Gg0GGO5nLO9vSuQaVZXicTzu7s7GxU7l9fGvNCJP+SwyUcngf8Tj/O/1Qvdd2Hd5/nu9zgfYCDgvj7/aS8LzUAyBEKITFNKlaHDfnO/sXM7X5ScqJxr26bOk1ikCSMohGh6npTSNE3TNLP4k5TSMIx6oxH5jVMnLjJde/ONt996+729Rpvpjo7aL/zCLzBGXnjpFdPUR8cGXddxCzmJrOWFBNyBwVHUpG5SUFqaIMFm5lE7pMSPvCiKTNMuFEq1Wq3ZbBeL5Uwsu26eKBrjnlUyXGM48PxuczU/WBTm8PpHFAf+2AZrPpXA96afdgnMKNKjFTC4au9t0dgPulEaaTqjnCi/2+FRwEyToTQch3OepfJyzoMgSJKEMba5vs6ozBULtWbr8tVrzDANPf3RG++Y1KBM13R69erlrtcaHR0+eXJ+7visxs594z/8/vLKvmW7lIlipViuDOVzlUqJZIU7sqo6hmEYtmXnyl6ri4gnTpzY2trinFNKNU0rFApRO2jFGtVtSy+EQSRT38HQj/aBDt/fRNwn/fRJ4A/m9J/Sx4w0zFqMZB290Os0dtZXcjrojIokSgWlSoBIDJ1ZOgEgmmFkqfmZv7rdbmde6EK5GHlN23E63e7NhcXJqeOzcyd1q/zum6+PjIzUG/u+H84fP3X+/NlWq/XKS289/ZnHduutjc0dy8lFqSdupVwgJaap6QCQsahpHiT5u66bt9JcLve3//bfDoP4tddey+fzlmUJcfvM8eOaMRhFmBDiFgfcnKYjx3Qd2chHMp8fXwn8qQr9kXx+//d7fzo9RSUBhJRUNwBJfX9vc3XJNSjFVIGiCJSAZWicYpZHtbm5GYYhIjqOk3HXQWqhRkIfHMdxXTdNxerttYTrlerQmQungMkoSU6dOXP27Pnt7e3XX3/bdV3DcSVQCQxQQ6KZlglKQ9DTgCNimqokUUIIQpRlMcvStrfXgyBstdpLS0vb2ztbW9vXrl1jjNWefmqniT98/d1UdB+9cPzk3LHT58+dvXhqaeW+puGTT59K4E8moZJKCaUUY4wL1W436/u7Uw5QxkxdM3RGAbteu9Vo+N2uECknLCuUkyXWH3b6kXEYU0qRkjhOKdMJIXt7e0HIH7p4RikYGhoKg/i9965evXLNspyhwfEoSngqAamQKok5MiJkmsbC0imlVCJKqQiTUnIBRJE0n89funSpVqsBQJIkMzMzvu9fv3795sIt3T2by01NHXM///nH61u169evVycYwPGPemo/XsTuCkD1E8h9o2/3KSHv9zgfXNTv3vHYvkidfgCYvnHs+yvcrPrVTOr3g77F0O59nIQYQFkc+lWkkbfVWr48WLCBJFGqHE2J0N+ut/Y6ITOdfMnhQUtAhdBGnDbtnJnG2GyFg4OVOPXQI+1gbWZqcGOtPjxwWmDU9ptvX3pjbFj7q7/6V67euPFP/snXd7aCUm7M79b8bpMSj4OXgBSCKNPthL5jMNtmuXxZSuHt7xJCdNtCJITg5u5WPp9n1skfvvrKX/8bP/dP/9m/rjWNiWOTF8oT4wU1/vQvDe7zcVOZpvRNbWUnntuuXKwuXQlKaW6Ehm3JY3AG/Jib0kei33s+77v/db9E/Pv7fj/qr/D+J7rXP01m+GRS5urVCM16ely7dm11fa3t+VdvLi0ur3LFiG5HgnDUlG7nykPFYtEwDNd1NU3zfT+KIkTKqBaG4fj4eKFQCEIvTeM4jh3HeebpZweqozdvLK+vbVcqA6apd70WoNCNg8gzHhS50hhjAERK2fG8dtfTTUc3nUTwKAqjKDIMK44CTaObm9tBJB976jMtP9xtB16saL5qQjSXE0Ua1/2ko3KFsWN7tbphGDoBlSYZyCwr0PVRT/ZHSXfbwB9bY/1jQh+UL+DD7o2UpRIiRRB8d2dra2t7oFg5fmJ+YOyYjLthp1n3UrcyCpq9264VLWrKZL/WyBeZVBinCWW6BOWHwdDQiOP6pmX4fndt7fbEzOj5C+eR2Htrq1wttr32+Pg4SGvx5kIYdAFjSjXBlZSKp1IRnqniAGjnba8bSAnAhVKxrjPGGOfC0lHLm/VGZ2urcfGxRy4vfjOSdqPjnSQW8WvT+VzXT5bbsqPcqdnpjaW3T3Dp6BClHtE0xQwhU50Z8k/wuv3UBv5o6MNecIILU2OUIQF++e23i8XiyRMzI5PjA0pTifeDP/yDysj0n/4r/zvFrOuX3mEyuvXKy3JD6rrBGLNtt1oplEq5JA1sK5fLEQBgjIyODU9NTemaeXtte2N5A9nU2tamZjiTU+OGRm/dfCuK24jIuVQSMxWAEBBSSSW9JDVypchPlIyUSIvF/MTEzOrSGoqu45qE4cLi+uNPf/HEhbOFgTG+soRpyP0mcc0wDCMvUoSUqyMbG4O7u7uFYTfkacQBdRsSqWRKGO2nyX5SGbt3X6RfIuWn9KHSh/2ApZRKCaKkiMPr166eOXPGKZSvL93miphWQXcKpy48NHfyQcmcQOrXlrbzxbKTL9g5N4jjOOVOPqdbtpMrlMvVkydPp2mc8ujBB89blnHr1qKh26VitVKuNhvta9euSSmffPLxz33umZHRoazqTS6XKxRKpmFpTFcKhRCa4546++DkzMmhsWndMt2Cc+bMGccpcM4dV9c19523rzBNTU+P+15immbZBsZYm+s7XcHDbj6pmVQ4E6fWNjZtTPMsFkksiUYQVJpQon1U8/yR059o++EjpA97I3BdE5QCwddWlpVIzz9wIeFqe6+5t1e7tbhk2+7I2OSNxZVby+sDw+PFgZHd/X1A6uYKSSoUEsO0U8F105idmXfsnGFolUpJgdje2eScT03N6IZmWZabs9M0XV9fT5Jkbu74iflTPJWUsmp1cGBgyHVdXTcREQB/9hd/8cnPfv7kmYsDA2MKIOGJUqLZ6FBNK5Zc28rtbtWTsDFQNNYXF21NObmS6eYCpbeEEXHpYKDa2yPloh8Ewq/nKWcUUwGEAFV9Ks1+oqm3AO5Wof8kbFpH6aPq0/tBUb/nZRjQ8VOLwaV335qenKhWq692uuMzcxNj46/88NsEZBAEteUVAUZxeHBwuH2z0TAMo1AohWFYKrkDA0O7u5sEme8HQrVKpdL4xOiVyzc555XqkO+FQsS6QavVskIt5xaWl9cGq9aZM3MAQJAZpgNU41xyzgHQNO1uGK1v7TDDzeXLyKiuM8uyLlx48MbNHwEB1y5EbqGxv3Z86vypmcmhMXs7iKxEMJNrZi6mruGwYPe2PahEsdza3yyP6a5b7UTCJsgYSaVEvLeb/uO2nj/w9fapBP5kkh9AEkaGoa+u3J6angiCYGNja2xicmZqIvR9r9PtdrulUml+fp5z3ul0FFKmm1GS7NebYRwLpeqtZq3Z2N7etm1bKbWzsy2EKBaLmqYlCT9z9uSJk8fGx0cfe+yxL3/5y5VyNUn4ubMPMqYBgBAi8KNWq+X7vlLKMIxbCwvrm9uzc8dnjx8XQmxsrC0vL5fL5SQVzWZTSqkReumdVw0iTs1MMhVf3w3qzaYuA8exYr0AdsVr7KjtG5VKpdusUZ66ts2FQkRD1zj/kyiEM2KU/GRvvk+lfPiQm7z02/nuN0zYvyjT/R3ng9qIVZ9KqxqD4bHKuy9+26RyYHjy8q3bFx58cMA1Nq691ant6fny8PiEYZGlhXfGZ+esgVLC44Jt6wQH8sU4VDvre82GNzE7XJgePXmi3FhpvfnmdoDG8sJNDZtabiXY5bu17luXLufyxbW1fcl53pXXFy6dnRuWcdjx2swZKpRH/GAnCdtS+QtvXp56bri7d1OF0dn5J19+9Ue7HXruwjA1KkbBNB2+cRuvvdn9la95J097v/vv1gqJvrerhkaGWbD0wFjVk5o2c35fxcZCzWA7g4X95t7lPMxL22l22lVKvX5erI+ZhvWB1T6EgzT+TyXwJ5OiMA797vbOJoASIs07LiPk5s3ri4uL09PTs3PHNta3ms3m9PT06OAgVUoqMTIyJKVstVqFQiFfzBFGC/lSEASU0lqtFkVRPp8fGBjQNO3WrVuVas51jHpjb2Hx5uDw6PH5U1JpN66veF6glKpUKlNTE+MTY+VymVLq++H86bOlgYE33n7n+q2FiYkJ2zTWVxZ52CkWi5xLADAMrdFqLSzdrlQHJyfHJ2ZHmCaajV0m4rGyU6bSDP1RXTNyNhBXCKNStHTV5X7qugX+4Sb5f6zpJ83AH5Tz5n7pJ3ybPzHqd786pWHgbW9ulnJu5HXjKNQ1jEJ/fX2V6dr4xFScJlGUTE6MMRSX3vgRQaFTFvmR5IJQCAIPCRsYGs/lcpZlraysbG5uGoZx7NixsbExzrnrUk2Xk5OjYxMT88dPF0qDKdfW1puCqzTlQvI0jYPAS5IEkSqF49PHqkMTu/WWH6Zjk1OVcr5d29pZXUSm7e03kiTNldwwDC+9d0NjlkCuWYSrZHN9dXNtCeKu8hv7Szf2bt6oB416F9c3PFsXJTOkUcQotNPkJ7mWPlb0J6Uq5Sf1NvtBMi2T7W81u83G6ZPzgd+tNVvDA5VyLrdNVMf3qkODOaW1vCBot2Uadfe2HYt12s04TAYGhjhPNne2TNsdHp+K281yubymVL1ev3379sTg8NjY2PPPP887+0IFn3n6caEc3TQvX15qdbnrWIZhSSnb7bbPt3b2NjnvMEIs3eRCGZY1NjnjGGaSCsc0Ygp760vlkVPt5m2FtFiybyMsLm60u9FebdsdmKTM3qu1VpaWncKoAGOnvh/uyKkzJ4gauLlYZ641VJroRimPICHE/AnP+8eGftJAjv6M9OEy2E+7t7kf9ZtPIsXmxmqjtiPFVMfzkzABno9Cj3NuudQpFCDFvdsb3//2t1XsJa2ahZxIkSSp67qpgijxBqpD+fyg5li6rgdB0Gq1NjY2ipbjmtW5ubn2pnJti9rW1p63uLS6vr0LShsanUBglGgSlYKUMoWEkhQZM9qN/SgKjx07roQMo4TqhlJSY3Ricrrb2WK6BlxyJeuNsNONSmV3ZaNmGaYXsHpXeBKGJ0bZ8BhXbGK8mHjm1bfe1JfWH3h4qGKKjTAwCwWM7t1395NKvef+qQT+aOjD3lCkSNZuLzf291aXlhQzSwODkkc7G+sS5MTUVKFYdpj1mFu8eentq+9chrATQEtnY6EfKYlW3mY61QzLj3mBKqVUHMeu6/q+v729bbIisfPPPvssauTFN9564YVXhkfOGGYhDBNJaJJwQgiAVEpYlsm5iGNfcBW29jr1vYGhScZMnaiJydmV6+8ODg2nUhBme0HEhNB1HZS5u9M4eebYdnvH1JzR0XyqMF+uKJ0YxNaIpTESKBmAUWursBMV3XjdjxHGP9TJ/DjTp06sj4Y+bNOo3axvrN7OOTYj6FimbRmB3+20GmkaB1F4a3Gh2eoMDg6ajIbtBiShxlByrhGtXCoRioSQUqWiQFtZWdF13TTNubk5SunW1pZt27Ztr9/ebLd9r93tdDr1ZmN4dHRodMQtFpRESrU4jn2/C8gJQSEUIVrSqd9euM5AUaabbmFidi5VxHQLjuPYluN5QRT7xXLJMHKXr9woVYuJCCIeFIq5kYGKhdzgQZGInBReo7m2c7swNGzmpra32zrxckYsoo/6cf7EqfegP2XgTyZtrm/s7u7MzExdOHfm+NyswbRWo8l5cubcWU3TNra3VlZWL1++evXq1aDbtXQ2OjSYpnG5XD575rxpmkjU2MR4sVC2bZsQsrS0pGna9PT09PT0/Px8HMevvfbGytJKsVg+Pn/SC4Ou7/mhv1fbJYRlScUKpK7r2WvGmIi8lYVr7VZzZ2fn9uo6022im1yoBx58aObYHKWUK5nL5TTNvHljgYskRZ+rAFSS+E1/f8NK/AnXHNFYzrLjxBudni5WZza3a1J6+Tzr16zhTwKxuxJl7z9/8n6pH+r8/mwYChQAECQAIKgsHRdBgmJZ3yeJh31fEaB/Z/QPm/r17+2v0ffrE3vvusEGs5JUSqoiEdu27bWa5XxOQ/rmH/7B9MSxwZmJKFfxu+2RiZG11aXKwPjZL/zFkZGRhZu3wm570FXjVWNXTxGE5ZSbKZV2tWGWmhG1dFdTvNW4PebWQZHK+FBZkWPzj0Zg0fLQC9/50fHqyLrvDI6OTI6FIG5HwXa3sX+iNGGV9Ci1g6RdLNv7e1IloGuiVMIYRC5vXL72RkqcocGJwVJ+du6Bd95d+7k/T0fPful3X749kdsaKpH12/vDoyNX3nj7Sw9OvLqqau6MOz8Wbrw5SEXYWUuKY5sbHW+jzqcSbX682SDx2tbsmNtU+x2tpIHSlGBKUEAOSiAKAnq/hrx98sN5n/XJ+vho+jUx+6BMNtpn3fZWw0+zBMbsGaiDh4H3l1L/ySApgTKUUjJCpUh1pumMra6udnxvbGws57g3btxIkiSXy7VaLdtxHMeZmKgSQl5//fXvf//76+vrhBDHcbqeF4YhowhKIKLt5qIwvHL1kqnr66sraZrqut7t+q1WKwi9gYGKptHx8dF2s9Xtdo/PHpuemrpw4UKxWIzC2HFyhmFomua6LiJGYZKt5mql8rnPfe7iAw+MjY8MDQ2VKuVmt7uysjo3Nzc8PNzteI6TK5fL7XZz4dbS6PCwRiSPA8vQ7FwxQc1Psd7yVBK6lLsQsDQoVYYWdtoxmqbGGApUkigAhZ9Uh+U96e5spI/6ev43E0pUkMlXonpvJaBEkACSKIlH3n5kl/khk1ACKUrFmUZASMvQNAZX33vPsMxHHnuMEFLf3RMp39zcTNN0fGrSdd1vf/ul3d3drDXZ1taWECIIAkQqeaoTaDfrYRiPDI+Oj4/qFCulXM61R0ZGmq3W5StX/G4XpEDF0yQSPPU87/q1G0nCKaWWoVdL+ThNuBRJwienp7/6i7/8+ee/kCsW1lY3ZMpdyz5xbLZcymsEFcDg6HiscHtr33E0TaOtlqdr1uTUOGPs1q0lkIpJ4TW2NCYLQ8Opnme5AU5Mz+vokLCgpsXtkbHp3YB1Y2FKn6FkILJNXAICIKAiH8uOcx8s3S2BP+wF94GRAjzgXokgUQEBSQCIAqKyBwhEAWbjkwsgkZJTBgCSUgpS6Iwlfrp088bs3Fy1Wl29fXtibPzY1PTCzVtOzi1Vym+99Va73T5//vy5c+eSJBFCVCqVNE2pxixTH6kWUHKJUB4cGhoaKuVsGYeOaRiGsb29e/3mza2trUZtf29rPZe3t7Y2HMvqtFpxGFPA2t6uaWmjo+PFQjlO0nqzubOz02p1DMvOl4o8SUGIVmMv6naV5O1uZ2RyqjQyvrG+W6s1dYMh6PValxCoDpQYtdfXN4eLORa1NEjcYqkZKjNfNa1cjJpm2X5jP2nsAQczV+k2akOkaahEI4IAKASFJLObENVH9dx/YvTTKoERVCZmASWAJCAz5aknfjNpTEACSLzPglUf5HV+yJQpGIQQoiRFQCF3Ntb9dueJp5/a2NpstVqPPHhxamJyf2e31mhs7u6USqXTp08j4tLSkhDCNE2l1ODgYMKFodGxoYGcpWua5oXR2srt7bXlkYFyMZdzXXd8cnrm2HHXdS1dmx4fPXvmeN41pyYmH774yKn5E+OjI0PDlanJ0b1aI4hjojFKtM3tnVuLy4Efxgk3KDM1fXt9XadQzOdjLsZmjs2eOnf16s1WuzE9PZnPldfXt3Z3dxDV0ODowq2VuanR8YppQAQEt2rNJBWYxmDlcwNTcQpRu1PbWCvm8o3N5RHWNjHVQBJUAEQqlJlq+ckXwD+1NjBRkig4lL2ASuHBW4kgESTJXitJDtj7k0lIIasLJSTXKEuTaOH6taLrFEqlhYWFseGRnO2sr9z2fT8MQ6Tk/Pnze3t7t27dMgxjcHAQEbMC7kw34jDwmnvb6+udTmdre/fWws0k6JqM7GyttVotP4w450mS7O1syDgI/Q5BaLeb5UI5DOO9vb2cYxfyVsJTqZQfRs12Z31ze2tnlzCaK5YKubyta36zCSJpd5pRHBcHhmZPn9nbbTabtWKxYJl5wYlUvNmqh4G4tbBsUjw5MWDIIAo7MY9jr6PHXUiCQnXYKY3kTJvFvoWysbOm/LqOQkNOQCoACUQpBAB6/xK47zx/QN//wOmnuCZW5oImILPKxnjIpahAIaACgiB7b39q7uv+Wr1QipwnmqmnYaRZWrflX796bXxk+NqN61ESV6vVhZu3bq8slYulmcHZYqX87rvvJkly9uxZFOkr3/+PUsqB4YHmzsbo5Mz+9uba8uLWTt0wS5phcJ5Ojo6aOvnBd3/oJYwLEcWpFgTvvfMOAbjEalsdQjC3t3q72+4Mz0y292u3quAMDhUKJdOwddNEcJVSHS8wGDNytuTC0rU0DC5fXy6OTDPTGp6aNXTn7bffHhisVCvDCfi2bXa8ZugnCW9u3F46ceJEsHC7Hchy3o3bNUtFrmi51rwvcwaFsUqxvddCqntxqjsCgKSZ5YQE8GB/v+/Zv8918pGvq59WCXzoc5Z3v82sXjgcd95+MokQwpWklAqRMkLTJNnZ2hisVPcb9dnZWY2y5aWler0+MjJy/PjxxaWl7e3tycnJoaGhVqsVBAEhRCllmiZXMgiCMPBcyz558uTExISu6/mcUyjkXn755TAMz507d+rUKUrJ4q1bBJRtGZ1WO0mSMIjHx8e/+MUvRlGwfntl5tisk8+1Wi3TNJ/7mc9/8UtfGhsb87p+HMdxFA1Uy5Tiyu0lRRCZZrt5y7Jfe/1H3W53amoagMRxrOu6rpupVFsbm8OVgk5kEvnlvBM099N2fdRFi0EYxu1mq5xzgyAoDY2jXcq0rY/QW/lREWP4x8oH/qh2IEWzDrv9Op7fTQz63OYHlIf8QYUu+sV7aZ95lrE0FEbtds4xQIWv/+h7lRwzMLBM5+qNq8MjY3bZqe/eCOqhMTt+bPYM2gXXZDkmulvL3v7G6MhAJMJQ19Lm2uyJYyKIIUkefviZrYCMl0eHxNZ22+uyod/9wbVnI/3cAyfAIGPbs45hpiL3+V/62YmZ2esvfmN6eurbb196e80/O3+yvrS4sLk1OjASr676c3uPPvEz3t4uKK3bXWkkU4E1FAbBU09+LufQ/aW3JuZO5EaL0dKl9R99y5if39lbt8B1c4U9pMgmXnz17c997kEe18JW2m34kPpr7U1mVmfobULsl9++9ubVW+NVN65vRg3rF57e3ih+9r12QYrQ0lKPE80o0EAK8/767vZfDf3iw/3ykO/rtH2pLy7jEF/waVXKn27SddZse7mCwwh228393b3h4WHG2NLiwtDgyGC5UL/NGWMAQAg5ferEC6++fdnv1teKO9ubSeC3SUqpyhUs5ACEpalXKJT2a7vSGpyaGDfqbSXh7Nmzpr3/7rvvNtv7T37+S089Za1duUpUyIgkChr1ThivxO7IyOio4ZpBoqqDI7cXV4UNi4sLmxtdkQb1vU3Z3S5MdKVIbcsILCuMwmazWeh2Jkcqy2/WYKhsuKXByWNee2t4xA0wXV3fYVW8sbimUG93moqx5n59d3PNtltmacAZnJwcHyaaPlQtaoPFoF176crqwPn6SH6wHugpgMY0BkLTNPFJl8l/3GSGj9wG+GPTx+v671eSKwRKCaNIlWru762uLM+MDm/vbvlep1wut/Y2tjdv1/Z295XaaXjWq2865cHVG63LkougAyLWkaQ8SX0hFAgRcyFLleL25kZ+KlfMj5KApalgjBkGrdf349S/8PizY2NjRaoqRb4TthZu3trZrmtGxEYLuuNwFIOTM088W7x+5TrV/HarsbC7fmLI0lWYHxgBqbbWbpu5ytjYSByHXhIt31yo2BoRIZdCaKZRHV9ZXTptO5q/XyiX8hVjc7czNTVFWAt0wy5V7SRkcde2zVLBdSsDQcLz+ULBnbh26Z1L+/hoY3+0MB5Qc58bOUPT0kQh+elfn/em3n19KoE/XnS/Cy6Mw0IxJ5MYCKwuLe7tbGuSx543NDrYru0mcSCT0LQdwzACrm5fvTw6MWMySkTK/XbQbWoQ2o7umPbyViPvuiYljuM0k8g2tf39zTEm40ju7+8HoT80NDgwNEipnqZienpqbFhFW+TStfXtzb1CZaAyQpFCo1W33VKxolHN8v09akSR3wr9cHiwEPiJYxpExaYG5XIxSm09jISUkHbPnZyLQeq5os5ZyGyBVIqEo5BMT5VdGZo+dcZe3qw7lUGSr5LG0uDIoGYR29AhJKkSKTNagurjF712h3Z2NDqSSAtRIYhESqCf8Godn0rgj9f1368ElpJrGo1CnibppbfesTS9WMyXqkWkWhR2GrtbSnA7V3QK5bKuD45NWY4ddTqbK8uURznbsgyNMYJS5gsVUMrUqa7rg8Xq2NjQ1tKbJ+edWm3fNPXBwXLFZefOP3jq5LmbN66stTa67dQdf5xq+41mSyAd0kihWHadYHt79+23b2Y9TeM4LJUKhAbVanVjo20ahog6gW+1vWIQ8zRJ/G6HEvnoQ+e//+rb1cHh/Ghuf22h7oVhlLQ7dQpxfXJ6b7dZLpbevbEwOjgxNjhz66WFIIqZ6JguOJrVieL9eiMFNj7/sH/jh16zXhgetCRPk5QqBPKpBP6UfrJ0vwtOM40wDA1GN9dWNtfWjs1OX7hwJpd3Oz4nxbzf2i8UCtMnzlKz6AV+uVQo5ty3X3/tjR/9qOwYU+NjlkHCqBsmyZlzT6wsLbqWls/nzeFqqeRsxd1ioXr1rS3LsiZnR5NOa2hwDBTdWN9S3vqGRU4NU8NxqwMl3+/eun55Zrw0ODm5t71x/cplg9FcztkKgkJhRNdlkASUmX6nvbZ0k+Rq281uN+KuaSXtVkE3cg4JOo00Dk4+8OTexuKV7/87jPyCq3HOGy1/aWn1wvkTts40267OnLz2ktXuhOUCM0DlHDNN/dWdbZ0Zbq7U1EvNgA9AMqBhk6uEWpphCPEJL1j5xw0j/cQC1h9z+kAexn8CUY1kAaS3Xn19YmT41PxxwzCCICCGEyQ8DMPB0Ynzj3zm4mc+Ozx9PBUQJKI0MDg4POLmCimXbT8EprnF0tjEpATq5ovDY6Mgxc7mhsbQ0MD3w1arZZja4GAVAPb2aq1WizFSHjqu9Bzo+okzc6OjZb+529rflWGIcTRUykVBJ44CwzSZplHb3W13tja3d7a3o6BrmZTzpNPx8m5u7tgx1Ew/6OYt7drltx3HOTZ/qumnocRq2SkW8jzmkRdYDM+emo2iIOJy+sQFrnTHtE2QJAowDNu7e47GNBD28LFGovm1zSrzDYYRUA4/9VDKfs+994Wf2jjwpwQAAFnVZQT5zttvPnD+/MjIyPLK0nuX3x2bmqVMt53c4NAINSxquqmAt967sru3bzpusVRRVE8FUM1guhXFKSANw9BxnOHh4VardePmNSSCp3HOzXe73VarwTknhOVzxUqlYlqGlRvkiiWpKJTyJ07OfuYzjz504XzBtAdK+acef0wmSRxH8/Pzo5NTI+PjxeqAWyiKlBNUp0/OP/vZpx97/PH5+flyschMUwgxNTm6cONqkkbD4+NmvmjkSsNDpWI+t7+7t725ubO1NlgudDstP4hm5s4IRaWAsNup72z6zbrfaliU6SjKw1PtmNa211wV2qaWCEzT+4sh/TQSIagj0RUxJBqCGARVb1ACvQEHOT13D0R1z0FQ3nNocO9x9LxHB7J7D0ruPfqdt+8g6QcyKOX3Ne73OIjJPYcIQ0fXf/DdH5RLgxcfebLWSRTLm8UxUV9845UXqF4anzxHUnr51df393Y+89zPuCx999UX47g9PFZudPa5jBnDcj5X21zDOBibnPnR1TWrOHBirFxWga3h6LHTX3rqF6Ld5LVL7723s7ETkjDJJZCve17ciXNsSKjBKKGDBa25u5wqiFJX6M7ww89tdC1TYrFYvbzczZPhsRnDcBLP61h6bnRgyradjdq2cNTg2c81zdHy7Fy7vnLlzW9Xh4eOn3/i9krNoe7kcHVoQPe76+++9lLB1MqWWrn6w7wpKi5hTJYmZ9vmkKpO6KY2YIds/QeObE7On1rfDw2q26nniE7Jgn7zhsA/kkFQ3HP0+z4l8p7jzm8JCqIkBUFRsf4qh9ZnECnvORDJPccRkNT7Rj9Cde/xKWVk6Fqapm+++frJ06eq1ere3k4cRV/8whcWby1MTExMTE0uLy++9PLLlOFjjzw6PT1149qNra2tgYGhsZGxYrEYBkEapZblpFHHtjRUMD05eXxmKg09JWJTY4p0r9164/KVNxvNvaDTaOwux+E+gXhnYzWOutWSTWQSBV2N4cTYgG2xnZ3bod+wDMg7RESdrfXF/Z3VNOoyrlVy5fHBwW69dvPKu3HXM4GGdV9JOjI8Wc0PFAyjubnlErCYWSoPtdvdIIrtfHFq9mSuPLS5uW1T4aBfa3tarljrRInSmJ1ve7HUrO2G5yWqXq8TmVYK+b3tdYPIStHtet5H/Xw+dCIGcANTDbiuUg1SCtgbWWpeNhioew6q5D1Hv41AEXXP8QGbDj9x+rCfU7/zGkxbunWz2Ww+88xnlleXd3d3pycnL5w522k1Fm8tXL16mWrsxKkTI6OjQvKFm7fKxUoapwYz4iA2NJMCFakI/chr7s/PzlAC+7ubCzeuri1czzmmkrI8aDhFqA7nZyemSpbBw/r4sPv44+fnj02amrRNqbEEZRx5zbGR8iMPnVhdX9nb3/Q6+4r7SvqCe0HQ2dnf0kjOMXIDpWIatf3WfjlnF61c6iXVoclSddSy3JnRqRtvv93erTumDdTZq+23u1695XspFZq9u7s3OZAfJH6SpPlidavWavmJ7ToSYXxyRjPz63vNzc3NbqPmmFq3vqtxX5dxkiQf9nP5yIlZyAUoqRAQlVIpHMTNjsYzlFKI9zYn+q5ceW//tujzA9InfJKllXz86cPm4X7hJRT82tWrw8ODhmW++cbNcrk0MjS0vrLcrDfanaZVKE/MTg6NTl69fiNNU1vXxkdG87ZDJWysradhZJsWQ9LcqwVBwznhXL12reVFjAhTtU585WLK+c0bt3RTm5iY0nRbBrzeXDB19FpOHPm8vSvtPCPpQLVoMirTSHC/GSayaKGhB2kcC1EeHR4Oedxcv725a2kiV3KMgQHHhDD2O3WPKiyN5ZubbL8bPvjQQ7/9u9+9ce1yaaBqV6v1rSvVwelmN6w3OqODBa/TOHd6dq5qXt3fGM7P6hTSoG2gkp3awNCAZTohLTGtILuh5Gm7Uy/7NSW0oeqol/RDYn281tV/8vphJkmUQglKAACCEgeMp5TKFk32V4M+DNznxInq4x7T+3SR66tH3/s48gOb/w/mQB92GZd+88x9f2NlZXxi9Pqt60jx+LGZzfW1nY1VnZDPPv0Z6hSXby9vN9uU0pmZqWIh95vf+5bi3NBJ5HfSJCjYBQTR7jRci/m+30zCQrFqadxIw5xjX7r67vVrW0NDI2EYLN9cgTRN4qabt66q9JVrS2PHzymldpcujw6Uzp4/02631zdupyyXr4xVh/iykVNoHD95YfbcE521Wy99+5vdJKh73oiu65Z5benWxvLW2RPzzAIt7+x1g2ceeQDZ97793W9OzZ91K059JXEcR6G+tb2/3+jubuw/8/DJ03MjN9dWRceaHio6GJOobqcNB5zBQvFWO3INAJ1FVPcC35BhicQdGXpgfKjP5SMn5hAhFQpQSoIElSVBK6UUKAV3eLjfAsJ+Rb36dG1N+3BeP0Er4acDSXO/O+gHxfC7m1u3V5Yef+LRJInjNDKZ09zf87tesZCbP35sP0iu3rxx7MSpzz/3BQbqrVdfX1y4lsZdr11LEw94omuFJIoUD0dHT8ydfyjRS4Qxv7ZBA8klvvrWe4E/ZM1UCYSdnQ5wP2+no2Njhp3L5wfHp4/bJjs9PWpTWqxWdjbea7W98ZHputIwlQXdyjFjuDxYHJneQdW6cHZ/YzEMY40ao8MT+/W0be8XHc3fb48PD9y08oV89cKZs29dum5SOjs66pluu96wLKtacDVd3/dqC4u3Hz47O5jTV29dV8wEJct5x4LQVAmPvE6rpTpepTAoNLsTpiruVirC85pojPSZuY8oCaefJtVn/fyvrhNmUimklIBSAQAwij2mlVL2XnPU7+tCNbh3lUkl710DNO3Dp6TfjfVrcvhTUtDsg1K533zjtZztOI7dbDbbXrfsujnHrW9vW44KgmBsbEo5eSfvdLz2ys2F3/0PvyNlRCDd3FhGxTWqNCoVk6PDFd2wBkcmsDDe7LQNSIrUKFYHNLuwfGUfdTU5Vj11cpyGNA6jkSlntx5/9Zf/0tDxOb/bEq2d1196ZbsRhJ229eTpMpJ3r16uLa8OILBOa+HV14zK+t7ydSp8nStvv7V9Y7Oa33U4mSgWRbPmL12vjAwPmLnOTmeqNPxG7YWtS2/a4XHNtFaWb82OT2hESxNpWs7NlbWt/Y5lWUurV1M0fK+T11HXqNRs5ovFhVtxo1sdmKFuQURy+daNeSTjkw/Vgg9kmj++xDRUBJErSQgoAApE9QhVT5GO++xYQtxbtdb6tBFN+jDYn6zGGB8cvfv2O48/+Xiz3rixcH10eOjYsWNevS7S1HVyQojxqQl3WC6tb1y7du3We5du3rw56YQKhB/4w9WSkqmSiWPpc8dnvZjt1BpeQ7i53OzUlCvqumEPjU0E/jsvv/Li6mju0VMnxpxYt4JiXq1s1De2a6XpuVionZ3a977/o1Nnzw1VbDdXuvzK7/3o9WUhxOl8Eu6s31je0yvjNGpFST1v6LwVXn31vYXru4lSBk2S7l707R9OTx7b29pfqQzYGjXDlGHHW10WRPrtjjWNrXZ7da9pF5zI89e2dzV7NFceNIpD25urawvXvU6zOD5f0Ksn52Y62/V8dXxo7myBnlh99Tffee3FR4rTwCof9SP6cAmvLG4ffZ8xZE/w9l6E6n3OrZ6go31s1KO+2exF9tfrg2wLBe39KjtvJv8ZmgpBIggEQVEQUJhFntwfvxgAgD6d2nVIFCBklbKyTQoIAJA+IansmIiogEhEdSgyUcb3vgF57+P0qwvdt1oxakKI7CmQI1Bei6lao1mqDHEBIBWKtGAbP/jud7732/98cuY4MRzNMEdGRvxWbfXWVRV7Eeq2bZumWSwWC4VCs9lcWFjY39/XvC1KKedc07RyuVwsFh3HyefzOVeP43hsbHRubo5pBFGZppkk0dbmehD4Io11neVcK+dYTAPJRTsyC7lyHCQ3rt58+Yc/aLd3L5yf/zv/+d/81f/q1/Zvb+XArpjFSmk4YTorFn0lFVQsy2o2m4ZhUEoppa1WK01TTYCU0jAMzlPD1MLQZ4wJIbTYVzYDldhBdHF4bHK4Wjw5vhY3H/vMk7cWd/YaseYae/urjb312bHZYxMnYOKc73U45wOVskZx4ebNZrM5WC1/4ZnT13fDHZE3S8Mo08jvFIrlWtvP25aUUgnJAEXKGSEUCSM0lPd2XPfLy+0nwEg/RbDPOqGsz/rpU9e69/HdvuJ7qnaIqCl6wCcISqmDv4elXo7+6q4jHOVeAKB9JDmhve+oTH0HlEpJKQQgIkFCERSgQsgquUkO91KY+3XrU4dfVYff6d3Ova8HJABIRQCBKCXxwB/+YVtOiJitlczvcGcyCVQHB4MwAUrTJDYIJBwWFm/s7e3ptmPYBdNyLJ36nXq33RRxMHfmDKW00+msry5uUQoABNJy0bGdIU3TlFKUUsuylFL1er1er7dbe0mSDA4OXL58OYoDKbnruohqaLAShqGp6wMDFQRo7DfTNGaEGuVRwdtREFUHB/78X/oL1bLbbu/e3tj8c7/45/1G16WmiaZluV6cUNdVGiVWQQihlGKM7ezsxHFcq1lRFKFPoijSdJqmKaXYbIaUIhKa10tCp0IkTsTzpbyiJE64Uri7u3v+/Pn/+N1XaEwmR8eQR7OzsxrQqLM5OTC8trGpYsMXSig1PTffbrc3NnYK5akgMcM4AiE0QqMgNJmW+k0EShEBGQGUUgrBEyCofzBPuN/G3Y+BFb/3RqDkvQWSPFyJ7C4eyATgXcJTKUUIZKtXKXX4AgCAp6rHokd5VUp5Twncr1KgdrjDKaWkUuqgHp1CwQFRKSRICBCJiIogYCqje+4UaR/vtwSCoKQCBEUQhEIEpYD0s5npwUYgswlHRVR2/fdZgKG/86/f9xWhqAg5dEAcKAKtbkc3rFQiI0gIFovutffeXrh1zbLMSrFQLA8KJf1OfX970/e7jqEzTCqlyshgIQxDIUSapp1Ox/M8I9WklJ7nhWEYx3EYhu12m3NumURKGQTBxsbGfm1XSl4qlfJ5d2P99v7+vk61Y8eOF3L5/Z39Wq2mUWYMDpiaUavVAs8vFvLHj00kqa8bZHs7QkTLtCXnjuMoxPHx8ZGRkbXdxSRJCCGmaWqaVi3bjNDR0eMmz3e9tmEYlBJdZ41GwzA127Z1AjFRnufpfjpMbZVwWnEAil438DtdIsXczPTAYLG1t+u1u6WChu1dltMLjNOk2/Fj02CVUiGO41atcWxsPpSKJWnK05zj+GGQsyxDo1JBKiBOEsIMQEZMppAmadjnydzf8xX3ycDQpxJLv3qqvbPeg4GPMl5PkyQ9r9Hhh+rgHRxl4N7r3mHvlsB9VBGD0gPNWSkJQBAlogIgKA4qhCqJiiiJAAgE2WETjLuOT/rkV6XAAEARopSSh/evsL93XSkAoKAIHJSuzZpc9Ctt0w90e79ONZTZJSECyswRgYgA+UKh1fUq5Uocp0gUo+qF730bRfrZz352fHzccZwwDDvtpkPlUDnnWmYY1botTggJw9D3fc/zut1uEAQWaJzzbrcrhLBtO3tkuq67rqnr+uDgQBRFXa+NqIrF4tDQgJI8SdLQi0Ex1ykHtmhiJFIoFipSSkop1ZgXeg2vMzkxevr0yX/03/yG7hiC4l5z17LMnGVqTI5UCp/9zKOMsf39/Xa77TjOysrKH/zeN2ZnZ4tW5datW0HglUqlyalxz+skScJ5eubMGaJpzWYb/HST2AbRWSMfaYA6hoF0Lf3Ku+8Yhm4xq91sgZSc826nNT49E4bdpNutlgd4tzaY00k76G4sAyflXLXleRZNIAotjIPER0IRaBpxM1fmCoRA+eGX7+i73vrwhepjbPVq1t+DgX/8LSIScXBv6hBaoQ6EA7mLheCI8dyT53c2gj6yConM7F4kCkESVIoAAJrs4PgyQ5rg4WHZvVmG9WGYzHKVQBQoBXjIyQRIH/e3lACgkAgFmS5wqLR8MFUL+x1FKXFwBwiYXSwoqRRDnSHwJGEAIo1vXbm5vbb86IUzEyPDSRzstPZEmjCCeUdHqUVxGIfB/u6O53lJkmTCNuO3IAFCSGZ2Zq1PCCFCiCiKNE1jjGXatabRg/+SRNfshEjOpZJEY4amGRKlo7t7ezv1WtPNWYViTil1+frNd69c03XDtnIx5aJFgjQmKHy/2+7UL71zNZfLRVEEAK5V0KnlmPlirkJBdb1mp9MaGi6fPXvKzdlRFHQ6HcfJIaO1Wm1lZfFS3RORiKTqJPFTn33CH45KhfLytRtpwk3H2theGRqu7tY9pdTJEycajcbe3s7E6Fgm6lnS9fzQyhUnZudXNnelopTiUKVck6xQLOcrQ1LTx508ECKUiFNp9cEp3O/zpX0KCfTT4AjtU/Osjw1M5IHb924G7ic5e6ovYu87Cn7MuO+p/veUPJnx3OeCROb2BgCFBxsSIhatu39wcCGE9c7S2y8AwO/TxUxX4oBjD0pXyuxtv2ZWnCAACKUIKomYsbECxD47oviAqpgROPDeEUIYpQAgpRRCRl1/qFTpdLxqxQ158qNLl2aGBi6cnNvd3a3v73Xru3HQTZIkjuMoSaM4bbdqnU6HUprP5wkxKCNEKUS0bHKES7UkSZIk4ZyDinVdT5IkiiIpJSLrdruMkVbDj+MYkQohgyAIQi9JIo2xxE+YYkwCUdI2rWKx2O36C7dWXMijqVFHNy0dQBFGu364fHvtlXf+IEkSwzAcx0FEwzCiCMIIKHBCDST6zm7j5VdeCyM/TVMh+Lkz5yzb3drY3ak1Ez+2dFsqpJQismK+cHvxVm17O+eW6916uVi5cOHMpRtb1YGKRmi73eZJ1Gk3SoXJbqtx/frNxt728NBAo1Hb6ybLaxuOoZ8/PZ+ff1ygJhSJYwFIkRJdZ0BlXxX3fp9jH4naj4H7mZb9jsMOr/NuhfMo4x21hxk54oXGO6zIVc8whl746egndxnVpA8HZ04pPLhopJRkPti8e6CWU0BE7IWF1fvpTsg67sPAgksgSnGFJLv37G0/sGwgNaUUASkzkBhmGoeSqs/Oer/1hPt8zgjlSkmlKCG6phFCOOcpgA7EZNCKouZW3NzbXF+85TK1ev3aOzdvRV4beSCioL6368eJZjmUmbbt2g61LMt1XaUU5xwAOOfCbyEi57zn8M84maey5zwzDMOyTM/z2u2273FENDRN13XKIOUBl77JnKAZmIaes2yehvXdHV2jpm6V8iVUVBJOFdWAUEocyyaaWe/6AhkHAQKYgFptPzOGl1Y3qoWSRJMZxW7Aby1tNJtNplHDMAy25tju6u2trhciUo1SKbnOtLfefOfEsRkRR616jUdo2bbBtNffeFXTCn5DUUpb9Vqz7XNJiF4TUm7HND80mR+p6oXqF59/5srNZar4z33xZzp0SNP1VMHGzi5QmqYxQ5SCU2re87l8UPiCvjZzH292PxuY9qpS3vPKjiq9GftRdvB0AfCIH0vhIbIqY6EeI/W/gXt/flTyE0J6PGxbEhEIICGEIUHEzIrmKfRYN6PsbdjHm0fVgWgWIDLf1cEE9KnYEKGmABQSpYCCAgUyu/QPGSdCKZESlQJCUNMyRYwKwfc3d25ea7SazduLt4Jm/fbN6y6R77Uau3HIo6Bg0YLFbEt3C/lccYDqVrMd5QzXcRxKaRAEElApFcYJE4Ic9RcezlulUrFtu1AoAICQjuvajDEAKVOVJImSihCkDJVKk9QTkqRBjAJRqELOZZamES0Ugie8UM1FYZwkEU9SzbKKhdLg8IiU0t3vDNpDURTl8/lSpZymqRCiWC4NDE7UWl7HTxBZrjjAzFwcx2HoG7rLmKlrdrFkZksi6Ho6YcQwFxcXo8Ar5fJxmPoqZL5qBvWKxRduLx0/dZYQkssXy8MjXQ6nTp+v6UOnJgd0lXTD5OTFJ7ZjbW15MWGOQJ0QXYGSANmCowz76of3T/24oN/yuV8GlvLg+0zI98loppHeae64qpTi8h7BYQDg/H18m/EeAIBUSols2TNGmAaUIgBQfkdiw5E1xAySdTBiBBiVjCmdSkqpRZxMVvSCotlfw0CllBCid+oDU1kFvYvM9PmD63x/F2gplVJCSlnWDSklVzLrhSYBhRBcSpMGiJiVNRRScQlSSqEgSCUiSkIUagoJV0QoEKAcdVeQGRUSpVS/etQR6ohIACkqAKmkECmXUlrdrarjDA4NbG9sNjYa66trt5eWt7e3t7dXt7e3EdFxnHq9joitJCmXy6P5Sqk01+l0NE2TUqZpaubLvu8Xcnqr1SLAJFdp3LUsCwAI0CDFiB+YTzwKGWPMNCiljIc21R48M5mkIeeJZTmgjtfrbVAkCAJd17MupJWSffLUcd/3c4Vqo9EYnjvT6XRyuZzruvr+vnF8Bgybc04pHaxWfd+vlssEIJ/Pjw2UOp2OzUDFPgHggZ/P5wuWRg0YnRxSlHueBwzzpWKtVhsaHSPlIWKa1nCUqfSEUtMp+b5fYbEAFSioC09pKgxCFo/GASSVCgq9Mj7jCZISNjk20u12h0o28dq7W/jYY49dvXr1xttvlyFto6RCtRmxFBDgGlMYBznLDKJY13Sl+kCK+pS+SHv9QN4vmmifZre6uFtdzd7qeDdfHLzok0SUmcxKKXYXNpn3a0gt7hz36N/M8Zz5RbIzEoKEEFSgFFEHSf+gVOYVkgxp71Yz3uvxJwFERI0io4Qxph1q0e8Lhx45LxxaCEdtYEppxth33GYHnE+OageU0uyCNUa4VMAJVwCoMkApARBIetMMSlFQBBUFJQlVBBUSBSAQUCmigN5xcQEBKSALOEno67MDVJJm+o3IxIDUKALFIbdkWVZtb/sbv/NvV5dXCGCn01lZWUGiTNMMw7BWqyGibdtpmgJAGIamaQohdF3PbirbuYjGsq4LQgjOeRzHSqkkSTRNQ8QMSpF5rRhjhBCX5ZihG3ahkhumFBnTGdNnj+uAqed5WWVpTdNarZau64ZhdFpd1z0bx7Hv+5qm6bqu1IlOp6NSaDQapmkyxrKTpmlqmiaZHgUYzc4ehmEQBK7rDgwMdMPIEHrVHs8uu16vawV9enokEaGrU8+SIQjOuWWxJFGmlOVc0bIMKZ16ncVxrOusUilNTIw55cqNG+3a3obkgW0SkBEjnGI6MuBub6/fusZqO9srC0wIIZMkDRtuvsJkylBaQEFIlJQSDZQGEN37gfWhO2z9/nyBfhI4C0vexUFwGPVAOAzfHP66H2Q406KUAnYXKKhvABretzf8mMZLpJQZ2xBCGGNKCsSs6xg5LNxBEAkIoJRmC4Jzzjk/UNEpUgRKqaFRjVFKKcM7qIYfn5HezdNe/ElKpZSmaXeJ5WyxMkKzpQyHES8hhJSo64wKTIkkXHElBQEUUimRgoVKohIIioEgqLI9jxGmgEiFQmGqJAMQQASo+GAnJhKQohIKFOAf0RWRSp61FFRCSskZAZ1pjLGCYxaL+VLOfvapx83PPTs8OHjz5s1vfetbU8fmJicnX3/99TfeeCOfzxeLxbW1tUql0uh0LctQSlCKUkqlRJrGUnKv60ehTwkgIiiBICklipGcVTga6su4WikVxGkch8x8S6pESm7brmFYpWLVdqHVagGAYRjDw8MZMwshTEJyOafVamQnZYwYhoGoBsuFkmsWi8VMcvYe9Pz8dIYwM00zwwikaUoI2dvbOTc3Ydv25uamlLJQeCCLWnMpAGDQVY7jZE8tiiLLsvwUDcNIksTNmdmGVSqVNE1L0nRuamR8fDgMC3t7eyLqGASJCMuGkC4ZdJCWjPbWYpqmU1NTBZaYJErTmBCi8VBGvtRtwvT0j1eE9n1LtA8fSSGgx7TvdxIfrtjMc3S4wvs4TSk7wGKwu7xufYtkvT89+MjrrPgGEIIic/QCgaz3J6GEMKUOYtoEKaUUZMw0appG9gjjGHqwQUpQ13Vdo3rGwYcYhp6AvQsc0qOjX8hcrL3PewxMdYNznm0HmUzOdhydUk6RCCGYopKmqZCSoxSZGkwBCCgNlU5Bo0gJRilTSnFELmQqFAeSApegUmAKCVHyKA//EWSolCiCIIUSSnAGaFJmG5QgdNptkfJqsTg5OVkqFPe3tw1K5+bm5ubmLl++HIbh2NjY4OCg53nDw8O6YSEijxOepFEUxXGsuEjTVKegUUJAMUrB0HVd0zSNawxB9cRyRtl+l/gcUe3sNvZr257XdRw38KNcrqAbqtvtZlrx9PR0o9EAgE6nU7LNsbGxra0tAKCUDg4Ocs7DMHRNgxAyMTFRr9ezx1SpVDRN88PAsixELJfLvu9blpUkiWVZY6MDm5ubuq4jYmaBZ7uwzphlWYQq13WFEIVCIQgC0zRbvshiYCMjQ5ZlZTKDcw4yVeNDpVKJcz41PkQpjeM4TdOz8+PBeLlQKEwM5YIgkFLatr27frMRLcWpyBWKQaoME4y8q+lmmqb36+MggOperNFPEGZrWB2B2R0sYvE+ZGHvhegXpjqIaSK7K/5B+gWOj3zr6CG5TIgCBKpAKRAKpFQgFWiMMEYppUJgkiScS6UQgDBUhICmUcYYIaCUSBKZ3VUmyTN2I+TAJM6e0FElObvfo3G2ozOCBy6JOyji7OAmQcpolmLRU7ylpEpyBKVTTSIRUsYkkZJIDgQUAUlR6RQMygwKJiOUZA8MuJSJQqpkIiUhoJTqqgOd+SgPS+irQjOVaooCSgVSoWCU2kSZROm6HsdxkiSe5+3v78dh5Pu+aZpBENRqta2tLc/zhBBBEHie1+l0avu7SqmsTRkA6Bo1dGbozNCYbdvZtEgpOedSyiRJ4jA46vaDw+1M0zRK0TTNXC6Xpkn2OKamptbWNpQ0GUXGmJLmznbbsixES0mttt/ttONMP3fs8ubmJiHkerfFOZ/vxvv7+0qpWq02MjKSz+c3trcIIVEUTUxMtFotx3GazWYul5ucGFlaWmKMaZo2ODjo+34WKy7krcnJyWazGUVRmqbnzp1rt9vdbrdQKDqOUy6XW62WUiqLk1FKieSU0iSKKaVpmuq6bpomRaJRLOZdXdfdsREhRBZpMwzDtOKuF2vMRyQ5m7uWikgUJ4mt3dsL3Y9Q3dF7M2vr4PM+4SgECeoAHIwIvXF0Jb/vRR9sScbAiMjk3UZyP6jXwQ/giNzPqCcYe3JPCGGZVNMopRQSkBLSNOVcCqE0QwHIQ7F8UBlPKZH5wzNN+MAjpyQASMF/zEl2hznv0qsJIYLL7AWltLc9CyFMQ0NEjZHeRQIgAEkSTpFkx+WSQObfQ4kAiJQg0QkwgjojhCBFMIQQSoJAAUIqoQM5wGRmzon38zDpp0gBmCAIKAoEiQKCjCoDuCbJ7l7dtm2q68AYUsZ0PZFyr9GY53xra6vb7dq2Hcdxo9EIw7DRaESBr5QiAIbGMj8WJQgAgdcFgKymTBbspZRmYMbefGazlP3VGQlDnyAfHxu0TGy3uzxVp08d77Takqdpmrq2NTk+tr+7wzn3PG/29KkwDL1uwClXEsfHJlvNTrPZzBcruq4PjYxv79YY05xcsVQZ5Jybbl4pFQtVrA62/TBIuBclpQF7dWsvUZRp1l6zibrNOQ+CuNvtdgKn6SV7e3uMsTAMgxR3dnYIIVG3ValUcrnc/v6+lNKyrGq12u12/U6XUlqtVk3TrNfrQRAMDg6OjY2t3l42DIMxNjY21u12s+1vfn4+nyN7tUbEZYrG+SfVnFWk+RH9j1ElvSdjDhivDxvRg7JzgKAw06IBEEAe5uHfUZ4RlFL9kiIQsgIcyO7S9AS/t9eUAR7l3t5fQgBAKnXw+lChFWkaZ7L0kC2BEiRIKQUpZRRFR83mnogVQnBUCEpKmanQgqe9BZeJhQP5fLhF3bV9CJH2vtnjXimlrtHMzZN93tsOdI1KUAASECklukYV6EwjXNCedw0Rs9wGDkAoV1KhElQqQZUEQRUqBCKkRALv52Ho3+5SA0FAMZSEEkYoJUiIIjxKJOpAETAWkEqUqBHNYobzwgsvCCHW1tYYY61WyzAMXdeFEOVyOUNiZCZJD3QlkjBzI2VWaJIkuq5LwU0zB0cUvN4N6oRLJsaGixcfuoColpZWXn31dYOJn/+5z7RarZWVlXa7ffbM2PCQ0el0XnnlFcuVcydmB4btKIquXbtWHbIuWif29/c3N2uU0uFKYWywrGnazk46UHR1XQ/9llKg2cbM6JDf2A+CINbI3MRorNSNGzeiMHBsa3xsdGNjI01i17GnxycAIPYDy7I8puVtp0mZZVlBq+PYBYJMcBQClEERtJ3tWs4ten5IWWRZGEaQpHRvv5ukO34Im7v7SZJ0ApVp9Z1Op9FJLY036q2IKzNfnTqVgDCBa0T1gyn0pYzBlOoNBaoPzwHAIULrfcpz5o7NVsr7M4UAQfTtF50JXmR3Kev9vGcEESDzs6meVxgRsvjw0UvJ1LMwDPHAM47ZdWtM03UTMZBSxnEMPwb8kFIJIQQqBEXIwVRmHN6TGACQcWDvajM6enY4XJfZrzIeTuKQEgCNIoCUQgqRxbsIo0RKLiVIRYikFA3QGWNEKABQhCpApVQqUCiQUhpEgZKYeZ+lVIRgD38CUiJRh5itP+IpAmQqumIEGUHKCIXM+BBcET9KkzheXLp9+cp1Ari2cvvWwrIQYQZ+yKxfIYSmaZ7nBSjDMOyZ95mjKNunMn9eFgHKfpvxOQBk3uDepAEAJF7WuGh8pDo1NXFseqJd3zM1ePzRk4ZhvP669b3vfc+1+ZmnL1iWxYi3s9t6+pmvUkr39va2d1YMU33u4Sd0Xf/hH760trZ2dn760QdOSyn/1b/6V6PV/JNPPvnlzz/z2muvXbp06cyxyRNTo2mavvjiizQNvvj883NTo+vr65ubm6fmps7Mz9y+fXtxcbHsutPT09V8fnt7G9P0oXPnSo6ztbXlufmZmWO6riuFrVYrl8vNzs5JCdu7repQZWxsrNPpNNqBbuWLxWK1Wl1/7z3Lyg+Nloul0vpWrVgsVsx8sTLS2tlBWiq61uDEsTOnHpmaOL7vQ7vlm+4HAIdWSrF+WXcHWGA4/KuymjZ3cd3/qgqtDj5HdheWUGemOKSeloWICTkqdUnvr0gBEfEAcp9xFFFKccFiX9Eg1IjSNag4Ws61TNMQKbS6nW43kIpqpkOYnaQ8TBITJENCpdQUYVwRKlABgFQiY5ADsUkpMVDTqU5DrpQCzMpfKpJxDwV+qEGowzhwtufVQzB4anFmm6hrGjIdQAkFKuWIlCDLtj0UgkgJUjJ6aDoKISQoJASAIAlCgYgKKQNUREgueMq5FA4zOeecx9mk9VxryHR1GK8+GpeOMCGKcKlTpMiVUigFKoWUKM0wb968+Yd/+Ie+15VxrKTMOVYSpUIIUGJ7fTVN08ymze6RUirSVDPNOI5N0+SAlFJkGiKalsM51zXDDyKLMC7SgbzVbDZNx4njmFBqWVan0ymVSnZuvN3dsnK6xiDohGWrOD8+CdIvusW9vb3HH3783TffLeVKA6UBpdSD5x78/vZrDqWlij45dGzj2Wf3dzuTAyP5gjH6F/7Ur//6rzM9vvDg+SRJfj547tvf/vax47/EOZ87/gtX/2+vMS2amBx56KGHuGi98MIL86PVx84cbzabf//v//1Bmz366KP47BO/+Zu/ubi48Nxf+Kp4/Nzy8vLv//7vFy3553/pi3Ec/+vf/i3hb/2ZX/5LYfjICy+8cOXKlZPTpYfPfq7r+f/u3//b45MTx449UKuNv/DCy5bJPv/Uk9OjxYWFhVar+cVnn6+6JE3T11577cJnH00mzHajoedLpDxQOjaxEnQVQWZ7QJx7MgzrAxBKUWYyUyrZE8OAwOQdHumtRqUUYIZHkESBkgIPdWep7uhEh6yOfwQDa0rL+JjdlaCbZpBkpAcyF4BLQAQUaW/x9VRZzEIUR/bynkiUGY6BKIUKe7al5IZhGLFFaZzGgocx1QggYYzxNAYipSRSCJltEFmq0EF2zh3V4DAUlElaQFSEEEIB8QAW1psCPEqASZJIKQlIXXMZBVSYphzUHQ0cDj06lFJQQgEByAqGgZKZUM3Cy+RQV7pzIiZjikpnmfZ+J/oVSVQKBKDEgwyKTGAzSUCBEiLlXAqQEoQQUoJl0/r+3vbWVr1eQ8ENTQ+jIA78KPazLSDbC+48SE3Loim9XSP730zq9iYtC/Ye+ON1Xdf17DuapmUmYqvdME3N77T393c313Z1YlYGBpUM3nzj7eHh4fW1zfnjJ/d2awSZZVkaM0ZGRjqdTqvtG4bRarXmjs/VajUuHD+MZ2fmRkfG9/fqQ0NDhm7NzsxFYVIqlTzPu3D+wTCIz529sHBr6cL5B69dveHmWcfbGx0feuDiyTBuliqW7/t/6qvP/+P/z4ZlWbZtj46O/t7v/Z7rutVqtVqtbu3uvPbaa5ZlVSqVr3zlK1euXMnn84888sjW9s67772zv7//n/1nf7rb7SKy1159a2Zm5sKFB1dXT/7jf/yPUfq/+tf+fKPRAOHxuPXzP/+VVqNxa2V1OwJQMo0Tw3So5sh+qlOf6EwmujJ32vvMYHWAb76j0mbLmKBSgiiQKLPsdlAKADWiHTWhe7/qi6k+XOTsrmycJD2IU2HWjiGD2kmp4rT3S0KIIqAEICIgf58mdsjDiKgOK14gUaBEtuqzBWQadppGYZrGqaLMIFSTnCtEgJQAcgKEICUEUVFkd+0OScKFUKlMCSGEAKFIKUWRdYRAdQgUUaAUAUWUlEoRAAEZUCkMgVFimiYFJaXMwio9bu85ydJUZdwrpRQHu2vmVUYJEhUVoCQoUAgEQRBTRYf+c0SEzB1ACGmEUmXJzfKOvZCxnlJKCCkyKZ4IIZSUMk3SIAiazYbveXHg52zL73TjJDRNAw6x5Yyxo1sTPUKMsUwm42EIPfswS83JFkTGwBnbI6JhGIhoGYZppLOzs6Ojo0u31r3Ac3N2PlfYa9S///3vDw0Nzc/PG4bhed4Pf/jD6enpn/mZ53b2VvZrG5zzCxfO8RQ2Nzde+dGKadvFYvGll16qVCqZP3loaGhhYcH3/UKhcOLEiW63+9Zbb7muG8fx2bNnFxYWjh071mq1Tp48GQRBEARxHHPOn3rqqe3t7bGxMdu2v/KVr7Tbbc/zLMsaGxubnZ3NgGWjo6PHjx/Xdd33/anJyYsPPLi0fNPQdWdo6Myp0ws3li3TLOU16/j46ROTRAXDAy6FcHykSCmvDlVK5Vwn8MN64miaHzORgkoUNfpAIPswMD3IFz9k50MntMjyyI4AAZAgAKYyRQABElWG+cmEgGTijm189EU/7LE8TONldwU67mkCH6qpd6j3dfl+INRRIoiMAGXICCWEAEpUMok5IdSynJRjxMMkTiEFypRGURwkJEmJilIqMzlG1YGpkP0jlVSCC4kiRUTKsuWbyWwEFJmb+fBe7lxYtncAQJIkzWZiGIZrmaZpErxTAwwOOeRAlCmUUnIFXEgppVAIIFFmYl5IQCGVBBQKFYLLCGNZbCyzvTORKHUUCpREKVFmytXB5Oi6lMA5pygIIEWSufMIYY5tnT11+tr8ezeuXBZCUIY5zSXszgo6qjJkeKwMPJPFThhjmTS4o4wdxueOygo8gLJIAAjDMEeQJ/HkxFin02k2m4MD40srK4Ap5zwM40ajNTwcXr16HRHX1zer1cHXXn+5VMpHYSokHxsbMQzn9sraa6+9lisWBgcHS6XKjRu3FhYWzp07Vy6Xb91avHTpEiHkoYceiuN4a+vVd95559ixY+fPn7/87sqPXrq8vb39wAMP5PP5b/7uCysrK2NjY4ZJ1tfXX3zxxbGxMUQsl8vvvPOOlHJscoIx9uKLL1qWNTAwcPz48SRJFhcXdarlHff0iZOLN2/puk4UnD9ztlmri6QrpfzcZz/r+/6tmzcHBgZOzM/v7e3VWk3kia4h8Lhb39OcCSFBM2wO927m0C/bjIq7Vd+D9Ubet656u63iSqFEBQokIBAF2dujEKOjKm2/eLJAkjEFu6vsI8P3YUEJPYi7mLqd7fHZIujBAPphVygBnVKdoc5Qo6gRQhEIyJQLBYcpvgJ4KpEKQMFIVus5uxilFIJCJQG0w7z2DJ94WEBacokEiCJUKiKAUopEIaJBRG8qs0S8zPzMrGghhBIpgkJEaeiEEEreh+nvGZZCAleQcW8qlJQHebqoAIBkslcC8uzIqA4rPVF1kF8hhFCIiAJAKZSSHNlNEBEUEFCMUGRACZEi06CIpkMh54wMVG9eu7S6cFNyzghxbbsT+Eefa+9vpkJnYrmHY8leHzU6sugoIgoBSqk4jrOoklIqk2COY0xOj+VcZ+HWYrPVGh+fs51co7nz2quvPv300w8++OC3vvWtmZmZf/Nv/s2v/dqvLS4uLizceOihhzTNunB6vtGsz84UFxcXL158ZGB44Dd+4zd++Zd/OU35r/zKX9rZ2dnd3R0ZGXn00ceOHTv28ssvnz9/fnt7+8EHL46Pj9++vXp6/vylS5empmaUwq2tHdd1m8322NhEpi9EUfTSSy9dvHixUCg0Go3vf//7jz7x+IkTJwDgW9/6lqZpp0+fppS+/vrrtd39J5984oEHzyrgr7322sjw+MzMjOvmVldu7+zszMzMzE5P1mq1xVtv53K5B84/tl9riaBTLhTLbRG2W4475icx6qRf4F72AdWpHoPdJSoJZLkwcBgTApSAqPWcvkAoZl5vefTnd8nC/sjIA2J3ndcgB15cPIKsQMS8bfSsLM55kkAcCwSO1LhLAme/ZSAz8cgoEioJKjyI8Sou0zjmScI55wCEIGNMVyrKlAKCjIAiJCsVoCQQqaQQPZl2cJNKSBAAwDOdlzJBKUVUisDR3SvjYSklYZSnnHNOUVmW6TiOaZqZMqEOw1FwxPWVCCWl5Ae+J8kzBgeipDwEtBKhlEKiJEhESTQFmPKDe8z0YQDIGKZHvc0lTSMAAJVl6QKhoCQBAEOjmqblHLtarhzYsQBCpHDE9UAOIeJwiBXFQ2RLBrHqbUbZF7JE3DAMNU3TCQOADMzQA59yzqvF6pOPPVbMuaNjI81m/J3vfn9oeGB67kSlXKaU/v7v//7p06eFEF/4whfW1tY8z3viyccs0wlD/fLlq5NTI1Kl7U7TtkrtdntgYGBzczPDey4uLgZB0Gq1KKVDQ0P1er1Wq62urn7ta19bWlq6ceOGa2tA/L/+q3/z7/7dv/vYY49duvTa3/7Pf/XWrVvf+J3ff+qpp0ql0l/9q3/1n/yTf5Jd/9/7e3/v8rWrr7766pkzZx577LGZmZnvfve7lNLx8fGL5x5wXHtrY/PM2ZM60yzD3NzYCINocWl9eHh4cWkd0PD9aH1j79SpShCKZhCRNB0u0bLrUhlD6vOERiJlfVRo2g+Y0VPx3v8FepjndyCB4QAsbekMABCBIGYAewBAVGgY6hAE0XN59tNtAUAcOrcYvr8Yj0kFIYRSktlOvbXCaAa6AESgROgaEKSGjp3k3qpCxkoUFSIQBVJKzhNQGCWSS0gSIQVQypgCQCrF4W0gIZmsJoQchLZRCJVmvjWUPe1dykxaCqUUoUApYYxRikjvXMZRr49GDkxEQ6OWaViWlWGP1JEIc2/KDqxTqYQQqVAiM4AVAijBpQQFADJLYFBKEQAFfgJS3sFgA9DMGy+V7AUJATBD4YACxRNEiqgQyIGJLDMV2pE81SzTtk2dUd00Y4oaZcA0PPRq4hGvXi/Mlt1pphbdhdfLrGKlVM+zlX0hU7ZzuVy32x2sVoaHBjIpTQj53ve+ly8Vf/nP/uIvfeXLv/7rv/7iiy/m3MLFixcfuvjIiy++6Hvh8vLiE48/Q6n+G//8n/3a//3/XC4Xv/SlL/2rr3/jtTdf+ZVf+ZUTJ07U6/V/8f/7erlcvnjx4sTExKVLl377t/7t2TPnJyemLpx/8MUXXo7j+Ge/8vP5nKGU+vf//hvPP/8l3/cfe+yJlZVVKeHZZ5/NQNdXrlyZmppK09RxnL29Pdd1e9Y7IaRareq6vrS09Lknn7527er1G5cHKsVHH3pY08xm7Uqn1QINLzz8wOXLly/fuHL8+PEvfOV5pdSrr746ceKBPMu3m12VcqKS0GvauSplKumTXmr07xBywKiHzpTsL4WeTZvJnOxzhUJitt5QETh4gYgc752Ne5dmfoeB1YEkv/uyNJQGBVunrqllwzGYpZEk8bKRpj5AomnKcbR8vi/uDOGQ4RUoJUFyyUWGAYyiKItVZmgEAEiSRAhxWPaRYOaIUj3Ao+ScZ7GTLKgrhOBCcaESLuI0ieI0TtKEp6mQqZBcKi5V70U2lFK9GquGcUdr+PG8pQPprbL8wcMatwqVUuJQqksJR7ldKfDitBsl3Sjx4jQSKlHIkXKkR/rD3Rlw4Hg6+CfzI2a32Wk1W62W73fjMArDUPIEFSgQ2VxlW+qhEpREUdQrqdELLKkjkLXMNmaMZT/vlXQFgJ7NnMvlLMsqlUoG09IkWltbq1arjz7xJNO1IAg2NzfPnz//3HPPZZBGKeXw8PBbb731ve99RynV7fiPPvro3Nzc1WuXM1Ffq9X+0T/6R4g4MDDw1ltvfeMb3/jBD35w8uTJnZ2d3/qt3/nN3/xNzvng4OBv//Zv//Zv//a777577sxj66v1//c/+o1v/t4PHGvgycc///V/8e//x3/8L+I4fvzxx8fHx//BP/gHN2/ePHfu3PPPP99oNHZ3dz//+c8/88wziPj1r39dSnnhwoXnnnvut37rt5Ikee655yzL0nX9O9/5ThiGjz322NPPfcaLu4arP/T4xTMPnE4hubVy89GnHtE1Z2x0GoFWy6Xp8TGNKo0qP+igVPccVOE9R2+eeysnIyJF1uXvaA9AIkUaRkkU8yhMoziJYxFHaRTzKPI8z/f9MAyzp9kTKv2ot1wZTxVBQFRZyQvLzhEKmqYxloEEpVRcSmlRRyklQSmJQmCSHhimXIBSIERPjiGllCBhKFAiT0FwQGS93SVBBodQR00jzFBakqSpCAQkistEShn29h5EFFCSSgmBUgopOYDKMhuNtHtEpUQuMU4lQKJbJMtu6zlaMwmcLzpSSgICAS1d07XMWX3gsM04Ocsyzw4LmCLJqtkRKSTnIDgKQM70O9opHN4vIRB6FBFJNumSHGryzLDiOA7iiHOpAIEwRFCoXF0g1QBJKmjMVcQZFwyA0MSXSFsdeWt1x62MEgTUU85Ft13L5/MAwLlAxI7nO47jeX4u7yZJYrtOFEXM0CVAoVzyPC9JA9M0pRRIkIuo0xUKlFQ0lVQqKVEGYXdqYnJosKqUcKxpasWGq6dpur+9NzamPXJh4hd/9om9vb03Xn9pdHT0iccvViqVTqezevvW5sbqhfMnHzj3F69evlIous88/YRrF//g9144Pnfyq7/wFTefZ4xtbOxUq9X/+r/+b//7//6/GxoaWrm99LO//FUO/OXvfVeG3bjT+C//i7/zP/zT/+nta5f9oP7wI2e/8PzTL7300oMXTwl56nPPPfFbv/Vbv/Mf/+Opixft8kBpZPz3vvPisTMPnjhxIpTG3/8H/99v/Id/v7HXNfMDC2ubXsoHJsaq1cr17d16Kt5eXPkzv/ynhdKPnXn03/2bf+tz+uCjD377299GxNmZ+Ua9s762ffPGku/FDz/wYMdvQCF3/Ox5qlG7tpU3oQRQjxLbtjPJEUURpbRUKvm+nzMlIsZxbFkWISSzQQCAI03TNAgCxlhWpjejNFVSijiOs0BdtvcxxlIFPRsnFZIYRmbKmfXdLJeDUpIlXZTL5SiKTF0PgkBIbhgapTSOw5THiGgDUKYTzWaICAiUMoYZtDBTngllmbolpFRSYpocJOgokFKCAlSgpMwSfY/KokwPJBEcQCx6+t4BA8s7SUKZMMlEayQyWQdZP4ieJh7FLXVQ8lEehnyREFIquHgk6kMOI+aOgZls0TSNHCbEykN8dRaXE0IIApTeqTD548aGoelcKFBcSSmkUBKAKRQqzVzlB1rGQQReKkkIOYClE5JFtLK3h1FZBphCNlcIiDQVioLKSpkhIiqhpBISLENHxK7XjuO42WyaujY2NpbGketoABAEgaZpmT5pGMbQ0BAXaSZUs60nU20455ZpAkCWsqdpmmVZPRiWUkJnzHFs3WBxHHOeoFJJoizLyufzY2NjrVaLEDI8PBwEQavlRVF0/Phx0zRff/31DAo2Pj4+OFhduX1L03OWZbZaza3tNc/z9vb2igXrq1/96j/8h//w7NnTN25c/7/+X/4LwzD+n//Vr/3lX/3rukb+4X/3//ret79ze3PLcp0/+2d+6eFHH/n6v/7XDz300PSxY1/40pfa7fa3/vAPn3nmmTBJdNftdDqFfOlLX/rKww/XbNteXFgeGxt7863XHceJoqBcKT3zzDMpD5WSQRA88+xnlFJXL13+3ve+o2nGQw88+OSTT2SGUrVafe+997a2ts6fPz8/P69p2qVLl+QDD4yPj2qm1mw1lm9v7O41x8a9+RPnNcPJZlLX9STRpJSmDhR1h9FOp5O3bcsyV1dXCSGD09PdbjdOAgBwLJamaaflZVpSGIZxxDPu1YgNQlGQoITBKHKua6AU6LqRPZQ4jijQarWcaVVCEESl6yxJojD0I0+Mjg7rul5v7Kexb5tmmkK73R4brnQ8P0kkEwq1TG4wRilS5BQVRaCZFxhVhnOKlVAASgFXUgJmDQ2VQqXu8Ge29DP7JIUDfumxR0bxgTV74CTr2W9SaAdeXgWZYp+ZuwaJDyUtY4wwjWRqZNF4H6CUHBbB0zVJKWUaoQwJQaUAKZESkiQlhCBBKWWaSlCCMcYoqkOM19Es4mwPokpxRJKZOcCVAKmkFLy3uWSoGyE4ABg0A8IfGDhKIRzkLaXq8BpTISUIAEKI5AIUAFFSHGxtApUEBZ4XD1RK1xZu7u1sm7rmuu7QQDVN0067nqFTHcfxPK9QKMRxXCwWu16HECKECMOQUpphVA3D0PUDZGVva8vuS8iUADiOPVAtF/MFKTkBYprmmTPHkiRZXl7mnJ85c0ZK+eabb0ZRND9/MgzDMAwXFhbm5uaUUtnO+NLLPyyVc3EcCBkD8r297TRNT5486ZjWv/nX//LihZPtdv3Y9Ggadm8vXXv4wdNbqzfLpVwYRyfPX+h0Ottb66MjlcSvX79xqzowtF9rPPHkUK3eXFhc/uznfiaMksKg+8abb09PT+umcWzu+P5+fW1tbf7kie+/8P3HH3+8QsuEls/55zrd5sVHLk5MjGXJMKdPz3eandXbt+dPzM3Pz29vb7939dLw6IhuGlRj65sbk5OTE1OTjVZzbXONGaRardTqu12vHifB1ubtmZnpJPFrtVqz2QzDEACKxWKpVAKAxLSjKAo7pF6vv/baa4SQJ554Ip/Pe3HcbDYty8pUuWq1Wt9rXb58eWpyenl52XGcmZmZyclJt+B2Oh0Zt01GszQyx3FyIyMoRRx7VNc5J5TSUt7inANQQkgcR45JDc1aX1uOoihfyOXzrlKcp6Gu4e7u7UazTTWLCSVRUnrQ0YBkppSUglJEzIoTZ7KXHMSmEbJlntmOPWY7yqWIGB92cjiwIXvWecbnGbMe+loAUaOipzkfwq0VIjq6hURlFmMWaKUMCSGaTHu2a8Y3GQ+nKhVSCC6oouRI5o3kilJ6mB59EGBHIJkfqqdpq0OPtJTApZCHFrcUIgtTZ4DKHlNImXnTZHoUoS7vmENKACAqBRKIzMp9IyIQLrM0Eq4UCCkRFKOKEmVZTjFfuHn9Wn1/b272mBBpt9NK09T3/Uy6Zpm0g4ODWS5uJmCzy2aMZWJW07QkCUzTzERQ70PLsmQSmabp2GYxXzAMjSdCgWaZOiKWSqVut3vixAnXdbe3t0+cODExMWEYThRFGdZ6YGCgWCxubm4Wi8V8zhoeHnJzZhh2Xdf803/ml/K58qOPPhZ7AWNyfHz85Ml53+9evXqVUfU3/vpf7njtWif+5h9+51f+2v/+zJkz3/7m77Trmzeuvvd/+Fv/x+np6ffee2+/1hoZnfxTvzCORM8XKhcuXBgbm6CUXrt63feinZ2dWq1x+fLVqbnJM+dOWZaxs7t1/eZlL+g2WvVcwbZt2zCM537m6Vqt0f29Vq6YK5VK5UrRLeWUUrque55XrVZPnDjxu7/7uysrK3uuvrWz5rhWqVSYmJywrPbmxv7SwuXBkXHu16P2fuD7rutW3Golr8dxXN9bNU2z3mwqpT7z+AXf99v1jVZNxQlPkmTkxAkAubu7K/xGrVbbW1vQRLSzevv48eMmJs2d1SZAltW806ivr6/XarViseg3p1zXJYQoXa81g0wDbzQahUKhUCiEYVgul1dWFt9++23HsR555CFfxJ7fLRRy40MDG8vrzfpGvdFhUgIHgRwRhZQqRkGIIkJRikjgENKrOCglM6lLpAQBSimUh3GRnhe3x7ECDnBkPXhopqEa7A6yCo4seoOlRyVq779MmVmWQBCJkigTlaKAOyUUez/JNg6RCERJiETsaYxKKUUUKqVAZYEZhYwIIQgqJJg5b+WR+j4AoCSCVJkvnREAqhBJds+EHIAllVICQCglQMb8CObmqDNDISJKIFwKKUGqbNMgUhEpsmQsQRAztz8hZGxw5NatW+++/RZjbHJyfH9vZ3t7O43DKEky6yvbaDLzvt1uh1GQpSVl5XLu2i4zDJZSyjRNRLQsiwc0X3BN3VBKBF4njRMFgoAcGRnZ2dl56aWXHn/8cd/3EXF8fPwb3/jG449/JjPJ8vn8Cy+88Mgjj9Rqtcyi+853vvOlL39eCLG1tfW1r32t3fLffPOtzbXNL3/5i4SQldtrq2srTz755Geeefqll16amZvZX95y3OLK8urDDz36ueee31y91tgdTemA6bqDo6NvvvlmPp8vlUpvvPOOlcudf+BiqVS6cuXq8u31RqMhFOYKpYWlFTPH2u0mF9atW9eXVxaXlm5ev3FpdHTUcpllOn/q537BtfMCRBB5qiGCIDIdu9vtupY5UixQSm8tLa6srU4fmw2jhmFprW6zWMmVS45GMeeYhUKuWrZAmozkS6WpUqlkWZZhGI1G7I4PmaZpauC67szMTLfb3dvbE0JIgGazOTk+0Ol0Ao9Vq8XR4dKZU7NXr15jJLEMNVh1oyjyPE/XdctQD5yZc3S1YUCSJO3apgbVarXKmNhcXRwcHDQMQydioORqGtlc3WzVtjdu387Z9NzZE6YGb7z6Q9/3T5w87rX307A5PFCMQ49JhaiAS6EShYhUQ6KQABBAlAftRACV4Bk4CbJ0dgmoJMoj1TB6XHR0ER99e+DUQdkDhBzlQFN/X42CnvSmGcTsIFExCwgrpQTo+tFTU0qJUgRRZTW+hDzKRfD/Z+1Pf2XLsvwwbK09njGGO78xh8rMmqu6ulg9iE2bTbZNyqQJUzYtGvAXUrJhW4BpAwYMGIL+BAMGDH2QP/iDZIhSd7NJsQc22VN1d41dQ2bl+DLzzcMdYzzTnrc/7Ih4L7O6CMnWwcN9N+6NG3HinL32Wuu3fuu3AFiKG+IG9NoFC965BF9tk9WtdB5QjEAIESwSwoNgMcaAoPQW5UoRKYH0T5vnn/0TxXfCY4g+Ou+j8zEAUkSPIQSa3DtCEJxITqXkjBFvzR/8699/9ODh5z//Wa16q4forTM2xpgS3a7rrLVt2wJA3/eAMbnHLMt2NCznXF1OCCEpB05os7XWWgvBQYjOmeBMcD44IwQnBEej0fvvv//aa6+ldt/pdPrBBx9MJpOrq6v08M0335xMJnfv3q2qahiGs2cXdT168vjZV776pdlsdvrs3NrwX/9X/+wP/vBbb71z55/8k//j/+X/+p88O336H/6H/+hXfuVX/u//j/90engis/LLX/uF/enBD//iRyfH03fe+Xg+u1gOTznnwzC0g+qUfvjkqTHm8PDw4uqKMPbe+3dCjCEi5aIa8avLeVbIopZPnz1+8yc/Xq5nyqj54mqyVz88fUaBHp/sf+0rf+Xa9cPRdFRmZYAF8fj+Bx/8mz/4g7/5N//mz//8z3/wwQdISF3X6+F8UoyMb588vTefPavL0ec++6WbNw6NDfOr8zt37rz++uvB6a7rjo+PnXPzWTMMg5SyLPMPP/wgiYpYa/u+XS+XVxdyNpupYXCmGIahLMu9SR2cXi2uGImZoAOGUZVTDKePH9a5/OJnXw8hEEKSSvZ6vf6lr391FwbmDCgJn7l9XQhxba/KsuzwcP/Bw/tPH91v23V0nff+V37pK7dfujkd1wwoAcAQvI8WI7Rp+hBNS3kz7xsJEINJmtQnGbaYqIXJFX860Y0xIg0p3AZIgM7moMExBJ4kN14gG0S/QX0QE/Vq68nJJt0kSBKfJZVUB/uJkgmNkTEkgOg/LXO3CRBoinYRADjZ1LdjAtm31ankVDeW7zdMEURknKY8GzAgfJLpheARIiV9+MT77r7hnBtnvYnWBRfDhnfjPQL1LkAInAFjTEqeZ5wx8q0/+9Z777w7HteckbsffgQYVN8rpXiebytYQQjRNE2ySS5YEpqilCZ1O0LIarVKp5d6g621MUbvPWOsZCQER4BxLiL33sCoqm9cP0k+/NVXX10ul9evXxdCvPXWW9/4xjfu3n04mUxGo9F8Pn/jjTfefvvt27dvV1XFWfb51z//8NHd1bL7i+//+E/+5Jtf/MJX62ry+S9/7eOHp7/+z3/vK1//5af/6nf+xe/+EcvH44Ob2fiARLj74f2clpeXl0fXjh48up+VBWVZ13UxxrquQwgC6Xiy573P89waf3p6GgIsFitjjDW+bVvCyfnVxZ/82Z/86Cc/0ronghyeHAKF8aSIEd57/+3PfOZ1yvH+/bu/+It/9eDg8Nvf+2HqnUxqXlVVGWPW67Wy+vT8SZ6x5Wr2+OHqxrWbxwf7k1H1+he+tljPfvDj718tLggHQsjLn7lNCPmtf/avHj58+PnPf/71z32WUrpYLFar1fe///07d9597bXXrt28xiSbz+erdvWTn/ykqqqqmkSChDOg5P69h3fv3v2FX/iFW3vTTEhEfO+99+7evXvjxo3PfvazCTs8Pbt85513yrL8uZ/7OaPalIF//OETwdnh4eHTJ+2zpw8n4/L4aHL79q2jo6PrR+NmuWJAGCUco48RQoAQnHERt635hCJumSJ5kNtaKPoAcWPGMdLndrIL3mKCq9MglC3Zm6SU2mugEQEJ0pDi1BgB0FnxohvfMlEgUIMbzvMWOQIPAMo81xAiJDKGPgZCgL8QQ8YXInyZxF7j847q5NJTCrtjBe/iAqv1LgImjMBGk5pm4nlYHja6sCTGyLn8SzcyJnjKdVNeDSSA35xJAqQlwaQMyRgRjPz6r//61dXFycnJer1++uzxSy+9RAiRUpoNROkppWkVTiYT732EkDzwDnUHAK31arFO2S9jLBXeU0q8P8oZIZzTIpfgQ9s2VV0cHBwkqDn56tRR8Hf+zt9p2/bnfu7nqqrquu4f/sN/eH5+/rf/9t9OWpOfefmzT548+upXvp5l4jvf+e5ffP/H7dr+g3/w76/Nd956663f/zff/Ht/7+++/Mq9s7NnQOT/7v/wT/71n33v7vvvV3v17/w3/+JXf/VXr86vBh1ZlXnry2okhJjNZm3bHh8fC5kPw7B/cMQ551J0g7q4vNzbO4joKWdcsI8++ujb3/nz5XKe55kQDCD84R/94Ze/+spkvPfk9EkI7vT09F/97r9er9vPfOb13/7d3wkhzGazX//N31i3zeuvv9723eHhobHq3Y/uvHTrhGEAdNYNP3n7rWdPn37553/52rVrQojFYhFjLIpCKXV+fn7j5s3ZfJ4ajJAQLkRZVdO9vRhjEvRCxBs3bkgpnz17hoh1XZdlyTlPmrtlWb700ksvv/xyWkcf3f1YW3Prpds/9/NfSxlcVY3+6A//oKqql1+6PZlMUpH/7scfnT+7+sVvfK2u64uzJ0Z1zpDo7e2b1x89+OjDDz98/bU3GPguUTMZAwDmLAOAtLyCfx4DN5t2jF1wC8k0GQAACTECEL+BpiEioKcvJmM72yhEpSNqDQApyt2pzKYQF3Zmmaj/3mtKKQcOSHEj7xRDCJ5w2HR4AABYj+ADQKhElWAn50zcNAxHRPCIlKCg1DsI0fXaUIgIMHgJGAFYomnEaAEDABQbylsidQR0uBPfS6cIMUIMW4VZqISJAbcEuE2+DQCGWOWHwfkQhQfibCQUKGfEaWc1gZiNJwyhzCuj+n/6X/yX68XVwf4UITjnDo5OjAvFaGKtLZgmhAAw51yvFjHGxUpxzlfzgVLarNvkQgEgy7K96b7i2enpqWAUfAhKWYKvXT+Z7o0j8Yt5I2T1+OkFJUGtr25dm/zKN744OjhYLFYffXT/g/fvdJ32LnZdPx6Pj06uf/nLX/7xj988Ozu7du1a27bOuaqqSL/+W3/rr9nubLL/yv/6f/4PL54sjbO/8S9//X/8t/7uvXs/Pnv6wfzqi//7/83/6tq14+Bc21561ciMQkZvvPFqj36t2+OT/QcPHjgff+3Xfm29Xj98cO/p06dvvP4ZzpkaQrB0vlpdXcxWq8XNmwdaD4dHmZDi2fmDq8WzxWrWdm1Zl8NgrLWvvvr5+WoZyVBV9X/93/zGMAxCiD998/f/9M3ff+udtwSXRlnnwp9+yz59+voXvvDyvY/vHk72zvPS26is6QfrZ5dCsvG18f1Hd+/eu7N3lPVDp7wX4L7z/W+GQHgsjg8mqluRaN/9yduf+9znTp+cg9ey4LPl5ZPTR0dHR0mymwr03k/qUXTeG7teLF9/9TPPHj/p1o2UmXO2H4brN2+fnl8q412ggJTxPC/xxu3XLy6fEIkObVZVAbMvfOkXH3z4TpFNORNtq6wJdZ1Pp/vGGJodPb34UWBPNp0rO7NJ8utx27b6vJnxufROfOFrSk03X188XgxiX4xmX3SMu5+8mPS++PwYYwAKgYCDECNA3LKgIJBPd4Gkb3qvtw48zTBDgnTTopuaoyNaDxSIhwAQzEYRPxXMELYDho1x+JwKg0kiFxG9fw7U7TiSMca47VZIYfk2WCZCCEpNOqMIiCQm4Q2tQybrTFJtfC6LtjPf/973337n/bouAULbrhOLgBDuvev7FjAmnknCpQghQ2+WugcI1m24AUKIPM8RQeluNBrFGJvVMngnpRyPxyGEOx98NNgGge8fXHv8+FmRcx611vnx8XHbqh/98K07dz6az5ecSc7FatlcnF/1ytR1vVqtFotFogoJIdbr9Y1xaZ156da1Bw8eTKfTf/yP//F//l/9f+4/uP9bv/Wb/7O/9z89PDy8eevGzes35vOr7/7gBxRxf39/tVrNZrPDw0MpZdoHV6uVzIqzszNjTFmW4/E4zXPinAvJfvDD96+urgDdjRvXP/u5z5yfn/72b//2rL0SQlxdLsqydDauV12e53vTfeUZo6xZ9+tVl1gWlAjvPQJp21YwmVziZDp+443Xbl6/8Ru/9U/H47E2w3Q6OTjcN0bt7U2cDT/+8Y+Xy6urqytjdSJvP7j/5PDw2r/3d//9pFiUxLSXy+WTJ0+ePHkiJZ3PL9588wf7+/svvfQS5xzA9X3z9js/unnr+Ktf/UpZCS7gjc++cnQ8Xc7PHHqCbDCrvGJA3dnlo73pASFkvjrbP6ptLJt+EYk1TredAWpa1SqnOLBqNDo4Pui69vzqfP9o37ru+GSvHkn2abCHP1eNeNGQaGTb759/3ZpNTFKyiIARASIgforcsXt990LrxYs9jz8teL35Bimknj18UT0revyEAW9PA1TQ200hEgKUIUUkEWMkPmCIMXgksHGRGFG71CcQ04TxHYPKp46lCBgiIXFTGtoSMz710WKMNoYYY/CJpA1bBmw0ba+Vdc5B5EmJMFHKIuHGA9gI3o5G7OHTp3/8J3/26Ol5JQAArLU+OMCo9NC27XK5pIRxzjnnCEQrkzYpBEJ54JzHyJRS2nTWDRumZKRZJo3iajBFXt28cUsw2jQPZ6uzg/1rnHOlewBWS8gyeXJy8v/6L37z6ZNTrU3XqsX8PMuyEKDv+6//wjfeeuut9957L+2zXdd99rOf/cIXvlAT++1vf/szL//9j+9++J/+P//fv/RX/8bXv/71RTf7xl/5+tf/ys/nef706dPHDx8dHR3t7x8+efLEAjjnlsvlK6+8cnV19eTJEynljRs3Vus2wW/JPPJtqv8v/+W/vHPn/UQ8att1+lDj8ej+s8ecc2OCEPHiYj6bzUejkXNQjJgH6qxPnTYI0LU2xliWtTEuVcjv3r27mC2ttZPRhFLkvHDerFZNCA4wlmVZljibzT7++M7Z+RMkIISAiI8fP+s6/du/9ztpi7n38P5sNhuPx2+//fbp6Wk5osvl8tnp4yzLnp0+Ho1GDx48WCwWgvHr169fzB9fzB9Pp1Pv/aNnHy2XS8JwPJ5+fO/OfL5su9n5xYNXX31NSil4MZ6yDz48/+3f+U0p5fVrt/b3D7Oi+vJXv9irdtDN/tGkGn/xyZPH88XiW9/+tixZqxbYq+ezkZIlbLsDN7qN298i8zsywCcMOEBE3EwOwgiI6XcYP3k8L/NsU+Ld1/SND59w18/Pyu8Y0f7FX3nyYt34uR/eoNAYCEESCUWgEEiEXj0vGpMIW00wcM6lPkRKN8UhQgEReMY3hhoi+OeJwC7P/NRXDWEbQief7CESgNgMXfCEEBoD+uB9DBF8xMC59MEa5zNGTy9O//SP//CDjz48ONh37ZmUUmZiGPww9Np4H1yWEy5ASiIEjXGjEZtxzjm31sVoIMYsRy5SHThSSp3vCRX1KG+bhbW4tz+1St++ffv8x4+EZCF4Kbkx2hI4PNrvuvbPvvndqqpeffXVUb3v7EdXV1eU0oODg5Rvd12ntb5x48Y3vvGNk5OTpmn+1e//i//oP/pH1urZ7Krrut/7vd/9e/+Lf+8//o//b14F76zqQ/Thw48/6vqhKIqm749uXr958yYh5Pbt22+//fbR0dF0Or28vBxP9r761a9aa7/73e8mfE4p9eTJk/v37wMEpXtrzXxxicwePwAAwCNJREFU9a1v/dnDhw8ur86N9t6BNWE+WyXJPimKoTdNP9R1LYTwLgy96zurBk8pLXJ0LgQGq9Uyunh1cQkQ3njtdQCYL65u3bq1WCyWy+XJydGonn7h81/WCj/66P26rrVRp6enk/G0LEtCyN37H1JKX3nllcvLy2EYqqqaLy+V6U7vPkuauP2w7oc15zxpX073qst3H390/20hxGQyWa/XeZ4zxlzwR0dHlxez8/NzrU2WFS+99NJ4NH38+DEinp49nZyPOOePnz0o8ooQYjqKiLdv3y7Lcr1evv/h+2lkLM1NCPbwaMp2ZB3cNfjHjZHF+FwgLwmG/LSNbUfeb/8IU+z9l/dAvfi3O5PeObSftgoA8IBbQOs52Qvg+dCnn3bm6Wt6zeTYQwi9SZ5zN5ccNy2biTlFkYQ0FTGN2Aax3SB2JxO3gNmnMoLNRoAkhBB8SvsTQS1AJAQFEywEprV31nhwhAQkqMxCcOa9ikA/vPP293/wTYRuPDokxSh14fjQa2MJhfGkyvOccj0MwzCsIcaiSpo4MQRFOV5cXGqt9/f3r50cImLSuCtY3XXdpB7NZ4DES0nPTy/2D6aHR/vjcW2dPjw8XMwvi5x+4QtfODt/1vdqGHRRVDdu3HjjjTe8t7PZrCiylPm/8cYbh4eHN27cmEwm9+/f/8EPfpBl2XhcHx0d/dqv/drZs9XlvPsf/A9/5fDw8PLp6dXZ5WyxPLl+8xe+8YvPzs7f/fDDTBZf/vKXX331Vc75o0ePyrL85V/+5YuLi7t3766b7u7du9baJ0+enJ+fp37mxWJhjCqKoiiLqtofVPfDH/6g6xtEXC67LMvqepTnedu2acdsmk77FpHWNQ0BOJcAEAJQSrQynAtCWAhw7eSoyPKyzA8O9x49vd91XV3X4/H40cMnUpSUyK7VZ2dXjLHbt28vV4vZbCaEODq8fuPGS303nJ6eUorr9fLs7CyR7Rkjbbsej8eMScZYCG4YDKXIGElfs0wwxppmdXZ2iojT6TTQiAx5zjvVLRaryWTy8MnDo6Ph7OqpUqptu0511tr5ajmZjLXWzx7Oy7Js1frVV18djUaRxovZVYxxfXHKOWEZsBdXIQBAIJ8a0JI66SmBTyJYm4chRsA013fDLUQkESLipxv9t4DQrtL7/MUBNpPII8RPfXWp9pzQ6m0zMMALc7m33Vrp9fn2vQjZspIBESCN6nAhAGCImNQAECgDhhDRI4ZIaMSwYTRTb3alL0JImmOOiMY+F8178dNp4mPAxBtPUXbywEgoRJq6lwCAc0ooiRge3nsLEYZ+PSqyi/P705GX+/XQPykzYX10zlGuqxFBRMY80oEJL6L3MY0d0eg551wIFjyvaikk5gVDkgpigw8+IvWhLarxy69eo4RXIz6bnwmJX/jC5xjNzi8WdV2pYT2ZFq+88tL9j98tyzLP8xj95eX5weHel7/yhbOzMyHZ+fn5er2+ffv2q6++ulqtvvWtb11cXBwfH3/1ta+dnJx8cOe9e3cf/Mpf+3cOjm+vhua73/3Otcl+s1o0q9XJ9etSFov16umzs+vXb/7whz986623vPcPHjx49uzZ6enpbDZ7/PjxoMxisUjt+4yxx48fl2V5+/btqioeP3k4GtXT6fjR41UI4caNGyE4T5bGmDyX0+nYe7tYLBCjlJxCAQBa61SCKooihMA5ZyR47xhlyb1nuWi79eXled+3McaPP/74+OjaMOj1uq2qyaNHz956660850i81no8HlNK+743xlwtLi5mZ0DDql3MV1chhPF4HGOcTPYopV03FEVBCAkBhJAhdL3SUsqIZL5cWWuzohyG4e79B9VoZHSYTvf7XjVNS5CvV93Q2739yWq1ZjSPEYd+1bU6xuXFxXmRTwPx7334dkD/7/67/5Mbt2/94Mc/WsxXNPf1qFx1ipHnHbYBAEJ4EW1+Tk5IyhXbzG67ghFcQNhIYyZ5r83DT6XWzw14a3C45Yjsfh1jCsE/ZcabrlskuGmqTF/p7jV3kFhEROZSQAGUIqG4m44WKXURIKD1kLRtApIIkQKPSSw/lX43QUTkIeysl5AN+woRjftExrE7XAzxOXSfrlsAABIgBOM8xgic84B2vV4sVvO3f/LHaug4hXFdYDAnx8ya3qqriyuLuOnHKDLuvVeqU63KTZ5ar5xzaYRKnud5nis11KOM0tI5t1heJKALAJxeU8Kta67f2BcioywwHgDN9esvz65WwzAoZbTWo9FRlonVamWtHo9rmfHZ7GLdzm7evH79xgESmE6PDw8Pi6K4c+fOBx98kEha+/v7B4d72gzPHt87Oz87PLidZeLR2erps8dmuTo6Onn19deUjd/80z+79+ipcv70/ELbsFwurbWpt/Gjjz5CxOPj437QIYQ02VRr/fTpUynlwcHBV776hcXyylr9+MlDpYaj4wPvbdOsXnrp1unpadc1w9ClkxmP6/F43AxLAHDONU1rrXbOWGvzPK+Lsh/66ycno9Go73uteqV6ydn169dDCMOgZ7PZcrnsWgXxw6KoUp4/qCbLpRBiMV+2jfroo/vVtETEXvd5lY/3xk3T9Lp3zlUyN9oul6vU7eOc29/fh0i4qLSxxvZXVwvv/Y0bN5DEdaM9DIDChzXjhZS26x0h5PJqRRh2rR16t1istNZHRywC0cYDrjIoCGHnl2fvvv/us7OnlLG8LJQftIbT0wV7kTAMAOg3OV7ywztvjBL+2xy7wHgXG+/W+osr/qfNe/fDT0XXPqleko3Z7/4R8hzK3obNCAAEI0nwFQFGKaGbOW7ABPXR+RhDAB9cIBDTbkMBKECih5IYQyJ9IksuHmPE5D9xKzCQ3nSbMuwiCIwxxoAvDhtHoJTTGMOmb5HSddc8fPjw43t3PrrzQ2v1ay/f7tt1363RG2uGw/3x1WJOCEEiAQEwIgmEOsZD8FQrmxSwOCsIIc6Gle5X66vRaMQ511oTQtI4la7rCPX1qOiGxWRc+wBNsxiPq4ODaV2X89kaAJRSMuM3b97c398/Ojr6yle/1Pf90dHhrdvXr67OCI23bl//3OfeWK/JvXv3zs7Omqa5ceMGYyyRdRPLv8rf+Pznv/jsyeLb3/728a0bL7/8sl92r7zy0mrdffOP//jbf/HDmy9/5rWXXyWUX792rW3be/fuaa1Te8DBwYFzbnh6Op1Oy7JMVy0xUhaLxXvvvaeUOjjYe+/9R0p1gOHq6mI6HfdDRyhywWKMo3GdQK+Hjx5cu3mYmKRaDyEE7y1AyHPpnPMu3r790nRvfHl2OvQtY4xxmsa73Lhx48H9R5zLqmIffXT31q2X9vbrZ8+uspyNxvV8Pl8t14IXy2XriTs+Pk7EmCQq2HWdc850mhBijHMupPr50dHJ/v7hYN18thBCeEfn85Wzp4QQKeq+01I4o9dlWRVFOD+7LIqqWQ9SMiFySqlWAVEQIozxWnnj9Wy5ODg4Ors8++3f+92+GyjlASHPxtbqWbdmjcWYRoEmDgBqeIH5CNtaa7ZFiT+FvhrIYUvhCCGk/wHA+0/M490Z82b20k/lyJ+KSHeemYKDCBuK1sadEkT8maMreEAEQpBQCgSfe2FAQiKJnkbwGF20acVo8hx1354KxBh7ldqbIHErcUuftPx5x9KLuTrdMjFTH3LajK21FsXVajGqSmO7SmCzfu/8/NtXlx/c3BstFovl5VnHOSFACMpsXO2dvPFGuVgspczXq3a5aPKs8J4TkjfrIQ3yjDFSGhKsKqUs8+PFbEmpo5TkBTcalRo4z0SpRckopT2uggtPly2d0I9nb8/sx9Pp3qufldGVYMlnP/fa07PFogVZSVEKXogY4/7xdURsh3B22Wo9OGgdtIfXqvG45pz7cFhV1Uu3x9YM1rGHj06t9ednT7t2/fWvf725bb57563f/M3fvPXyS3/tb//yk2dP967R8bg+GE2ePGkpMzklXABjDDFQCjeuXW+aZrVYFkVRZDk7OIwxYoR50+ajiQX2+a/8/I9+9MPZ/NKTYrZ2avYk8ZNHdV0UxXq9Xi5nERCM8r4fhvZLn3upaZq7H9+/fv2WU3055fUk+/jBW8654+Njf6WttZfNXGC2bjsX4vnVWVEUozqLdK+eUMoJ5UJpL+X4s5+9defOnfPz8/39fU5Ds7pCRGPMMAzRa04DRbAatbHWRetiVU/ywredIoRU04oJvlyvM1mcXLvdtappFAAdT44Isq5tmqb13lDuKFeE+Xqac86h7WXlh0GvO8aN9FFwl7PoV1eGc4xBK2WcaxBRKzWeFBmVbLcQt4a0Q4jxRbQ4bpuIdv82DzduM/0hSdMJP2WN//8cCBR/6tjY2V92BCAICJBKRakhMiICY3R7jggRCdvwofkLmiSfiBG2IfTuYsSkNL+th794EWB73ZK7xu085BBAGVuPJlnGHn7w8enTO48fv7ucP1R6KTlHRGu8Umo6He/v7w9D/+jhk/F4AgBd13kfpZSEbECKpLwRX+CWwYa5DUIIQtAYs1wOKdwYjar1qofIpJSUSKX0ctEm+bv5rGE0r8pRIcpclEdHexcXF3/xgzf3r1373ve+17bt66+//qUvfYlzfnZ29s4770XQAHB5eTGfzxkjXCTlLfuVV44IF30/zFfLsqxffu1lwbNODa0i3/zj77ed18p3XbO3X63b80C7y7OZMUbkhLOcc26Ma/tmGPThwfUihjRoIoRgvdNad0PfnvcRUvdVBhiqqmKM1HW97i+ttUp1TauRjITEw6ORlHJa5oxD24o0gCJNPFuvGuCyqipCcOjNetVZE0JAZ6Mx7a4+AgDz+dw5d3FxodVpKrafnZ2l7us0bCnLUUpZVdWObQ4ARVHMup5Synn6MQnBG6ONMY3qrbUEWdN0XXellREiq6pRXZfz+VxrXY9K53A8qafT8WKx0NoSwqTIp9MpIU1SQWOMGaUJIYwJ70LXdV03INIsy6zr29YB+k+PVtkxCnfHtvyzM9RPGvALXjl8svj738lQf9bzCSXwM0Luv/wgJGWf6Xxwe4dc+KTn3HJExS7QeOEbSDL0n3zflJOHTww6T79BALBJygNi9CGRTJ3zPkTlQ5nLVbP++MP3Pnzv+137hEIHYWhFobWNMVprhkxrbdu2Wy6Xxvi2bZeLdZ7XVVlb6yESRHQuOBeSnH3ah5wL1nopmRA8L6T3mTHKe+ucIxStga5TIWCWBUK4ELmUsiiKbt1o5SUbNAnTcTU5GPfdlbPhvQ/uRCSfef2Nk+vXL2fz9XptrT04OHB+qKoqa7MpmTJGIviiKLRWV10LeTZYddWtLcPDo2NE+vTy7Jt/9p7S9Etf/Fo7zN//8L3xJGMZjvrC91lVVWUlOWfeBTBeGzsMw+np6Y7Hmshkm8YSGWOMITrrems1IYEykuVc1qOmaXzsvR+sJ5xzJpAw2zRGZlwp1bZrIcStW7c4z7p2GHovOACE9Up5t9qMGh5Ct54nO9zf3y+KomkaQshyucyzOnXatG0bY0xTyGezGeMhhOicz7K8KEprHSLWdZ3JGgDW63WM3rrBeRci6YdulF0XRaGIappZ1/YJ001FPoDgvAkhq6qRlJwQVhTV5WyW5zbLMiGysojGmOQJQgBE9C44F7S2xjhK0NHABThvnfUs+E/wooKHFJ9uJSU2D80nW/N3i9htQuuNE36RnPTf1uT+rcfWsyVbwi3OBS9UkT9x+C1Itk2Xtz9/cbDyC18F2YTnyc3u/HvYpbqfrGxZR1949xeuW4iEYAgxQEjdGJv+YgRCsGnni8XpenEmqK5zGhzxSBGYkIxSrpW/upx77yeTPYIsk1UIbQzgPc6u5iFERBoDBg8JYfQQIXqtLQINUWs9RCgoRSEppULrgTFSlgfGGK3sfLaklHofgtdGu0JW/dBF0AMBKVjXrawz0/39HsO1G9fTRM979+4BQF3XymigvlXrZbssy1wIPp83yCFA+NYPf/DSSy9VVaXQuX7lV7Truo8//vh8tnjjjVebfjVfzgP4QVuOZPn4vBS5B81Z7tzcKHAueodK6XZ9vt0xAyJuyCoEZcadM4yJsirabuFcMKa/uFAsQ+89oxlnCJGqYUMRP9kbUyoIha5rOJ/s7U9iIFkuJMkpFVprRGZt8D465xBdymPruk7KOEmjM3U7XF1dGWOyLEtKBlmWSSkpxa7r5rN13xnGmHcIAG2j8oJTSrWhiZGeF7mUUmZU2xiC73ullOKcl2UJAE2zOL+wUkqt1dWVuX379mKxWt6f7+/vLxZN3xspslRVLsvSGDcMA6PSe2+09j4icCmSIpqfTjJnwTFkAOQTtvYz7M5tPA8kK9q5WBs/wdzauaZPUyv/fz3C88bA53gYAMBzcflPHtuff8rw/Eb4cmutu/jCbCdRvKDLg4iO+hc/1PPXCX/5xoGepGbjJPS9ZUQTwQFA9808uM65ToKVLKesYvVR1zUhhESTZCzLczoajaz1Uvq2GRjLYsBhMM5u5ifsOpZffN+ylIieMiAEOadFkY1GRT0qHz547L3XWl9dXTHGRqNRahsOoXd+IIzxTHRD9+jp/dXMIg9f/OLn+r5fLmcffnjn9PT05ZdfznPRNMvOzRDx2fnT/f390bgyQQ0GjVHzxTBbLdKEhBjDaDRyzi3Wi+Mbhfbz2fJsUF1WFohFsITzqtdXkVApfDJdgsIE68CJgu+U+lKfM+eMUuqiMXYoysloVCxXAkA4x1er1fnjLoW1jDGjvHPRWrA29FlflllRZMPQrddrQhhn+Wg0AlqkkTplWSaX2/c9pfTGyaHW+vr16/P5vG1bQohSKsXB6XySMlZqNY0xprDAWm9Mm2wMEa1Vzqskx5EylASCeO8vZ+ssyzink8koSX8ChK7L1s2MkI1Oo1Kq67qzs0utHVJOiQgB+l4JEeq6RIxaDwzqGNFZSMKsaUSA9z4ELIqK0Zx9KmX9WaGqjfCpBR03RItPUy83YNV/R/v9twTJn0zRtynoz3h69C+4zk+QujbI1wtDlREiWPeckpn4kulh2NaZt/nCtq4Gz5uWXjzn57MqPtkL5YblxdNnb7/13eX8lBHPGHE2uAgcaAy067rlsimKbH+v8N7PZgspMqVMCEQr65yBjXoopZQTwlKMk+Y3cS6lzLt+6ZyRWQXgtDE+aMSIxE/3xokQknI5H2yIhDPOJQND1GAYoawf5qtFltU3bx3Ou2G2PAcAF5UNg3Yd4dOsZD9+8+OyzBft0kQN4rgYl1Jys9Z75UHXdVdXj4XgSKI2QyK3LbunZm6vX799tbi6/+DRzdufcTZyLhF88IZPCs6EFIQQhsQzTjNZJ1JEjHEYhr7vre0CkGpUOg9ttwS0XbceT+qqrvKCN61HxBhBKZ2A91SlX60W+wejvb0xZYkZ7hknt27duPPxU6VU4k6llZBcfYrIkoYJAKR6bwgh1bHKskzi+ADQdV3btpksGWOC59Zaa3wMnjFGCLXGURKM8ZTCRoa14pTIEBZ5XqfWSK0VYpRZdnBUX12xvu/39iZJOHQ8nlgTuq4blaO6qhFx3Sy11owR55x1xlmTePjOho0NR4wxrpYqOx6VZf58pPF2oW9Y+2lV76AsH8LzvPeFNHhHiErrG16sEv/3cewIIZ96wZ8lWB/xBSN/AWQiZLulxPSjXZlq08b4yYgbMPjtm+KLn25XNnqOcG1eJ2F4GCP4ACGkeY34+KN37t17/803v5VxR2gcjOu6ASO0lnRd55xVgwGAq6u5McZ7e3x8bbFY9Z1SSsdAOZeIPniYTKYA6JzTWsfoCKGIhFKWZVkIbDyuKcMQnLW277umWed5DoBlme3vT4pCJi9RFIWPkVB5dbG2OsCIGW33x5Jzc/fs8un5w6IoipG4Rg+Pru8RERbzy8neOMsEExQxMkFFxiNEkQnJJaXUeyulIBTyXK5WC+tMCI5QVMYYZ0MI3kWl7fnFfG/C+l7F2FOGAIFSDNFXVaXs2kUWSc4Yc7Fvh7m1lnO+L6d1XV1cnDXt3Fqbaea9Lori2vWDJPFjbSCUpeGpbev2JtOyLCeTiZDUWkuQK6Uo4YvFFWMssdn7vieEeG9CwGEYYoynp6dKqbIs00PnHGNyMpkkbvZuRidjzFqfMIvUXx1CkFLmeR6j8w53ciiIWBa0Kussn4VondNcUB+C0h1aIWQxnY6l5CFAs+68D0VejUYTSrn3UWtHCCBQxtJsEBdjNMql7cb7SClnVIQQjDFqUBARSWC4U815oWYLn6okIaalCT+NY8Ff4h7/ezxePJ8X3yL+jFEXPu7sDV7cUJwLn/zzzTecSXjBcp8/YbNDfNrRkxg+ubttnoNA0t6XfHAStUMkH7331vn546FZTk5Gq6W6uLhwJozH01bNlOpTQVXp/unT0xDc8fFx36vZbOZdNMbnWXl4eASROOem00kK/5I+c/I8IYTpdNy2rQ8WPKWUCMG7LirdA7q281VV+WAJDdYNTasGJamQFNkwKEFljEQZPVtdnT190vV2UC3jKITIC1GPCu/9fHE5nY611lkmUpS7WMyNMaNRRQnnOZ/NwnK5JDTk+XFZFYxVWrmiHt2/97goiuu3qouLs4PDk9cOX9V9o/XgLHZdb90gM1JVxXhc3rlzFxGLoiiKQms9qDUhhAu+XM7LsozgY/SpQ+v84mI8Hmf52IdAGeSFpLQoisJ7H0E552azGYCL4Djnztpnzy4Isgi+qkdJHHtQHeNESOa9n06nCUJL9pmEOCmlmcw2WkXD4JxLhj0ajfYPjlKwjS/MAKCUhhAJoVJmUkqtdd/363XjnN/fn7bdet3o6XQ8GueFoyE6LnC5WNf1uG372WzGeaYGs163o9HkatZ0XUcI5HlWj0rGwAeXrnlS/qaUj0ZlVY60Nuv1OqJnTDhn8I//4v2k953i8sZx76L13keMhEckPoILQUD0myJv8OABIGIAAOKy+CIPZGf2REMkhHAClAIlgEnMw5LnExUAIm75GBQLpVSe57u5EkqpqqpCNC8a8M6eY/jLZzJlTBqjQgic0+244EgpFWkaCiGcYllks8vLsiy11gPjjIm+7zkXEIm1VohMKUVE/skIfHMwGneqVAkISQ+tpAQo8ZEGezAulxdPfvSDb+mhOXv6vXv37mlt9vf3rfUX51cAMJnsJRkQShFJ9N5LyQFi0zRlxZPOLmOsLMskH0sIcS6s161zrll3l5dXo9Ho8PDYGLN/UCT+oMxElokYvVJKKcUF5ZwXRWGMmc1mjLG9vT0ppbHd7GrZNgaRnpwcTaaF88N4Unzw9no0zkPUSVCaoLCGQKQOzssiAa2NMS7LMsGzEMLB3sh7v1yur67mADAZ7wmRGWPKUUkpXa1WO935uq5jjEWRpSA5VbOn02ld15TSq6urHRfwRV3BLBdlUa/XvVauqqrVet62y5NrR0hUKvMURUUpdzZAGp6Khm6H1+0mnnPOBRsrpYqi6rpuPlvGiMYYSlkmq0R+TKtCa62UIoSMsknTNElCMK3D1L9ZjfhOCDlsa/6UUms2voRS5IJSStPaznKetobU+5n6PRljvbpEpF2rjA6MZk3Tz64WxriI1cHhHiIQCloPzuuqKpxzTbu4umggiqPjyfH1crpXOItXFx0XlDN5dbVkhHEgFAgFQCBJuS7EdFLRhwghBgjgN0J2ECBGJAAR8DmP+sUPlrYo42mMEa0jBBghFMAHH5wfkqcgFFLJKoTkTKJ31tqduEECCSil3m72hfhC2/C/JWHeXdytJNDmmb3tBGOcMBfReozUEx4ZxOkoJ4RImTPKvfdtqxE1pTaQjYD7LsTYbroSEGmaQhhj8BuVXIFSD70UPMvEanH50cfv3HvwbvTq7ofvFkUxGu8ZbY3RR8d7IcBsNiMohGBFUQKGYegAIKk3HJ9Mk3hV3E5C2c4fZGkB5XlIIg9Jg4ZzQMRt9qiFEElnfMSrYRiSmkee50lXzTl3cnJoTdBqobXXWhvDAEMIoHRHWs8YARRGg3fGGBc8ZCWNMUmFiwQERvARXIxRa22tLoqsLOsir/q+b5rVYr1KNdiiqGJE5wKlXEqJ6MlW+ldKWdc1IjZNw2iptR6GIYmNpG5bROy6tXe4XnVa2xTglGWdZVlZFdZaa71Spu+XRruiKKfT6aieGGO01hBJnpXpWhFCrNkAk8mWEqluOzN30yGTDCzJQSdfncQD04SAPM+zLFutr3b4VtzImKbRcHma2kUpS6Jlbbvu+/74+AgR1WAW81X6aEkyup7kIYSqquhIcpaXZR8DLpfrbgha663Ek6EUhcjKktd1yciq72yMqJW3BiBSQljbDHlOYyDMeogYSdptQqqgQgASY9hYcYgQY1KT30yCSWqOEYFg/ORA+p0Bc1o553xwIUCMzifsOoDMil3456ILSacKKSEuxrjTJU83Wym11dz4VNnmOUn7U8dONwNfoEkjYl4WQnJOWXQ2MhB5xgQFIppuxhiPMSIRIQJlDiAw7nuv0g0m23liMWK6urhVpU85UrrrzjgaIVozW8yePfngwzs/OD/7EEClcDTL5NIp64a8kLkQ/cBU7wGYsUpr3fdtUeRluT8aV2mp0e206LA9GNuI5gQPnHOl1NXVVQihrBghRGullMpyKaXkXFLaD8OglELEqqrG43Gy6hACIuFc1nXNueJ8U5wcelWUfOi7GCmjMvmQELy11roIwWY5ISikBCGYEBwJ98EhYpZlSQmz6xtnQ5Zly6ZVSiU6WrpKKZrw3pZlKQTV2joXjHEhhKbpCFRNM6Syc6pUSwmEEOuNd51SSmvPmJKSMsaMdkLSPC85D7OrhTVeCMm57HtFIN13mmUiueK0nJIGoBCZEKKua+eC975tO5JvRP/TYku1KEJIapxM5ej0KQAg+ee0vyTXkkrWzjnvIcZAKSUEuKCJxJ5GTMUY016cykKMsQSAKaUIoUWeAQbGWJYLWAbrbN/TFC0ioZRSa5x3oSzLsgBrVlqr9SoInlOKQ++Wy85Z6iwypT11GxfnvbdIfHKzaZxg9AiAQFzqicU00xQRt2s6Gnghvt2l09YGQkmWC4CA0UOAGAhlPHDqnNPaJDEqAIgRtbZ1uQlH09aeFrExJg1PirCrTuP24V/ugeO20BJCiPC8RGQdAERHLITIXEQitEHnIyVUMBljtNY7GwhQABK9o0RC9EkdKKncB++dC5I5xhjngBgJiUmpi9KYecjq6ursyZ33fvzk0burxQPAjlP38uu3L86vtO5G4zJCULphrL5+/ej02RIRjTFaD4Rglou8kEVRzOcXdHvsPH/yEikdSrIYMUZCWJZlq1WDiM4ZgJBlWZpSKETWdsu07Lz3yY2kv1qtmhBCVRdCMsbSHkcByPUbB48fnS/nAwLGCEJwmXEk0Wg/9D5GxzhQyilN2vrE9N45h0gJCVrbodcAIESWyVwrY42jhOVZEQMMw9B3A2UkywpE7LphGAatrZTSGFcVNM8zREh2vrMQFygASWleCCFG5pxfLtdN646Pj2OM63UDQI6Pjggh5+fni1lflmVd10KgMW63jydCa9/3aY55Ese21qUFlgwYEXe6wil43i3jNC2h73shqfcxRhcCcM4BCKUcXpgKoJRCEtOsqfF4fH5+3ve9c66u68lkmnCytu3yskqMCeec1jYGlJJXddYp49xG6lxQESM0zeCca5rB2ZCya+cEowOiWa/aYXAYDQBhxidRp7Tfg6O4pWQkkaotwYgkgBdCjIAEIsStTEX85JE+v3eeAgL6GLQ1KkYUNCdcBGvsMChlCKF5VmZZEWN0DlJis4vDE0JAt3Podpa5s8+fFUUnxxvSLBUMyQxCCBipNYEiSs4JohQsWIcIwSN6TpAoNcQAWVZ4H11EGUXEiGQ7hgwx0BBY4KLbnqeXgjAmnXN933ESqOfnz+48+Pit9epZP8wImsmkDCH0Q8s5H41GyQ4pIyH6sixj9MYYKUf1qKzrmjHi/Qadots5zAmY8N5z7oXIGGMxICJJ68x7X+RVP7TWekLAOdd3A6FICCuKIu19y+WyKIpkFYjYdwYRyiqL0RljCI2cSSlKIcR4XAZPVR+VMt4TISopq641gCGlmjFCiMY5xzlTne26zruY5yVjkjHo2qHvGpFnSQHDuZDnPM/Lrhv6XpXVprV4OzlgO5AZuqJio0kdt0OnAQwiMs8oYYgRIkGghKQZQOi8advO+6iVJyS2bQ9A+t54q4NH72AnEZW2g7qu+773PlhrgwdKeZZlIURKNn14u3W7yby2QXJKoRljicEKgM75ECwhVggvhGCMc74h8nnvrdXL5ZDapFM9v+uGGON4zAhhXTes12ultFLCO6QiVaRVCAEiEYILEVNByxhjrUshJGNsPbSMsRBtCMGa0DWOUOeciwGNcTEiI1Rs0BqIgMS4ZLGbMdoEkCEQgpxGHyEE8GlkZoghboZl7oz2xZBvfzxpu9n5+ePZ7Gnft5LJSX1Q19P5+olSyhqfyXIy2aurKaXcOU+KgzQqJsEGfjtqjNI0cmXTQoy7RuKf0c0QnzdWuCSOm3D/ktPgPVCkLOpe2T72XSclZ+VIKc2ZZEwgIgAZ+s45V9eJCw0xuhCM9z5sduCVR0wNfaPRKJ9MhmF99uRxv7xvjLnzwQezy2fO9KvlVZYjO95fLpeCZ0KIxWLVtn1d14zyJ0+ejEdHhFDGKJIopWSMGKNSFpdC9GTDfjvYKQV4ACClBEBrbbr9ZVkaY7wbPAZjHOdWEilFVkmR/EnbtkmSMjENVstBCDJmZZYLH3SyqK7rQ3T1KJcyb9ZqMffeO0SUMjPGK6WNcRI4InEOjHaUxsXl2lqLSI3uCWHOekQmeFEUPC2J1EabqqlCCCmyNN9CcFmVdZLUHHplbE9oRiiJMUZnndfbpGyDSBljhZAxRiF4VU+sy4IHzsi1aze0tovFSg0aACghzgWljJRy25Zku244PNznnHNOhBBaWWMcAAzDUOQctwNo06aZbD76zQ93QTghJMsy51PA7He+JFm4tZZzxjl3bjMmkjEihNjf30/uJ8U+TdM457Is61rNGEv7UQI4vDeATpsBgeZ57pxXgzHeAJCqkkKIvKDCRUIAgowRvQtcUGtCCC4EYD7S7XYIAOhCICTu5B4pRkIII4SKEGO0Hp2NLkQPkQQXkKSr4DfScJCsxVp72d07P394/+E7lxcPvVN5XtbFvhTFxexOCBEikzIv8lrKkiCPMV5746+nFs10XRJ7JpWvds71ha8/83DOpagTIKaxLynsvPfwRwBQlXlZlovZlVFD13XXjg9f/+qvzOfLPM+ramSNf/bs2cOHjxDxs5+5lj6aUiqJpKRTqkoaQkg5WxIKvby8fOfNN5v2J0M3rFeKIO+7pmt6yceruSaUEMIQed+vlosVZ1lVSe+xbZvE4wvRGaOM6RNYlYYbJULPbp7ojkC/Wq26dqCUpZVxeHio9YBIGGM+WEKYlLkQmwaVNBcvxsgY214ZUIP2nmx8L6dCcK1C2/YRXJ7nlHnnQ4hMK/De9p2hFJzX1louaIzcGq+1BbDNWjEmGGN959UwxBirqs5kDhCkzAkhq9VK66RxBYg0RhwG7b0HIFLmQmTWWsYEp8xbaM1mdiwiZYwxwiNaSnlSKQKAodfWQlVVCNw5TSlKKQnyvtMh6BACl4wSLngmRUYptdZao7U28/lcCMG5TMbWdT0hpO97hI13TSa6I1Gt1+3uhymbC5thQIRRQUkEAJJmhHgIBHawebpNybyttRAJZ9IY0zZ9CoAZY5TwqqryPE94dZ7LRDKJIPi52a15zjki7/u+a/VoikKKrBBScmfE0HutFRM+gkeCCIFZ73b+EwA8EowkQkKoPBKkSChDLiAEDBhjhOBCiBgxAAREkTYq2GLRyXn+xZ//4Xz+ZLZ4FEJTFQLD0M7nfWdluaaUU8KdYevFWfAYAoFI5vYwhJDS/b29vQRFSimVej4h5cUQ+mcd3vsU1CNuoKxUzfuLH/xBLuXx8eHeZHpx9kypwTtXFq++9fb3Hz16NB5Nb9265Vx4662fvPfee1LkDz7kCTTaVV83dxpICGG5XIYQhuZLgvjz8/M77755cHLpPYzHJSXF7OqKIMtkfXXR7B/JxWJVV6OqHA+9UcrkGR4eHD98+HA8Hu8fTGOMxqj1etn3PeO0qqp0MXeEwbQ/KmWkpEVRMCooZdba1aohhAjBGGOpXJRsHgDadgVE13WdcNS0dodhCCFwLq3tm2ZNqEPEoqgwIzHYtPsZ21vX5aXkXDYr2zTd0UnZD5vRhzGgGux63RrjBMm8w+ADAHKWAZCht117yUtdVdV0Ok1UxNQb1HVdUhFOHy2hQZgmAOqYHFQKPfI8L8syyzgXNPlSxjwhrOvWxvZZJnww1lqtLcSrsizzvAQgi8VCiCyRlmOEvlfWWgCS5+UwNM65GIe2bbt2MMalAdFJXjNFfDvzSx1R6eInjnSKI9IH2YVFG3+CGGNMrU67suLOi1gTrbVa693MgF0PUwhh6F1ivxBCAANBcnJycnp62nWdc17wgrFU1HRN08s8VLUsWe64HPpmUB0LLgROCAdA/Kd/8iEieh8hEsaYGTQSIAQoRR+M97as8rouTd9lWZY85Gq1Sk4yxkjZKK2MRAEdj8fL5fqf//N/vjj904TQALosk1nOYvTWWs7K3e0M0eW5TCMqpBgt5s31ay/96l//25955QtDB33npMw64cuy7LUZhkHIDAjVWgNhZX7wYrlllzGGqAAlYbk1flSyD+9878//6J9dPxl/8OaPyjJHApRiljNjNCFweLR//mwRPBwcHEwme/P54uLiwmgXYxRs84K74uSW1pI2EeACGSPHJwdd16RfnZ2dhQDWhL5XanCI5MaNG8ath2EYj8dlWaapQvv7+1mWrVazFCpnWZYKkkl1dX/vujHGWg0AQnIhGAB4b8c1pZTGgEoZpZTRTmtjrb1c9XkhDw4OGCPL5TzGWNVlQn211gn8TPFhWrKMkQSDJYJ0Gu1hrQ3OEEIStznFFyl4OT4+TBFHgoidc03TPHz40FlWleM8r62BZH6MgcyEj5Fxkuc8z3NCmDXRGO8sOGeEyLIsv7q6QgwRzPUbB2WVnT9plouWEjEMGhH396c+mEE1ySCLIlO6WyxmRZEdHu0zRq21qbycbn1d11mWaa0RxK7bPoWByQ7zXPa9AoAUXdfVaL1utdaEWs455zkCaZrOO6zrEQLFMKTcjRDGmAAAa5zWev9glJibiaTVdR0AFEXx2mdP+r432gHQtumXy3UIscgrxnGbQcRm3RHC0hyzakRTXwQilFU+DIP39vj4+O6Hi7bpnHPex2HQjLHkwCfHWQghRuQsq6sxpXJ2tTg9PS1HIeH2LOoOCeOEBB+tdgiEIkKIxhgkPs8ER29VU2Tc2j5JZoYQUidKnufrdZBMAgRCYwy6ay8W83NrL70LyaMKkVMGRpsInjGqlAIIUkoppQ/Wex8jVlVldBiGzhglBEcCl1dnwdObt74YdQtAJOOYk4gEEUlWhhCUbQCA8BS3uzRFMIQgBY8xem+10TOtnj15+uzZM2cWk8loGIYIQQjRNipJrlxdrm7fupWQ/dPT0+VytV6vIRLOeUiFLvc8PImbyiEwRhkn1oJStmhy51xRZDEiY9nQq64blDKMiizLOeeAcr1q1qsGgTDKKWHO+kW/LKsywTZ9r4xJhZYoZZ6GHm3ke4wxRjHGhGDLxTrVV0MImSz29ypr7WKxeHQ245ynomWel8YorYwCdXR0hNiGAAlKQUSttfcxz3kqDqcyWJphyxhDilrrJHmTgIMUUib8dpdYpns6nU6jL5wLfae9Q0pEnjHKImPEKpfX5WRSc47WWu8dQAjRlTWhBDkHITgAeE+GPhitlFKD6ij6GHETgsImAEkwR57nMU6cM2k2ytHRkRBD0zRN06Z6TJblQkiIIgRQSqVAPYGghETnAm4HwcdNnRKzTET0hECec2NcjB4J+mCkyNtln+41Ymqu4JSRguVxW5RK+yDZLo+zszNrfJpXnzwt5yzP88XyKoEOnFOxnyFSpdR8PrcuK8vSmtgPbd8PQvA8LyAyIYSQBhEBLOeUUsY4iZH3nfHexwic++CBEDaoltDAuRQiI4Sww0mBSITYfP4EsSJGQFGWOZLw8OH9e/fufeHzrw/D8NEHP3706JGU0ptVURRZlh1f+1qeS6UHY1RZccbww48e3b//k9CtnDMyE3VdWuf6vkOMVV0ktwMbIkvW6na9amOoi6KYTEeM4+Mn9+9+/OBbf/59gtnf+Bt/82u/8qvaWgJEMFTGhYhICQQkfAMnpNwpJQ+ME290xAiIgpIYkTFSVUWW87Gs+qedUir4iEiLYjyqs5TZItC2bZumGwZljGFUpJwzBXuwLeTsUtM03zQEp7Vr27bv+6ah08kBJYIQ5330LiL4vu/Pz8+PjqeI1JgN5Oica5quaZobN49SmXFXMEwt+2HDZ6AAMKjeOVPX9WhU9bZ3LkBkgmdCSCGyGFGK8tq160II72Kz7iJ450KMkTHSd0PfDSmDSGlVDBB81NpSSlOe7FyI0SDSLBMUadpKCGGIFJESQhljziXQZQOMJ0LCaDTqGqaGTg2eIGdMAgRKgXM6zBdSho4rQiOAizFGsMYOMjKIPujgvY2RWOvXK+294zRSSilBSjil1HkTYhKX7RFRKZVlglAWghl6W5ZMDSZRNerKBg/Bw9Br5xxEi4gIqViCCOhdMLrfBclN03jv87xJRbWyyqy1ZSVC45A4RqVzKsvY9nZDOnmAJB6yoYKk36YxkX3fA4DRqZIMBIUQghAGgIyTvb29vu/n8zkA1tU4Td4pisJoLwV6D12rFXUHB0WM5OJiptQGA3MuRXwmrRYEtmEBBxdCg4hIYDItq7pIMS+rBHhvaYiIVEgS0RVFUZT51dXZ/Y9+8vDhvY8+vjOfz9vlY0R8eO/D5XKZZdnHd/r1ek0I+Xf+OimK/NmzZ1ezs8985pVXXn3ZO81o7Kz3HlB7IxMuJ4XgRV627TrG2DTNMOiyLJ0LXTdo7a5d41VVNk3zR3/0Bxfny/Oz+Ze/9HMHB1OMQVJifYguMIja2qCBCs6pDCGEGCgCYZtxRwAAYH0A570UEqKVHMejghMHEDinQw9dNwCQGHjIOcbs/PxpXY0T/JtcUwwYY0yFe7oVx9lurpyLVDbzKfoVXC71qm06Soq+H4ZBxRgJTXwSPwyx6wTZzgdM2VSyh9WqSeKJCakKIQyDHgZd5HVKopJVh7B5IzvIoddSYlWNYoyXF7Nkigf7Jz7Y5XLZ922WSUoFYVAUxWw2M8aklgZKGaXcueB9zIssLURrrdYqBJNo+qMq222IKRBNn32XFiY3nkIASulysdLax0AopyGAc456pJQJXjmLy0VLqK9H+WQySkyJrlsLTiBq771zFhEJiVww1bUxeuesh+i9XzeWcchzWZY1IvZ937brFIwQQgBICMvklsfjKWNCa922vVKKkixVetNOm87TWt+s2zQUajwmSqk0QAcx7u3Xq+U6y1nfAxdESto2yjpVFFVKzUJwhEAEa10aDScSoJAQhx3MPmaTGJKxBSEE56lW3+7v76eQXgjJGFuv18vlMjFA+94452JgXEopC2f92dmVd8R7j0i5YIyxdEljjAQ4AgJuJmkjCWVVjEYjowNnHKJlQzOPMSLSPC+rstTePH16t+va07Onjx7de/zk4enpMyn5j340y7JspwA6nz+7uLgQQnz/e79dVaPVat2sO2+a+cXFxx/fNZ0jKAIYY9xy0eSFKIqMURlC9MHSzZjMlXOeUREDHXr79OlpVdV9Z64uV0PvR6Pq5NpxVWfRqbKutbYafSGKvldt35cyN55AAAJEMLEDz7z3gRofvHWWC2pU33dN8K4ZFmertZQb8V4hsmQkZVEvVrrIfcIwCKExxqQd1w5t0l5KfZvOuXTzpOSbNwrOGDcMuu+VMSaZkNZaCFGWOSFQlmVVVZSRJOzMGBuGwRiT7sRysYoxdm2vqE5juAlSsp3/lDhkUkpEkUxIawcAzoW+U8OgF4ulc05KqSMDgL5XIRDGJOc0xgiRBE8ICkqk995ZQIhGB0KAC514QmHLe00ZY99BjIiEGu2cC0LI1GHHGNniopg2ssS4CFseYtKO8N4iRueN99yYEMEgsTKj3sfkz41inCSeSbS2L6tsuleMxuXlKRNtv14pgCAki5EICXmRCcGyLAMIiUqViqIIIgbSNI3RfjweUyKcVVpb52JW5hCJMXYYdMKcGOOC0xAgiUIjpFvMptPxeFLXtRyGASAQClkmpMzaph+GrmBSSpllmXPGWJVCbi5o12jcdown4mfKONbrLiEg3pvdhU1IAaW0LMtUN9mRGtqmY0ynOT6U8uDBe08IDRjyXHIupZSMCWvcMAzW+lVrYoxplKdznm1xEzV0w6CstaxdLxIokGXZeDyOgn7v+98+O3tGaMgyWdfF+YVz3pPAeuWMU1xSFwwicknLKh/6q/nsaQzk4OBkVBVnz5598O4Hy8V6VOcA1GjjvEr4eHJiRSWkzCnh3i+HXnMOwaPR3hijhuhspESWJVGD+8lPftKs27//D/6Xx8fXuBQMkFOfyegdBN/RWJGEeDu3Kz5JznUknAlCQplnl2vTdWsCznnrfcyygnMPMDBGQtDWuYg8STqmODO1iSUSO26PHWSackVCI6EMHXStXq1Ww6C7biDIjOkZIzIr9/YmWZaF4Moqz7KMINtxUQA4IcEY471LzTdpa9iVfBOhJ7FxKaVC8vRN13UItKoqALJYLFerVeoOnc/WrBgBpmuLWllnQwSvlAFAQmjqm/Xe53lOCM2yzDsTdhTxiBAhBnDWDz5wzilFa721jnOZaj9Jm6KqKmtt0zTGGErpZDI5PiFd2y8Xfd/1ISQR36iNsTYruJAyAyTpDL0Pfa+8w61wIqYOE0KjEOTatePVsjXmPAYcjUZcUCEIobHvNKW0qiprfd8rSniWZZxlIVhjXAhKytx7n8KK1PvlffA+AGAIQWtjrQOA4MG5EIKWkue5ZIyMxlVVldYOMYAxDoEmsIoQprWOuqvruihy59G3BjDWdTEejxZMJ5eYquspDKGULuZNXdd5Lrz31jsheJ5LQnLnQgIIr65mQ6/Lsk5BddN0WS4pReecc2bdLAFACB6C5pxzTjnnWZYL4dNe0AyKUNykit5YSzhTlLS4EQF3jHDmBqWM0dYOWt99cu+d99723maZIDTO51dX89l0OqnzKoTABCeMBohSCJFJ612O5WpxZY3nNJvUK606KePJ8UQNnmAUQgpgSKLRllKa5zljkJZsXY/U4BAYxADgIZKhd0a7GAlBAUDaZrhz56Nv/sm/Pjk5efnVV+t6HCIwmVlrzy8ujqYnRVFIISDohJqmCsRl05bVHqAM3l5dXZw9ezL0bXQ6BmibDjBGCIA2yxliVHohpdySWn0iD3MmQwhFlu9IUQm/SRWC9XpJKU80g1TpyWRBCM1ynExGeZ5P90aUotI9pWht36tNhTxBwZQFDoAE+s4lqmCMEYAkBTxEmmLFFEHxyITICSHO2aoaZVk2DEor613kXIZgre0EYc4ZBBpjWK/bVOkIISQWGiFMa+uckzLPMllVowiKvtC1k2aFEkKqQj4vgVirtU4f3NhhVwXZbWej0aibQFnmjIlzP1NKCynzgiNGwFJmTEhCCHjvtbZD79Xgy4oKmaIADAGsDcv54Gwss5JQjNEPg0VEIUlZZYiRC56ilTwvvUPnvFZODQ1S532kdFNVJoTlOXfOGe22RAuMAY1z6Zo7bzjnWZEfH+/LjA2qCcHPZpdIvNYeogcgwaPRlhCG4J31WmtKEYkXgnHBx+PRaFxJPr24uEh3RykVY0yIPSWCEJaUeijDLMuESNNOIJFYR6NR36m0WSdW3GRSMcb6oaU08RRUcuwhumFwqbcMgIToKWV7+zUiOufbtvWdj4H0nTV6OZmMnA3eRfbjH//Y+8iZEEIg0qdPnz5+/Ng5IwTLCxGjz/P84OBg0S4JIQEBGUVEkWex7+aLxeys01pxzi/OLlWvQwhdu5BSrlbOOcM4kVI4p7pucM5xzrtOd13HaFaWo9GoIMitjcGvZ7NZlhVSir5TLriyqCCyZt1880/+zeHR8S8Pv3xy42bbDZPJBCl/79131c3ZrVu3JjduFBlTvV4tLrsmtln2h997+9qNV8aTw73pwf0H9548eVJmqsjIrVs3tR64YEIwHzQitO360eMHR/s3+04BJBHJwBhL5AchaFrH6ScJxdVay5yksWmpTCJFuVq2XdcdXz/YP5gKwTmngE4IIiT3rfJBb1tYXEraAQMXmHp6dxFXiiDKslytVskb931PNeGcJqxLCNn3QxJ/qesxIuXcUkrXyjjnskwwJlTokydxTjnnpKQQN5QD72KCfNq+SfXStD0l7rGUMjhjrUtcN++D1kbKTAhpHSaTjjGmOnPCsQB9XZeUcqVMWDiZ8dGoEpJrQ5wz1uq0TTgb+k53nbn18p4Usu+cd0SpnJKs74xWPexBWdZFUQzDYt0ssY0Rxnkuh0G3bcsoz7Jq03KA4H0MxlBKIZL1qnXOjcfj8WgcY5zPGmOcUmrHCMiyrChK7y1AXK1WiD7LubF9lnHvvXWaM4ngGOPeR6UMJYwQJrLMObder4Uk9Sir66IoM8QohEhAyY5llOgiZTmJIbRt75ypR3kKsJerueDFYrGQUu7t7ec5rtdtKnoZo4RkQggkRV2XiLhYzowxnKemlMG7mNgsiJRxejTdI4QoZVId3nsMHvrOxLhIKQz+n/9P/8nx8XHiDDjnvvujtx8/edi2S2O7g6Px3n41n186b4jA/f39JK6fULgExLUr45zZPxinMdAIHEFcXS6Xl1FIFoKJ4GRGkQRELzPOJW3bNhXTEPHo6CjVM54+fJRkOIu8Zkxo5ZXSMUZjXFXLk2t7L79yq+/Xs9msrseMCRO6mzduF0Uxm83X67aua4jkwYMHTjtK6WhcMUZWq1XXNUggxvjS62PBs7YdILLgse9N3+lnz86undx2zjLGEKOxihAiJQ8hjKt6l/2mGQgpsSEUg8e+s9bEGHG9Xnb9Ksvkq29Mbt68meZBpyplqhO6jYZGTNhBasdHRGd43/epwSBl12mZOktT/TCZTar1vfHGG0zo5XK5Xq+VUlmWJVX0R48eeT1O9IDEtdixxwlhIbiUqye2ZlkWWZbJwqQlmPiVaRFkWdYt21RDSvywtHnFGMupXC6Xh4eH6bRTkg8AV1dXN67fQqSXl1dqcM4FNWjnApMCIkk96IRQzrk1vus6hkIItr+/n2Wi7dZaa+/dMAxlxQ+PDiiNXd9oZZtm6FpDCa+rvR18uOs0iDHWBU9ls3QmqalYa913aZhTUVXVarXy3k8mE865dT0ibpVjAmUpFaKjCaeEc555h8tFs1y2CKwoCsZ9Yk2lfTzP8/F4zDlfrVZd18UYU5Mm5zwF0npgSqlf+Wu/9PDhfS6I91abgXN2fqmcV3v7Y8YACWQyX62a+WxdZyUipkGHIYSUlQghkEDqAweABHmmKpQ1LkQvJZUZW6/Xp88u+t5wJjgr0wVhPqyVZl3vUy1xui/OLg0O+trR5OTaYYhG9oR6YkNMHc+JoZLSTr9RNugYY4gQQujatbOotCaMERqRhBADYmqOg+BhtbzM8/zwYNz3/WKxmM/OknmcnBxorbW2EEFmtCgKrbO+741xEMlysX5IHnJOAch63S7mq5ObB++8825djxHocrmcXa0IoU3TS8YAg7XWuZhQpbIqsixTg3UWjXYAMPRuveoIYePRdLVahZCowtRv57wRQtbr9Q51TFtyylHzonQ2ItrUdJaQ3ul0cnx86L1vmmYXbHvvh2FwFtIQk1SZxO3M4WEYkoWnBtQQQoqd0rpkjCUYvKoqAOi6biw2uXRVVQlaizEeHx/f+3CZUOW0BWxWA+KO4oeIqTKZ6vadOkuGsTOPTRutiyl+Xq1Wqeqb9oIUYKenpT0okXaqqkISEaKUMsF+CdQpOIshbsF2umPpOedi9MvlkjFiXSrVBu8941mMngs+5iNX+jwv21xr5V8kge/q8Clt2RGeUp9Q2lYgbhqJ08rcomupOzY1pUVKESHpWocYkEvBOfdbmwk+Wmt98M4FIVjKsa31TdMRQvp+CAHyvAAgXdf1fZMEK0M0XOAwdN77UV7H6IdBPz2/cJEp3TOOo1FRVgUhxPuY9prd5wohpCZtIcRoXO9ih3TR0mdhjFsXrLWUQVVVN2+K5bLt2t7ZTRmVHR5nx8c1AJyenq5Wl4+ePlNmQZguqrF1XdMuKYtCCucpI5TKLN3OGKMUktS4Xg3Oma6zztlhGObzpRqsEMXx8T4AdH2jVBp1G2KMIcLxtZEQoh6zsq7KmmxvbT+e1t7JrhuG3iBxMpdcCMq8t6wohLFd36lXXn3pxo0bMeDZ2flglDX4ysuv7+3tP3709OLiaj6fWxMZsSGitTqhpoAxy7LJZNTpuRqU0R4R+k53reYcpShiVDESIQTnFF1Mmar3HgJobRFdMiq/bcrTWnsXrLXGKK0tITAajQ4O9yCS1bJJm2AikyZbZbR0FofeJargDs7dSRfsaEPJklfLJI7l0/Zf13V66NymQ6ssy6R4GmPc39+/GxeJ07uz24TJwV8i6we4bVhPW0nqUE3b0KSsU0yolLJWC8E4Z87F4IFR4Www2iHQGNAaLwXlnPZ9j0BToAAQijJ3VgCiDyGZBAAmfCG9e3o7rV1qf2OMlmVZlgwxUprEHCNnPnjsukVwG+ZMOnYfISaEHghEdM4NUSX0kVLcGXBSmElmwBgGDxES1ZFzTgkhEXzfa0pFDFwp7X1kjAWMzgUfbIyRMbaLudKN25USE6ScSoN1XbvcDcNweXUGGDOZK6Ug8hgYYUApidEjgSzLgkdrPCJhjDvnQgCtrfc+9UUTEoKPIXWvAgQfnfVphMB4nBEqQzA7orExYejVrvuAvfrK7ddee+3w8PCtt9568803CcGDg/1h6IKHy8tZ27ajUdVbwxjDiDvUNC3QsiwBQlFmhCClWBR5ng/BY1Fkq9UaEawbuMC9/TrPBRLPOc1z670PvmGMTSepY8b0fa9Uwl3ROTBm6DrHmBCSZFmWZCImk8lnP/vZL3/5y+PRFJEAYRcXFzdv3r558ybn8uOP7v3Gb/zGj3704xgXSZNdSl6PKu9tUWRZliknnTXWRme1Vh6AOgsxOCFZjKnsSXwgOxRH0CxhPLDV4kiikMYMwaMPNsk1UUYQwRgzn/ep3QSApm011WCbro8xBo/BIyEkeExEvHpU7JpgkpdLpOX9/elyuVRKE0IoRa2Hvu8pRa3JriSbIKXkOVNtLM0QSAsr/QqAbDeImN4xBD8Mw2Sf79D1ZMbOOWNMGqnBOSMkR0RKSRpn4XxkTIQA3m9YTcaYLAsnJycpTlbKRPBlWUqZ932vbQjexq1e1I7KNvQ9Yh5jtFYzTiillJI8zxHdMAwh2iwTAATiBmDDSF50vLuiQIplXnRW6bcp70gGLIRIWYD3ntIUNeAWj5SIMQTSd513LaXKGu9cQKSIhDHiPCUENyM8kCZLo5QeH59cXl72vUrpiRDoffQ+Hh1P53MwRh0cHHHOnz07W696wQtRkcm0znNOGUEg3gdrnXeRZjyxctNbUMoRAyJNm3j6OMk5p0pB13WpGIEYtNbeQQrchr7ZGPBq1q73uml9EC2RtLhx4+bl5eVsNleDHwY9DAFj6Doz3YcsKxLvoizLYdDr9frg4IBxXlUVIdEHyxjUozIEQikuLjsukAuoR/n1G9PRRDrfRXDrWZdUggDAGmWM4YwdHuw9fTpDpAQZ4zQEorVy3kqRhQjD4GSGVV1QGvt+XVXFzZu3y+rg6Ogkxkgpr8pR3w+np2fWWilpKsHXo6qqc2stYwQg5FnBqIxBzdpl3xsEBojexd4PqegqBLMbggE458CbFGem65j8MKXU+cGYoJVzzhMKQgjGibU6RFeW5aieOOcIdola5J1fLhuyEWFJhsdjRM5d0vveDVLaRiJxf/8AMa7X62EYuq5JwTZjhMssNQYkGnMahH1xcZHisV0NLOWx8YVeDsQYtpwQpVRRV8nD7ILbFMAneCzLsqSfnDwzIjqMbCuwmirASexK69Q26I1RMYY8l0KI9XrJWObZtid8GygiYqqEJ3mKelRKKRmjWZYt1+dK9ZSizDhnMs9rRCp4ZjdSaJ+YmIEbYlnKdGiS6AFAQjBGm7Za7z2ldFfAl1Imzd+w2YAcYwSRMCrVYEOw6WXTjiOECCqEGIdeLXFFCNHKOOsRCCXMaLtTaeeM9mEYemVtXlUVJXx/f392tZzP5+tVn2XZKB9NJiOZsYRchECcDc5BSqRTkI/bVlzvfaq3b8uNz/espmmE4UUhZMYSXYQxNp1Ol4s+fV72/vt3zs8v33773adPn4YQxvvjx48fOefyTHqPzXqIXhRFHexAIilk4Y0vZIEBu3UXbOhdm+VcSBJjpIwWRe4dxkBu3q4JCSFqmaHzw6CGEDVl0RovOFhj04LQ2oo6K/KKsZXWFmLI87IoJCEmyXoKKYyxWZFHMI+fPLi8OivL8tatl46OXi2Kom17xphS5rf+2b/4zne+ffPmLUrRmBghMJa2twgYfLCUpZYxtlqtnTOMIUEmJQ/RJw+c9pSwmbGaKJs8YGpJNYiYSSFFnjHfdyZ4NDoY42IM3tu+12VVADBjgtY2BBIjdJ1OAr8xxhB8CGmnTwwNLrN8t0B3npMQoo2q6pJQbLtmUG4ymTBeCbnhISd6VsJCk21rvSnLpTQ1oSxJZhkx8QcwAkkPk6eCbU1rRy8jhOScxhillGWVA4DzRqsBACLlu7EYxljGOCLxPlzNLutqFCMSCnVdj8aV0c4YwwRPuUNynjsS8nRvT+vBey+lTOMIvXfee6Ojd8Qap7XnLDjLYyAEZYxq52N3Bgyw6UxMrLBEb0h1+x3pNcH7G+V3Y1JJBjF6H7q2Z5xmWSYlr6pJ0zRKqQR6bOQrtu+SOM9JTD+lAJeXl2meOACkt0g+8/TZ1fHxsczzvlcPHz6kFPcPxpxzRE/IRq6sbTpGixAgBnTBIyICxoCEUkogYJop47Yb7qbbiVJKCArBYwzGGMZT0IR+w/3YqA6wX/3rfzXGqJQa+hXn3FVQjZCyKWPSB6uURAxCsqHrZz5IKTGCt246nkguEHGllsYoQkWeS8ZEDBQiR6Ter/I8DzF6r/th3fWBcSjLXHXWm67ruhTnOBMHNOA7ITKCSTYNCWFZxihxzoV8JLXxRcmVXp+erfI8R6SnZ48PD8+Konz06FGRV5zLu/fuWKfbblWUIkJI3XMAwViVyiSD6gCI4HIyGSNSa+LQG+91lsuwEeneLZFNKcVaNwxqGIZEXUhDdLKyHHrbd3o2W11dzpXuI1hrtZSy74ahVyloTAAyIWRvf5wK7ls01VJCZcYnk0naGhIwk6woxqiUrut6Mpmk7CsBWuPx2IdhGIbkwRLildqJmsXQ933q3UtDutfrdYwxbuVvETH1RSeZt2Hok9Hu1nqy9v29yRbpTW6ZcE6NMc5SZw2lNEYYel2VIylyRkVVifFk5Kz3PlLChcjaZu6csZ4wKhJmk3L+BEq3bdv3bQghBDebzYZhAIhKKTU4LgREYrSOHoLTIZAYnsfPO7vaWHLYyNC92IKWEPVkxsmz1XVNCOm6jlFBWeLG9klqRwjBmAgeEUgM4LynLNKN9tUgRUUIU8oMgyYkTWCI1npCmBCZc25DLKF0GLS1to511xopCu/UcrW4fftmVVVCiEavjNU+GKX6pmkySQAoIUQwvk2CkkohAyCIzhiVdnDYqsrRrS4fEgLgk/OnRIQQhr7fXRn2V//aXxmGYTabrdvL2WzW96rpLpwFNEJm8dbto+WyWTeXhWR932/nxNBr166VZamU+smdt7RWESxjiaHeG+0plS4+K0fHk3rivey6brlcexf1QIJjVOSCoeSSU24jEsgYKSCaPM/TKlHWMMo5l4REzkmISEho2xWhYbpXU8r7rr1z5/3r16+fn58lzn0I7qWXbmVZBtCHEIxRXdc5Z6zTdV3neTYMnbV+PJ5OplVRlKtl17anXa+tE3EzHW8jppdecLVqU6yIiNPp9Pj4OHXqNk0DkWRZVtdh6HUEn2XCebaLhdI6S9vzZDKhFGJExgQhJGWbidAStn2naSMDSJ00Q12PU/fP8fHxcrncSMZK6bxPfWBJpTURpA4ODprFKtH0EXF/f39/f//evXtKKQASQlr6EXAjqYWI6/U6rYwQQvp0QogQQp3z5FvSHpGaBwkhq9Z6nzY4koCPlKu37QwRtTJ9r4p8ZIxbN0trrfUxz0hC1Da7Q7DW2q7trDXpky4Wi7Zt8zwLIczn7XhcAwTnI0V0EYKPgssQmk8ZcPrq7caxp5wfAREibhGylNVnWTadTrMs67ouBuScA4a06wEERnmWZctFk26XMUpmqY86DIMejw5CCIn0uismpewJNgRyne5gKqYW+chZIITVdVkUWVnmjIOQOJKj1WqR5IMSzYOAACQbCtw2f4HtKA/vIsQYNyrLERkmLaHValVWBaVRG+2cq0qx66nY5MA/+uFHZ2dnSeH6u995d+014kbSNZMSAHLJVG+LahJa/+DBva988Utf+9rX/srXv36wtz8ejz/48P6f/umfvvPOO7MnzWRviiGMKsk5J8FxJ/q5AgBBZM2rQMOoGJ2ri8vVRVUVKHmnl9lI5iUd9IJxyjklhDOaxRgJDd4b6/TlgyAlJxYw5kjisHBVJcCEvu/ff/9950Ke53lejMdpRqMmlFf1cVnmZxfnzuu9vcmqtav2SvK9s9MHPuDxyYEd+vnqar02EGUuiQvDK6/eYMI9eHBqFVw7efnpk0vQWTRxvx7t7Y+4IOi16owxerwHzmkpoSqJ5Nly0TnriWNtY/MCD48mEfRsdpWX9PDwKJPFejWoQSPiMLRp+yckFLlwNqxWLSGkHtEYVapVUooRdNP284XhnB4d1/2Abbu+uLq7Nz0hhGhlV8sBIg8eL3XTtj0FvT/JAaK1zqkuY0ccYbCGs9wolRD4ENxisdDBVVXFyJgSqnpqlCdEUko9csbYugsJ9eGcA5XRMgAAygQ3gQbvfZFXdbV3+uzUOffSSy8BSmexbRwAj4EZEzBmwXO9CI4OQvitnLXTvTJKS8akZACAHjNSYkDXAwDZH49ijDGiQIkeKAYpGKWmc34nnJ+WefrPBCiKAjdiQ5teNCEEBH90sD8ej998880ik/fvfnz9+vVmtfylX/6FZ8+ezWazvlvlmRiG4dbNm8vlMpeV1kOjWwRCkQom8jyz2n3xC5+rquqtN9++e/f+5fnVrVsvDa3T2rk9ICis6RnN+s7EMOztHfV9P7ucF2X2mVdfHtVV9IEzIgV9+uQBJQfn50vvvVJWsEqSrOsaKSWA2EYN4NwGmWOMAPCdPcftNFkAkFKuFmpb23er+XLXwbb52//yn/7nIYSTk5Nr165FsEkUO2V94/E4NV6EEFaL9Ve/9OUv/P0vfOkLXzw+OhqPx0PbSSY/+9prL928+ejJ42/+2Z9+9NFHl8sV1BWvKu/j4PSOvp/cSJ75qhwBrJ1LFTCT4jdjnNHWWYBoE9TJOaUMEbEohTG67zUXKDNJCLRdM5tdzlapA0EQCLofrq5mbdsWeQUsliXlLBOcaG26tqUUOec26iLPo4fVYmlNcMZao3KZheg4p8MwMO/29w+djYyxsiyvFleISJkIUbfdYK0hNITgTq6/PqguRoKIQmRVRZ2hxoRFs0bkSf/g5OSkaZrlcplnVohCZgIRQ/TWWsDovNVGORvTHUICUvLUm8kYG1QC+bIQfGKG5XkJAPP5nDE2nRbGhLbRzkZrvVJqXEkA8C4YbVar5uLi6uoykW1I0vdI7J+u64yNhBBBRQrM4lY/MO3oqaCagJ+E/aR0euhN27Z7e3tlWc5mM611URSr1UoWNnho21bwXIqko+R38Ni2J36j2J4i9herWbt6O2xna+2C4eTn6VaU83kBaWvDfiuxsHHCiJxzrbvVamW3Gq6pPl8Uxfe+972iKKy1o9EoSUYmZ55IPt778bh23sxms/F4xBj70Y9+9JWvfCVFJaPRKM/zXqptaEbcdpBSKlVQSouiCME1TSMkSSdfVeXBwdHTJ22qzKcPFWNMAiBxOxxvF1P8NKi+iztgCzHuLDZd23StNgb8H/xv/3GSjCCEPDt/erAaFovF2dmZUkowfnx4JITouu4rn//iz3/ta5/5zGcwxOA8DeC1qQ+L87OPb968+fLtX7x54/js7Ozd9997/OTJYrFout45l/j0fiMFBs75oq5SZc9YZa231kNEwWXfKqMHZ8G5QCktikwipVTuHxTr9RIgllVeVVmWS6Vaxsiolmk+EaPEGBe8KfP85OSwmLLRaCRF7oOybkjV2hACo1k9klLKGBMPoZRZnxes6zom6HK5pMwdnxxZE9SQJJECISREPwydD0ZKfnR8PJ2O+77vWhuiI4SowVoTg4/eBcrQe7ter5GUZVkkHQaElNwGQkie88QDdy44p4zB1MTjGz8MJLUWKdUrZaZTQin1wTHGinxU5AERZ7PFMKisLg4ODk6fXd39+IE1vq7HlCShFkJQeIda+RhJlpVJ8yShG0r1abVJKT0JO1x9hxWnCDkxJVNbZYpInXNFUTEmxuNpnpdpwEeiavnYeO9jBMYEY0KrgEilzIfl8/RsVyTbGfaL9JJkEiFuCmO7v9ph4y96pN3i5iTQjT5qpBCdd8G5SPDw8FBrvVgsyrK8efPm06dP0+w/55walnt7e9euXXvrrbeOj4/Ho+nZ6UWiwSXKig+2KIrr168DQFJEm06naZx3epHlcnnrpZvplHBbP2+ahjFWj8qkuNR1zFp/dTXfMTTSFZ5MJomzmM5/RxBI5reLhHeb3c680/MTHWXrgclPh99strg4PDws66zrur2D8Zd//pceP3787rvvPnnyJJUrxuNxXdck4OMHj1dXy+VyuTeejOvRfD732quhvf/xR0VR8Ey+9urLl5fnH3945/zZ03wkGBN1zfO83JFph0H3Vmuts0wi8L4zxsxiRM4p58Jo55w12jOGTgQRGOE0LxhgKQSrqiLNz87z/Pj42DmRSuFSZjGgoCQEODrYE7WN0fXdHKPdm4yd9atVs1o1VNhcjCb1xLrBez8ZjeyRi4EKWQpBhSCAKEWBMWjVA8D+/rFzznvbNtp5GyuGMauKw4vzj4bBERoQo1JGKw+Rew8xeutCiJH3sOEYMREjtt06xaWMMcqEtUgdEgpCZIQwgLSgN0JwzgUAopQDMABB8AwkMiY455NJ1PoibAZw8rSsOefeRq3SEBBgjCMwiIQgYzwSAsaYGH0S6ElWarxNOTBulcbS+mCcJLtNRb60vLIsWy66qqrW63Y2WxBCtNZN052cnMicGG2G3hLUCMN8vmybXmsTt23DL6625H8SortbspuykN3GkdsF+tO+6EUDjsERZJQlsCfG4CiBTPK0VpumGY1GJycn5+fn3vuklJQAgps3b9+///Dk5Pr16zelzP/4j7+Zul8YY6ChLEshxMXFRZ7nDx488C6mfGc+XyJiKq0lAAgA0hut1+vEiQEIxpih1wC4WnZDr40xIYrEpbt16xYAfPDBByGEPM+Df26iu+u/i4ZexNvJdrbBbjdMDJwXYwFEZL/7e7+zv7+f0E4AuPPe+5eXl/PLK90PGOJqvsAQGWOruF4t11KIvu/tjZvL+fL09NQoE6hNlUnCWQT4wY9/9OTJM+/jctFyzvM85yxHcAjcGKMG49APQ8eoGI3rBMxyJqWQnNLgNUIkBAlhECkAQ6CEBEojpRhjVIOy1iYZN2+8HUwIocrqclQHG2ZXi9n5TBqrBtN1PSGsyEeMUME4RXL95Liuy3E9Wq19367KohbXj9ummzeNsYpQHkK4ulx6H6yJ6/W6JBPngtbOGGeta9eroYOLs07kOkZIwXzXDc4Zgkgo1UPvPI4nZYxxtVpBpJzLoTcRFCJ6F8uSE0JicAjUuzh0KsIG/SaEcCa4YM5VlDCtddcNhKIQJpWIUtZX17U1/tGjR81aTSYTa/x6vT6aHu4KiWVZpRXpveeCpmiTkI3pAkallImWb8eX0O38B+fcoFpCSFEUSbgnzbbeBXKpRkW2M36GYahHtWEBgHgXhkGvV23bds6GOhvtDDK9eAqGE0HtRWx5V1vGF46dAe/s/BPWG2OeZSnt2vmloigODw//1t/6H52dnT19+tR7f/369YuLi8ePH19eXv6jf/Qf7O/v//7v/z4h5Gtf+1qM8d13333llVcmk4kxKiGIhI5u3br1xS9+oe97RPKDH/ygbbs0o1ApJYRMiWS6YgnGy/NEd6GLxSyJcnFOi7wCDIjEOZ0XGx35uq4BoKqqEEJRFJzJXQpAXuhjT5nmLjDZ7aG7y7hz/ulIVFxEZKdn54PSidl77dq1ZuG7rsMIRweHWZYxQpvVOsY4iwtnLCIuZ/M7d+50Xdc37c2bNxfrpRBiPJ0oY7TW8+WirKtqvHd+8dg5HyPsNBw4F96Hk+s3ZrNZlokiHyFQpXvvYbFY1dVB8DFGJMgp4Yg0BoiRSplrba31IagNqdDGGI3tYuqk9wb9GExvh1ZZawtkzjk1hCwjRttUv6EUz86erdeF87ZpVv3QSikZxwDD3t64aZosy4yx1gYEWhQiz/t+0SGi9w62U2SbpgMgslCMIWUlpUTrflAdQU2p4JymAowxZrlcERSC531vspxSSp2zjHlKQSmXHJHqwVrDGKMMKUUAkucy+EiQOpfYP6gGSygyRjiXMiNKqWbdWRutgRg2/s3YPkSTZp9SCjJjXFClFCKLMWittd6MZUECzrnIno96oC8Mf9hIFFKafpVAlNT3M58tq6qqylESDMtksV61164fCBGkyAgRwUPwSFAIsbndOwoH2cqjpzrZriy888DJp73oadPDxLt+0aTT8crtW865tm0TPk8wFrmsq+IXfuEX3n///cPDw+SjJpNJiqKvX7957dq1r3/9G0dHR9bad9555w//8A+/972/ODw87PtWSnl0dBDB7+/v37p1azQaLZerO3fuDL0ejSbpCiSzuX79epKYTJaTZLESPzzB0Yh0Ot1P+UgmK5HJxHVLlnnt2rV0/nlWpl6XlLOwrQT6p6x3Z8AJPkgFkfS0NKtp9wQ2GAtNSyldNm2vH0bFk2bqwcGBlLLv+zRTZ77ucyHzPFfOyxBtBFlWvbFNb9166ExoutYYg5ROj0ZAqRS5c04r672y1qbww7v48MGj9XrNBVssVpTiaFSluYyr5brvlVaes0xwCpGEAN4F72NqjkWIzoU0uNcY67oYPJghzNVyaK330ZmIUXQrQymlURSi5pz2rucZZaRaLBaMEPCRE3796PorL90iBI8Opo/OrrRh1tq27aXIU2+n996FFWMMiIshRIjOG0CGRGSZJDRwzoQko3HBOEGgiKyaHIfoCEnyC2y96pumMzoQkhMSQgiUWMZi31tENMZlsowxUkqkkBH8VszBtY0hhFDKvbdKGc4pYxkidc6maQxVNRp6t5ivY8C6rrXpkCAjxFpj3RCiAfAxOs45odx7n2Y1wk7biT9HTXZ4Zoyxqqq0OHYOMz0tz1kIkVKWZbn3wTnHuQghLObLEIIxAcEAYIzIuSTIMilgy4gKW5XjhAvuwsX4XOIztd9/IoZ8Ad96HlLunn98sN91HXhXyI1cLqWUE/zP/rP/LIUqWuvvfOc78/mcEHL79u3f+mf/wlo7n89v3bqVhoaOR9OLi4vVagUQEtmjH9rHjx/fufOB1vrg4PDZs2dGu9FoEmO8detWKkQ1TQMAO+NJrnuxWHTtUkpJKU8CLOt1msIx4ZKly5jO8Pj4OAW9zm52NyllAolTYpw2MvzkkSJn7/0wDMvlMgkeCiHSzMqNAf+NX/21P//zPx/6/ujw5NatW/1CJ+nJGIKztu+6tm1jjP2gnffKGm9sWVdCSilE27brTjVNEwmnIsdABqPny9YYMy6Ec8EYm4KxLDMpIAk0eu/BwOXlZYwe8TohRA1m6PthsMEj5kmXHGLEEMJisdBqq1psHKWUEm5NXM+aoigky7XWQ6OTLCVj1BkKnAAwSgRjFHFIiQZjNLWANc26LHMhBKGxqKZrZQghi3nqQ5Cw5Sd9/ou367pmjMWIEInWWojs4OBgsZj5oKs6z3Km9f+3tj+LtSW9zgPBtf4pxj2f8Z475XAvM0mmmCRFiTZF2hA1uVCQpbYfDPi1/WAYaKD62Y+NcqPKNRjVD/aDgRa6G2io0S43bD1YtKyJMikOJplMZjLHO595zzvGf6qHtSNOnJs3jRLgDlwcnLPv3rEj/vjX/K1vFVWlEaSzECQ9IRllyKx17/38wfvvPfAeyqKmpKWSoZNgtOOcOws0RCuKwiiKnHdk8azVzorhcCiEoJ4774UQoirroppHUdTvBc6xPNNRFCFw5+DmnVtUdF0u1wx5v58OhkkQcsqvBEFgTG1MTS60c84LaBrfofWinXNJkrSuNWW/yb9Vikspi6LYbDZRFNGoh8lkorUmYncEwVAkiRc8FEKEgpOPBw2mFxoywNaKdjcooSy6YR45/IRC78ozvb/K1vRfg8FgPB5T2lwpZbwXQrz++utk3yilP51O33nnnZ2dnbquLy8vqea0s7MzHo8BnRD0LS7laRRFxujlcvnOO+8cHR2pcTgajbMsG4931qvMOVebior2iEhmFrdNFNswJIqiOE61toKrJEm4AmqbJdwE8XtGUXRxPqUrbPUaa0Bd3ZCh/b31oulOYUvT6dfr9XZZ/tv/yz95+vDBZNTTdRaFqh9Pzi8va6NLYx8eHz85Oa2N9gyNzdM0pbO3NDSMsaqcjsfjKIqMccfPTlarDTU6mpoTwl5KSYABCs98lU0mE0KlkXqmlMNgz6+WG+94XVvwYjZdxnE/TVOVBE1C1RZlnuc5TfFilZjNZs650WgkhKATxnGc7inKedKOJMdDSvns+OM4jgeDAZEhtxUI6upsbVRrlKibDJsOW+riQMT1qkiShOgsB4OBtTbLsjAMjUZiLGgfsDFmNps9fvz44OCACAQJcbG/vx9F0Ts/+4jgHM5CFMWkmHq93vnFSdqLsyyrqoKA3KPRyDpTbwyNMhNcJklCHLSMsX5vOJ/P67pO0zRJEnrwpPhJHqbTqbV2NBr5LbBROefIUyjLfLVeEGStv0tD57SzqFQoRVSW1WazKausDWVJukjC98b9MIw26zzPy/Oz6WSyG0VJoKK93V3bENNT4YTmWlRVNRgMBoNBi3Ckrtder0eZ3idPntDKHxwcSCllw/VHxTZyWa21m/X64uKC6iY0AGBb42j0gm9GCxA4fDabVVVFIxpp924rl1XVvpPaQqhxirZli2Ohh05OYutT0CahbWNMTZqu1+tRoo76KAi2BU3/Y+tilNWKtj1tCcpRSSkPD+6wzvw6imgYY0LSzDrMsoxKffQI+r0xbV1xcXGxWC2jWCohuBDvfPRDZCyIE80MyjwZ+AiFB8ZZnyCsrOGw30bT7CVqj1IySOL0/PySc1nXdRRJ5waUpqeCxDYTCyJNQ6X6SZJkWRbH8WuvvbbZbMJUr1YbY9xqmdWVOz+fciaFUEGqGtgNalMT26hSymS2KEakTcKQOofrIAiiQeKco+9qs9/Ouclk2F5MnuerZU7p3DZVwxgTAhjbunMnx7MWKgxNNp8xVldmsy4orKjKbbNhGFZ17Uxnvt5oFPf7wzTt9/vD0WhEbtJqtcqyjHOZ5yXtp806J+c5CEKmmHVaKr7ZbLJsTUx3RZFRm0GgQs5lk0DmUiJFUPREXcMj2QZOw+GQYEOuGXwTU7NYQbHuts/BOi2lBHBBYBgTxoCuq6IoKqbrypRlubO7Q4Ffi3NqNnpKvYcNj1+iVIjA2lkkJB4U8LfRNYWR9FDIwC4WC4J2UQWLMAi0uaHBNpOYEXqsKAraAN57QqqRAFR13cbS5KO2NADW2jZmNs1oNWwywNBJCHvvdYeYDptREm3Z/JMCLCVvg3ml1GazaQaUzrs7kzfMalme0QOiHdWS0T948IAugxQK2WRETFLZltbbvJfWej5bk9YQo9FESnnn1mGaqCCUhbiM4zgIo3VRqiEcmAkgr4xenM+iSMYxEaCuy9qRC1HnPssyzsTR0S1ErlQYBnEvZcMJJ63Z6hVEDMMw4DGZxCiSq3Vea7taXywWi+WTC2MMcaNLGSnFlZLeQ1nmnHNAC8gBHGPgwTgPUSzTXl9rzbmTyknj8iKzRX6xXHrvCYZOsEGS0tXCUp3TNv29VHiYTqetM9kC4q21RV5S7o2CDdtwhQuhaDcLIVbLqhE/Q9uG7lcIoWtDvfiz6bwsKrIGRENF/k+gevS9cRzHceycWy4XFxfnUlGNHijZDuC2WAURICLfkjajEEqKgPwg1zRg0J4jb/Pi4gIbNmPczjGtlsslAPFd06SPmqSRMVgsVgCs6f6jdbacsy0El3PKUVMPfVEUN/bGUsowDK31nCmSKGvNYrGAbpm3mZXFOScvphUbUrIU4Cml2n66s7Oz4+PjJE3JO22usEm50eQhAMIIkRVSSkETzJNctZneKIrIeyfHm56+cy5NkjYr3iaNWtVP1p5khs5JUuQ7832aG9lqK/rePM+J2KCuDaW4aAVcg9+2dlvSa8WS/gtxQ96Taw76M8+3Jye1Rf5LURRSbhst8A/+7b+bz2Z5vnr46IMnTx9MbgnjbJGX89WyKGsulQOoa4P1loqB1oK+frVaKdYjgaRo4ezsnDrOkRfkS9DDcw3EfJCEVPgOgiDLsvF4zDk/OTlpjInarHMpg7rWCDzPc5VE20IIRxIS5wwAKIaEsLHWxnFsrV2tVsaYVQbkrtd1PZ/P0zRN03S1WlWlbn0HSpC0LdrdtErHbmyTqO0QA1r3KExmsxmFInR3pHqt37o3vGGEb7cvlRlYA74XQmRZNpuuhRBRFA2HAwIMnJw+u7y8PLwxnkx26eRVSc00UNcm4om1NFgMlAqVDIl/tCiydggwOQt0m5R0IY0ODUM9ImpNwQKXUjpnal1674VgGjPqbSRMFW0O8sw555vNRmtNGRdqe05DNRyOlov18fGprl0QRNQGeFX96Jg1ACBoV7eCQhqTtjtjjOg4yVnVWkOjidpsNm36QKk2Ye693+aiGfMdKXINXITe1uv1bEN1Ak1lddDvt242dtr6OOf9fp+6NSlr2J6nG51iA7QgmmGt9cHBQRRFZ2dnFDA6B/Rxmu1KTihjjOJBvh0Z71tZZUy0a9WNgYkohmwJPSB6Lq2Eiz/8w29lRaYCpnVhAZ+eLMqqWi5X6/XaeeRcAmfgGdPcGCPlln41CEAIUebciVopxVmQbcrZbJ5npeCh0WVZZUpt2R5oYwHAZuVO/YJzvl6vKdcfRQenp6fTqcGtueN57pOEW8MAIFtDXmlEBDDEx41s6yOh93G8NSxhWAsh8lyXZRnFPWQMnHTGgpOCRYFMlbA88lv/yoBtuva11js7O3Y7ynQ7otE5dA4BFHjnHVrDHWLDjo8MbVVZzrm1WNfOWlCKO8fiuN/Gz9baPCvKsiSVRxgpz5rpTdYZDQiyKmtnt/V6FYidnXEYKiYqzn0QcABHAD5rvZS4mC2IvcF7ZEjTPQRjxCCn6QG3xoHMHe2ANp/USBTz3pMAe2+NrRFRKVFDQcQU1loaU6yUkJIjekQfx6H3AYUSSonRaJAEQRAEWs/W6zVDWdcGgPVSzLOsVYXtXidHo7vzWm8/yzLSkuR5JklCKq9ufMg2r7NVvo03xJqOyG2eYvt4rxLd9O1U9aFognQxBdU0UdE3g0J9pxeFmklgO9y0bqtBz4lW4/FW5FttNhtEJLFnjHmPbdxOg5RIGWldsettg40rHjwnvY362yYCaZe23g0ptbIsxfd/8J+cN2EScOWM0U5oJUP0seTcGGcqY41D9OBQiMg7UZRlllWIW/eg5nkQOOdy73C9zqx1RCOEwK32znHwIbjtmL/1UgehJvpfrbXzRkiW5WttKgGB2zZbFlpvfbksX4Ssh7hlpldKqoCmCjhv0djaeeO8KcosCAJk3jrtoAJglfa1qRxU2uZFhbXJTL2dW0tyC9vJV4m1XmtLjWauqWc455K4750BD84iAFgD3nvw3uhC1xYk07W1xnuPRPsYhpFtyL6dc3leUB8iInPOU2jcWAxXVTXnUmtbVRVuvAczHg93dsb7BzuX0yd5sfZgycbq2jhn+/3h9GSZZRljQteWEubek2UA6OAcWgEmp5TyAt57Ch0BQKnIe8JqCQBnLMEzhOMOcRtvIvooDpMklpJXlUbEXm+cJMlqtTo7OwP0ztv1er3ZZLPZzBizv7e32eSz2aIsat6Uf54TYGiUZisz0MmyEhkd2asnT57keS6Voj3QyjDdDjbeDZ3NWku9U67zde0FkOUkv52cI3L7OeeL+Zx1Bqm369bOE8ROKYtQKO2NuA5teFUVZJ+aCGs7TTIM4/v376dp+ujRo6dPn1IeXmstZdC9d76dIKFbqW4fJf3ZONjbBSRnXspAiK0WE1VVoeBZXtabvLZlGKrdSaqiABznAXMWVstllmVMMcqGkTvUhjFgfV0ZrTUA8x6liAIVWXMFaqWvJ/d9s9nU2i5XG2MMIsvysta21haQW2ONqZ0zzjnGER2gd0JiWeV0a1ygBGjIFnWeGXLdGWPOeS5UFCtjfVloznldWa21s1iVxtlca8uZ6np0XUcIm7TE1kRb2zpO0ECC2pxKUW4AvQerTeXBccEBnQdb5BXhYymO8g4FV1EUrddrhgIRKSnlHVrr6so4S+ZRAUCWZVJiGMkQ1dHNw81mw1DVlS3LqqqM1l4p0+8PrfUMBd0OIcy9Q+dMm2honDHGGLt3795sNjs+PqaMSFmW/X4/CAKtycMk3W+so63jkyRVSiLzWnt6ClVVaA07Owfn5+fUSUrRb6/Xi6KoNNvxfIeHwWfuv358fOo9Cq5ay/ac/XSdxol2a/omuYWINMBxZ2cHANbrtTaGlA4JXntrvgNBEVvuEURE1whYKwb0vWmaUvxCFSC+JScXZVF0wxwSDBIteo50nlbYWnyF74TBjDHqwSYiS6UUpQmMMVTs6Pf7BNJuIc1p0m8NfivwVVXVuuxmYaAd5mC3BJK8Yfmie6nqZmDF/v6h4167elN4ZlhVrJw3zDr0Nk3SJIy5d9lq6b22dsvDqJRC9Hmeee/v3rptrc3z0hhXVauiKISQdV1HsSjKvPVwuOhzzp2vFYsX8xXnPE1TowF8IEXKmXHeWuMRGAADL72z3gnw0jmPwBnn6JFhQEVXo5mSPV1ngkdSyqqqwAcMQ+9ypxXzwjrnrFJScpBgmUCPjCZHGUQMw+1oFfJtuq6UuxpWTlGVp3mixHIC4LXW5Bq1Gpeea78/LIqiqijml5RaMsaFYcyYqOuac0O4f8Yc59Joh8CF4N7rPM+srZBBGKpXRgc7OzuCq6dPT/I8VzLiXEgR7OxE3nvwNLo+C4LQGu+9r+pN98G3seLBwQEpXDK/NOeac845JXiJaxLRevoIUY6GYcBD9N4Sn2Rd281mc3Z21uv1yLmlWI66kb0n5jpD6f1+vz8Z7z5+9Mhdm8Z6BfxinYpu6+kEQUCbhPK3dKobN27MFwshBKUYWrQWY6zIc7KohGekYCHP8zhJWouKzdB57/3u7i4Bk+idbfxJfKDdZFVb2qEYm/7UDd9gqxl9g+5u9IgjLgFSTMRJROrg+Ph4tVqlafrSSy+tVisa0RoGcXsSEkWS5BhDql+0Akx/LuYrCp7JcWhT+lEsyVMQN2+PmBRFUfzsnbMqLxx3m81KmzKKgrPFyjs2HOyJJGFMFYWua22t05rozhMAOL9cu6YLzFjwjGVlwTmvSsdZiEBGGPIth4Ctnd+U1WgyLEAzwcU4Wn2czdxKaSYDKZQCgPl6QztAhEmxnhtTj8dj732e0Vxcapcx1lbz+SZJkl6vh2izbMm5jxQYU3hjwDnrGQfFpRScO+tjGTgui6LQVSmEUJwLjsNkuFgsymKba7Xaeusll8ZYakelbBZsPTfK/RABgPTeU0an3+8vl2vnHOeyrs1qtSEtYC0RX7EgiIqiLEuaNgaMCSF1VRlrmfc8DidVVX343vnOzk4QLJ1z4/E4joZ5SKxOgLzuDaMKOEOZm1UsovWq4Fyl6bBaGhlFzjmykGVd7wyHeZ5/+8//kjr+j46O3nrrrUF/BwCSJNHgjDGUhmxpqznnQeg45+AhCMKqKq0xvV6PCBkPDg4451mWEUnywcHBarVa1ubmzduxYdPHx3/8599N4v7No5eSpGceH3PF+70efcRaKzmnAhuJEJOSjEmSJNbaSApEfOONN5RSP/vZz07PLo2x+weT/mT/xz/+cW8wGY1GFxcXpDfRoQculSTVkBfb3okgTJIkofBECE5jVshqLqYLbWwQBNZCpVkcx8CT2XIZcBUEiXPOmEqpoImfhfPeOuRcAIrlchEEwd7e3nQ6FUJY57Wx9grRbQCgzIttLcDyKayCIKhKt7+/v1pn83l2cbH8zGc+U9fm9HQmhKhr8FB14lu/yXP6M0x7LAguZjOKegBASmPtxm8zf3pVVqRBGl0GVVWNRiOx2eQe0RgjhEoSXjsWBBHnTCkJ3mhNs4JgvV62UQT9QrpKFyXnnFpZEJx1Fr1jwApdICLnTErJOFCuxXubCD9K+8MwkRyH/cENmY5rxq1a8e1cPMaYbngPwjDs9QYEMKBHSGYtjkMpJY3YBGDWeucMOSrMbgFobV2UlEtZltQSQGakjZ2WyyVZjKIo0jQdDoebzeb8/FzFW9AcvZm8NVLhXRcREalMSsbcNWXPViVThoMuAxtKKkoaU9TdOocUB5ZFVde1rs1gMPAO1quNDg1nwnud5yX4Ks9zZ7m11ntTFBmFuP1+v6oqmsZ2cnLS6/WctsvlUil1dHTUVnE3m42IAq01YfHm83me52QQgpBwLBib2DrNGHqHiHh2ek61NGd9r9cLVFgWlZKBs77N8XjvV6vVNJxS6rXdIXmem2YSGjnDlCPgTRMvIj5+/HhnZ4fM8mw2Oz09tdYGQYBSzWYzbAoKtLzWWuZsdx+3hnEwGKzXa6J05w3GmzFm69pYJ6W0DoALyjA7586nl9Rg0D5TMptcICllmj1Azx0Azs/P2+j0WmBf67acQfhKuvf1ek36a7VaOeeo91BrTSTV3WiOft4dTyiwJ/Ay3QU5jN1sQqM7/GDQq6oqDENR13VZ1xQJFEXBlNe1tc4LA4hCSaFk2OsNdL2l0ivKyrmiAeUw7p3Xhsqg4JxAZMg4IIYheSbWWmMtETUrpVxRKc7rTV46kwTRer3OykI7aw0655lkSoacyboyRjuvUNvtOL8gCGibrlYrcnIoWG2zjmT0qCRDRT9ySGgsDRFNkc0hVJq1NgxDzpUQIs/zy8tLYgwkS+XYFiBBDAfUbsYYq/VWPlupLoqC8F6tl0glMXIXSXe0aYk2um7DLVIl2DSaGFNqbVeraRQlSoVVpYnIMs9rhpxxpVRQV04pJUQghcqLDTb5zPl8Tr8sFov98Q7d6XK5XK1WtPj0v9QHR7zH5B9uNhvrKM2DjAlEzwU6550Fa30QqDhOnXNBEMWxy7IsTdM8z4VYVpUNgiCO/WK+pqw7rTzpYhJX+l66Tar6kB9LyDyi/nrrrbeSJDk+PqY6+WKxiPuDqizrZmxVC+cQ0Pqu0AY+pGJotanqwRuIaCil82CMqWojw4hcdEqA0UXSXmqVL+DWfaVH3KJBtuwLzWNt8yam1u3HnbsqEdFn6ZpJFGlZuLjKC7SxdKuG2nxVex53vRO43e28AcaJqtTrLOOca20Xi5UIqD2OIVgAVldltnbz+YKo8Vqvva0PHQzGVMvRHiytlC6NMSwO6rr23kkpAZ0xNe2PnWgInHkBBoyPVS68HyUZ1iFT3nutNYEi7XbOtczysgn3VVXpoqi8RypaEDshdTs454xxjPHNZhMEAXG7LRaL4XD4+c9//t69e7/zO7+zt7dH4Yr3nqA5YRgiislk4r3/0Y9+9K//9b/+9re/vVqtkiSp7BYwTKEjrT450m3MzJspYRSqtQq1jaMoG9zaWOjkHtt9Q4+NHn9ZljYvnHOXl8teuomiKM80glnL0vkqDGOGQoogzzJrPWPGWCRRpBpJnue3b9/+23/7b7/99ts//O73qDIcBMHu7i7tJ6UUCyRlXFgDMtu21DFgjPj8uPfWWWa0qyvLWeAdlyIyxtSVY6iMzkibk1g2/V6chhjS3bWpgW7uh2L1NrNF7xyPx5vN5vT0lOzw7u4uAAwGg2QwjJowlS6Vgl4wuj1hdwFbpFD77SQ8SZKUVe2cA+RcyjaCJX/HdygESKtSWp5q+/R8yU5Q3gQbgEp7LxwZWc7WVpOapgDBOaJ8iihzppQiAf7kQWtIG4bWlhzpFpwDDT85bPsKGT078eabX7qcz3q9nrF2tVoNJ+PBsCcECMnKor64mE8vVpeXM0Dz6NGjy8tLwmcjGucsIiOgH+Fa6SlSXg5CCQBBoNI0VYHw3tK3msI753q9RCqeRPHNmzcO0v5777338w+f0WChxWKBCNTyUhRlmvSzLENE73C13Hjve+mAHn8YCO8QPOia5oPUYRj2k4QQHbdu3frqV7/69a9//bOf/exkMqFNQEZJCDEejxljaZqGodIaOIe7d49+4zd+49vf/vbv//7v/+mf/qljSDJG2ct2m8L1Vmxs2C3IpJOEu2ZeGaneVjd3jQb5FKRlhRBFUTjnaB6vlCFnQV05wb0UkRSRrr2xljNXu5pzGUURZ1II6b2fz5ctTuDg4ODv/t2/+4/+0T969913//v/9v/63nvvkV/NOadyqHOuzHNy83QDMq3rusWfeG+9Y96D9U5rX1XaOrdaraVUiLhYLGngbVGUBL0ucr1er7OsYigp20Sneg7jiQ2ChVxN14GOtfzYhMah66zrej9Ng2YCG+1sOrPXWzYC1xy0ngRupW90HZqLsiyLsqIasqOyMHIppauRRI51KJpbu9caQ99BUNI525P7Tv2iVRmu4Z2l1h1KhhFMeptV9uaFAkzbsvXMSTO2fmX3aDbSlpFffPOb3zy9OB8OhwReS/ujXj+RigWBDILIaK9rtAY++PDtP/qjP/qzP/uz+XzOOR/0t2Hb2aNHL7308uc///kbN27QetHeFXFojKnryhjjwSLSQhg/iVxtRlEUe0yZvKGlwoEtg3c9ShnUtSFmWWKsZ0y0QZpvGEmMMZvNZjQakefpmu5TymzfONj/tV/7ta997Wtf+MIXSKm3bja5Z2RCaccoRT1f26VJEvXrv/6rv/RLvzSbzf7p//w/ffDBB++//z61ClC+NE3T9WbRimIXEEdShJ0GTtpzbf3JNmBM+jhpB2MMPVeCBOZ5HkepUt47vl4VeVaXhUGoAerRONG1n82mAKyua8GVc76u6yCIjDFEQ/vFL37xN37jN4QQn/3sZ3/7t3/7X/yLf0GRP+Ef0zQ1xtRWQ2fGWhRF1trNZhOF1O6HxjjvLYDXta0r1x/08jwnHNtysabZQkVeVLUOw5gEQymvZEQr0Ko21ikId7MGvAES06Ok6locx8PhkJD2lDGm3SkbMq1WgQrwbTBiO91OpKDJhSax3BaZtoVTiUxUxtZ1LZWhC+gq4jZsNs2kaNIFra/e/ek6dWBvXTff7huO/rboTb43Vaq89yTArTpof6EtRFdOi0YLSD5j+43tUrgGsyC++92/XK7XcRwLJeM49iil5MbWAD6KYsFDBBFFvbKa7+/v/72/9/fG43EYhpeXlw8ePDg/P3/93qu9Xi9K0/l6ReGiJCKOajsj01o7GPYOD/cHgwFjMOzvKuRoNKvqUZSOouhyby8KwieTgVLq9PS0rVU459I0dc5EUfT06dPlcjUej6VUxphej5VlxblAZM5Z2htBEAyHo7//9/9+mqY0vC/LsgZatG06oVCWEPBRFFnrjWmbY6mZAUajdDRK/2//y//0zrsffP/733/27JluOns45w8efti2HJGf03TzLem0lKqhxiMCBtI1kD5uQzVq5KBWTcaoXVFxzqvStNWgqqoGgyEZ6ldevau1fvr0KQDMZ0sy9UIIrR3FtAQ2+NGPfvS9731vMpkcHx+3jWxHR0ej0Yieeq4rAIjjOM9zqg9RT5XggXPWewOeWM7BGKu1USqUMqD2WhrDCQB1rY3bJhGGw2EYGu9Ya9DaHF67QbsmUTbToegnAFRVRQnVuq7JDrcTbWiz0rFNGTrbbuV2Z/umNksXQL1ElGeVjAVVDQBltS0IsYZXpI1msYPZYHZb42lVAzaQct85rpJYlsgVRTeUJTGjuyNF2ULWWQO8ac/wnPBjA8snHh/CgbqmDkc7J89zxG0uQLz11ltcSinlJs+klEKlQSC9t8h8GMTOsao0gUo85nQ11F0BDSAmjMRsvZytl23wUzmT1aVAKj07IcRgMLh9+/be3h6AU3M7Go+Luqh0OTnYs97Mq+n8IP6l0VcPDw/jOE6SZDQaUe4nTVPG3WKx+Of//J9/61vfIsEmq0IRRevcmmbO/T/9p/80CILhcLi3t7e3t9f09PrFYpHn+WAwCIKAiqJHR0dBEBwfnxEx+uHhoRBiOp3S+fePbjT0xdHR0REJ22w2e/3110kwyCy3vErr9ZqUF3UmUD6MkplU6qRXqEmtLMvxeKyUury8bLHiBLRYLvIsy+jh0eDyrUKUTCk1m82iKJrP52EYHh0d3bhxYz5fPXjwgBrNACBJkvF4PB6Pf/1v/uo//If/cLVaTSYTYm9bLBZpmtZ+izH6wz/8w3/2z/7Z6enpcDgMgkDJyFpb15UQyhiwXhOPwny+7PV60+mcMkNEPQnA9vf3B4NBkeu6snXtrAOSHN6wYbWpJtrQ0JQGWsQ1mTjjPaFxKOff5mnIMmMHJrXtTyyL1kZBA8lkjBFam/KFQRAQf0Ce59CQSBZFYTw0mcKtEWs9uPacNL+mPW37ur+O/2l/oYunxDtZbHLxeIelvY3kEdHYuv1sK8NdMW5rMXQ2up6u70b+nVJbhSKCkcg2dW2cCKOy0uVqMxqNFou1tbbXcy15H2eK4rSzszMquNMzQNEjn7n1+I0xQRD0UlaWJQVgo9HTouozdv47v/M78cHaen84vAkAq2z1R9/61l/+5V+u1+uYy376ixz7gpX3v/I5esZ5njtjh0nw6p2j92/sUWMQDWhFOXz06NFoNMozE0ZJmoj5fP7s6YWuaindcmUePrqw9q02yxL0E2PMnTt3Xn755adPn+7v7z84+eloNKJBZLPZh4eHFzRalnM+n88PD58URXF6ekqP//79+2dnZ3Vdr1ab0Wh0cHDw7NmzPM8558PhsN/vr5crGtWxt7cnhKDSpXPu7t27UsoHDx7QDiC5nU6nX/7rXz84ODg/P7+4uCDz+8orrwyHwwACgLBeWgALEAKGtYF67X1dVy4L0uj99x9bVw/T5PDo9s7ObtofnZydaWuXy+V4PH705MnZxUWapr/2K1+bjHeHg1QIEUfKe8+wPxgM8jIry9KYem88jJW8uX9YbPJeHAuJVWUFove1kDgY7DLG0jAIA3ZwcDA7PVVKFUWRKkWxgM1hdbGOwmRxPrPWci59nSdqopiTgjNXgzGRRINgTE0kkgIMMLBVxpXi3pmyDJXSUQTUPBxHTnKvhPGGJSGzGPKgl/SE5/2oZ0sjuXTaWQSPgAjOewck2IILIaO4NGsRRpzzQhu3yYQQeVXHSgKCcVYqHnJelxurizTiyxqFZNZa6zSga3NL3uk8W4fBWArkzOu6yDZLKdDUDgC2Cd4O26b2TikCJvooCsMwWC4XQgiHzjMPANppEYja1pJJKSTANcqRVmExX0qMuINYRmVZOtDRiFtXFKt8d3f3/PxcxnFRFMvl0lQ6EiF44503ZSXQs9c+c68q7WKx3N+Lg7DPGLvl99oiEDmBNPiwrutX7t1olZYxZplti+nkRZDn4L132pC2qKrq5q3D23eOvvOd7/x3//0/efXlI+rtpqj98ePHRcaG/aOdwTb5AQBPnjwRQoRhuFqtrDZpmv6tv/W3fvVXf7Xf75OVGwwG//f/5//6e7/3e9QwSH4FY+zg4GAxm5MfS+FTURSkHUHJsiyd9bPpfD5bSKGyLJNCITKa7GiN07Upi4oxRhND6trUtUG03hObD0PkVIcgRU5GiSyDc47gSlRpJEd9tVptNpu9vb00TSlvJIQgLxoa9OxoNFqtiHzDG2MG6QBedMhE1qYGiYiY5/lqNl3P5++89RMVJ3/yJ39CCN6dnZ1nz54FQXDr1q3/+MffohkfpJXICZxMJh8//MAYc3R0q8grpfitWzetdfSUsemDJd9YKdXv94t8yTmnXmLKA5OaFhLCMCQSPO+9lMF4PJ5MJru7u5T65g30rw1iSekTko/icOec5IyGWSdRPO4NmOBJGA2TnpQ8jkPnzGaz8t4rJdI0UUpNV7PWrW19ZmzIMdp9SN8uGvqB1lS27isRWZHJdQ0DCQAw5L5hnCZ4dvst7bNoHWD6OmgK/sRbQp4zNLNR6CPd5m3oTADupsG2FlXI0WgkJT842Kt1HgXDKArKMjeGwJjGWm2tjZOQtIBYrzPvvTbF5fRsAhPr3XQ6vXHjBuNIvAdxIgCgLOo4jrXeugot9/cNJerOEArTcBows2XrAoA33njjF974zE9+/L0f/+itD959j+g2qfRCJY39/f1f/z/+jlKK5g9RTnt3dzeKoiSKSTLbTkZ6El/5yld+/OMfbzab+XxurZ1MJmTtb9y4QWcmpmvKgSVJ8vD4WZZlw+HQWiuU5FIYZ4MofPjwIXWQhHFU6fpyNqUn0R/2Ly5nxydnnPMoitabfLnaED2Q8xgnvfUmpwYUIYMoTh88eETukzFOKUUYifV6HUWR9/jo0ROKUYka4vj49BesbwbwsDwvZ7PZwcENY9z5s4sXCnAcxr1Bb7g7CsOw1iFKEQUBA9jb26M6Vq/Xa1n479y5c/6EyMoH4/GNolgvFovBYDAYJIAWmQtDcXl5Xlab2fxcybCF6PgGrEKuO29mfFPuQDbEdFEUedAkz9T2TKRQSZLcuHGjxTNgB4RAAI+25MYYK4rCWmvt1mvtp8nR4YFvUrtpL7p1+wYiUvGSEpCI/uDgoOt8UsWOYEiiATy2IDnGmGLYOqVdZ76ua0rg0b5tA2nOfNv6NxwOoWk77brQXR+4m8TebDbG1lEcUM5MMBRCpHHUS+K9nQnF5EKwFsCDnZLbbH7JWSCl3NnZfemll+7de+VXvv7XRuOed/z4+Phf/st/+fDhQ+dcGMlePyYIBl2VeO+d986Oz5IkquuyFwcXF+t33313fb+g1OjNmzfJC711644QYRimZ2dnRK5VFBdRFI0m6fn5+e7u7mo+I9r+qqr29/eLck2I2TiOT08e/8kfr43Of+s3f9XZoM3UUfJGSjmZTLBhoiEoKTaDXum2CZsRx3EQBJRTBYC/+Tf/5htvvEGbLwiCBw8e/PznP+dqmwulpz6bzcqy1M6ORpMwjHu93nK5TJJeEEQATAi1XK6bkiyjyXdaW+8xSfrz+UqIgHPe74+iKFVqUxR1VdXEtonIvCf4MQ/DaDzZoYparz9AxPz4ZJPljIv+YMiFXK7WFAFGcSKkAmQ0ioEeP9lP0lB5g6177tissyCNpJQiULD0cRgNe72d4YA2Gdmfuq7X6zUZwC+8+caPf/zjg4ODv/61r56cnDx79mx3d/eNN96IUlnX9eHh4XK1qKqC4qM0TZXs0calBFLVMM7k2YYSB7SqFB9WVSXkFeUVvV43BzTJ526KaDAYkNYmc0dlW6VUlhV0wrqsxsOR4BwR1+u1VDgcpVrrWudRnAThls/VgmyLDm0LtHOuKCraG206F4iERAq9JV0ISDG1gR7JP9k9kijGGGfeGENtvb1er8VjtUmj1vKTwCulqOJQ1/Xl5SUi0pN1dkvWL4TY29m9e/sOIlZVFSeKvqtVVXTcODqIo35ZaKXC/f398Xj88ssv333pppTywYPx4Y3dLF+SS7VFtoGiTL442DuUkgshvHVlXiXRgTNyMSuqqsrzXLCEtlQgR8bMDg8PP/7w2Dl348aNp4+fjEajLMs++ugj+QvxkydPlsvlrVu3Li4uOIZGb37wgx/Ecfzbv/3bX/ziF2azWVXns7mNo14YhnVdO291bZ13zstai/WapWna0LW4qqoISeeMpYwiVZgJWuS9v337dlmWn/vc53Z3Y+fghz9859mzZ0II6wiltM2IkuPqnMN1EURJv99nQsVpP47j2ri0P3z1/mst4jcIgjjtUwgQRMlgNPHIASBJEhlEcdoHJkQgojhmUqgo7DEEABkGFnwYR8ZZa622xnuvrXHgGWIYRyoMkl5KOkWFARNcBqosapM48EzXGjzrpYMwiLXWcS99oQAb67gQldZSyuFweDiZ9JRKlASAu3fvFkVBWZ979+6Rx3Fy8tFsNovjuCgKynjt7e31+/033niDWOkuL2fTy1mS9LIs45w/e3q5Wq2oCkj0GkopyvyRIiYTSotZVVUYCUQM1JZkw3sk4ekCm9pgj4y2acj08jwnv2k4HN586VYQBN66ndFYChGHURJGm80m6Ee3b9/WWl9eXtJnSQ5PLxbUvUC6hhBa1lpjHCVNiOOOQrDWf95WkhqPgPKCukNS00oyofdnsxmptn6/Tz4/Dehput9c+34qNPCGmSDLMoqkCFxEGc3ReLB/sAsAZVmGoXoucUU/y7qKo77tAQCjfU7MG1Tf5pxPJpO7d+8Sj1pZlgSnreta/PIv/7I1jiaDTSaTy4Ubj3c5V97rJOkjirq2g8HgyeNny+USPDs9OR8Oh2EQLxdrJcP1Kj8/uczuFovpaj5fTIa70/P5ce80DEyVF4O0N+z1e3GynM2PDg4nk8mzsye9QV/rKzQSYyyOt4k7qjwRqPPp06fOudnllEwExWAE9b53714URRTT7+7Gi0X19ttvv/3228PhMB70JAI4dM55hDCOQoicczIdIGKSJMPxiB7hYDTc2dk5uHFIRVEKikaT8TaCcri3f0i+FsWEo/GOlBKZJV9gPNklm0lqYtAf0R3Riwc3blIWlDG2s7MTp30hBMUdUkoVxqvVOgwjqlwMBkMpJXUOu0+4anRwJZebdVbnSvL9/f3XX36l2qzL1UpK+Tf+xt8gj5EcFsZYmqZv/u7fWq/XBMOqO9Prd/Z2iqIIg0jXMJ+tDg+Pnj45llKult8nodoWJ4To9/vL5ZL2K6F0aCoSGZA2OwjbPDNSGEWQo23eoeNnkhmg95M00nluf+bl3fFkZzLRVY3GhUoN0z4i3rzzMrEFUgWbrI33Pq/rtrBEZKvEEfvjH79FBe31ek2uBHndsZKsGaHaCrBvyjykXNqqkjHG2Zpsdets47ZkZb1niALRE7cEgOecGVMDOO/Be8s5FkVW12mSRJIL7azkzIIXDEMlnXMYKMTt7HXWoBtoCFYcxwhorSEqctsMVYrC3qDvwyDlbB2oRMnQe89QGWOpFCfefOMXVsvspz/92cXpvMpcPBm/9vorFJ1So+NsfhbFoq6MLACZiROpAizKlXVlELIsq4KQZfnCQ60CZNzGiZwvznuRMrXx1qNHyaVgAj1OL6Z5Xu7uijCUbUaK1vdgNIqiqN/vE8623+8Tqntyb7xarSgnNJ/Pe73ejRs3dnd3P3hw/p3vfOenP/3pYDA4Pz9/5513iqJ4+eWXX93bMcbURdGqVdpYgYoYY94hhXyIuDPZ44zHURAGcfsIldzmBupaK+LBbnDO9CcXQCtDiCjXtB8mUUrUObRrR6OJEIJKR71ej/7M85xuZDSaOM+owkTJJ/Kj4jgGiF4owLVzxuosy4wSCwbn5+eLs7NsNutVBYW+FEqQmiuKIgiSwWBE2gBRMsadA+cAuUjiPgBTMl7MN3u7mOfVZJLSlWDTYk6XTd44lWepFWnZUI4FwRYaxbeQXWijaNehpPKdgid5zrqZP0Yq4F/+P35vf3//M6+8+uzh4zLLOWAoZBSEr7zyuePjY2PM5eUlqQPKq6lkW9ym6vpqtZpOp6vV6uJiCg3ulYy/J+7VOKKQu0218qaHnmI02wydoCor+O2A2Da0IQE2tkbjCSnt2n5dJjfrNfnVta4Zh7LKizLr2QQBdFXZMLTWemu9tc5a9N4bjYx5h64z3Ng5JwICPtVlWWdZhujJvK2WGWOcoUQQzuJmXZCbE8UB6Snx3e9+tyrN40cnZ2cXYRh/88ufPTw8DIJgvV5zzt966628mOdFWJa19WVRLYSy1uezxUmUsJu3d8siSHtBfxAh29Fa3zjanez0F4vFpD9xDg4PD/v9YZYVl5czRD4aDc/nU2vAGC1FbYzBWASBYCjJwaC9SM7V7u7ufD4PVdACMKIo+tznPnfz5k0AOD09/Q//4T8IIe7du1cUxXw+39/fv3PnzsXFBVFgk4Ymatt+v//lv/Y3HEBVV4joGTrnaGsW64psjgdPbA/GWqeNUlFZltp661EGERWTgImyzh2ACsPAGOTcOSeUCoLAVjXtSKr0Us8jBS1kOkjfE/NrHMfOiyaaQsqjUM2ZSfZCAWYAoYpUKNHZzXJ1oc6r5UpwTjk/YhdjDSAkDENd2zAAXTulGGecAKdBwCvtpRRamyTpJUn/8ODm+dm03xsSBLcBh2jyVqIoqqstnyNh12jvKqXCcJuB59tW5GsTA3mDIiYZhhZpbAwl9gi/vVwu1yaLirUBuyrWuiq5x3VNPcCjx48fO+eIgYyccCFErrM2q0S1ADKSi8WCMTYajcjfJvHbbDaKTZrk4tbetmmntlTRJpO01oKrFhdJN07qo9Y1NHAL2+CWZUOuTDdIzhed0BqtdUWpY2u1tbrVj3AdoEaHtVapOAySLCuUUm3iDZErFVBDizFUJfacS5J2a614eHYcBMHk9ui1L98vy5KjuDyfkpbKssxbeOWlV+fzua787GIVB4vTk0sKIRbTzfe/+6M4cOv1ejMaHR8fCyG+9Mabr7/+utZaV3kcf01KmcTy+OmDzWoaBgEDfXv3YDcd0CrTnXPgqQwP2Xi5WUuJw9EAOU+D0Ut3Bio4MXneuzUibA3xOevSO+eUW/y93/nVVZYPx3tMKu3QOB9Eoducc67jmJ2enhOuq9frTSZJIPSzZ89efvnlqqpWq8vhcDifHyPieH9SV845K7k6OzsbDHveG6nQGxdK1NUqkJJzsLZWHMGZUGI8GJRlrrhXioVSWWudLsIwIUon8kKpccoYU5WmP+gBuLLK0l7svUXkzqLiGjxjklcOlODrbBOGIXJu3fPY1zZe8tYjcACOoXq2roFHALA5W3D0/X6/z+Sw14t74KxmjH34+CFBrLTWL730Ul3USRwYAKWEtV4pcffuzf/mv/k/IeI3f+1XvIfXX7v3j//xP37y5AntsN/8zd984403Xrt//3/8H//JSy+9hODSJDK68s445/JsvTZlGIZWVjyFbUAr1dqe2KC4mM0EstFg6MBt1quX7t49Pj5+9fbt3mj4n94+Plk8YRveTwc7g7FdF+MirB8tv//kLyhaoRY8IcTH7z9pFFxDQLtEAAjDsMVgmAY14b1HDwzQVbp0K+9dEocykKIWO4PAubpcr5RSlTEhH9SVc84BCzkIrDFUUU+p0lSbPDe+tiaw4IraVwaL2i83lRA2DEPuHQMfKmUb7wIkBjIUzm5mc0SGwAHY7b2XvYdxvK8RPVvPllkch5Vhs9WW4C7i4zCURblCZrWunMMoGk2ns4rpzeYZhS2oYGdnJ6/rymBRr72wYS8obZXVeRjE68UKEa3Ltwo3TQYHBwcHBwf7+/uISC5EqxVu37lR169prXVt5/P5ZDI5PT1tdV4YhqasptNpr9c7PDwyxgRBtFptEDEMOBfovKl1WVZ5rUvGodZsb3ccRwrAMnRxFFLWerWcPXr8pDfojw76KnJuvcxLGw16R3dGCne2QSCB0MB58GDtrZde/vUoZoxlWXF2cU4JjDzPCQAYRXGeF7dv3wmC4OWXX07T9N133724uHjttdcAYDqd1nV9cnJSVdWX+l+M4/6HHzwwxv30pz9F9FGshsP0c6998aOPPqKKNMWxN27cOD09rXVJlvall15KkuTJkycE6GWodnZ2pJSnp6fbfKm1t27dkqFaLpfWFXVdrVar0WisVHpxfplGQmvNuASAKE0Q0VptveefYoE/7dhsNt7qPM91XW76fe/9ajlfr9eR3DYbDQaDd9/9+SuvvEKZau4t1eTIAbu8vMzzfDwen5+fU6aQHIednZ3Dw8MbN2584xvfaFO+lJKlDRyNNlrr4TASQsRhzTkfjVSRnYwSJlzgvVehQcQ47d98eZdHZpnNmMXBbnS/f8sabyrj3KYoZgAj35SLuz/xRfgnSuS22W/e6W2q6hoRnakER845ghn0ksEwCb1Je6kOJXnISSDqugbOCrBVVed1yWsJALXVjLko4K523nFf52hKX+egIymiWGKtfRQFQjBEX1XWOa9ULwikCgRiFARRnhd5Vvb68f7+4f37989mC0Q/GKS7e5O7L902tiyKbLFYTKdP67o0tkySmMAE2lRFkddFRhRIURQtl0sKIbMsCyNpnbaurnWWF0vrytnizFob9xVjTIAQSToyls0X2Wr9SAhx88bEd1CmFK4IIaIoLMsySZKbtw4pXqI3hCI5Pz+nPlvqLKENXW4u0AMAeOu8dVabypdWm3Ga1uVGCMEZA1eXuXny5Mk777zzhkhVHGXL+cv5yig+GPcVQw0Ibuu3uAbPTX/WRstABUo4bw52x2maLBaLJ48e9fv9LWLh44/v3LmTpumXv/xlRLyYbThf3Lx5+/LysizrXo/VtSkKGum2xU48ffo0zzfDUe/wcPfNN+TZ2dnDhw8pJmeM3b179+HDh8g8VYMnk4kx5t1336UkbV2ZN998MwzDH/3ohxRErVarb3zjG/v7R9/5zl9ssoW1Js/zL33pywf7N//iL77jdV7XJumlRzduvfFmzDkTQsgwKKvq0yzwC19XKjC1J6imZKwoivd+/s577713MNmlrqy7d+/+xV/8xe/+7u++/fbbAPB3f/e/iuOYRvVQrv74+Pjtt982Wu/uTdJeTBk7xmGTrcbj8ag/uLi4SNMeIS4FstFodHh4+OjZ+4vFwhjDkR+Ox5RWKOri1n64jtd5WTLBQfIojsO0D2pWVcVSa9XvjeIbRVZOT858qTlylLJNxvKGrc53sM2tBaaj67LSCtB7pGJCCAaOoReCAxohcTIZJ/ny1rjvmx6AXq9HicalcQ+PT8/nUw0IAHVVcGdCgUe7t2/s3Xjt7lG/3z86OiIshxBC9OI4pokZVZZlWmtiRHZf/CwAi+O4rkxVEfu8D8Nwcrh/cLhLTOZBwI9u7jOG5+fni9WJ15lQ3iOUlXc5L/KL2Wx1dOfundu3Hj58OB4NpZRVWfzwB99/5eWXknFvk60YasEN51Uc8yQ1WutNOeecCyvExx895Q2JYb/f//k777XFZVpTigGiWEBDZ5emqdaaIqI0LtdZjkL2er3ecERiPBqPbbwdiimvyB+1MWZ3d0KQTK3r1Wphrd1sVoyBDJPFZrP8+QdGqaOX7oQ8BItVVvR6Y49gnXd2y8XmPQOAYRK4KpNSsjRN07TXHzIZLDdlutQI3DsMVHRxPp1NF0qGvV6PMf7o0eM//dM/Ozk5OT8/Pzy8kefF5eX0Z2+/XRXG1DoIonyTWWvWy1W/F7WFAUSkoVhhGK7Xa6l4tzhBG9daW5RZGCmlxCZbUQxzfPK0rPKqqh48+EibknO8uLi4d+/ezSN2eXmpmM3zvKyr8XgsBEMmtgiev+JRVRW47QQJwnsBwGw2m/THsxlxQcn33//QWn98fOq9p/f0ekkYhkLw0WiklPr3//7fC46/+Itf6vV6bSn45ORZVRW7u7tJkty+fZsmDL3zzju9Xu/NN99cL1e+kgQdJdab8/Pzfpj0RDKYHILgBv2zi7PForB+s1xACf1i6VUY9foT8BtdbqDSAdsprGnzvVSnIePRFc5WgAHANIQn/nq6Xvs8DEOBjKGXUnhnjKk5x4SzvX7Pe09SFzNE7xLBFfJnZWFWC9nv7ezsKByyqlLebvJlvlQKTYlmcYHZQlL8v2aIiMfHx7Q43vsoihaLxSAJYdv952jGUF3Xk/Fu5djp6amU0oM9Oz+uqoJz/uTJk/3DQVmSO2ClCIvcnZ19XBSVEOL09PTVV1/9tV/7tUePHlFR9r333tvZ/fJqtfBgGDfOFzIIZGAclIFwjAHnIN7/8CMK2wjhWGWWkDQt7IaOXj9gDTUe8Q+RGA/7EQkz8bnT4x8MBjqf0miJ4XDovWdcJUHsvTfAQQQx0crBtK7rl+4dfv7NLx8oVdd1pfXO3m6UJsAQAHtJDzwgguAIyDy1gDEGCAfj8WQwRKne+/DR+x98bOF0uSlOzi/Wq818Pl8ul1WlP/74HWvtj370k6Ojoze++OXLy8s/+IM/uLy8fPnll51zl5eXH3/8cZEtpmfzW7fucuBg3aDXK8tMl1tgI6nbzWaTN1xqm82G0PCs6TInj44GBTjnqAGL3GzG2Hq9NMakaRxGaja/RPRBEISh8qZABtZqrSvvrXO+qkvjHeCLXehPs8C11gy2252uZ2dnZ39/v9dLkiSSUu7v7+7t7ezuTvb3d51zRHaXZcXl5SXNFhqPx1/84hc//OC9lgSPc07l3ziOJRfD/iAKwtFg6L3/D8cnf/Ynf/rzd979O3/nN3/wg8s4Vq+/fiuO48GAf/azt/f29iK2G6cJl+LJyfH/+gf/5q2fvls7i4i9g52yLIPQBiLLV1m2KaHSzvK63gJX2p4b38AMXyjALRTRddp3ELEqNt57D96DN8YYXTEP6/U6qStrnFIqjhKrbBiGznrOxG4YHw13PPDB/v6Nm0exEKKuJdg129JWklNzfn4+nU6NMXO7JdZxzlGthHN+enpqq7LXTwhK8PnPf/7wcH8ymfzK179aaPH7v//7SqkbN44uLs6Hw+Grr756cHAw2QvKMpdSrlabQMUX56snj08Zhh+9/55z7gT8t//0T27duvX+u+88fvDxS7dvfdtml9OLs+Nnpq50VTA/RGfBmVBSuwUK4ywgIGdcCm1NZZx2VVFfjUujhXPPDOUYSVypU9wYM+wJyr/RwRp8KeeWCNyoscY5RwnYjx89I6KwNE2zzDgHk/3R7ZfvaTMdhKExRnCxLkt9eUaawhreKuM2YcgYK/KKc1GU6+/+4N0f/uQng+EOSnV+fvHFN17p9XqLxeILX/gCqcDpdHp0dJQOdv76X/sV59xisbh161YvHdw8uh2FCfiCsguMsTt37ownw9Vq3utHZHLTNCWHM01T4vpYb5ZE4Og7TadxHKdpAuCN0VIKY7S1Nk0TzplSIgil1ppxl6axUqrWJefoPUZRxBrAMHLqrUHr/ncbXwBaXnDbmcNa6zRNb9++ba0dJOHB4c54PP7KV77Chf/N3/rmq/fu0kecc++///6HH354//7909NTY8y9e/fqKpvNZuv1utdLhsMhxaLj8fhoPDk5OXnn7Z89fvDw/v37vTjZGY1tre/d/8Jffu+nVVWdna8/+ujH6/X61VdfvZzme6M1l4JJUdV1r6dee/WO8S4IguPZeW2LbLF+VizqUuf5RjqQUkp/BY1wnUb/FhvcPn0SVN0M8vPXJ5JyFjjLLHrKAjJkiLws64qr3PE4He2Nx9SqRVXxGMXNe59flBWPYyllXRWuKiS680qvVqvjk4vz8/Ozs7PT01OaX79pSKq8996zKEqLosjzShcFY9IYMxwOb9+6+8qrL00mk9dee02Euz/60U+/+MUvvPHG5/7Vv/pXHz/48Pz88sGDRz9/b71er+7dfwURnd2cnkzPTi+Gw53hoPfBBx8ESnz80QfnZyfO6vv3Pvfs6ePHjz8oy8JqN+yPB2lvPNzTla2qyoMhQRBSCkIR006SnJbyqo7ntx3PUmvNhai1tq5CZmudA8Am1y10kTIc2+UWnDxJwrUjIo0qj2TYpuAJ4Hb38eXx+UYlSRRFWVFIKY2zTHCq43u9hfVQ+asNkIRKqrKsy/KD995fTrN+bzdWYiDl++9/WJZlGIZVpXd29oIg6PUGSZIUtX399c/RJTHGOJdvvPEFxhjzudZ+NNwx2u1OdlQgqjqXEuPe+Jd/+Zdfe+010lPUcf7Vr361rHKqHO7s7AghqJ9JCHH79s0wVM6527dvuoamUymhlNrf39tkCyFYEAQqEKvVknNelu0IX6NNpXgkJY+iaJOVfyUBJqvjO9wat2/f3t3d7SfMe7+7u3v37t2XX7k1GU1u3T6w1j75+DFj7PLy8vj4+JVXXiFcqrV2MOxtslUK8eHhIRHEZVmmTdXv98n3c85JKe/fv3/nzp35fP7Tt56sVxwgPj0pHz5YnJ+fP/h4vtlstJ1RiXU0Ghlj0kGfrm0wGqL003yxXK+8R2dZbR0X2CrB1qi22A/4FBeaddoJoelbDFgMAIKhR2OtVVIqGRR5/ajarH/6LlXInXNRFFGJkXOel0Yb8ICV0XmeGVsKCYv1tmZGz32Z1VVlON8OMaJ2ZcHDXjo6PT0tC9OPR9aAs84ayPPKGsw2xc9+9u7tl4I7t19Ok+F0uozj/mfuf25nZ3zz6M7Tp6ff+ta/49i7d+9V59xkPL28yMIg3mSLb3zjG2QFiVcoDMPBYBCEXGtNES4iHh3dGPQOrLWr6TlV6cWmyJkUrq4450VRJCEi95yD4lyIK8oLJZM8z3u9yEMtJTALNHXWWWG05ZwLKZ313gG5HxqZQ6GddbUFsMaYvDJaaw4BhZdt3ezHb38w/o8/HPY+H8bRMtuA5Bo9SrEusjCO3SZjzYwc06HML8EU2XKnHytTol5zo0Pu6nzjh6lSam9vb7FYjMfjPM8JlIIiIjwQRSnUG1xVFYCTUp2enura3rp1i4Y8OFdTJrDf71NapSzLoij29vak4kT9Q/ikr33ta347/25JsOSjoyNq2aEm9TyvvvnNb4aRQPTL5TKKEsHDX/plnwRcyiAvC2dhPB6XVZXndVnlAH+1LDQ0aCHy3tfrdS+Noyiazh6HYahNOp2dTSaTi9nJaDRy3t6+fZuyOEEQHBwcECJVKQWQXl5eTqfTJ0+ePHjwgIrSw+FwXVjO+dnp6dtvv/3nf/ZndV2/8sorFxcXizKjvuvDw/EXf+l3qVUDAMpCGWNWi2WZ50+fPlVCruaLLMtW2SrGoBTSYMak1L7Oso3x3vqMkE/txDnWMIS9MAtNXl6DjroaCpsVlfeeofSI1ntErmtPNefl6SXB1CkLu0VfKu4NeMcFk8iZAeuEhdqlMq1NYQ2AAWOgckyDACaVFFmWMZTIxXAwuXF4a7XMGF46i0EQ7Ez2hIQnj59prRHhe9/73mDyn8Iw/N73frBaLb7ylV/8zd/6rTRNwzA4PV7/8R/9xyLzr7z82ksv3XEOAjn4+OMHUXSbEsP7+/sPHz7s9/vgbVlk81lW1yZJkiKviqLSJcznSyFE4JUUYYCReO0zR7qudVnUOg/QCr7lYa3KOm/wNIgooYeIqyLjjDldgfdUgJNxLGNCeJeBBCUQwIKAvgqttYHi9FxRMo4uDkTutQctI3AWjDMMhUe2XOfrwKHOOZeokTEGBtCnVQb1FQcSGgPec8aYQBGURnFVbWzlOUP20bzismLc364Ka/XjD99njOWLmRCCIO+bwhHGYGEMAe6z+TyKos++dv+tt946Pj7e29ur8hUDyDe5917rrLe7i4i6LLn31XJJPQARB5uvUWuwtig2ZEAk56GXH//sgzAMDw4OhEZExjE4e3gcBnFPxsIJ7/1QClMaD+bO7hG1whSqCMMwu1gKISCrQHvXYU5r417vvcArpgvsUKvEUZNsCwLroUTmNhkiHu3vKKVCK5XmrPCHwwMABHQggJd2NwzPGf93v/f/6kUxB9ys17/9f/jdzc+f/uQvvq3CkHN+fHrCBE/TtFB8s1rP53ProM5K7/27P/u5tfbs6TEAA84YCqGCKI7TtBfE0a07t6ngFEXRnbuHURRF0X0pJRV4W4B0VVWLxWK9Xp/NzuimLi4uqGXCOTedToErQju2taUtfgOM8wj+iqWIWcYYy1YrKaXjnAAYy5WjXKzEMBn0kmG/LMteMx2bvOLW7DvnnGvqyYAsUN575qxESAJVIwCAiIR0QoS8qqqTi+PBaf+Vz7z8W//1b/7kw5+v1+t79+599rOfLYri3/ybf3N2dvYP/sE/ODg4GPT6/7//z//3e9//zr1XX4rjWEWBBZjXZ4P9+HNvfvatt396fnrmjHn80ftf+oVfyPKl1jVyZ4x59d6t+SJ7+uQUmUowH493hv1Y7k4A0Don5EBrPUniy8vLx08eixs3blpTO+eYd4jI8KqzhHQV3djycta6MR2HB1b5vFWQ0Mm1rLJV22mBiM57a7xzTsUx9f2AZ4hMCKVkKKU0fIOdQezNsrqevJoE5URL1KIx9iTJnHHnwVljjDO6CoNhr9ebTCbExUH3YowZTrbYoLIsq0oAAOGBnLNSijiOlJLOWa11UeRkzYjQi5wFaoEMAgWzK7ZRyt5Twq8oqrIsAHyWbdpVyrJNHMeAzjptra31FprnPDebWkoZxUGvly6XS+9dEEophW0oflpZ3crwdkwEtLLNt5t1jYhJEkVRFMehlFwIhoiXl5eUS4MOOYb33lpd5sXl2fnZ8UmV5Qq5t05X1dv/3fuL1XK5XEZJXBl9cXGhgmBTFqKXZllWZnmZF8YY8B6dd84FgXTInHOlLur1xl1cUFL+z7795+QH8obUgtaHahmtbFObDmNMRleMFsTWFARBlmVJOthK1PXBN3m+br1Ckna6wcuLi9Y7q+uaqDnCMPRdylgAaAbwtmvYPZu1NlBx2+Sgtd6GElp7MLUQSGT/3jtrdV3nWWYvV8qYsLB8VSYeXh7ty02dP7tYMFHP1ztx7xc/8/mxjKYfP4mSxFp79uc//FK496qJnpxdPvnZD06PT1bT6UcXuT4aIrNBFHhva+NOzy4//uhxbUyxWY3H41u3bt28eTNJIu89ei+4eHJyuVgsfv7z90QQpeAsoufIkHkO2GYU2j2EiPr2snVmWuny3m+y7dxkWpe2nSgJEtHwpzjnqIOkru1qeUkAMYaCMe6VYj5ioJL4gnV6oLdCAk60ZEWMEcxwW+iPIs65ZIIz5pw1xpsajGW1MZXWZV0rrR2lOgAcQK+XtK4XaSXc8jZXcRweHOzt7e2Nx2MKtikjoLUmuiZ6tE07O7blaNvQ61aVLsvcOeO9pciCdpVS4unTJ7KZ0U4mBZr+bxrpIKU4OzslmhHOufYIHSPMW5JEuBoX0lokY4yCLXMyoYV5O37SZKaZBthKCGOsrIsgCJI4DpWUGGfrzXI+z7Ps0ePHk8kkiKOyzFarVaGrJFLoDcwXdV2jhziKAACdt9oYYzJTeIfGmEobbb0Kg16aJEkSpkmWZWVZSkRCUxdFsVitTMOWDgBEwU9CwuR2g7Xte0EQlGU5Ge5CUxxuu+G997t7Y9Zp6KdiHnB+eHhI8NUulJVmL5NAtijoFqfdlkh9M/JOa82ZIkCLlHKz2Tx69Ojhw4fz+Xw9n3IHcRxrGQRCZYtVvlyvpvPidKq1flja2YOnUsp8uYRl/sEPfnL+7W+DtspCXwRv//F/PPnxz9M05VKMaugX/sH3flJU1Y393b1X+8XN8rvf/957D94DNHEaMQbARVGa6XQByNe1FLW8XOn84xPJPQdv6qooijd/8Re/dP/N6VKLMOmDs1sMt/NVVQFwDww5Uo5hu3/qbU+zpwGVzdFXQZt14Nv58YiItqjaMil1F1ERfDrbjo2iQ4qAFPbemJPAk8z7Bp1D7Li0ptQxR9r04WxujK9KW+ZVmWeuzo0uras+fPguVVNI8beXZM2LqUw+/9nXiM2jKLPVeqssAhYwxoytkfkwUowDY8SDVe7uHDbwfUfQPzrVzu447cWU62qzdNZazrZEEHVdbzab1WpFFZp2XTlHolkIghgRhZCt4fXeO6e1cd77NE0BPTKyAcx7bgyzlodMTKfT+WIOAGma0u7PsszovJsBap9L2I85+srooizXq9X8cjqdTjer9Wg0kv0EOS+yTc1BDVIRhQbAl1dWDhE5R8mFcy6J+sa4vCpxk/uydgjGOe2dCoO8LKx3AkEoqYKg0rX1DjlDzoBmrIKn1ksASIMImxl8LYFjXdfz8/dbj0M0Y8e891qXrCFJbvFYjDERBfTxtoec/otyqC2uod2r1Hy2fQYNRYZzLlDbzhAquCwWC2rUi7gAqRTjyJzXZjmdZVl28uRpn6k8z2fTKel96lKcTacavSvrg95oNNrdZJfZ0/PxcDQejwvmB6PhUpciDXdeuT3c2zHg352frH/4Q2tNUZXOOWDMg9S1ZZzf+cwv3D66Kbg/efLIFJtxP9a1OT4+mf/5Dw4Onr77/hPhgCOgB+698eBZkLaJTb8dPw7oENgAaDeQF9FsMonrNk4DmggGAAAqiFjD6CtVGMXpYDh2zt28zZutabrG4WAck4mjfhre0HxCQ/OPDftBWZZV5W8c7VaVyTbVZpUrAZVixkjnzbjPsUN00Dj8bnqRk2fV6n568LPLk6qqXDOCnTaBlHJnZ4fYQqjTgFphNptNrzdsz99y6zDGtJHGGOe091umWErRJUnahqzIbBgJIWPnQsbYZrNZrqbIbFltGIfhKJVSFtV25ku7CLRTabhU6xO5hkzX5CvvnTGElYe6rqh2HQZX1E2u6cUDgNH+xFr75OT4+NmzxWIBAJJxL3C2Xq6KjHGutQaGIlCrIqu1HquU1s1pgx5EGxcxCYwzwWUUasC6rlf5ZlPmDGiIqQKAxWJBAkNNs5QI7OaiGGNFuWENUzRFK6SgAxG0Ikp3Sn8ydkXH3T2aqbyeyGjpqWVZNp1OieQoyzJyc6ghnnXagNsogzEmeNCm02idtzpCCuqNoTQ4gREZY2sOFVjh0YB1WlccrLVel9Kj9JjneR7kfRV642ytJePLzTJOE6WUA5guFzYQGpyKQ2wmJwJAbUytoSzLvFhN3Qfr9VqAvzx9xr12N/YlQ6Pd93/0Vpp+bK0Vy6xEZxkgF8gBHUGOEZAhdNL3Or+S0q4J9V7Diw4NFhygR7RbAlQuuWQMgTo2jDHGOgPghGCccwMSvRBeCC8YSMAtT+dquSFTKYSQUjDGUAjuA2c9k5AkqRJ93dNGl95Wzlunz9uN3jr83vvJ6Mg0E2Vb3wwR63KLu7AN9SwAUCegsbV1WpsKyHcEa50+OXnayXxcVdrKKvfNwItuFiqO0vadZBDIPeOcE6HU4eFBEKhnz559/PFH5+fneV5QWyXNp5QN0jDupXSR9HV0tcYYqGrG2GAwIG+ZQhjOuXFXmPbthUkphLi8vHTOzefzy+mURrEgojFmlPSo+mq98wyRMWqiLFgGAAyo1oraarAanS8zzVAgZ4jcIxNRwJlAzlx9bT94AA8eEKIk7kYQHqHStbVWyW2rkBCCNClpWIveee+8J4OBiBQKWZqNhAwZItvS4nPOi822E5ssIfnqtF3Jk7cNdSlVSaibdbuGAOT9CSHCICEixzYwpGSHq7dM2t57wRCddeDB2QqcRSfQoeLOYe4NchRCmsooIS3H3JtYcR7IDXeXOpdlPX966gUzDBbTmYjDVZE9e/bMOet8DRAyBlygRGQctCmXxw/y+UkgBUMfKnF2diIFM84QMDtJIhGEKTjL0XPOObJVXm33H7Ku1yGjK8rPrmBL7L9QgBm/2j0WwHlkjqFHjgEAOM8tMOsZMg/IgLFpBpw7UVRSOs63bhIAeIdNyKqF0Iwx2seYDJxlAN4z45kGhs6hAy1EqrWmNq6OIEGWrznnUomAXZGVAoDkUXsvvlOEpHiJbJe1tp1mQCFum1ZpjUNV6cbaXzGeAcB8vqzruihqIs2GJgtFdr6qqqfPHm82G8Lo5XkumOx6ItiMICiNble+a5mhqtrEgemwN6G4uql2gyqlvNVCiDiK7t+7ZxrEmHY2Bl5VFReirCtjjEMoyjIIAqK8EUJwZOi91Vsl2E8HxrhK18ZYhx48Og/eYxwE2ylzjJETQXkEumbeDFhARE7PcTugeEuIH4bh1n0118rC2NSNZNPssV157413zgHF//R+rTURbpNGWCwW1IrcfrD9rxY9YprZRYP+mGhJ2lEbFI7lxRqVaFMS1jlDQyqZ9AhFVVI07qwTQijBgbHKQykx487anAEyKI8vsl5pGWManPZu/tFqvl4xwYMoHAzTonSA1lhjrBcyDEOpAjbgxpmVdYxJWZWYbebeW8bYePfm2dlZXSkRhTGC996CdR5s2tsKZFd/O+e5Auc8Ou+3BPMNMsZcTRvpHrTQpD7pJMZ78FBbBHQAzDnuvGUeEQWiCKIUER1i5cFr3yqLQG1nzCAic5S94M65clo7563x3jn0BsExzpGD1xF6JXmE4irH6Jzj4XaKFLnuvkliWbMNR1vd1BpwCr+t1c65uvZao7U2ipX33tq6630JjlLGrbXnHTrC3d1d15D9du02xQ6z2ezWrVtlWY5GA/JMdeXa5Ao28westXUDrYHrLvRmOm3PT0JCAkYDU0lo2/SvlBKMrusanQ/iSCkFiEEQhEnMSk15pqqutTUWPDnYlfcU6uebrC4qqw0iouCbPHMOvPfIpRQKOLPWWWMqVyEipX9JO2Az/8E3U6NcgyTnnIO13ntKGtN4CgL/GM9aF7ob9HLTZclwiMgBAQEbIRQNxzp9b/ulvJlTRef0nf7+drdbay8uLoivq9frYcM67r1XQbC9Bu8J0huEISIyD5Qzo7vePghkJsDNOuNCSFdP52uPgFIUdSUDkZfF5WzWG/QN+kW+DJM48vrGus6yTVhLAPAMQwDna2O0qzecc2cwLx0g50oisErXTx59HIYheoP/5//h/93VcBSlwCd6jlEq6OR+Wu8R2dVk9O4boFF4rRHYWmZ2VRbCTp0Tm8xwm/pq9yjtQmywHK1pbS+yfadzDtA896VbsXQv7vLpOtvdS0L74tYCxOyFrzNvPvmlAKA4677Svm5d2Zr6br0NTfji62SbF77udd0o2athCIhYlwVtWRJg3nTegd36zNRSIpspExpcG0e0u7bZ1VtD3dor770AdB2sReu5GLg2i6T9xWjXXmd7AEDdJNu6m8p7H0nevtjmjb33dSnaNcTO4aV97gnS74mK2y81zeGckyK8to2bw1n23Jk/ube7d9119Fr7jIh1lbXpt9ZZc87VeXb//v2vf/3r//bf/tvpdEpJL2utk9ieExroodZasH67kt0FbxdhO+SqPURnwlL3dYfXQuKrRWS++07qNQAAdt0mt8vK+dWD6Vok2ZFYay1VDgn56L2n9AZ9nPIftjP0Ca+VCq96zbriZD8lVuf805oHXsxNhV698HXYPvj2S6/NdG3/q30DgkJABAaegefeMQcMERFe/L3evfg6PUqyP5xDm2ZnjCVRShk4yoe1pkaXBUksuYi8oc44ubykaY80crkpwCFj20osubjt97KrnXwtLcLUlhLoua3W1refO1yj+J7boNxvu5Se27VGu/b9XQHT8GJF7Kottre7u7z3eV62X9p+BBE5U1d7fvvVTecTAjLfZnDZtt5Jrhz9A9KTiDAcTtrL8J1QqxcHXLBNth4M+71+2lZV1lXR3iZ06HKLjO4XvAfGcNuu4X0YbtdZUEzvmswe2bpPCnDtrtTDlZlCZPxaWRibioWvrgl8+4ttwNKdNDMAgDVV0FFg7XmAs7qutbEAIKUUzfBFY670Dp2QSizWmCu5hasNhEy8cAPhdUVzdfgXv472U97PmxiVLqb5XuevvAzo6BRgCIge0QGCZ84hekRE5l/czYAseOHrDK80BXaSZ2HAm4yacI4bw2gKFA1vBkAmlWfWE8jBX3uI3VUlAl3KiHSfPrNXb+tegOs81+4te3H12XYzAEBebJov8q1yBwD01/dHe06ou1fYnk25Fz8XmVwpvvYGnXPgr1L07XkAgHPZSq/toCGe01NteZJotNn1AxEFfw7ytD1CFTDGNsVqvDvs9/skd2VZzjdF922tK1QUNVzXhr5hZabLFtQ22Oozzq/FtO0dGv3iqWoIjDPO0AMH6HjIld52hHUzYQDA+POPvPm/LZshdMoGAKCCUMg6CLdABcYY4Su4kO3SQKfU6RrE0nMbiH+KQHa34LXfX/huAM9evLGYE7QkvjGz9KeD69qkPTGy1so7jwhb0yvgxQIsPgUjjaKNDz0AecgewINDRM+YY+wqFvDeh9Ji4+yYZqyUtZbacp0F79A7BM/AewSompI150hPkr7IW7r2K8fPb19+PvSgNzAU0Bnh1f7kTD73zu3hruSzezYuIn/dVm/3lbx2hivxNqard1oJwQ5DZfd73YuXv3PCjrgiYpZd6c0uDoIcO389LYqISoZ1XRtXJ72oP0wJcGJc3ev12sWBzmC3T64YXNc7oi2rdIWzvdvm2WxHS3S/oLkxaC6et34FABgl8UVHOy6xFVE60qjfuW4PwMjxa7mIySEEgKIoKLXR1cTtgnb1ZfdxOvspGr27QHj1wU9pywUGL7bkHq/a3K497yuOq2uuNeDVrvH+6mWPn2KB3ad5EMx775FR7b7drFTz4Jwz5rsbq6zKrppvkXMkEa0+pF0AnR3/3E5i9pqAtffLAvmJK0REZPiC2BgAnPPdd7a/C3EV63YXVvBrsWv7KS7L/8xG725v+mDblth9EQCs0/CcabnemQykWzwhj5ELjwiIjnNkzDFGFgskV+1NkStE8bB3SAUzACBUAue8LEsvYmAIvumOBOBSOOfaYWjP6aZW0LbTKNpEXyvP7bu3iwWf4gp2LN5V7cf7IIy7C3e1gsgBERCRIcNOkQAYInIhuFDQ0XNlWRJnN9amKGvcjl9y2rjuZTjvkYjOnH3uVpsH/ymCBxbo/dsntBWzT5Ng92I9AOxKQVwT1DZ0fV6nwPPkddvr9C/+Xvspltl3UgGsE4PIziYERCqnevC1Bdv0HFsLtQVjAYBBZ4NCZwMEKoLrotX4F1fKAj4hMN2TkAHwnaRA640DbNf+k/ukrE2DGGruFDwAGEeK+6qdEAER0ZiyeYxXSgcAFFdwfT9TPkcI372p9iOSXfWfQ+d54XWKH/oFEduQ8wr0SpkI4N192IqV1sgYsw618WZT0HNwnhlnW13DERhjnqEHRJDNbV472qqYMMa0jqtpAsjntK/33nPxnIluVpwYEtBa75rZrQAg5fMC4z0gYl1fxa7YAWBabxiiEM0gdipCWLsptgikphq8PYy/hvUHaOpbQFigjkVFAAD2KTEwte/56wcAuI6rf+34xMT07dfzKwHoPnv2nHlvrs2D674ZYPuI3P8OV797tAoLEdE75hkjiDFz3l3dztXHjTNm2xXknNO1dc4zxtAzICnzJBLN6sir6erby6Tnbq6Nz92KLkJlK+iILraNu5/iWeRZ1b6zW6GQYQSdnda+3nhY2/W6MgAmhhc9RwZXnpHfpk7Be2+dB/DtFfp2SiDznzy6T+Fqtbcxs2sE2HUFWAnexhcAHsAiOkS0oIypOecOhLOO06RVFVtn8LpXT78TtPaTBzYGRmRZppqRrTRzAF4kwIxx38lRdSJb4Rqy3O6CsuuWpz2IVcs2PWK2mdHW721p8XynjuobzGMXHd2+gh2Pvc1PBMHzMRX9NNWLy0KUBPrkM2P8xRvOuRdns69MzPO+Mi331RBq2JYfri1LKzGfNpnBfYoAdJLB13xa48tWirobCxh6hPYfURcxwbtJ+vZqr+6llYemT4OC7OduwTdVDLhuVAGA4XPte9vn1U63eE6GN2XdCAbvXD5ql3V3FGMMARFQYOi32QcHW0QvPdl2J4NzvklLObYtQzLwlHd04AG8N2YLyKF7ajVF+2wRoXvBVOhmjHnvOG+nGUPtrsXeiEiXJENZFCURwiI6xpgxZRhG2noaJwIA22cE4Lx39upmuwtumtdFHAUkD1GosJ8SEo2Yh9rsNF1oO65Oa+2MFkJIIa3VzjtrLVzPQhelbnNRrKGPEkKs50VrdQVr4iLvl7N5u3BdpStFwJBx5IDAwVmwxpi61oLJbnqMxrF67y36VtS3MkU+lrxW32ujhnaWT7tH6afrAG59xwUQLOnu2nYzcXktwLs6G3Sy4p3zf1rym33CtW4e2ItfF4ySy+jhWllF8aSREmudZQAMGGOMe8vY9iFaq503gGBsbdu6N9sWStrgBPH5Ypv3DhT4a1prewT8Ksm0jeiQIaJ3DAEQAZm/drImtGlXm37pqxdPqOAubT2Ero5wuI2BgbdSCwBAjb6wfS4MPWfeMwBtCoDOWnNGvpjw/IXPEUwNALTjul9NQk7/nNsqDkQQ0ZW/AJ0cDeM+TgKttbPOew8WuIBNtizNVazePXwnJOmutTPbaxe26VCjDxCmhDVQb7geIbevt4ko8mpZ03Havt5y4rWefTex5prG7nYhCLx6fZd4aHz9rnom4W+HmFwLPBhzfnvN0JEubEA57eU15Eae0vHPyTA0nMNdgUeyS9Y8d+auWD4vvf5qi3ff9l/0wOu/b/+1N+i8A/Db1LH3zuh2HTrX/Fdk4vr0ozFBV9L4X/bGu2aNTosdYOwnv+uTz2X7v5+Sa2itaJsno1/Q0Zei9zQLiq4CqWrW7sN2PxMUvb1mZ7f4LQOOUv3gGWElkHkEzlz9SekFAGQvdqF9E2qJqiq6H9D6qvDtm3bqVj6xk7GgPCfiVex+7YONr9WueGPHTHtX3duezdbdFh9yCgBAqZAgKc5ZAN8A35yUwm07cnWrIwAgSOIX7pWiKLrf2yKTuom37rNvNdonN1C7Qf/zGwW6oe+LvuKvdHzySv7zR1sn9I0/uYW+bLOvL4jr/oscn5b1xb86VdALj+eeF1ytKj0Reg07/7v92f0Hn76enItmD9vm4nHrTGyzryTLSPU61uRccZuaZR4AEY3rJmgBtg49ABkwuBJ6AGDeS99I7HUB/rTczVUZyVynI+ZctivVVaWt5WzNEf1J6f6uq0ACXzdNEduAlqqTHqzdxhitAG/daSG6SPfWZVUKjKnrunLOcc6t3TIYNvPmPOfYWksAaIFlcF1g2mD7Oalzn1L4a2fMPieT3X353Eeek4TnxPX/XxaYkk9AW/XKAjunuw4EBcvQWXnSY257zeg+DUDyV7ycVvG1Oq4R4Gsx819VH7UHa4Z0w/UlbSxSa/Dhufc8p1gRP6WcAIxkjeSVMaSlY2xrwK6ZR0QSsK7s0VksMARkyLCjcbwnX4cRXNFf6QIQ8ip30P35afuzBSb9b8gq51UCfO4cAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display cropped image.\n",
+ "PIL.Image.fromarray(distorted_random_crop(img_array).numpy())"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Apply all transformations to an image.\n",
+ "# That is a common image augmentation technique for image datasets, such as ImageNet.\n",
+ "def transform_image(image):\n",
+ " image = distorted_random_crop(image)\n",
+ " image = random_flip_left_right(image)\n",
+ " image = random_contrast(image)\n",
+ " image = random_brightness(image)\n",
+ " image = random_hue(image)\n",
+ " image = random_saturation(image)\n",
+ " return image"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display fully pre-processed image.\n",
+ "transformed_img = transform_image(img_array).numpy()\n",
+ "PIL.Image.fromarray(transformed_img)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Resize transformed image to a 256x256px square image, ready for training.\n",
+ "def resize_image(image):\n",
+ " image = tf.image.resize(image, size=(256, 256), preserve_aspect_ratio=False)\n",
+ " image = tf.cast(image, tf.uint8)\n",
+ " return image"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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R125cmRwdkWR05d33w0poeWt9Y2s38oXJqZmFWCTcbpkjI5PJkXSnU0kkMoI5tqiHoxhtArOYwA6R5APt4EOO86FMhSGfNdTgBy86rH57YK+GbHiAaP0EPPw4HWGo/8/+foonkfPWJY45cvUgAe1WfXdnpd2uIqsWiUl3Hny4tiJdfGrkxs17lsO1UKRSrzVajeeOP/+dv/i9UrP5aL2GacNs5tPjF+oNO2VX9U4HkJBkLEmyw35CloCgIDtCf+1RrZNHO9YDokEP3a2Dld5DaGkDH3QoHdSF6zECJITRaRSLGyDsaCSSTmbGx7LFUoFiajF69dadWCKZyiRlBcrl9UePVjuGNDp+IhIbWdlYX9vYiCZCyI5UC4agFhBhO44Y4Pr/lOkxqumH7c9w1x1wHHmvn1woxBMWksERd9Nj3NOWZTYb1YiWMFuFiezUiYUls6FjplSqLYeR9a2tv/Fbv758f+2P/+T/2ypUwuFMm8fbxnYynTk2f/zYiZndW81ayaBjgtmI23hg4NMwXTr4FnjiA/fYaKjXH+KaI1GBuqrHABTo4Fl42Df50XDe4AMPOg5hPAFIRFM1JIApYdRsWZNTF6amcpYU4crxRyucSJoDTjhm75ZWU0kSCePCTr5WMoRtR5DTqFTu3mpk0/Hnnh0zm2irmVMiEdZp2g6yAfjnNE88OLABOtzCDhgQAYQBI8AgEDDUjRgXAFwILggWlADBgBEQDO7vR2In/1g0YAU42FgZUCtxAB3VNcPQoBqLgRMCcQdAIMGByko6k83v7ExNjGVzU2FFU+VqIm1srN946sL5y5e/8PbbN1Kp8Vg8pYUNkMjYZLrZrlHIUxESthEOhQmVFDmsW4JA1x33ienJqtfBu4ZpZkAIb+BGAcCFB0wjhDCQvrKgCEAIYByAe6UNXfNjAHByiC4OQd0HHU1ViM8LMUcgjDgXmqZGtdCdq2/8zDe+joVx//7dZCI0Mj4ik3YuJRMpvb1rXjiZy6Tkq/ffVyPUtNsT46mYOlKrKdXaVnpkBhCSFRU7AjEbE/lTDvQ8arbo0uHWNu7fy5EfA98NmEKeXscYuA5E8SME/OPntM9fLNChCSEQAggFhARCWFXVVHq01SgW88uddoMLXK3Vf/VXf5VQdWe3lhs7xhgSAoxmRyO2ZWyrIYy1+EbBrNUq8bhGsIOAUQIg+BMFs46ODnSoDT6Cd33sA3z/NwcQPot3ffVua8St8TG0an3UdBg/wOfU74MIYEAYA0fCsiwAdenMxd38VV1v2qZ9985OOjOWzWVNs6Oq8VQyFJJlKpEvvfD8wmzO0Nsf3FxNZ44bjmY6DiZMIiaATiDMkSTEcNXIH9+rfapfJFDn3NN4XBXIDVtx9XvRLSXJ+4tGCTGgLtATWFcDKtBwIQwH02dPJmIEgIE5AAJMwwCIRjOjd+6VuNU4ufhUo1HBTvuNN9/E2MFQr5bXtMycbsiLJ3Mz8+OlVqv+5sPREUti5XA42mo3RyKmojmVpo2xxJ7gDmGD6VNVgYKRh1gAQkAwEAKUAMIgUwB/seQcBAfL8ZjeexAHFuAad+l4rNS/Agy5mA/l1fuMzQEXq7QsmyJhOzbC6M6DB4ZttMoFCecvnT+tkJUPrlyRFPTw0fXV9ZXCZh4oBe1SsXYylowsLR23Gw1qtKITi+1WOzRDI1HsbBpYk4B/2vx/OCN40Km+kwNaDpwZEHrLBEFAKZJlkGQgBBTZq1vPGbhx7JLj34vATevTLeHwfc/gj99VGlCBhlvKDxzxIWXJgdNvYFG7Ae0M0W3OQJKFYQkZOUhf3tooa9L0fDJWg2gbzLtrj84swP17y8LUImquVryPk51f/ZvfvHbj1rtvLWOcqBbawM18Wc9FL4j6o42YmApNRWKjHZ3JlPZl4BzhV3t8ylXwG+7tNYEAABCC4M437gUIA/bNBk0C5JaloUAJYAyOzgnBlIIkAaWACcgEkBsGC54NIDAAABfAODgOMAdMm9kMOMe2jWwHOAMbQ19u81D7M/449F+QEYwxWCZDAI7jVCrVeqNBNGOtUJiYO0GItblyhxssER398KObkWj03MVzL730Rb1pFwvFUEjFiBAiW5Zt6B2jk5+Ynt3N241am4BJZMI+n0ZwkIIBTRj3H92CS12z2GHAHGA9PxEhru4vEAgMAgEhQCSgMkgySCpIGhAKyJ0zEkgyyCpoYRoKU0XFkgQkuMfSY3rlJ/GQT0BoGNfIcAdngBEORSXTNG3LjMfj1dp2QxdNk2SzyUL+vsPM8k5jLDXW7rS//tOvAEPvvP6BbbYbjQYHtLW1u7m5mUrFTxzPjI6NtfQYRpKwmg4Plnl1u35Ex2Mc3B/1LHfkMQkcvaaqACHAtsGywbbBdryDCXA42BwcBjYDh4O3bYnrICMe+NM9iAREAkpBIt6K0Z1gwS4fLfU7wh4fnnA4v9iQTrdhSAA4jCGGq9VqOpM+NntsfXUzk5oCFGl1SoqGBDV2Nnclop05c3p3d7dUqjAmipVdgnGpVDNssfxo5ey5C2dPzt1fLnEetx2uabShI0yCe9s9RsP0qOhHwJcu93f9U73E7L2bXR7lHDAC4YAQwBlg4rVMMFjY04IoAMF7LUNX+xfAONgOCA7MBsedPxzYx289e7Tj8ZlfAY6uKUkGjAEB0nU9nU6vr6+fWjw/NT52aunkzdubU8dOSzKxkbF46oQiq7du3ZIUMjUzLhEhq9L07Fw2N4kl2m7XLFNUGxVFDe+W85FowrEYZ5+5YLhhaEAIQ3cd8KXvx4bQiR6jVgBz+ZiBbYNlgmGCYYCug26ArkNHh0YLak2oNaHagGodak1odaCjQ6sDrTZ02lBvQr0BrTZ0dNANsDk4T2T/8UGhEAfd80kSHg9sp/+aowsA5ACyImEJOp3OyMjIR7fvHJ87o9BOp1FKZ5YWl2azqfqp8ycmJ3JXrlxp1fWW2DpzfuHipbOKLKfTo5bFv/aVr83NT62vlmvV4mjmBCMNJqGQhjiggwr9H56eJMCEAtzPg/Vlgl/RNWcBBPPLcWCPeQkDIYAAMNYT/S5AAEgSYAwcQAhwHGAcBAPOgAM4ArgABoBFv4Q+ckggoAINfMMDrwnQ4c3CPk10qJojQxFzABOwDMasVjo5MjvrFEtr2Knk71Wee+4XJdxIRPn/9u/9nf/rf/vfq6oqSdLt23cmZ0fCoUgoEi6VNmJRmkmM7O4UsuNnbRulMmETTKdjMkFgAFjyadPADgkP6Oz9x14VS3A/gq07B7AHxImPQyTRHoeIHhZ3fwoOwgEOYAuvffB5w3YAYe9CzoELAO5VNujfdPpxEu3HfQPeuKAMGKga9tEw8QEDv1EfqOw50o+CBAHmAJEgFccdi01MLtTK120sGKIjmeit6z+cnxT1WnR0PCVLqmAiooWwo5xaOp3NjZbKjeefOrb2qKjrVlNvG4bisE5KQslQa7MVQowOI5ie5CTpH0ZfUiO8VweB+2LeZWIBIDhgBJQAIV7QLcO+64p5H2JAyaWgkBJeswLA4eBY/oN6iPH+zYC63xl3U3UPZQT8WMJ3iGC4IVwhQ931aZPgwB2gElimzsCJhsP37xQkUmk09Qe3X89vP6jURte23sNUNFv1/FYxOzomOB7LjaZTcRBCRfjWjbuyzAv5lenx45Zp4rBJVZNbSKLa4TzoB1aVFoe6a/Dg+4EJ4LOIK4Bd7N9tUqJeWE6XOO8pY/FxjQd1hCG+/oAlZZAaOYza/EnoUBNgSPqMKcEEg6xBq9Pa3d6MZuLFYgFjVK8XjVajuHW1Uy8AjH10/cPxsalKaaPdapdR5Wd++oVGrVIp53XdLBRb9Wpei2uOXQ3JZHNtWVXwqDIjISWoEw7ocxBnHA7g6sdYDwWLuXcI4dlUhAICEMRbYIXwYEfi28FCgCMAwNPRexGZAUjdoP4c3MkhUsJRoJ3hql4ffE2X6IFFzQ5X9QwdYfbaEdk9wgGqAmPW6vrqiDMSjTgSFbbljI6k9GapsLtuGufv33tEkOrYdqVSnp6e1SLKgwc3p4/lBEb3HzyqNqpCcWw7tLuzsbOzq4Zg9oQZjai60f8sD/buoeC3HGaABngChhvW4FUEuUUjQaIgKSBRcBgIAcwBgD2NBdx6e7xf1nYhoAEK6UAd4UhEd8AVgIbUcIZmvs86DHqExBk4JqiyZFuGobdlGW9tLuuGOZqbBoHarTomxDHwxupOJBQbm5wYm8i+8darOztFw2KWDbph7RQLlXrt4cOHWCLnL11ut/DmallWpGF2tvzUSZMgpEJUg0gYomGIhCEchpAKYQ1CqveLInmxa/0M5LoFXAdW0Dc8RCb3ABrOLxQM2D5aGi4a9HCz+RB9fZyMJMkgmLAsW1OVbHaUOY5gOiBKlbjNtmVJkyitlpp60xxNj/7Gb/7Gf/7Ot+/duzM/M9NoGYCJpGiPHq0yyifHnlpYOk4lZeX+DW6FEGKM4wO3SR0oFIdCnH/8uyAAFyKAsApUAioDcf2sAJQAx8Ac4AIQACGAMNgYhO1BMV6lYfCdYggQAjag8PZhKOjo5YNiPx93pPdnbH8AFBiCgeLkUPNExsJG4BitUCQ8PbVQrbVGJ04YnWo2d/Yda1uJJ4XgbbODFZzOpQrlQrnckKS4btOIpm1u1yYnZsYnF1cfrrzwLJqbVG7eaplkBitcARuB3NdLPLCPgVfzdfP9OdpdcAY8WLCXCVzO3osT7rqr9v4CALCFt3srIaCqoKgiEeIEYbd+kQfpCCAYqLzXAiIgYXAwWNgrt7rPNeb2EHn2K/dhzWEiRgd82eAlQXM/UHYVoUEA10Ck/qBnuY8LTIAni/AMMHEOtCaHMJ4GkqKBYKhaKYyMjlbrbUoJwlp2VDNsPLdwXphUorRjmV99+quxWPq9967PHz9dLFRW1u/FwiFNtWOx2MzM3L07t1WK2q2qbhijublOuxVLkIFbvRy4aqKuZYk9C0G4hSvEnqbbRdW77Qvu8yQC8OFO4bOXB94DqAgoAYmALEEoDKoKmordeEzOPA5GPfE2XuSPA4yAjQEjsBzgDEQw2QV78QtcAEfAB6FSA8Grg03eARbPgGv6141B3D8Mg7hD9xlbAR4ntZsO0aRqtXLh0lNXrt7JpOIgRCikri6vLBw/tbuxDki8/OKXzp6+7DgiojTCoWTu3Ey5tj42PlZr0lg0kk7HXvzCSxF5cn1XGFbz2OR8uaRbYANyAKQf/fSg88SFX7oxCN539W3MvQmAfOnpasAcCICkgBDgWB68380uF374WkwGWQZZAVkCWQYqITf/EHHAGAQGECB3U9H9HmIJmONZw9wFggZY08A5YAwOA4QAi/7cridMA6fNMBPAHeGjKY14VDQULDhkU0HBQCWCBAERCscFEMNsGWanWGxIilIul5cfPfjpV37+pS9+8dGDtXQiF1bj1UozkUp9/ZUvCyHe/+DKz3z9y9mRRDwaqbXacjppmyVZboNkmGabksjH7MjR+/gAoIE9Yb93HgFQXxXu0T3Ah+0RBipBRAFZBcHB6IBjAyCwOYieiEvi2oturi0BJoCZ3nlKgFI3OxT2bRrmalwOIADGgGGgGAQahPkIwF03Fgfgg+rJHV0U28GZJ4dpdY8+fytAUC8c+k6wTUeitFiqjI1PMrNQLhV5BE6cPLuysVouF0cymUSsoSlSOKIYens8N2Wb+sKpCdMwV9fWHcdcOjH35//p+xYyxud+DnGl2alosTbmOsF4QMxMoNs4YJh24Xn3J3KdA77e72EgCIRbOwQDxqBKIhEFRUOAwA4DdwAhYAJsByzLi6YUAiwHbA6mA4R44KYsgSyBqgBGIMtA95spnmvMnUEICAKCQFAIhvkJ5OW1cA6I71nJnzPyO0w/xWzugdleBwdZDJcjFvwkDgcKIhLRms1OJJJcy99JJWMy0hGAIkuyTBr1SqWUl2XusLrByrs7TUyITFOJkdzJk6cjIXVsPOcwxilr1JcBi45BoqF2OgrbDXE4QeWZlX59aTcEwLUsMQFCPSHtau0YA6agSiKmCUXDVPJ0I4QABDgMTMsLw7RtaFvg2GCZAOCj+zIIDgSD7Ctr3Pu3HqcsA+RaxhQEAOYQ3GwNYW9jHsCAGQgOzjA60KHF/xADO8A3N0zjn18bYKjUgsAZTAALsCy90zFkFSxTn52deXTnyvrG2tzC+Wo+Uq2W15cfheLa2ub69u7O9nrl/LlL0chlgsB2HIIhHFLTqZTBre38tXhsgZDj0H6YHVG36jbAj73drODAhbezAXbzBilIxNN/CPEgSySAOyAEAAZKQJUhHgIqAZH2Iu8xgEDAAEwHTAssC6otMNpgGZ4P130W7wbZcwAsGEfQH20l3P2lKAHAQDngwATA1JsA2AHmAONgBFe/QQz4xBIbxJAc4qJABy4AQwrcQ9LhBiVo9AzRRU2DdrFz98b74TjCshGPa69+9/8zvXB8diERktrcQkSKLK8+mJ1b2tk27t+vJKLSpQtLb731mqQisDo3PsrHtkoRrcNq+fVlfX7x/O71P+XNhxcuP61S1LR8RAcDxXsxhp5wdaugOYCx52lCHBABSkFRIBSCcAhU1asTiHyLGWNgHBzba8pdEySKNBlhAhj55gECgj2TWsEgJHAUwABMBdt2BBeAgGCMQWCXqBf8gwUA96MhAECA48OalHiiURO+E8CHjNxNoRgHy4ZOBywDQgow7u5c6KFD/SGWw0Gl1JUhrl2BvCoegLzSQ138ygvXw55E66qSTIAQwJhvvneHkQABUFx4wG1WeO8oxBBGcBAJOKoM2MOJhIF3DdOSay8apsEalhZrlbe2ZEUyDJM5/Nb9G5qmCSE2t4qyEicAIRleeuHF7e1SLKaYppUZSeYL20KOddqmoiU4tyyjmMuOhSdiK48e0XBWxgpzhTQFijynkgvwd01Z95sR7PmhXJNUkkBVQFVAkvwJ0JOeIiHgsjfgGAMiXuMYob1qPNy3k307m1AIqcAZOBIBAIS8CYPAh1wxAELM2r9lkwDh9A8kZz04FQAgwNgzSJgAWQLBwDQ9AeRGNxEfij34wwVA8O7MxwQI8jIkuxOP+9mVri+P+LgZ8+srCj8ulfjYLkaeSJIl32ktQHDAAJQCDKMCBT0Yn0WDZ7g+MW51Op2EJgkuWu12JjMikNxpWavra/PT8VarU2/b69vbP/XVLz//wtP1Wmt5dXNmPNpotEMx7cGDu9HMiQf3V8emZzDop46n5o6fu3Pr2ub25uIFgaiwbCAUSTIQ5AcU9DpcCEgUSHcCIKDY+5MSX6Rhzx5APpu634/3+psEcv+py08cA2DAaA8RxwIiYbf8DnJZFiEf8xF7X9SknnbUDffHNvSRG8kMPTztagTuVrRMAs4ATEAYMAeGvEyYAap74NRA3d37Jz/IQpJAlv0JIIA7gBnwbqo+AhDAnT1LvWsfYr/DrllFMUjUwyEQByCeExDjIaJBgx0d6LL+dGkY/uccLMtIJBJLS1McR2rR2PaOMT9/wjZYq9UqlsxyqeJwwbmYnJyQJPztP/9uKJbhLNFsdmoNq1ApLTjztUpTS5jzM2PTEzGMRKMtxrOjsbCQFTBMoBIoKpCe9MJubIwsCYkCwYgQT3fHwluRMQGMhPdRKXL53n0rggCjvcF2PzDnPdah2MsZwgiAesuF7OeaIOR5l/dcaX5zROpZAdwELqt/0Ezk3dLNdHHdwxyAMaAYOAFCATEQBAQChwOG4cKBPl5NEhy462EggJivAnHgzMtYwAIw9yaA8IfILUXq+umQrxx6Ra/dyYO90UYIgAkhAKMDI1iG7v2nS0N2p9loJxMJVVF0B42MjBhG8vjcid2dRi43mog7CONmp/7yF79Qq7eWlx8tLC4JkDOjKct2DMPO5aYcJtKjmUwm1W43OTMSca1cKS3Mz6sK1zSwNMAUJBkk5MlI5KsNrryndE/Su2txV93vyjwvc7znxfaJTuR7cP0TLuMyX0/tlmzYS1EL8qL/d++U8GRnEE4R3vrglnMDAOZ4RW0pAUaAE5AVYDYABm4DBm9+DvVFPv4idw44jgd/AQLhWt4CJNojOxAQ13gQwN1ESuYpQp632x1AIYABRshdDQgGIMAYEDIMChScqYMjXT5VGqI/RALbYmO5sfv3b0WSk2FFTiSSSBBDNx3mHJufxQifO7F4+fLTd+7dp0oiEtGwYByb0fhkSA3PjkXadnl+YU5SaTwy1Wi0S9ffO3licnR0kiAe0pgDFFy1FYPwZVK3Y4Qg1wAgxONOQoAQQMiN0Ufg66wHUE/Yj6uLI99xhnsWnGHsq+6zupELNID6S7K35nAOnAkhBBIYMHAECIA7AAIkARiDMIExYNx/dBCaCbzIj3hHVxv0Ng3AgJALXAFGQCXPnYcJUH9LAdd17QZyM+F7Bv20RIJAlbwaRJQCwXtLxFBGcL/2dthonIPp6DyIQXJMoarqiXNnr9/5QA5bhl6xbU6pksnk3nz3B6nU5anp0d/8zV//3d/7w1gia1mObTcvnFm0bTE+nmtVlE6dS5J8bH5mZ3s9kUyOZHLLyxtjUzOyGqIEJMlNL0EYBCVCYCQAueEJXAgQAiFEEHJlvGcEE88O+7EI9f2+v4QJ+pG69ce36cVdkMD884QrABOAXFVDEgIj1+ssMQAQMgMbEGNAOQgBDvM3Mel1tMHBpqTg3gQmBKgEEgGFgIT30F7mAGCBJZAoIhQodf3ZAgtXE/QnAAeLA2PeHAAAgpGiAMVAqIdPEEDE8wMMYQMMOYr7XiZ4weNcNIbxxmPqGOZO08kp6mJY4vdXN9Pp7PUH61OTJ2cmn1al3Ikzx3/3d38/EpE02ayVt2VZth0rNzo7N3tsuVWrt8pS3FyYnxodmdjcXLccHamqbtjY3GVchEfPNB0EAmzdQlR2bCR8Y9DfxRuYCzsSAOwiOUf07ggksvd7sFXPGPjRTbhXBFcACiBAEC81XAjgXCCMAAHnoEpg24IJxCXg8l76eMf0FBI3273XndyFXN1SuEx4QRxceE4PgoFiUHyEgBCQJJCoJ7mpiyN3sdFu93uwWhD9MduiG0SI96SGLAFCh3OEDQEMBS/51EkIbpr6w4f3T55cqJfuCG4fmxq/ff9+p50gpLWzvWJ2srlsLpPOAMDo6CilNBQOvfjSc0o40jbXO04D6e3p2anvv3qjXqvVG3XmoJHRbL2xm8mG2nrHEmFKMEZUMCT8DxBUB7gA5BqywbyTI3nNwB+ipys/+oFBOYIAoBuSLUAIJLqXeSg7ohQ4B4FB+GX+iQxCABPAGbCeWtBdiwIAHNcPyIEj4NzL1XQjlFzZLFxns4t4Ug8mpnhPKfLeDSHcBdz8831Lqxe4Af48AUAYKHZVoEOEQgxUgYKYbuCmg+fEY503nLUaNQFiZmFhc+Vt4A5hVqO6uc6bhFjFgrm5MhGNRnZ38/FEvFqtFkvF+fl5WSPVcunB8t3d3crxhZFINGw7pmkaGxsbWmRSCNIxLKpEO0bbErIiKYQRgbx4SZd7kM893UEQfuTmkVPfuuc9rhvngzw/wMdRUHdyESS3t15rgNzoa4QBMcAYUbpnQ7ssiL21AhzmWaWGtYc1eWVR2N4q4WVgcg/2RdhD6wkGiXhgqOyq7wjhnonqmshd5MDVoAa6bnvPuDPBXYEfVyjEgEUCDcHbAzO+D8UoA+JDBGs2y6Ojo/VamTOj2arev3NdJlajuiET2TbF1tbOw0cPx8bG6/V6qVRKJVMnT568eu2KJifuPbhTLJbPnvvZrY2t3d3tUqlYrjSWTo9fv3G309xJjUrhZNK0GWKAhS0jCeM9DQf14DOeQOXABSAErCca+ag0or33hX3ojcey3FOpBypLA86g/ivcM544wwAAsuxNABfLAgTE3weAEXAYCO55ebtwqgDPZywAOAPm/uIACM/R5vp0ZQqS5EV0yxJIdM/C8WIi3Vy2LnTmewwGKMCBcjuumhR0Wg9BQ9wTrOgmhilnMBA+G+ZxAeV1wMrGRKtZC4dUveEkYiHLaBWKnfnF6Va7tfpwLZ2I1FvN5eWVEwuLy4+W11fXXv7Sy+tr64DKsdBYu92WFORY+KNrt5uNJmdsZ3trZKzWMeqaZG2s5+fDs4Coq9G6/mDSo5cDABDonRXgVoNy9vy+XTdWHwaKYVgR4CH1PWuOcOv59KD4rhhycTzaHe0fAUeKvWY9XAvtOc5c/pNozyJDAGMAG4QQ7t6BmAAIULrTxv+P+76Me5llTIBjeUzp1lokGCQFZBlkGSTquRFRz5ByDkIIDiDEPuHazfTfG0gMhPjvIrxr3Di/z2Uw3OHIsVipUJAoSScmjE57enJsd2d1e3t7NDPaqLSjF5KRRKxcKr/++uuzs7ORSGRlZeX+/fuvvPJUq9ZWZW3p+InNle1IDFcqJYqpaVr1evPpZ7+cipM7N9+cmgM5JBMJCCBMgSjg68kA4Kn7XVPT+37MLf+H9uotoz2VqYs1C/RjwG5d+brv8l7tCwCYZ+y6IZ+DhY5P3GfWrvEKXa8T91jK9T0JfxcwV4oDIIG81FDR45fwpmJPETjh28omByYEE8h1b4EEVPL4nhJ/w6WuRS8Ag+DImzz7+hwIYkUMHL82Y9dFYDkAhzSCD0VDqUCHb33wSfd7uHmGeqvWbLZORCOMi+1CQ9NSkYRtO83dnbKiaAhBowWjidx2Yfebv/zTetv+1//694QQBD3f1uttvT05fey7//H1xRNzmzuFF57/KSVcOX1qamY2XSpWbB6xLEuLWhhJKiECMYwIAd/k8jEK3NMxDOAwYC6EzzyuQgIQ37sLYcBIYCS8fVh9Ay6oLIm9hr3fuxtJeHp/j+7RZVabcQSulPYnp/A4UvhruOgWxgIhuAAAhLE3pN2B96eQ8DUr6kdc96jj/tQBL7KVCC+10vE1NMbB8g0D6AL8CKCr1TDg/voDXt+EzcDmCHq33hD+6+9/631nhLcS0sdUGOVjGPJx0YCW/WxDIQBxEAI67Vo8nr5w7tLVj+7H0scqxeW5E89YrfWrV65deu750bG44KFSrXXi9Hy1XtpYK6pq1DRso2NYomU6VrVugKLF0tPTx1pPv/jzP/jet+MxR0DRdtix+UuMdSRqICRJBCyHgUS6mb4uKxPww9GQxzFu0KLLBO5PEHterX7fsO8bIhjkQZHXXUAQgd9ad2hca48BB68cohAgEJjMZzJ/AKm7PHDgAK4Mxb3s4k7mLp7jP7ULsHR7gvy4o+6E7E5Rd567HXPXH1dgOzYYNtgcedoUB4TBYWDbPloggGFf9fe4HwmBLAdMti+iCdyIPeb1zT3JwM8a9bU1WQIQP7kqkKdmCEB+HOXO9tbU1EyhUErEY8lElKDOxMR4tWBGEtOTx86/8PyxRyuriZHk5fNfeO/tD6mqPPXMF9otS1G0cCh+9tRUvdK+dOGpRCx14fxFq6NHVNWxGOLCMRqTk+MCShJhmCCJCs5plydcDd7dNA664Whe9xDGPr7u+ix7DVYBnAMmiDHkXuOigVQCkHwdyac9qeaW7+R7K0CXbO4xB+8KZoTdABvGgDMPhHF3dnfBe85A8hkEY9eTB9CzPwD0/Lq3vAsvLNRd+lzrE2Pk4jzCL0LK/Z0BuptruHhR942YDYYALkBy7Wk/PUj41excrcx1P++zentVHf9Pb5x7gDLDdmHQA1np80BB5aprVgqXdQgUCtsnFhauXHnv0qXLrVYdYYoRT49MTM1KDGKdjoWR+au/8dd/+Oa9RGyhrlejyezFC4t26/rU5GyrwwFrBEnlcvkLX3rq9p31ibHRRDy8tbnbrrcz59V8wUCYU8mN+EeM90hHBJwAF15yyR6I0ac/cE+MdXOCMfGWBccGzgBjoApQWzAJMEEuXOiSW6qEOR7r937m7vjYjq8duco3eGzBbG9rI8EAYxA+kuji914smhuY4O/25T3U92PsqWT+K7tv7cVgkz1/E3dj+hkIARYDh4FlgWWD7YDj+Dn4yBsN5gB3gDneDmIOBUJBsP4szS4A1UsMAPz8AQBgDGy/bgD4PXFzBj5bSfGHpiDsFaSQJocjUVkJ6Z1muVSolBv2TLJaLo2Nzyhq6PbtG1/58uX/+bf/ze7uzsULX7n3/nIyXZybnE1lYpNTc//qX/1hZnQqkUilM0lFFmannB7NMUG0cMpo7TKbWYZpWw7CwsKIYWACMPf1eAzg9GjDPioKvmHK/bXbQ8SFFxTgBvpzDsx2VwNgAFxC7u+4ZxHA7hd1eYV5LL5/gEC3AQCY2LM+3VBnzrydG4ED7iL64D2CMHChKELAoUAIMN/b1Z3JBO+pQB7SDwAIMAdA3rT3wE3mRXRyDg4Hy9nbXol1t87uIjzMU8MQeG4B6niOBeRnumA/bhz1TELhJpF21woXYrK9jnVrXBs/2SiQ8BVQ15JzBKiqJICoWogQ1Gk3nn7m2UeP3m/Vy9EYcZzQeNKKRdVGPn/54lJihIzlIiPJSER1zp4/EY6M2ral67qstkZoMp6Qjs+P6W22tVsfnZlumsXt3bJlM91wbC4cghzswws9iVTE97x0AR/i53m4YCV0gxl9PcE1Abv6TNcQFOBVN+m+qSsXbeblxbvYYh+5yfKu4uEKeA8r7DpoASS/6JBbHt3le9caRgTcGDgvA7hnBSOwx7vItyqEt8p4T++6urpbBXMA2wHHBssGR4Do2kg9c9fdNcyNGnTj3jAA7z4F9syXLg7uiRLhzTdPxHBwfDVJ+MuU4/xE2wCu28HVDdylUAspzWZrYWEpv3W31W4snTx148YbptkJO01L79AMW1tbyUZjlpUnWjSRlDqNUrUiz564XMw3Tp89lUxNrKyvSirRwjgSpZVavWVCY62YDKfbuo0QNiyBbG5TZAmuyISJvY1EAXsfsispu+kyrjbc/Tbu3hB7ViaAI7zsR+RWMkSA+J6Cx13uZ2A7YDlg2mDb/n4T+4n7tdyc7hN7GMJlWdfIprK/RQACSfIYF8AT/Kx7va9RuIHfXjYP9gV2twgXB+7CO7BX0M79Oq4N4LqEXcS0i1a5K6csgSJ53E8xIOE5icEXEG72jehxTQgOAvnRuLA337rRQcK/0v0WtM9Ddvh9WPv9XkfUznBNBfdqZhwoBsaAY5AVaJUamHEikNXplIrbmoKvvP8mgVaztrZ4YnZra6udTt+9X45PZkrVWn51Fwx9s7K+eHLs9p17taJpmJbF29EYYnqDImk0Fb9160GzZIaoZY7HrNAMa20uLc6uF1hDEIshWQaKPAEmU8AEuASE7zkHEAKB93jd/VS9mKBrm2JXweimwJIeoNNnRC48I9J0wLTBcrxlBHwM0b2H+A8CH9txlene8faUZlfj4t7i2b3GReL3qgn5AptQz9hFfqqDYXu86CpXQniR/XteEdd49bFILED4ssDvCnABDgfJNecQON0Fs2vags/cvlAHt8O+p8KLBuXgcDBsb7iEP/1cT2UgFuhwE6An4Qi8Bx1yDvS3M1wjAwIf/OAQIQBTMDvtqx++9/SzX1EVCsIql3carQ7ixenJ3Mqje5gqufGp5dV827BqtZalV+/cufPSF17Y3S3euXW7URGKIjuO0W7VRxYWH9xZbZRb2/mdnXwpG8ppqbMfXLk+ltilmAEizSbCKhIMbA6UA6MgBBAOwo8Own6wF/fLTnU1EOHncHQNBu4nWHkLuvC/7v4h8qIJmCfq3A25AEDgPQQz+GX7TyCP3R13AjiAMDALkGsPcG81kxX3Wg/UQghs19rxnRiAwLK9zoMPybu5xcJf9ADthUJ4j/bdNT0vBrYDBAMVwDEgAtjFprh/pT+N7W6IUXd56RkcEN5M63tlL2yufxCOyC2wp6V9Su24yg+lYFuAARr1Wqmytbl1fzSbaTYLi4szkpp69407czMnOmZjbXU1nfrpzZ3qh+8+nDk2vd5cPXNh6fTZ07//e38wkv1CsyZkKb69tdVuNxBVX3/tnXNL5yKxEdxsfnD3w6ejJ0KhJEPN9z68G81kBKKMeYzL/cWXYjCxn/OOPaG+Dz3slpdCHjeAz/dMAGOAuCe2++IpADyQW/iBZdCjZuzVQRm0tgdlC/d70t28g7pPFEAQIA4YgenbANjvM2N7Tbl6hWD9LbvqDfSIKldyu7HQXaymT945NlgAjO1JDccB2w/MFr4SyPZPAM9X6CdDexX4XOzB7UuP2fATawNgBMABuzFYHKqVKqXcZkaplGeC5XK523c3Uql0Pp+PREZi8ZhlWRKVdrbzmKBT504ePz73x3/wZ61mm2KaTkbWVneAiOmp2Xt3ltc37j3//Mv2qq5KY6FY/sTS8ampE8sP319bKZ/NCIQ849IDPTA4fk56tyoEoYAZUBSo5tITlSD8/wh/HWMOIJe3usZ019Pn55FIHEAAZh7fu8KS98TA9D3u46gb2U9kcPNqhY87mS6cInxL13eZdTsMAO42S6gnxIP6j+uaHC7etRcQMajMrbt/sDtoro/P3X+7y+vgB9X1vp+b9+iaSd2lrzsCe+WHXRWof0wOJW4HKiqHaOrQ7Qy80Z0DlAJnvFotE1mdmp69fetWLJYuFeumIXJjuQ/ffzU3zjOZkUq1cvfuXcexmq3m0uLS91797vbWFgiiqFqj1F6+f//SC8+Mj0/du729ubNbatbGx44jnLDbWyOjWKKi01HD2lhEJbrhBYS5PrguKM7c+hwcOAXuBjBiT73ZI77vM6LevJlemE/0BBchwAgk32dMiecY8iKNXSeXq08PMpP6hzHwi5fE454hvp/B9a12dz7tsUxc6hYs2Yu+9pP0u1+quzq5oW99z3XJhW6w6wMGQO4OqtADtroLXe89/iraXc2EZwTtQ4EEeNLnJ3YFcIsrcQaUgmNYzUZ9evp4Kj0xOyvGRkL53d1TJxebjau1am1ymrZaLb2jFwqFttH8med++k/+8M8URcGIVNsNzmB1bbXeqKqSVCyWJ6fnPvjg7XKjcXLphXKlEQvLUU3HuNYyjJnxLPBmOKq4WSPcV0u6OCPqGme+wOsKSORzjPD1Crd+AcVetlc3lUlwsB0PYPWdrIABOPXhRR/149z3IrkR+QF2dwJFUOz9ohQAWLcMCfKWoO58JK7buCfItwuDKqQHEnXb6RqvXRb0y/j4S8KAJcotd+fe0t2XYK+d/aId9dQT8KEEbwkFXynyvoJvSsFP8gRwNQcHqAqmY5umfnx+8fbtlbNnzyXCyNQBkXg4l11YWEgkkgsLS5OT2YUTCy+9tHjr5r0Pr3x05tTpkydPFas7zHEQoPPnzuVy2dv3N8996Wsj0ROEKjTKxqfT02MnJWYU28sGq2enFziqROJRSlWz47Mg90IpOfN0aI8lusECeD+v+IryXiZUNwPQFWwMnJ4CUq4/gfpBFt1PblrABTAMDgHmABPAAxU8g5q63YP57HUHeb+4aeleQB4GoJ5Zzy1vDndhX0XpN9503edUtMfsoo/vBy71CATei6TshoqI/TPGxaM8lLlnSel661A3GcMfZLelfhg0SIdTS4J3HWE7wZPBAEkOICgwAZjB6sqDyWOzuZmprfVXW9X7tQrZ2CjG49snJpOx3FeyU5fb7ZXFM/PhVPx/+Z0/eufde7OLF+6sbjyTnTpxas52nHQ2AUgr16y542cspl94bjRCHad6d2pcBnE8nBi5d/3OpcXweLx1/9HaCydP7OwwRUWAEBfIYWDZYFvgIM/2cj8G9931iHv+Hfckdz0+btiP7wMCt/Io8up5yOr+cRCezr2niCDgHGwGjhtPhry4BupH1bs+OBITnCPwXcicA+r4QXjU+zSSL1nBF6ISFgQjTP2KXRxaMoBbr6Fbfj2w2mDZQ+L3vl0gI9RxwGF77nDXWSYAwM23dD8r2sud96QA8rKEhehB/bk3nq6wR12tzH+i8Gf7T+wKQCVwbABXTHIUj0Ua9XY6PVqplU0bS7I2MZ358OqrY9nFM6ePf+uPv2WaS+GQcu/WNVVBMmYUWbdvfIBOn7x87vKli5c+uHKz2aoTKWRaLU2RGXNu3vpI00JCkNOnL0bCIYTA4Xw0kzHalhKSTQtxH5fkjoeTeBOgRxndSxvCntvO/a7YV/05B4t7Gg7FIPzaiQC+wPMdn+4Zr1k3F9Hx/VAOCA4Ue95ogrxaUV1CLsdzUDUA2FteEAKld98PDxdCyJ+W3hyw3TfwYq68IKX9Qkr2Czwif5YGdR4HgYNB+GFIjAODHqjUvQv7g+aPA6UgS/7c98tSuBtgunvYCNGzGU+XxPA2AArcfChDGR2qrn/wroGLxoBzCDgHigCYsE1HVcjqxtb85MS9++vNjv3Nb/zK1Ws/+PDae1/6+hy3K5ZZtcym2eZnTx3TDX18Ymw0E2q2G7Mz2S9+8SU1lHjjzR/eu7+WSBS3tzenxmK2bSaTsYcPH1XKLe7A6OhkJjvWbLVNvdOol0koJxByvVo2A8v1w/uYTxfwdOUc8Uv8eVi4C6VzcHy4E7sFVHw4T/TGC3Q5qceb5jZiWd4iwH2tRpE8BkXYzdkV4COtLssKAEz9mDw/0kaWAWDP6evyTXdnSM57dAx/6aCkR9PzifbqJK5Oxfr5yiYe6zu+qW0xcHrsKG8Kga/rIwAAWQJN9rrRnfym43m7Xb/BQATM7eGh6gIdagr0Wkt7TQ2hAg3lGgu0wxhgCgDAHKfTrjvEnpwaazVKut4Kh6LpdLJWKwF1bt14996Nm5Zearcrj+5vc65nUhHHbM1Mj25umZZei0bDlVqNc3N8LLWzk2eOoUmdREp74YUXC8U8IZJp6p12fWLyqXKprLfquWxyp2I7TLEcYA5YDtgOONxD0/f1XwACYH6tONJ1WuE9tyhCIIhfkt/xVn/iZ812RT50XaT+BHAjdjACRL1tsVXimRxdLZx7XONFgLrwOfPhSLdwnQfp8r2f2I9JRn7Imtsld3ZRf1uDvg/ixof3fsqBnxG7b+26kAVw5EdQ+68GXfwXvEVAwp7S6DXLvcnMATgH4sd99GGsPwYKFFwAPnUaMG0GTQBZAcGAW06rWZWQsXj69Idv3241C+MT2fd++DoI3WKdZn07FR6xrWq5vJnf3lJlGo1qzWbz5o3bqXQqlYy/+dbryUS6WNje3N4NqfFarV0qPpqaGSVEhEIyILS2viw4W19f4xwRChJmtm3ZoJgmOI63UwsXQPcrP+DzEBLAMBAMDHllcPZgbzfj2zcGsLsC8D1lWvgaf9et5n4tN4YH/K033H+VfHnvwVMcGPg+Yz9VwMNMu5uXOXvpUt15q/gVRRFyC9MKiQICRLolTLBf6LyH9rQ+fyLxgNuLCS9YdQ/G7YXR/HXS8xX6M4EJsGyvPDCAbwF7q5wXZ8GDe8sKb0OHIVaAwM1oCMndO2TeXYdKiRxwFxoqXgMTzxPsYKa3m3IEF/Ormsya9d1mfXTt0UpH351fnN1+tLW6sxtJOlSC5Qf3Tpw8t7a2WizntVDkhRdefPfdd6UQevbp5OLSAuP8xRdeeuutt9stxzQ7165daTSqzYb+aPlBtViIJXNC0Hp5ZWnphExH8gVLgOwwr/yTcPelQ/3whftBufDsPCSA+Ikv2Gdld/NqIgPxQ0eZ76ztMqJbv62XqOz7GXzOcJV55ruWuUCuCHR8RwEAOGJvKw13lcC+hOxOMI36KhP32AtRQAgo6tnfAAaJJFeW+0n6rpbSS1yA6JmEbH9azx7+s88pAoyBxXscIz2M5zna0L4x76PHuAIMiA4a1PiPpgHKmxhwW3BCUgycA5WAI8fQm4lorN0otpolvVN7+OC6YxKb1abn4xNjow9LD0az2WgkXioVrZs3p6amfvjelZ/7xtdDoTBjfCyXJRI5e/5cNjcej8V/5Vd+eWV5zbT0QmGXUjQ9PTU2OlWvVd984wcXLjwze2z+jTfemjzxCucxd7cIgUAQD3rjvsde+Li1K6G7CDdjXsAj+LiWVxFN8svbCy/s2RsaXyem3UpV7stjDxfCvvwSwCnCQgAGD6LBbsZZ16LwjZBu/Jwrfb2gbuQVYQYERNoDcF1ZuBef7N8VVFM58kO7wcs1Myw/8q+HG7qrkzcnezObwRu9LlLsvq8b++Rm7SCfafZmQrecUZCTXBXoQBg0SMNEjA5Q94MdGGJiDbA3hjNB3GBGKsAymvmtB6Y+QkSsXNoMycqD21eorCydPF1dL4cjYQszjGO2kWo5eP3OvXAs+tVXvoqw/Dv/5j+0251fSY5/+P6d3UIlFA5P5Kzz5089fPBIC2kXL13ggrVbxlh2UlIjxh//h7FcqtTQHjy4mzsubM4RBWEBoSAQ2DaIrijtQj0IKAIkAcLAGDi2xzqOCYbtYfwhBJq7+4vds3uAj2O6YI5bTrA7LC5nSP7mjS7HuHBn909XyQYOSAAhIPvLrAxeLTfHAYY82enOyS5C1U3ZAd/F4e4XRjA4wlPbFLmfAdwKAO5ruixrBFYAFPiywQKSttPvwPYWWOiZLV1YvAf07Gu56007DAx6ODzn8bUzkDABzkBWYXmn4NjO2TNnHaezvvVBLBxLJNK1WjmkybpF84X85OREOBputZvpdBqAEqocP774rW99q1ZrVWu1RDx95cqffO+1d6OxyN/+G7/6+mtvvvnGO3/tV35pbu74G2++/tYbb4+PzZw9fz6TGQEcbra5rEQoBUK9kBXBgLgbzg1auAD24RtdWw0LL2TSdkDXPf4jyIuGd/Vs1ypwHQgU7SkA7kzAfiEqECCEEIJzRoSflOiWUO5GSQhfbBPfFPZinjFYzIticEP5EYDR9cj62S1umJBbP9RFOfdqRPvk5qm5WTguRtmN4dn7ZIEJMKDk66CQoX7mHlK2uijqwRd+/M2fkAbiQkdI7mJaKBQmJsYXFhYeLW+oodTqxk1hM73T0pv1RCpRrVempifLldLa6ur4xNjISK7dat25dw8Rcubs6Uql8tG161jghWPzm1tbxWKFYrGdr9UbTcO0LMu5c/f+a6/+8LnV5b/2y79caTLTxolEqri7QSLHMZKJBCBA8kHDrhzagwLdBZ35hXf8mqHdNdYCaPnKjLtoYADJdZPJXr1YjEH28VBP+e5Rgl0JzTmymQcWOX6AkFtImfkh+9z/rK6Nh/0du1xm8oxRAMuHLz3TBbzkT8L2FKpg1cd9tXLZYDVpbw5370L9TQ0ZrR+8rG8qdR90cHXowfSZXwEAgaIBZ1AulcKRyPde/d5odioWS9wsV0KyHgmH2p2WFpJ2d3eUkFTI7ybTcdPUFSkiyZJlGcePz5umIUnk1e99f2Qk+9KLz9++fbdWqaVS0enJsXyhdOv23Wxu/NTpM7s7bzDm5HK5nVId41A0qmkqyJpab4AaBu6AJINgXmg+dJXXnlBQ4XcYuuka/vjYjl9m1E1wE4ARMAqU7ZVPIxgkPzQfulKzu6Rw4A5yc7LAF89uMoqrlnDfbQT+/l+uesABAHmB1r01PZ29qhL+euWDs674R358aC+5iribq+mGwZGAGA1iNYL1B8yKj1tID0uHUoHgaDrxBFYAQ4d2uz09Ofn9H7yVG00KVl84NlapbMqSWm80FJWcPX92fHxMUaRMJnX8xPHttY3t7R0AyzKdWrXSbDZz2SwisFPYSY4kVEV2HOupp58GJK5/dH1yajKXG3/h+Rdn5ibef++HhQpxRKqyuxuLnQ8Zo/U6njqWdRASXuUrgF7u70an+IQQAOl1cPk+f99fBsLTRhxXE+BAbUCuaiT20lNc07AbKOZ5o9merdsFWNylwMvM4nvKNAcA4TEx45445T0zyh9f7782h259FwwAHNjHfFYBIJAXIhoEZvpjYwFYF/z5eEIB6R5seXB3XBXoEBkwB/bpx2nr6JraTwjAtoBwaLZakci0qqp3b765s7Wsyk52JB2JRTmHxaXZ3FhOkuix+anJqYmz584mIqppGI5tb25uWbbtOLZElWK59sGVjxrNZigsd1q1VsdWw9qjldV8qSgYCkUiAGRt9VGjCbKaabeKd28hOWxatjqSfRmQijF2BOoW4tz7xj0rvsu4feuhh/JjT/unPRnGbs6ri+Kz/Y24j3GrjgLsKeuuodydAG4efdcYcJ9l+bpQN+a5q4EM1Fi6/eTuAuKvD3vFHrvkp2h6ZTzxXn5wb4N9Cs/hFYT+peRjLzyi/QGOigZN1WH2AObdBEi3mg0BRwDFbGfrTjF/++qVnUppRZNalDJEkKTIrXan3dF3X9+KRqOtdrtjdEKqnBkdHUlGk7FYJBIJh8PZbA4hSGXS4+PTX9TitXo9Fo3IEm61OoTSUjnfbreYI1QlBMgeG5ksFmrtTosrdn77nhxuhSJTlr7LuMI7ihYb4X4Il+gK+Z4tHrpO/t537Sr9wi984uUcCkAAji/5EIDt+Bf7PlHXg+saHt29IcDHQ9zfifCyjXm3dLMfjsHwXiZD7z8BeH5W6Ilkxn5VUNGd3oHv2MvZ6GP4Z0jj9UDqW1rd/nA3ZBDvledwexxIiAl0Pijug3BVkH6E6+GAdgJzd5i64S405m0qCoAp1Gvm8q3333/jD4q7182WGg2FBXCEsW4Y+WKxUq222m3LtikhBGMAIIRcv/GQCxGSJCYEYBTWQpTSUEhNxmOKqgJCsZAWj8dS6aimKdFoNB6PR9JRWZZTqdD8/CzG2DBMzphlWxZnaiQrwGg16+UqQyFN4Ei/jOdeKYRe6rfVel2hPUaq97LdL+1uh0iAID9xvicXxPvc3VLsLn5KetLb9wbbc0d0U2/dp3dNWCG8EiZuxS4XPqJo37LmT4W+N+n5r/BefwCDoP6/DqEkI78c3d57CQA3bpx6oRNuDTwkgkZwoFOH9OAe0Wwe9nEIgINgQCXAApgBZqPyF3/+B+Wd65l4RJWJLJONrXyjUa/WaqbtcM58BQOFQppEJcuyJEoBSRKVdEPnQjCOG7VGo14r5QsWY1wIlVIBQCSCMcaYSBKlhBKCU0k1NzYaDkfS6VQimYyEwzOzuXi8aVrO9NSx0ESaSaJt+Q6sHhpmiISfw+H+xL7DFcDDRl1Rg7ulSIUHjKJu5SwEaFAZZKz0n/HiIIhnKAs/J8tDTv3p4bKMayrAoJIcBwGVfq/67gpwWjCobhgK3oIRSBQw9rifuEulu1F2/wwb9EkOMQvFIBD3MDTcEEjYz0O3Rb1cLRU2TT0vQWNyLEFEZ2dns9Npb2znuxxIEJKppGmqw5xoNMIcFgqHAKBcaVJF0TAWQoRCISrLnWaNyIoGACCEgLbeUQlljNu2xX17sFQid+5tmg6TKTYdjhGEqBRXlfRIggkyPnf5b/6v/i/J8eiAUQp4goKRf8LP8+iaEF1ed2POCPJqRXW9YQgJN0IYEYR8vYgEph+R+s94IfjMLyAnvHhSRsBxgDBvP1YvZsEPNnY/075uB950gCwPXDRA1zgc4B4YRjdXAfvqtKdrcYDgLpEoGMcHh8J8xGHWjUOTm9xEJKiXWvduvre9ca/TXrf0QqGyUy5utdpti3l76VKEKSUYE4xRLBEBQNFotNGsxxMxzplh8Xg86th2RzckmUZIWJGooiqcccMwEEKyohBJ5oI7tuMwhzOOEFJk2bEdYtuxWNxxbMd2FCnSMTrVjUpuYml08ikpPBIcDR4AwfDHwGJ+OIPHfF7lze6y4BeZQ74HlGDkbrDuIpuABlml4CP9vWewV6MKdwONsBd9RHyrwK2r5SamuQFtVuDdgqIvKMuHYY/uG/0IGhjs3E9++QnuZ8ojAGEBPNb9AQ6JcB6IaQ0iF8VDCPI7Ox9+8Ea1cK+Qv9tqd5rNhmkbMpUxxgRxjDClRJZlRVEliUaiYcd2GLeXlhZBQL6QT8RCsZhq21TTiCwruq5zCUmK5NiOLKuYEMuyuBugLAQXAgQXAiQiM4fphq4oCiXUAIOGJKSGNZz6tf/q//DS135BCBLMQIfACiCCjNOtBu5j5Fx4sV8UgCPAGIjwYoFcE8j96SeJedYnH2RKDfAWdctM+Ea5hEBwIBww9upMEeSF7BMHGAEhwDIHfZI+wRqw94JZYyggNIcR/0GLOniXh5ihvQwk4ZtJPyEZYZIMtgMAsL21cefWB63aI9Mot00LY5kShUoaYiysASFEkmRZlhVFIZQYRrvd7iTiiV//jV9/++13PrjyIcX0qafOqqr65ptv1uv12ZmJpaWT1Vp1e2vbNE1VU03TtC3vYzLGbcdiDpMlBSFMCFIVFRMScUJUVWq1xuzxSydOPSUwIQwQ8lLOuzQQru7TG4UfqNy9R/gOIwFA3KBfBHJPlrBbvIQHHkADs2sAC2IPqhf+3QS8lFyEgGMvQZ4zwAwY9iJJYeAE6Gt5kJe3/5qBcccHpuwORFICyw3vaj7Ih7DcylEk+Mz9RIYRwAHz5ch2kx+EFA1wRAiQZQAGZy5danX+3vf/6F8WnKvILmGEM9EMVW1CEcUy4zwcDnPGLMsqFmoMK4gJO9z88pcvvf3a9yOa8pWvfBVjAC4USV4t7b78hRf+1n/9169du/6P/uFvb+0Uw6HQF158Frj46NoNSohhdRaWZpOZWClfMw0nnkgQLNdqjXA8bDsoFrFOnppIZhN2C6QIMOFv7+PTgEwlEQiQhH1wu0c928gB9youIgSI+aYCAmb0NyMHGg4+Su6xCsT+i7qLFfPL8gjfQEc48KkDn54FmWGArRo4E6AhFaf+u1CPc9o3A1xF6GjKo4vhVqsjoYHOcOYAEYAQ5KaTX//5n5G19O/8j78WjkcSoYTEiaxhWZYZw4ZhVMplwzAppbVmMxLTWu3mpdmzEoXNzbVf+dVvbm8Wd3Z2IpHw6dNnpqamEUII83feeWtyPLuyuvX1r73cbLUo4DNnTr762puGYfz8N3/qf/13/5t/9du/+w//0b9cOjH53AtfmByf+X//k38eiaaeevrU888/JVGFyoCQlznVSwNX6oFoSf+J3ikhgHEwg7EHwSEKXBJkSidYOSJoqg5i5X6BG7hm8KsF2jkcHTxoQWzTR4Q/fypQcDEFAPBRaoQhEsdfeeW5v/j383V7RQ4Ru2WHVLXdMAqVCgjoGLpEaSYyEjJNZpsqVVLJeKGUT6YSp08t/ekf/mk0GrWtDgL2lS9/6Z//9r/4b9P/u9XlRxEt8z/9w//7n/z//nRtbWVudmZru/D8s5dlRdrezv/+7/1hdmTsy196Nl8qO8zY2d26cO6SydFTTz07OzVFKBUymDrgQRjfkayRgoNp9Y3RAIUnuLYEVwA2xAR4ktjGUdEAj5P/GocNhhvwkP4Th0RBh3CxBb8Kxp5j1XGAM1AjMDU5197KI4l0rCY0oVnrtDq6TBVZCqmKwjgIoFw4qkwTsdhIJpUdGXnjjdcvXDprmiYATE2Nr2+uhCMacGaaZjoVYsxpNZqWZVMJ37j94Nf+2jcvXrr4P/wP/73D8bOXnw6FQr/4C0+/d+XKC8+8HFUz2cmp3Fhsc2Pt5LmT1Y7KAAV1QvExDtEfl0RQKosB7vOgvB8ATA3zuOCKFFjNjqrC7BOgo+kp8hPheo8nTB7qh0AAKCqMj8/obadWNhyLck7DoThGlEhEVVRJVkzDkmUlrKkAPJ1ORiIRBHx7c13TpBdeeOaLX3z+1s3r3/5P37tw8ZSmSS9/6UXLaP0//p//YyIRWzxxTNXkbDYhgF+58sHMzCx3rKnpMd1ox6KJsOo+BY9k01yoO5vrmNcMw+EAzN9brnsABIbs0DoA6j+6Vqx7cPBKfPYebr313iPYn2DLwXY+hY99dHR0WyQdAuY97IMGdtndVQq5NaEsaDQ6wOjc3FJUCW/nV6rl0ujoWCQaYQ7TdcN2GCU0pOFQPJrLZjHiL770/OVnLjqOlRsfc2xH19vLKxtf/NKLoXDor/zsz7zx2n9HEHv44P6lZy7Mzk1PT02/9tq7Dx+tnVyYjUbCs3MTZ86efO+dq5oUa7d0IKzRqettRAHZRknRRiwAwQNVneFoBm1A6MuAMRu0RAfXhEHS/cAzn2t6bDbAocfpoBsH5wSD576RVS/prlCqTEwcv3z+ue21Lb3zcHpmNl/cGhsbtyyr3W7bti2EUCVm63okotXrtU6nDVhks9lrH364tHTyzJnTzz77DOecUByNRv7xP/lHjZpeKJe4cE6fXSrsluu1zuz0DOfOSGYkPZL8rb/5N/7Of/X3FSk6Opo7fnqGqsq92ysnZ9O21QylsdEEQvv5O8iUAg41BwYpPCLg5ApeM8CSCl4TBE+H69QTk4efkGjQHXggBfG7wWb4EEN1sNdr0NcNkoUA20BlaJugynDnvQeF8vL0zOT7V9+RJUJkPDo2Ydm1ne21cDisqbJtthzbqtWsbC6SiCeb9dbYdFKSwrV64cUvPd2otS1DVCv1arm2dDbTahZL+RaWkKwI24QHdz+MRkL/m7/zVzHBsizresfqNCfHp/7B/+v/uLm5OTo6Ojc3t7xRUByiUB5WeUq1mg2VUUBBIKZvzIYbtH7eCkQRwyB2D9IAOOewUT0H0jD9gUHu6v52BkWLDAB5hlDt3XY+8yjQkJaivxUAxiAcuHP7hqyQUqlgmUY6nQxpSqNeIRhxznVdNwyjo+uEkEgkLCsKlSSMCUZSR7dyo1OVSjUWSzZRa2Q0Fk1EEJY0LZJIqA43sUwcE2zT6rTYllFxHEeRVcYdmxdzY1Oqoo6MjDi2s7a6RogyeSxl6Q3TbFHFCMlyw8KPCSk+Ilv6v1D6NDPCPrbxXgpsATv4LgaEgsOAULDb5s2P3ksmYow54ZAEwrJtPZ9vcUd3HEfTNEIIY0yWJAkThPH4+OTW1vZ7712VlZhK1ZOnlpoNXQDuGJ1EKhaOZRBqh8MRjmw5JHOLCDAdZrnBwJJEHcep15uNWl0IRLAkaypjjJuWTRpEhXqjIhXvhpWzFgtbR5RI1O8tPqwIHNT04Xo0BH1W5+hhE2KOigKqVP9qjoYC5yj1glgogmq1WMqvKHJZUaRwSKvXq7bZwQRxzgghiiwjjAUXlm2v7awuLs5yIf7sz/780fLGzZtr7Zb5K7/88ysry+vb+fPnZ5959ulMNv7v//0fNap2KKpksiOpRC4zqhGKFEWJRCIEUSwRLRSKRmOYylqjTik1TVOhcqG5HookjJre6uRHMnNtrNn88aCDaDgF47NPh8bBUP9fQwYRwaHLohwNBet+DoriGGZQ3A3vEQbOYHNtg+IOZ6be6WBuWkZboiBJRFLirVar02nrhpnP5zkXhGJCaKvdee0HbywtXji5GPrOd1+v1+u37jwMhSVViX7/e29+4UvPf+d7b6w8ynMAwIRKUliVMUaAUFTRQiE1EommM6G5+dm/+3f/7s0bt4UQqqLOzkyFlIxjYFmRYwkF45btKIDiRzBoA306n32wZpj+DHRxHnjTJ4NbDgODHlmmyyD87nBtYwzMAULB0u0Hd++FVWE6IBwOiGuq5Dg2Av7wwSNd1yORSEjTFFkBACwRWZFj8Vi92rl358Hi4vkvfukioujYsYlLF5+68sHV27dvExo2LW6aDhecyoRbTrvWEgC2YAQQxTSbymxu2aVy8etff3Tt6keVSuW9H/7wpRefZ1bsj771ncWT49/42a/91M/+lVR6Ml/9hOM1mB6rRvokabCPfz8N5L3gXUNNt0/dCB7qqw1p4gkQAqgEzaq+s72GsdAUVY5ogrF8pVUulXSzzQWxuY0pVlTFsm2H2XqnI8uS3jHDoYjjODdv3vorP/+licnJbDb73e+8cevm/ZmpMdMyLMtiAhwO3GKMO5osE4SYyQjBgITFjJgWvnJ9vVgqtlrt0ZHxicnZja3tpeNnv/zyL371py4I23nvgw/PPjuFYFQg5GZCBqslH55+kqzgg1CnI39XGkwM7aMBoZeBz8YHrctBP0t/y4MaHsAS+4HagTLAEeAAaATapXI5v2I6rNmoxsJSs9HaKdQi0VEt1FFJYruyEo6F9I7NOQqFo45hZ3PJVqM9Gp/RhV6s1BqN2ldPf/W7r75+7fodhSi6ZSBi22AygRHCDrcpRqoachwGyCZUwgAtXbd3mWBkdXvVssVbr92aWjw2MZ742s/+Uq3qxEPOg+VCs1JSmWkhoVOEbeDE2wJ6gEPjCQYRHJUqO+DjHx2T9vdxiD4PfPjHDewwCMvBx2AV9Me/69DkBscLDlubm9ubm8lUNhwZARyyHEkNZRGOECkpyTIXjGDaaDYFAGMsFouPjWdMy9jc2ojHY195+WXElXffel9TQ8emp3XHwFRQiQouumoG58JiXDdsjCTTti3bEgKEYBqRVh5tPP3siy2TFcu2YSvcKk5kzFazpdvxzNhis2WqCsIcCPG27vtLekw0mPc+ho4uHDrQiwMbPpzjc/AiKECigAE+unZtcmb+qaef4pzc+Ogd0975e/+nv18qlnd3Hl175y+44JRI4XBkdCTbaNVz8VQ0FheIR2KRubk5hOSP3r9SrTdKxfLFixcxRrpdwggzi3Hggnsbb9oMtHDaMjumVU/n0olIqlbZjWqh/G5lcnZm6exFLZrBuG3pBTU2XquVdTN5fGyuWN4+keW6TZib2w6DhM9PhCp/hDSMVRCkgcH5H9fOcCvAj3/JkFbIEKtLYCYPitDiDDACbsGjhw9PnTm/vLYTi40kkuMvvPjKV3/mC+NTp8oVkc2ORcNJm3HOcTqdTaVHZqaPHZs9ZtvmT/3M1xhz6rVmRItKRL7ywTVM8K//+l975rnz7gNjakKRIm635VD0xZe+urR0ORRNjk9NXLhwCSGcTMXzW6VWu3Xh8gVFCo1kQpSgYsWq1arI2oinUvU2l5GtUeGlAjMvW3ffkvhkj8PRMLL1yHp46GNodsQHtoWGeJ/gxxvmcwL4Zd1/rGPQyyghAA43PrydTidyYxO7+dr6+malUjs2t3Dro4rl4Jlji5ubO5FIXAAmkiIrqqwo505fiISjY+NZAc5uYXd8fEILafFEQtG05UfLhJDnnn2eIBIOR47NHEsm0hJRAOCv/9qvf+MXfuXypRdURbOYzRwHEB4dH+E2VMrbU5PxWmU7Go1r4ZjBtLZJFdriehljs1ZZV2VL+Dv7Bhnlc0EDvsjAyz69OTCgHfjYi/FjkhOPlT7u3b///e+cPLnY6RinTl+YnpooFQvVWq2wW0jG05lMrlKthcIxEJBMJkOhiGna+XzBslkinWq1m+FQCDhKpONT02PPPnvp4sVL62tb2dFxWVYokSVZMU3DYTZBeDdfXFndnJw6pmghyzJzubF4PGXaVjyW2N5ZPXN6+tmLJxstqNaaioQkJROJjxU3b8Y0sru9QnHH3bCISp4bJPipntjxXxR9HHsHVoABtx584GC7w83UQ87vQf/SalS2N9ezuYmObh07NiWcRq1aoZKcTEexxBkSAECoxGzH1I1CodTRLV3w0XTi9tX7bYNVyo3l1UedtlGvtTGSUpk0YwxhrGnUscx2SxcCCxAEo4/ef69eyWcysbnp4zvrpbYuFC3eNnWE4OrbH6UyeHJGK+8UV5Y3BLQTSVkJjVhAmWXVqtua1qHcBLpXjP9TZMqfmGkz1EryMXf1rwCHa93l+N5jyNXtqBZKJGBjdRWELctqLBYv7G7ev3N1YmLccYRhtOIJORwLYcwTiShznEQk6tgsnRrBiqoq9NHdNVmNdlrGB1fe393auX/n4WuvvVEu16Kx5J079zqtGgiezmTm509GIkmbM1UOKwp67703l06cAkculMrJ1AgQjAleu7+7VVidPJYaG4npeqveyI+PQCyEo5GURGTbdlSVa0RwDsjfSvEn4ThCxWGgvDvwGE5z/pgV4PNIgWESDmysbcWj4VazjpHI57cfPHx4bG5B1w3LtnLjsasfvAOIS4To7bYkU8bYxMRsJBpptzp3796LxeNnz53jHI2MpxIjkdGx0ReefWl8fGbl4W671bFtQSXChCOEEAJOnbmUHZt98HB9ZnY+FI48fHCNMba9vYspMUzj+999XdYikVTEFtbD+7c6jYLTzq/fu7K9s1Gt8MJ2LRYR2BREGlAp8fNKRziZnjgFYNAnOSMGhTEOc9Ogs+bu1tb8/EyhsA0AyXikbRihcOT4wmKr0arlm5vLd4FAvVbNZnNtvd3WyVePnxxNadFYdHdnp2zoF06e/sVv/nytspqbSP/qr/1KLJ54950PTYOoctg0rLX19WK52O5UCUJCQDKVWThxhhI1Hgs3qjvzc4tsE1RNpbL0/rtXn3nq5Wq9hrF288ZH+d3m8fmz91c2R8anRuLTN66tXHguGZPH2yZiAP01aT4X9AT77Er3YS47XOMQnABPsqLt4WjgyzYa9UcPbo2PZyyHpFLpRjXPhUhlRjKjuWsf3vh3v/tvdtZucaYzO0IQ4QCIoFQyNzUdF7xVbzQqxfzUaO74wokTC2lJ065eX36r8l6hWBvNTWIkE4IYtwVGGFMMUMxvWaZ+7vwFipx4PG0axenp2VK1KAAY8MJOkzFuWYzbEoioA2pmciYxvpTMxDUcf/et74/PFsbGx5o1INrQO/58lmgAtx0hz6Af+efREgIICvwjU8qHNAMO2+8+Ku3WCjvrG+srltER3FpZvg8IyYoaCkWffe6pSnGnWd/u6A1gXDCBEAqFI0JIpVIJIZTLZjudzvr6uu3Yp0+eyo5mP7xy5Z133kukR9RQ1LYYxtgwOpJEqCwjINXy1vra/bHc2LG5pTNnL6qhiKqFQ6FYpVZVNBVztVZrJjNpSdJOnzo7PT2NKI/FQgRBsVKU1NFWTciSgZHzeeT+x0uBLzsMg3xC3vuUbYDD+QGCJ1cermMqnTq5ODs7ZeidarU8Pjm+sbV5+8697Z3d/M46Z+ZIJilReu7seUVVkqnk6Eiu2WhalhWLxaenZ0YymXgs/p2/eHV7azeZSO8Wy7Ks2pwDYEmiuqFjimRJIoR0mqUr779Vr1dL5XpubJYQeXHp5Pz8gmFZsURckUJ37tyzkVXvVBUFc6smi+Z4nIaJ2NxdO7F43rYU06mHw5/XCLbDfLLDftlhjOBPSFRCAP63EMjbEOFxkAjoV0N2vr/oIgKCwBFgOUApEABVgWs/fPvk6afHj522TL3V6Yxkxv7Gf/1/FgLtbOe5XWO8xcEZHT1m8UR4dMle3o6Gwx29PDpqECpNzGZe/vqXFSVz49Z6s2JKUbp04ny19Nb27oORlKxGFdPAWEbcRNzCobAE1Gm0Sz9487u57FwyHpVQMhKNvPSF33r3vXsz03phrVLYLrx8dqZe42rirFP4aCJBAdeaulTa3D5zLlRskHphIzcWb1uUIZAQuNu8uybxMBGEwe11g2IsWAXocGF2AypHBK4Z5jsOk7V8JAwNPjB18GWuDdCtT+ZVSxwuAeUwdKiRE4GCqe6NggMhgABkGbYeWbphLJ06+eHV66dOLjiOnUimZuZmDbP2R7//R53mbqVSiUSjjUaLqFEuACFJUZQrH773s6+M7u5uayHVsRjjpqxoqqYlEunVlYeXL51LpCbjYWHZViQcdyxTwgm7ZCJsAYaFheOvvPJV3UBhVaFy6O7d+7/4ay+GwwlFFSMj6ZXVlV+IfFFRDC5QLDHCBKlU25WakHEHQzOeSN29f3d86rIkgcW9sjrdEikHD8mgEupBQ+7Aa4akIRX+odruuyhYCveIJgD8OBNgb3Pio3r2j3zmj30MXPLcb0AkwBioBN/9i/+0cOJEbnysUioZnU6hWDyxtFQu1W5eW//qV78KAK1mtdlqYkIphXq9bNn20tLJVCqWy6XHxrLtduc/f+c7lXLJNJqM281m487tu81Gm1KSSsWEQAKhRCr5G7/5N1555acbzY7Z1tPJ+MzMhCxTQCg7NrO1kZdkxBhnJiyeWuy0O6VCSZNQvb45ksvqtqaFs4bpCGYYja1MImlYsVZTlzFzN7gW/uAcho0GXvJkwaWjM+UO24FPoBd5EwCDX4DkCDHdI0F5g3chEOCXAgcwm/z6tauXn7q8u7PzzFNPjeVypWKJSPLa6tb01PTMzIxlmaoW1jQNE5IdSUZCEqFSJBrDYEc0KRGPM8Z3dvPlUrHdrJ5YOmZanXQyEY9GwyElElGi8WRIi7TbnQcPHm1sbCuyjITgjlXIb1EsWh3j5NmnNzeLtSJPp9OF3aqutzOZzMba9unFGRm3tJC6nW+EwkkihVMjk7Xibr1YSCazlfyjmKrLBLC/4Yq7cGN8wDHQBBrmmsNZioM7EPBDHdjtAQZusOVDMcgnpL0V4HGXuEPQ7y0e5kAwYBa5EwAEYATrD3cQZ7nxbKPRuHjuvKnr+d3dcqWyeHJGN/TdfD4ajXEOqWRSACaY6e16p6PfvXvv4f1buVzKsk1NC2ezY5wzRUaTk6ORkHpycWlyfCIc1mbnp5qNhmnZlmndvffw0fJ9QDgRiysSqVUKApjtsAtPPVMtV0vF2uzMbLvRKZWLjsMe3FuZn504Nh237dZusWK0G0g4k9MnVTXWrpWjGt1evx1RbIl4+k9305ehxvFIrvkJok+yAlCXw7Bwd0zy9dHH0s1DNR28y9WVCXAHJAw3rt2cOza1srYRDkc219euXb06NTU1kh0t5KsyVY7NzhqGEQppptmIJdPra49shyAI1RvNeERTZfT+D9+q1evttr66ttJpNrVIfXXNrBWqI8n49ML85ijXoidi0XhFb3MuDKOJCItGI0QAt/SP7l1J5+Yvz06HQom33n5TVZVEPK2GlK2NzcKuvr29evrU5I3bm+Gw0qxugV1OjU0xO0YVbLaa7U6T2SbF4HSntKu4H/TxBtqOQfV6wI1HpV4f7rbDmw4H0Cd8L9xtxWvnsUL+R6E1eS1h4DYAiJXllfljs81WO5cd/eCD90ul0uWnLq+urW1v7h5byJp2p1arYUJlWXEcXirlEbBnnnlmfGx8JJO2ifT973//+PzxS5culwr5/M4WCLa5vlHMF7LZ7Esvvvjgwb3Rsdl4MkYl/M1v/tJP/dQvEaroHd1xrHg8cv3GNS6EFlMTydQf/9Hvy7KcSmQs05QkWdft2zduRJNx5nTGRpPN2k4yYkfDSG8bmkyMTjs7NgcgYTgMEwwj7Y4cLvws0yd5U+rsz80bkKl3qBVBBDfJG6ZnQRA2MA2EAOYAtyEchbUHq43GNsG5drPpcBpORh8uv2cZE09fflENhYmwNpavV8ob8WSoo1tmY2c0N2br9le/8vNtAxTxoFlv3brbqFTe/MY3v1rXL2zee2Dryv/+7//fKsVlVeHf/sFVRWh6ZX19p8ab7Z2th19++Wc31u4WSzcLDYNos1/7yjdUlbWrO6nxdOm1qx+9B+XyTqoN4Ui6xsV/+P3/+KVXnm418ysPtvVOyTQ6Fy6qbSf83ddXZqbSRnMjnmgcO/lTj4pR7KpAFDDz9qz+EYQQHFjMcphrhqTgFqjD+O+CjDgkBtvPvoetFjwMeaUED/OET5Vcq4tIQLDY2ahgjEzL3NneSMbUZr1i6MbO9o7g9kfXPvjDf/8n7737TqdVrVeLkgyKHHIcnk4nV1YexuKRsfEREOjixQsrKyv/4ff+8Ozps2fOnR3Jhk2rvb25++7bVwQjiXRKIPXkyfMc4Nbtm3/2p39QqewUy61arWqZnVQ6CYB3twsjqWjHKBBJnZ4/t1toxhNR3dJNG+7d3eh07I5hr20Ub997uLWzEYmop88szp9YOnf5hdv3S6sry6NJQASIAhQDOiq2/Usamo5ug4z9dDjUZxgvnLsNDMEAHB7cvrW28lBCLBQNr67c3Vh/2Gg0r1+/cfvWnVRunlu60S6ZRoVKIdWJ1ut6WFPnZlLbO5tziydVjXTapq7rAli73SZIunT50tyC+v614q0bdzqt+sTCpOE4sdTUs8+9/M4b365USmvV5WjYSsZUgkS1ujs/f9Ky023DQKKdTaeBSKnRhfwbr1IqqWE1HI20mjA5OdfW89PzZ9VQaGxibDSbTINKpZCm5u6t7eZ3S1OTOoCGJSAcHPY52FriM6dNfTIF73GWRz+cyTscYQSOzq9f/ZA5FgOGMVpdvmcarZHR8Wg8ZRlWJKwU6sVatYSAYXAkAphoCNNINJJKJwAshM38bhkTdHzh2OXLl8fHJqvl1WbLDEfSO9u77VZt/pyiaqjdbG1t7wgh2u2mLONkOiyQEwmrhl6xmckEtkzTtlqvfOWLtY58+txz166+W623KrWybhmVinHhwtJHN1fnFi4jjKisWFYrFJYN2zAslsktWna5U8mr6myHHS409iedhuOHTzQBDr73UK0P3MpuiNsOvgkhYAAIweZKoZDPP/f8swtLx1t1s9OqjI2PX7z8BYTVSDSiSPjf/qt/3GlWZ48dB2TrVufZZ1/eXH+USWfmj88oGorG5Stv35+entROzJ07dQkEuv7RtbsPnHOXfjWeTGyu3797+/rCsbPbWyvv/fDdaCxcqNRy2UkktShRatXy9Y9+WKzopkNlLBzLPDY3/fZ7D0+dP/6Fl//Kf/6zf+pws9nkK4+2js8do1SMjk9Va5VKpRkORSMZwgV7uJzPTM2KDqo3Ook4GB2wMRD6eYjG/eytAJ+E8KFTaYaCfX78dzm4WQSIAEbwZ3/0J2fPnJqcnGg0Gmoophvm8YVT3/jmX3/ui19GWMFUS2fnIrGs7QibQTyROXFiKRSKHZtfsC2jWNjRNFIt1ztGZ2JqHGOys7Nr2mYmc0JSE/NLx48vzpSK60arjpmZSYXa7XooGtZC0ZbBlje31laWHWZwcJrN9sz0TCI50u40mo1ixyw/98IXqw07kYqPjmaatYZwzJdeuqzrndm50xhHoiFN4ibXG+XdbU0m49Onqg1gelFThMWBD/H6T/gY8I0ez6cfzA9DeAaHSb79EQDjZ0zlHNJ+R9BqtD744P2XXvpiuVL/4MrVRDJOiXpy6RzCtN3qrKxuFQt5WZbUSEw3bFnWAJCuG5JE4/FMtVYvlTYBrLGxKWHxnZ3dpm4m49lYNKmG0twh8Vj6zPkzX//6l2amxkfTI8+/8CLn9PTS0okTp3O52bFslgt7bGz0F37xG1975ZXp2amR3AwDhSpkdXnt2OLEaG42l8vOTI3ldzdv3vxwenK0Wi2mkhlVUQUX1XqjVmvo7ZqMzFhaWEyqlrc1hXP2edWB+rctHFJvCR4/5swZDJULT4/o53Z/U7Z+eOrgCX2o0FaMgZADjsETev+2bShQPAcAsIA3vv/Dc2cvTM/OdHT+4ouv3L/zPiFKNDz68PaK3jJ/5ud+dm3lzsbG8vzx6Y7RtmwjlYzvbq/Eo+F6S8zNL6TjJKyR8emZqBx6+50ffvTg4W6xaVl4ZXUdbJ4IjbaaZjSGEXaKxSZVYtHULDhmu6NXd9u5iWQyE6KAwOYYoNqojU+fDydORGPRG1ffT6bx5PgCsmF0JJXJxYqlHcfqcFauVFYSqbDARIlOYjVHFaldX7ebnexEzujYMudRFciT3X9uQMBCgIb5anuEABN/t/r9Hw0DELT/GNhy8OsPOhACjIAAULcpDAQDQfue273cPY8xUAwSAeoeGCgAhU+wgPyY/qsjI4TAMqzrH93+5l/9ZqFQJAj94i+/vLqyXK9X88UCxnRmdsayrEatTgDHI/FYNGabNneg3SqOjqQw4s1GuVbdpRJWk7jc2VE1isFqNDeOL45HwxKmFpUd22qpKjq2ePzeo9vbu6um3TSt+tb2w52dFUlI4yPj0bD88N5NVcIy4HBIOz5/ampsYuvRA95B8Wi6WuuUSlUmJC2UuX/v0WRWdcxWKj2+uV0jUsh0+Eh2qlIzlpc3rY7J7LZj1jUFbOvg1/+Mk7sU4C5T+kdQugfV3UMajftDSNwHcQ6MAxde9DjGEJZBlUDBoGBQCagUZAwqOcJdIoN9O3BBHwIpGti94m7Rsexjxyc++L0fzsxM2y20tbHW6vDZudmx6dHV5R3Hsednj5XyOxvra0hwVZErxULHaEbDie+9+l3OjYvnM9GQtrzyMDs2mk5nKWOF7fsTYydUDdfq27bTyOZSqgxqRF7fypvOCOOWabGR3FyhuLO6uqN3IseX2qbo2HZHb7Xjo7RRS6RHxq9ee3Tjw/ujY5NX3m+Nj2Xy+Xy71WHc/K2/9Vdv3i5JROh629QbnUZxcnyEKpKsxKxOo92stRpbSiKmhWSnL1P+yVqch7TcPOc8APKyPoLY4oCGA7u/oUDaAEKDbkR7S6P7aOFGlffMpb26YxgAgGJQMHAOnO81ywQQ8tj8AMPQMLkHA0LbhShsFuPxyJWrN6KxsKl3/uj3/zCXy07OnHi48rBh2BNjubHJ6B/+L3cIEdVqwei0YuF4sbgbT4TyhUIonNU0kk7G7ty58+4bH2UzY49uPezUa5yYwqm9+tb1sxe+sLP5IJ2kE5OjVmvLtKXJqaVkcpyL6te//ovPP//lf/dv/qft0kal1VkMhd95/4dGo3P6C5eVaEwOpWKJxP/8L/7pzLFTtuDxWMwwxM5ueWvzwa/92tdScd5urE2Px8EuCnMrrIaVSAwQwYjmd20C7RDVhZAY3/+2jy89YxAdUhr2akECQADj/cyNSX/jLGDzuNhGX3/6FDNXt0F4XwEe9y7sKmAUKAGp+1wEgEEwcCwQfp4QdicGAYwfmx9gGJsmmCM2uKH91zDG79y4k0olO52ObnRateqjh/cmJ3Jzc7N3HjwYGR/LTmnf/dYbN25eU1TcadcQ2IA0hK2lpcvPv/RXkRTL79xJZyLvvX+jsmXOTsTGcqNGhMfSIpvNXjz//AtfeoU7zxj1IsXa7k5l8djCoy1DQZDSlGwymUuNPPPUU3duO2bTGEvnamNOCW+aTevYdGb34ejzTz39z/7574QknIzFNlZX4okkTcbyhfqNm/dPLp1+9XvvmxYKhWRZAuF0trfXKqXOzMRsreU06qXJKVNvMUBPsGz0MClKQ9jluOvBFF4xfTxMuMSgM30ng5gSBZAR4B6zgRKQiJclhzEQ5BkGvaWXmRuYQ6C7GQBC/u0H9/Sx0kGTJLhKOI794MH9p597dmt7S5NJOpO8cbXGR6VsLpeamBeAf/jW7d/9nd/WzUat0VIVrKlEUfHZc4vRWDKezAociUdhbj5kOvXlu2+3rOrTFxZPnpxUY7qpw8//3K8sXXxmc+3Wv/wn/zk7Pjpz7IxZzr/2nz60q5uE4D/9t/8cU2W3cBcZ5trNe2/8x/9sC1qrbn7nD//92TPndx4+QswyG1vL114DVbq1tvncU5dq1ZYQ6OqHN04cP7W9U2obqJjfcOwWkITB5ZVHy2aHReKZjfU7IZWmZl7pGI9vrB8bIUD79+oLqi5Bex7hg6PFgmKUIpAxEAKUgiQBIUAREAyMCcaYYAIjJDBiiAgBnIMQgnMQAjBBblFK5O9OQikgNyVyX0eRJ3MHRLMNenMfXBoUxLb/TLAY+sAlggvgDAAA+RkSggEiAAgQB0mCW7eWG9XNwnau2e4sLszvbKxyVi+W6K3rVzPZCcO07t25m995aLYLjNmCqGE1FZK17MhYOCyvr7y/uHRmLBdVFXxs5sRXfubpWqegRqT46Egyo5gGbTXzzcrDnbV7D+5cq5QT3/jG2T/+/p/98L0bY3HJDKV2yx9JkaQQUjwx12q2r1y7izCt1wvso0dX3nyfMxYKKdmRSUoUx3RCarpSasRAXFqYy6ZyLd1ZWDzVaHKqyg8fXNcNfWHpzMT48XAoNTU9ee+OffV64blYKRRONQ2FaMBtkFUwDSDEU5eR8DJL2H75imAA6/QvrQO/ZeBkEAgKLtEfxxUEgcDeFcHsFhcq7cp4JEAE5gTuUZxc3iACCPedPwCAQKOgUsAIsPsTADgwBpwDZyAECCQQQu7s4hwE914BYRAcMAJ331GMgCAABJTuf2d3PggBDPmQ6se4NvYmPPJj2fv+uU+bHTSjghtluw3uDRYCWQXbAS5AOIAleOPV17c37ksSTcRHdrdW7965WqnujI6PrTy6c/3ae7IsVau1SEyJaUlCCCEkkUiYhvXg7qNmu6YoyubqKYEYpUQLKfFURAoltFDEZtrWpgXClJTa9sYt4TT/9n/zm4mURgm9+NxzM9PHRyLxTCzVNmwUiqrhDEKEcVar1hqNxubWlujYlm5gSoRgoyM5QolMGcgUHOPkxOjZ48fk7ES1Wv/Sy1/89rdfX1paklQxPzcd1ejMzOzObt6ydI7S2fHJSqk6m0yYHGwGIIA7AO5buzJVgHA8qLF/GAMbp/LgWAfVkmHcDoG7gunt3f7sWcOBby3YnmHqXkICz5cwEPDZHQEAULJXZtM9KVOQJe8pSABw7005IIQpEqI7Y5HLQgi5HeYCgAFz7QcCgL0XocHiZO5ahv06BQO5FvWMzKG994MNfAwYe3PXvaKje+dlBbbWi2++9QNZUcayGSpJmxvLW9sbEhLRGBkdGdN13TStWEzWNMC20ul06vV6pVIpFouNTjukUk0LtVrNjY1tVZMnp0cZM3c3q4tLc8dmZx/ee9BsNCKZHEF4a3MzHo9duHhSYGtzrYYAr8tKJBJWFO3c+fPl+nK91VQUNRTSJtKR0am5qfRUs1YLhUKKqhSL+VgiHouGTMGbteqEooUR4olYyWgxh2my9Nyzz9lmw7Zty6wiJ6zSTquxQ7CYnp7M767K2I6FtE4bJBVsC8JhIAC2DbYNiAKiIAAc+8BxHDCwPDgBhjlzoNAaZKiLYNVHjx29yYwBSGAFUKgHmHYnEtnP/eBuhA6eiOw+21Nb3P8LT/b3dn7fmsm9t0Q2AABV94sTJkAI4AgEB8wHrFPgGysYgAtg3T/3X8YHmlgHWV2o5xpXZUIYhASSBFwAEfwv/vxb0bD809/45YmJMcMwdrc3IiGhyLhS3W53yq1Wq1Iul0qlSrUaQrTdbnVMMx6JMMYUTBKJeDabVRSlUi3F4tGpqWlCULNxjTkQC6c1ulttNzInstVaRQDUGrVqs3np8oXX/vzfcC7K7Y5pmTNTo5NTI1/++itaJLyxvi5J0vsfvP/tP//26ROnrrz/AeP8qWcuEQKtdmtmejqZGV1fWdNsiFEVIhGhyoVC1dLZn/7BH2gh+dGDB9FY5O69O4uLp/L5sqLF8lt3QZgrd28IHNdCaUsIx+E8pDocqBSyOFIimrvWD4PV9F0z7OaKQeYOTIkBeZvBVSJwCUWAwPOREQQIgyL1L1wy9Y1Un++5v5J0jQrkM7crpjkHjAHIPm+04Pu6Lfwf7uqAEHI1dleM0LCyrxMOB96zhnJ3ugRH002h5IAE8EERbEGIH8EA4TFQU3RfGBOvGxSD4KBQ2F2vbK6u/OzXv6TJ5MGDm61GhTHbMOqFQms3v1qpVizb1ju6aZgYIwthjFBE05KJRKfTabXbzVZ7ZEQwxgglhGLLMm3LISAxm1uGhQBRSjWibFTqlmlOz050dOPf/ts/MHQjGktQ226bRqPd2d7Z+v3f+wMqKULwVCpV3ClH1TghpN5oCEHi8djk9Hi9UYuEo/F47J2trQc373PDahj28aWlr32NGq3O/Vv3iCS3nVYskWw0zTt3Hty7eyccUicnJ41OM7+7nUql06PTK+s7lODFpbPJ0fnpmYVIMjMRmXS/iDQMchGQLCR4V9AGCChXPCDLSeCu4NoSnCRdTcbFQzECRPr5wd2CCvlWKIj+IAshBMKAEOrys8shiCOXuYUAAQI4Eu6ubn43unCqpyFxxBG4awkNSdBLvDsB/GRtJvpnOOPAhK/3BxBf7xo4TGSL+/KcAaFAJBAcHAskArYFiPO1hw8VZIdl8d6V94uFtUa1UK5UTMtmDjItk3EnmUhK0ZCtOowxbLcxIQiAMeY4jhDCsZltW5wzSilnfGdnp1ZqC84xJpZtdcwWUNGqNEKSIhNsW4ZM00bbNASTmU0wkiUsK/LWduHqtdfLlVosGgUkECaJeEJTowjkdqfz6vfe1E1TCHZiYX5mavbO7UeFUj0qyVxAuVgKaer9mzeKO7uqFhmdHVEjWjI5IhhrtZr1ejUWjy8vrz58uLJ0YlIOpx1BjY4xd3wxkzsViSdNhwsATA6unPVxNCDSIWjgBhsPTpIhOhC0E3hXmfElJsL9nMN8Sdr1CmPkXSN8cYyxQFi4l4huO76FKYToinm3TQ8h8Ewov3tcIILda2hfPLRryHf1K4HBDlhUJgLBPRMEkDdhDspkHDAoEITGXCWPAyYgU2ACmC3yG63d7fy9O7evf/juxspHNz74wdrOlmV3ohrp6HooHI8lU3rHUVQ1Go202h1JcjrttuXUiRBCCNM0OeeU0lQmnkwmEUKyKkkSbrWbBFEGjiRJVCEWNx1ktmt1CiKqqRhAOFwiJJaIOo7jOLZMSW4kF42nQ5GYpEYIIYRg0zQxlVU1rqrJWt3sdEA3haEb5UIzKtfMth1WQ9TtUL2x/OiRqbcdw2g7qF6VitUdZonpmXnmcKJEihUzO3U2Pb40mtJOnnn66cTkR9euXnz6ZSInOEChVBFucMuAkR0wsEEaRk4zp/9MUJsfkLUWgEmCihPDAACIew9FrgbR5+Ry3bTgcQ9CILmxRsJTOgQAYgIxjgAQxoAQRsgvJoAE96uoIeSiRr32AwpAs+6D+tfFrpEOfkx/n5UsAFTsQUCua41xsBgwd+lAwIS3jGBflerOnz4ZxAEc4QUqgQBug3BYWGKJpFyutJZvPfzwg/dv3rz10UdXy+Wyoig7O1u2Y6QSmWQygzAiGGsROxKNModhbArBHcewzJaqqkwl7QazGAMA3u7IsqxoajRMlpYmj5+YtW0jFIqUizW9Yxt6R9W0VCqZSmm1ej0WzhRLhTEjp4VDoVAYOLcYWBazLatSrUxMjKXTqePzUzs7uwghjDESZi4bjyajswtzJrdlRUlm0qVSKTkyo6Um0uNVXTcIIUhtY96pNxrVjlFlnXazBDEQSOICj4xNp4r1XC4HgMPR5OZm5fyFLxVLpVTCUQk4HJsOokRgJBQKtg2UDlQu+884fP8/IQhuCE0BgHtqhitiKe5Bq13RG7jLgzq5fwkf4LujPh/udcFX7vf6LEAwT367vCgECL4HrAsA1j/bEaIYE9w1Elyudp1FmCAEAiGEAkCZcDuMoTsJBAiTO/CjM8IGh4P76g3y1xZCAAM4xAs8cgSwru9t/1LQL+8FeHogAxBAKSgKyYSJrju//U//8ebGar1W/+EPfxgKhxgzNza2NU0TgmJCDNOUZUWWJUAYY2IyE2Nk245tW7qhM85Mw9BCIUKoJFFV1RRFoZRGIookhScmjimapCqhs2fCiPBmo0Eo0TStUqmEQ+FmoxmLxWq1GiAU0rRWq2V2rFKxGA5HLMtijAFALhNzGJNlyTCMZqs1ls0CpiMpefH4qOPY+d383EwynUlGImRyXOu0hRbSWk2MUSSZjjvMqlSLiML8/LFkeuTBw+VqNR8KU1kGhEUyId+6tXnlw9fbzValvAYCmFWTpaiEQMEYMUEIGlj2sI+EGIToB03VHqjEw1j82/d0ocCzPCcr9i8LRCuAzxjdZgcG3XNf3rvc792yn3HdQLp9LWPkrhvd9rEvo13dx7UFWKA2Khd9k0l4K4QYoPcdQDYHJrx4VNxjrbvc7whwHLA5OADcNVN84Kkf9Ree04Q7gAQoKmgyxCUAgIf3Ho6Mjmytr/+zf/bPvvbTP3vr5q1//a//9fz8fLVWTSQS1VqTOYxzrhsGIdiybMtocSFURdENI6RptuOENQkECCEYY4w5jHHHMNMjyZFc0jCNWCyeimeSI1qxWJEkeuLEQrVaZYxHVGlyanJ3d0eW5Uwmo+t6VAtRQiKRiGEYkiRJksQRAgBJklwtyHEcyzYVRUYItZrNeCJhWZbt2ITg3d28qiqEEkM3BVAuiK7r1WoVAJLJpBCiXq9PT08Vi6VWq0UIjkbjjx6sTM9M7+7udjqd+fnjX/7KXzHsiCRJjaY9cWyOhGSbH7ytRtAPIMBHtXuIsD028rjKZ/2uyhEkSeq26F052OQFXzXyf++bS4ztAR7ez0B4nESBBFSurgjwnGUYKPVxc2/2ir5VUrhTdn8zmAj4JDnB2Od+8LVJgoAIoAJsAgDAOGAA7koIPmA0MYDkzh8ECIEqgea/bSSiRWMRTVVikcjU1NStm7fqjXokGrFsKxaLtVudht4xDUM3TZlSQKCpKhdclmUQnFKCANqtlsOYbdm2YzPGBOcOE5Iid4z2zm5Rkkg6mbEsvV5vYoRPnlp/uLzCLCedDMUTiXyh4Ag4PjtTKVcYQDgcSsSizVYLEB7LZmrNDiE0Gg2DEKqqmJZ9YmFmY2NbVeWRkTQgZBiGqklT05OFQlEIcfz4fFs3GANJUuLxGKUEE6yqKgiWTITT6UQ8FgYQCCHGnKmJTCwe43xe13WMcLn0oFRpqVoMSGwSjVNFNtsDeGLg19ljZXABjcBFLp9gX5FwDUUfv3PvY8EVoC+2+WMmAPi27L6loIdocFng0CeNCelfAfatTH6b3RhP96cAEPstTjTABPLg0MNMADehAQ16Ky8jgQATgDhAt+bcXsDUvoslVzeVAHvB2UIIQAiZlsO5aBtGs93e3d1dXVsFEI16o1KpmKa5u71tO46sKCFVolTCGNuWwR2707Y6nTbn3HYcx7YY51wIBEAxppSGKZFkMjmdJZTXqs3z58/evnG709Q1TR0bGX9wb9my2dT4bKPRsHTeNC1VCheLK4bjJBJOo2EWi0WLi0ZD3y2WTdNKJBOObTHHdpj46MbtQr4iKzQej3LBGvW2LNOp6bGdnbLtOKdO/v9p+88gSdPkTAz0V34yVEaqkl3VWk6P7ukRGMxgMAB2gIFekKt4ILh3PNJ2eTzjLf+s3d2PO+PZmZHGI3btdvdW2B4BkNw9LLDAYDAYiZme6Z7WWpauyszKzNARn3qV+/34sqqrBQYglnw7rCw7IjIi8gv393V//PHH79i5uk+MrfWz/qB7eLCII7F9bH25LMnT8ZPrGGg+L4+f2IjjyJg6S7PNzc3pbNo0zT333FXUy2Vh43z7xNm71rud9wv5372OjONm7nhLTP+O638jTWQ3Op/eq8X9XsxH3BKB3Pwef8Rz/iydC35LPA43IEd6j4W86wPxd6aybRgW/K3JLjBg73rT99UYP0p73v/T/cj1oyUsGQMBRx4CcCO8u2VTefuZAJqDFMAFCA6SAxEEAinAoyBgUsZl7X7v937v2WefVUrvH+yHEKqy6va6pqkZF9bY+WzunHO+boM/RCSCQJRqzTknIgbQciKyRA7Xsi9/+SeVFt/65p+ePLH28Ud+9fz5cxcvXvrcFx85cab/+ONPHT+z/oHhvVevXn322RcfePjOpMPffOPiYDDo9vp5qsaT2dkzJ52rixJOHdv03uxd3+/1uqdPnxiNptb6Xn8wGY+q2m0M1zgI1zSIUJf1dDJzSBDcfLa8tjvOE1WW9ZWr+yHgxqWO4Hw6L/Is7nY7B+NpINheX5vPF7Xzd559sS6ryby678EPPfqJXxpu/YXHitEt5oXvU6wFACGOIhN+MwRq3eaWp76P3SABu/Hfzczhnc8TnI5e7WiffZ8MRNyk0LXvSQAM6J176nvLsPyGox69JjvCVW+NpgiQ3v1+7H20whjAuxyAjsrMf8Fr/CMXO9I9PmIT3Xx1eNsPGCPOQAhQN9pyiJgNUDf4gx88+a1v1lcvX3zh+ZcaVyHiPffcM5/NGbDJdBpcsyoLwTkiWeekEByIMSa4YO0EamipIYxzIW4gvoK5NFEPPnTXpz79ia2Nwfnzl/7Wb/zCeDz+B//wH5w40/npn/v1hz585htf+9P/+O/8nxaLxX/59/7eXfef/rW/8fNf+7dfv3r16i/+0i8pKf/b/9d/+3Nf+vztt//t3/3d30XCTz76yfli/s1vfvOnv/TTH//4w88+8/Qdd9xx4sTJH/zgB8H5z3z6x55/7tnz589/8Sc+v7n23IsvvfnQgw9prTA8J4V4+AMPN5V1Ntx99z2XL19Wollf2/SMeTs5eeI4cO7DMpYx+Gg1nXbi7IMPfuK++86AZvUcePKeq/1n4fe33C/g3UlgC5W8o8hKRz/cfOb7xSkBCIBxRi24+E6fPPoiAzBgxIERo5tJwDsN4MbxhHS0GBNHW/eN5zHxHmPkRxh/Kw91E6UlgvalEIkAEd8B6DLG+TtjKcZA8Pf07vwvY/oAACAYRPIIV+atywoggBCOOiGIgBE1gQJwG4AA0BMAaEWvvPraP/8X/7xaLbw1Uaysdc7aN199qTHGe0dEAAwJdRQF9LESnHPOJWPMWqu18IjB+a3Nfl3XiKSUYAzSNE2USHuaCzzcHZ3aPlEuRwJkN+0+dO9Dg86gn/c++ODDz37vlW6mto+f+rVf+YWIR/fccfbs3/31/8d/9V/ded/JE8ePX9r5qSSBD3/i3o3j/8G//Bf//YMfuuPk7ffsjy7eefvmv/dXv/TVPzpx8eKF/91/9O/9xI9/5Dd/8zf/2r//V37+y5/9p//0nx7bTn75//b3vv6Nbzz55JN//+//X15++eV//I/+yU/99Md++Vc+///+h//kE58+/b/9T3/m3/7+V8pV/bNf+uUfPvHMc88+/zf/1t+4cuXK/+/3/viv/OynvFuVxt9272216AQEEb8PhfBd1VkC8O3WeDPwpLcjBICjjak9Fhi9jendigjdJCO8a+kW9aSj4wIA/C2MyRu+xNsznyFrC7e3vkz7s3E3EKAbuTLxo8cQqLUQju+2yfdG3W8j8giEgEhEPFAMAIh4ozTGBGdv/3rrQezfLQn+UYuB4BCztxMsAEAAh4DiiLYKNw5JILAGvQveBiQiMBcuXLi+t8sBbVM1B6VzBhG9D22mCIxFWnsfpJTeBwC4CWQJIaSUAilwobVmtyyldN2s0mTbOfPCCy8ork6cOP3kE08yxk6dPO2sf+XlV8uy+uxnP3vp4iXjCqXV1ubG8889b507e+aOnas7ddkoGSVxdnD90Bp35uxtSdqZH+w+9NDDKuaNW9774NnZaj/v6dNnjj3yyMec82fOnv3gBz/IGN/c3Pzc5z5/9eq1tbW1z33uc1/9oz8+duzYgw8+9Nprr5b14id+4ifiKPvX/+Pvfv5zn/rEJz74X/wf/8sPfvjun/vy51fF/tk7jn3q07/42GNPBKkZAns/Dhm8L1p/A2Gjm5nAu3AIDghHWe/N70jwI6+4GYu/lxzx9nkBN1wRj3yMsRt6UDdiiXd8yPbfm0cTHf1Wi14epePveJ/3Kzq/5y66yclnDDhwxhGPyBGMcyC6lSL6jnSIMQL6X8cB6Kgb/9ZchAiEACRAfvP6MgAWEAjJEwIQkUcMa/1+r9fdvXbZmzqgl1JwzqWUbe0JgBGhlKC1BmBSCs7ayggDAiklACAR51wpJYR0zjJg3rs8i48f3xoOh6/vnNMqcYt6vlyMR4cf/ejHVsvVzs6O9+H22+7aubY7nh382Gc+i55/4+vfmM5nm1tbTz759FtvvHXHnbd3e70ffP8HURxvb21/8+tf3726d+L08cVscfn8teVylef9b37te/v7+3Gcvfrqqy+//HJbQHj6qaeTNDl1+tRrr722tjb8yMc+0qby991zz3i6P5/OTh4/9uADDxpT5bn++V/8KQKT5eqjH/1Ankdpnhw7tj6aAwsOSL03AbtpAbcucbMQdhSTgL8F4L/ZV9BuQOJGkEKe2rj95nHx3vpxuBkysSMqALthwDcrPzfenAHdyC7a17/V+qllLrzNXwB2JFLCbqbOf5GmlPYKtOjnLRUMxhjQ0Y7ZJsG3uMGtrvd+dQA6MtS/pHsc9ae932mF+PZf1Z5HgSAECh5CIMZAK/LO/v2//3/+/d/919bUeZIUdXVUdm2vDGftJUvTzHsnhRRShhDaPwQR26M5jlUIXkpVloXgojHNmRNrf/VvfOnue+949aULZ0/fdf7i6499/7tf/vLPl2UppXz5hTc+8+OfePKJH37iEx9b2+ifOn2imw/+5KvfXN/a/KM/+qPTp0/3ur26qYMPjWmOHz8+m804Z1cvXzt56uRwsPHqy68mSdLpdqWQr7/++kMfvL/f7zzxxBMbGxsf/vBHfvD9H5ZV/cijHymK4vnnn7vrrrs3t7ZefuGle++9+1M/9onD0X5T2UFvI9L6/Plzx7aPdfu90WgUvB+srwfmsjg6d7H54CM/D6qr9HvwTHp3iwzcaEq8dQPyBIS38HAYiBveIW427Dq6JZABxuDdTfrvgjjbe/jb97Q/cEAG7MYzb2bKN+0DAMCHNlxpcYujtI0xxhkDOPrld5Hh3nchER4x4Vp/ajPvd59chDdLBEBIAECMEb337AQgQqDwfqMH//x1k/vwPp1EbcMoASIRUutk7bbUZqxKcaW41iLPkzvOntFSKM4AkAg451rpOIqTJImiOM87aZIqpQDAB+/aLMEa71xdV1VV1U1NhNZaa421Dhg4524/e/ITn/j4sePHKNAPHn9i+/jpn/u5L89ncyCIo/jue88u5osf/9xn1tbWx4eTyWRkbOVcQEQA8M4/+NCDVVnNZjOt9QMPPHD9+t6li5d/42//xmq1Onfh1awnHv2xDxXN+LmXv/8b//Fff+ml56fT6ac+9amtze29vb3jJ7Z+/HOfeeyxxxhjX/jCF/f2rk8nkwcffODMbWcWs3mWpoLzq1eufPMb3zn/1rWXXnzzcH/+0gtvYNB1Ga7vTjtpNuyl5F0w4Btg4R03CCDw3bcjawxv3zgdFU0FOxLMiWOIY0gTSGNIY8gSyLos6TAdg5BH8cx7bwEhIPgAIRz9jAR4o+hJbU8fMkQIxAKxQO8cWfk2+eLoXn5zsVsi/Jth27s+AL77Fjw5h86h93T0kQLdEv2/xw6RkDAgYgiE+LaVExFSICLGOGPqf5YDEAEiBQRP4LFlNrQXAgIB0hGBNCB4BCSG7XVBRB/aCJYhYCD0CEREkKZJmiW9bjdLs8Fg0O8PsjyP00RrraRERB+C995ZZ4ytm9p7jzdOa86FlFIIAQSc8TRNBoNBnud3nD076He9c4Hgt/+HP3j22Rd/+Zd+9U+/+9Szz7xy5rbbH330UwfXDx9//Im1teEPvvdsf9BfO3ZaKf33/vP/+0c/8ujP/PSXfvO/+0c7Owdf+MJPbQw3//E/+hf33PXgb/yHf/v/+y//Byniz3/+Cx/68MdefOn1kydO//yXf+WlF159+OEPbm5uzhfL2hghRKfT8cH1+/04Tpyzm5sbcRzHceysee6ZZzbX1++68w7vHDH60Mc/7Fm4frj/xZ/5qeOnT+xcPzy+dWZyOFWSTLOIY5KKKMCtN0ag+btvR4bexicIDEEQKADNQDGQbauhB37Di3gAHgA9BH9j87olFb71dnNXJgYIN6iQdPR10w03IGBv338jD3nX4dUe7JxzqYRUgosjL2CMHdkPHPnY2zcij++4vW//fQihrQLdPF5uMfKbsBNHZBze8fBf3OZv/Aq0qTf4G7tCG/8EIuvJePDhFl4QAyLCQIiECABMSi4EYxyQwHtqTCirQATj8YyICxmBkEJIIRUAs9Y3jVksV40xAYO1FgGkUoxzxpiQQkVKCKGUjOKYcQ4MiNFwuHb8+PapUyeGm33O2Lm3zp06tf2zX/p0v5+88MJzP/eln3j44Xt8sNY248nh3tXZeDT+8McevPPeh1586gdpmgy2Nv/kGz9QSkfJ+je//fRsPkvz/Onn33zqqRcG/c7zL771r373a73OxnJa//Zv/9G1K+PPPPrjv/1bv//1bzz+kY9/fL5ofut3/mBr+8R99z8ELPm5n/vlhz7woW9/+/tvvnXhvgce2Ns/ePHl187cfo+U2fPPv7qzs//Io48WTckk+8gjHwkcn3j68bNnT29tbjGh77733kEv0qIJTSkgSE4CAkMXKVKcIgVKYKwhUhRriiOII5AclaBIQ6RBa9ACJKAWEEnQHLQAchQseoO2CcEDIJjKgQdOwBCVxCiCLKFIYxJRGpNWTkmbKJclGMcgGMq2fS+0jVhHID4RtJUCJAzYohRIREgtBkghHDWqt9HLTe9ozSkERAT0BEjBEQbAQN5T++QWJ2kVfrDd7MM7CH2tjYWAFBADIlLw6H1AaglCDIi1TfFECLcmwYwx8Zea0EBHFCBGeLRJCABGRzot7BaQAQBCAB+ovUBckJTAgQUCF8A4DsBkoMbQzt6YibQ36HnTlPUKADBgQBJSRzHnggnBV6sVMC6Udt5LBUTtGROAc2DBB0aMAPDEye1+v9vvp6B91ukIzmu7+PLPf04q+corL9xzzz2nTp966smnAOChh+//0EMfff7FZ+5/4G7B5O//mz/4wIMf/vLPfPr+Bx54+qmnPvahO+67+/j+3t5d99/zpZ/5xOZw69lnn/qrv/KFV1698OrrL9525vQXfuLRTi997qVnfvmvfvmxx566dHXn9G2nT5w4ee781eXSfuTjn+IM9/au9QZb5y68euHKlcDFtGi+8sffbgxbH54qyjfLwh7uj199+Y2PfPjjaZqihytXLt5559mkf5eKo0tvvNbvbm4fOxs4cQEMyDrKcwgeJA9EJCUtl1WnmwLjjcHACBGBoxLKWNtUzntM0zTS0jPUkXCOQkAhmJBHnbI5IymQMTDGR5FA9JwHJRUBBfREWBTFoJ8D+YBquQw8ilwA23gVS0Kw1mqtAQAFAAMKgDeCbO8IoAUAj5rWmWBE1CqiMgFER0Gas6g0DwGkPkJviSAEIs4IILgASIxxIQQSBh8IQkumubEjt4ivJOCAgIRHSC9RVTeRVloI23ghWZs6yz+fW/gjF2tzcH9EYWAAgBAQBGPsnYAdwU0aEwuhLQyA9yQE0I2AyQdECZcvXT842AegUydPEIbR+GA6GSdJx5pIKdXt9ZarBRBVVQWMee+lVEmijWmIQErZ5gaIIUmira2Nfr8HEJIkOnv2bFGslFJnzpw1prl+ff/s7We11uPROEkTrfXx9Pirr72oIgY8cGhef+3NXrd35x13z2f7s/lBXVef/eynn3jih6+9tjx927H77v3AlctXF6vlz/zsp//w9762Ksp777lzc2vrD/7gK7/4S7/cWPP9xx4/c9vZn/zJH6/r5sKFi8PNzfvuu3/r2NZnP/+p9WPdD33kw1ub2yHgEz94fDwdPfzwQ//hf/Qbly5fWhuunT5z23Q229zaevSTn3rl5ZdX5fLsHbe/9PLL5y+cS6LdE6dOzRfXDw4O6rqKo2Rra0MKqYUgop3dneeefe6jH/vo1tb2eLpAQiFEHMec8+efe77b6S2Xy3vvvff2O26XAkNoGNFqMdORPn5iqypr8EwrLgQxxqWUAOQcCsam05FUqtvrhEAAvm4ms+mi092I045HnyYyEsJYw4CNDw+On9gCRmglMCEkF5w3tY1jCYy1uyEG4JLhUcR6VCQgJMZYG3879BQghOANE1x467kQBGiaIIUIAQMiZxwEs9YSkBQCkYl2gCu1WTUxOEJKQghCCM45MKa1YoyHgLu7u2ma9tbWQsB/ZxiUKPiASJxx3jKyibwPBEwIgXhUEr5JTSFgCBRCC7Ex55h3bVyEnGMkIE3ks08/ORkf3H33ncE7YxprLRey1+u31yxJYu8ttUCnjoL3URwjmjTNlFLL5UJKlaYpA9/rdY8f2+52MmubPE/W1gZZlj/yyCO9wfqVSxceeuihwWDb1NX+/v69990rlfbWrg27t995Vsc8yOhv/fqvfezjnzq5tfW97333iz/7xX43efqpJ3/ii585fuLYG2/tTCfFr/31v/PUU18ZHV786Z/5Kx98+OMvvPBcnudf/vKvRDr5wAc+6BzWdX14MLl86fJ0Oj915rYvfPEXVSQr17zyxiseMe/nnbzzyyf+N6+8/MRg+9jG8Oxge7tYTD73uc8j4ub2XU8/+c3X33x9sjzc3Nw4dvzYydu233rt4vkLLwkZ7V07v1yt7rzjjl5nqyxX0+lquVxaZ++6+/jo8PJodHm1rM6cOaPT5Pq1y0VRPPv099eHG0qp++45sb97DhH7/d75ixdfe+21JEk+8IEPZHmWxMlotIzjeDIZD4frSZLkefbGm28+9/xzn/r0owy2rTPD4dZ48trrb76aZsNPPPrjRVmVhWeBjcfjKIq+992vPfzwBz79mU/uXS+4SqRQjAGiEhKAmJAQ2l5zDsjJNo4LIaXknIXQkheYkExHkjEOgCEEyZixRZpmkRbccRUrDUTEQkAMQWgmuGQggnu7OsEAOCcAEJLTDZzT++BDk+dpU9ePPfaDP/nqHz/yyUd+4Zd/1bt/9zoAA6UEF0jAhAAGrSweOgfG31J7azOe1vo9IN04Oxw5ZxGClDxOlFK8WC2/8Y2vd/L81KkTr77yynw2DgRCCO+9lDKEcHg4qptaCGGMUUoDY4jIAKSUeZ4LIZIkybIMglnfGArBFouZtQ1AOHbs+DNPP5N3MiIYDAbPPP3Mhz700dVqlabpV77ylUc+/ogPHoA98fjjn/38p8rZ7q/8zf/00usv/NZv/6t//2/9tdV8/vWvf+uLX/rS1avXrPXXrx+YRgekH//8r44Pnh0fNp1+PxB/9Y1zx7a3L1y+/DM/90t33/WhZ576+uuvv2Vs8B5ef/MNz0pbwwsvPfPY49/7/hOPnbnjtk6n85//3f8DcWTMEltlqSwLGaVJr79GWL3y+msnbzsdwFy+dmX75Pbxk+vdbnryxJCA1U3/kVMfWBtucJnGKW1u9qaTSb8/VPGgqUbW1MtVsb6+UZYF483d95566OE7/+grX+UMT5/ZWMzn1rm8s/bQB+4TohmPxrPZzmBwNkvjZy6/efz4ccHD1kZvMp289ebF82+9cdddp9bX8z/6w38VJdGDDz2goub4ifUL5y+98tL3uUjStHPp3JWLFy888sij21sph2oxvT5fLLY3TjMUXHIpASk4Q9LLEDD4wKXinKdZ1B4IRCA4A8YQg5ScEQsYOAcpWJpyRM6YV1IQYrDGOi+kYAAYvBSCEENwjKk24WWcccal5AyYD54IRVsd46xZrJ57+oU40ns75xlVZ09v7167AMDkexJfuoHv/gVDIwYMxC0MXcEZV4qA0L1d7AAgxjgxFjxZh4iMC0ZEFMhZzwWliUoTRugf+973Xnv1lfvvv3cyOjBNYepaJyljbLlcRlGklKrrijEQnPX7gzzPibBpmk4nb4EgKSXnvK7rRAMG78gF76SALE2SJEmzJI6ToliNx+MkTS5fvqyUOn/u/Injx89fOH9s+9jutd3+sFOU5Izfu/bEN7/+nf/nf/3b589fyZL+f/0P//v/7D95I3h68pmn1obDn/mpX3jzlWfXNtd+8P3HJpMieFgVK2fdlSs7UsqmWiK4V1993VgPjEulgDFEeO7FHzzz3LOrsmwqzyJWN8Xv/9G/feTDHwtMM9blEvYPXvvTP/3Tv/k3/3aepwBMSFmbikf8+098d31t7fOf/VxvODjY23/qqcedryfTg1Mnz5rGvvbqq2ma9gfry/l1zsP1/b3Dw30uaLVcWGuvXJ3GUZSk0Wg0Uoo3ppRSSS18Vdx+9nS/mw0Gg/X1jaquPv7RDyyXi253PdK0MezkqdzayNbWNyeTg93dy1GiiOqf+MKnbrttrd/rBM+ypJPmHVN2rlypB+v5r370lxkTi9mIoIiSIACr2q+qIu1FCNy6IKWMUoVIQKQkx0CErUYBCyEwgljBqjbTyRRDiGK9PtyMou54NHMuaBXXjYs1Z5y881pyQt8YI4SKo4gAjuhODBgQBuedEVwopZxz6KxvJi88+1ivmzfl2Jvp0098fX90qLWWiNRipkeMMdlGK/9OvCDGmBBMsrehXCRqmwesIecCETCUQEBIIVCiuFaCM7Y/mnz1j77W7/eWy/lsMra2CSGEENpUhjMWRVGW5UQolVRKRXGMSEVZLhYL7z3n3Hvf7XbzPO/2enGiszQmDJzDXXfe7r0/ceKE1nowGCyXi7W1wWJebm1upWna7/UWi2Wv18vTfpyISMj/8V//3le/8r1PPfqxD9x3xze/+cNPfvKR7Y3+7/3+9/7m3/qFs3c8uL97/fvffezCW+fzTmf34CDLOiEExljTmDRNszxXKmOMz+eL0eHYGFsUVSC6unvht37nd9586y0mWZSr5aLurifPPvfM3Xfe9dY3//Cnv/CrZbm6cPHSbDZ75pknP/nJRxfLFRP06vnX14adYjkpVrOXXu5Huru9fU9t7aUrV7a3zdk7P+hxtX94OOj3k/RYnAaC8odPPXnp8oUHPvSxJE2MMU899VRVVwSgIs2Uvnrt2nBj67Tsdnrd+dXz3//B9z//uZ8cbqRZlu3tvfH9x77z5V/4NWKSGJ0//2bdFP31zdl83OnGx45vP/qpz+hIHOxd3T5+R7VaTA7H3f4g0rixnmvlOKwIiXC1Kg5XxZBhfe3q+Mr1q3c/dNdqbJzx29vb6xtDZ9vDHBBJKiEEK8v62rWdQSfp9fNLFy699PJLRVH2ut1PfOZjnV5+7tyFKOqcPnk7EGeEl89fuHTpMgAsF0sf/N1333vHnXdrrYUUGNBY29RlVa6UUoPBIDh+fXdvOjmQwr312jPXrl6lEJq6vr7zlseGMZDGgneACASBMYhiLiXI9zaQvr1uQYn/7CVujE5AarkiDAAaTy4gkQwBABkX4J0NwfcHuRCMMfiTP/nahfNv9Xrd5XJJwNKsy6UmgZwzDGjRgCEVi9X8yDHKqpZS5llnOj5YrZax1sbZjWH/7G3H4kTaJkxGBZHXOpw8uZ7m+XxZPvvsywcHY2uckvr48VORNm+9uRPHY+fdxUv7nTh69NMPp53snjvu/p3JH1y4eOHzX/jMb/7mP9+5vv8bv/7L65ub9917x6p0ezt7RV1a7w5GIyLa3dv9sc985tq1nVdffeXTn/6MVBIgYkDzxQLBC02DzcxB860//cZzLzzHGJOK1bWtawc6F2L8R9/44+t715em2N8fvfLSK8vF6sLOhdlq/9iJzb393bosxmiMqaq6fuzJH3YG253+Zm/YmSxHXMNb55+nEDY2BtZaRBdCDczkWeyDn89GJ06e6PC1/nDgR76TROVqRSGcOnVGK8khAWCDwWa/P8zyPhcdAOgNjjXGc5nF6TAGOHnyzsuXXu/0jgG+3lS1FLLT6a5msx/+8IXPfeGsM/XTzz033Lp7aYuLe5dvm9xx/MQ9AGE0PffH3/rDPHuslw0vX97dPdi5/cJZV8Jstnzg/ge//KVfuHTxymK2OHv7GdM0RbHKOtnO7tUfPPkYo3D2trNXr1y+cuXalStXtja3J8XFqinjNEqTXIhPolHnLrz+6lvPX750WQhRN02/37e0V1TnMIAzYW93PziczabAw8mTJyOtA6Jz7s03X0VW12aPy9XW8a2D/cr7UvEIIci6ZsEDAnDOheA32ojYnwcO0Y/2gZsSi28/lQFn4AMhMgJOSATEmUo6GkAAg6effvFb3/rTKFKrYllWRRzHTHBjGo/eWSukSpK4qFd1Y4J3bZtjmqaCJ0S0vblNITjTJLHq5unu1WurZp7F/YO9SZzI7a3s5MmtxaL6+te+/dyzzwfPvAvz+eLue+695557nn76ac55VVV5nt9xevPRzz7sbfmpTzz66//BX/un/+J3Diez//1/8tfvf+C+T33yE4eH+88880ya6CSNgfMoTZrFwtpmPDosisJ710ZoyivO2ZuvvrS3u7u5NfzwRz/0wovPf/fxx9668NZofznc7BarOk70cLMLQJPJ7PDgKcYZ/8Fjs+lsdDDhDPJOMl9Nv/yzX37m6afeOv9qUZVrw3Wk0O0PRtPD51/84XQ2Ms4Kxb/5rT++954PfPYzX+RYAxBCtbdzZXdvpzbV4z/83t133X377bd7tLPlVDP5wQ8/pDTfPL7NqKXGIHDqb/QdWQTPQUYx2z65SaJB8Ax4f9jDi8CA6ShZ2xg2pmmalSfUSVSbw+t714Tmy9Xet7/3nedfeqFo6nvve4ShfuPCubfOv1GWJk86VVWvivmi2CkrO5vNJ8srKrYvPPdCVTX3339fVVWHh6Nev9u4YllPR3vjg8mVSxcvEoFKpIPiuRefuLxz6e57bj916lSUfezEbadeeO1709W1pE8MPEo3K669dbGOoqpp7Gwyv3zhmrOhLIoTJ4+dODV49Y0XgSjO0mWx77FyWGwfH3zoQw+99CJcvHgZgXMBcrVEAuSCpBIEQMjaZk1xg8QfAiEBMOKccQ4tV+NHu0dLNWpLgBha6gVDRk0dnPMcBGcUiAISI+E91LWvG/Nbv/U/vXXuUqzRWWetIcCyrPav78VRnKSZ4FQVVUAkAJXIWERlWSzLeW0LzrnqDDudfOrM1sbWse3jzz/33O7B+P778mW5bCw7caLT2zj+z//Jv7x08fLh/nTn2m4UJVVRf+rTn/nqV7967tx5IZiS2c/+3E9tbq8//fTTt99x8td/5b/46S9//r4H7rj9rrO/8ld/sSzKxx57bHNryzm0zvvgGWeLxeLixYt33Hlnt9uNk3g4HG5ubiZJ4r1/+snvX7h4br6YcYm9fj+O48W02rk2rgs/Zav5YdNd02uMkjxuGm9qJyQbHcwBiHMuODs4OPjWN7+VpZn3Nk2zxprpdIYYer1eXdXPP//8s889HycRhnDxwuXFvAzGbW9vM/Z6WZZvvvnmq6+9gjy89OqLTz3z5EMPPTSZjC9evLS5vt4Z5t957OsbGxudTn555zUdx7PZ7OLVc5P54X337p08eYoYt1T/3h/8y+H68IH7Hjq2eezhDz/owmx9q//opz712muvfv3r31CJXhaLr33rKy++9NL25rGLV688/vTjxtrnX3zuW9/9N0Dsu9/7znJV7FzeswY3N9eZhOl0hgxBhv3xzp989w/G43GSJIdPXbGNtcblnVREbDDsILOj8f5oPEmSaG0wXBYz5JbLcG3/8sF0DxG76cbFK+d0yntJD5Ga68XOlavL1Wy4mQ/X1te2eyJiVVnv7OwYrLtr6dqq2+32hBA2lHu7lfGO+0bF6ot/5Yveh6vXrr311luyMR4YCikCUCDg1VGwzo7yCeZ8G6+0VVvOJEWKiXfQPNsSILv5vwAQAJxnGOgG+Zmc97X1UigKzDkfyAFngqvGBuH9t7/9x48/+cTGxsDZedaNZ/NQFIvAwtpWL0qVVpqIAlIklI5UXVemqeJcpd3IB88ZA+m7a/l4csAkdbr5/Q/cdzB/Qiqe51lZLIfrA0HNV/7t186cOXvP3Q84C1cuX93c2uh0Otb4gPqOO09+4pFP1HX9D/6bf/Zbv/ffee+iPP3hU6/8/f/rf7a5uVGullXdXL12bbFYzRfLUydPfuITn+x0OhfOn3/44YcbY6Io/uhHPnr+/PmXXnophDAej1944QXGybpmOg+/8zu//dprb0xHK+uCM7ho2qIVP9xZZX2T5rFtgqmDqXajRDDG0lhNp2W9uPadP/32PXffNZ6M77nn7r2964zD5nDzoQc+8MzTzx47tr1YLsfjyfr6ehTpF195YVXefvXaNWNMXVWzxXx/vJNlWVmv5stp05jJdDxdHl64dj7P8yRJ6qbudHIudRLHr736elXWt9125q477zp37q3pdMoFy/P8uRefT+KkWZqtre377ruvKJbff+KJ2XRWYpVmEXB8+YU3+2t5lnQ8hvli1e/BP/7//DPGmFY6iRICPh9XSVIyTsbapBMJLmeT+Wq53D6xJaUoyqKq6mpl5vNFlEiPdjkry1WtY8EF7O7uSinzfry20U87sRBid3TlldFLq6LoDTpxHG9sbASwcaJB4WtvvTYcDgaDdcE4S2DjxLAqzJW9S51Blzg13nDFtk5sq0TPpvMLVy5uHds6dfZUhdXhoisBqE2cgXwIvA7IjtpqGDDGWZtZc84Z9yAkcAcUUEm4wfO7afc3tv6WCgHg26J3IMKWMCsiJVCwpsSAHjgaWy9WU2NLCs0Tz35bZTbuYMZzRCwti0HEcZ7nGQozn8+ttXEcR1owThZpNV9ubK5tbW3VdV3XVabiWOvtU2tr652inie5vu++U0kSHz9+bDTC++6/dzI5tNZPJ9PhcPjgg/czRlGsF4tFf9D9xQ8+tLW1dXh4+NJLL93/8B1rw6HS4u/83V/TUX9rezNYc+XyBSH0xz/+yONPPHnl6t6Z2x84ceLEZDK7eu3ahz74waeffvqtN9/6yle+MpvNdnd3F4u51loqYWyzfWzbo3viiR8SMgAwdRhuZ4zxxaRsmtBUnkkmhGCMdfoJZ6Cl5AKkUEmKZ85uKy2I0apYWue2NjfH4wln6vy5i3t7uxsbG4wzKeSxreN33Xnv+fMXyrrc3dvZ2dnpdrvOW0RARKWksYZx4FwAgyiOXPDz/euL5UKJOO1lx7aPzZfLycHS+WCsXazms8kcAK5e250vl8755WS5vX2sds0jj3yitu7Nc5cXZrl1fDDcHOg8WpZ1VTvBubN0eDhfTJreIEmztN/vCy4Yg8VsFTwxznSk4zyqvFmuTL9nGefFsqmKppjb1dxEiZQ8Qk9KSsHlZLQqlzbLaX93BIIdO7m+vjUwtnHQWGdn0zkhVmXtvcs7WbebAw+j6bg2xgevdaRFPF8Uh88dPvTQB/b396MoEoJ3uykxJKDpfPLiKy+8ceGNvdHe/sGB1Ao550fF8LYrN0AADIERCOCkmOCcUYBA5AMxDsEHKYhzLoQQAhhnFAjf2TsUWoEgj4isZZ+2SUHwQMCkEqtqdfHK60+/+C3nm04Ws2hx8vbueLQTAjLGRMI7aeydW9TjKFEy4jZgWa+QXJZnKubbJ9aUUvPVuK4b70NwjUrW7v/AXWuD4Xw6sY39wAcfunJxtyKrtDp16sTh4UEU6U433z/Y7fY79z90J0LgnN91111RFD35wycvXbw8WOt/4Sd/DMi88uLLD3/w4Y3NU3/6+PckYZrEWad/7ty5l156dVVUjz/++He+/Z2iLEej0fnz58uiaJrmmWee6fV6m5ubO7s7Z8+c+fSPffrxJx5jgjVV1e3lTIBKI+BLDNgyW7qp6vTTAN45bxtUWiGClBIxtC0EjWmuXN3JsmRrc/Pg4IAR393dFVxdvXxt/2AvziMppZLyjTffHI/nRVV2e93G26KuSlMTURxF89nKO4+IWZYBgve8LM3ocCyE0FF04a39ta2cPHcOTeMP9qZVYbdPbgDxxbQqi1qr2WpVRbE8mBy++MrL997/gPF+NJ1ZQj0rZaSjOK7KZRMM2TAcDg6uz+rSC9HMJ1VZ1otpBQT1yiNRdxhxBcRDlMjgw/WdSZbHxaokpLVhX4mqrOrrV2ZJIqNYkmTVyirFAahYNHXjAYEBC2DTLOGkbI2T2XhyuKOUyLJYgMh7CQPBhQTEgDiajaaHS6XUaDQejUaMM63VwYgYQFXXtnG9sj/MIhDQG3Sl4CQkKqW4ZJwBCBECWIfWBR84ESfWEgpvEFkhcA1Hel4EiMD4rYIWLWkf2u5MRNZimC1JgRFDJClZZfwbb77+7e9/5emXv3rbqRNZpsti3tRFkosrlydxIjvdjpTSBtP4JhRxY0wIyJmwxluzqCqT9+K6qIXgSsnGOJRkQpl0jomISc273cHW1sbl8zvL1SLN4s3jJ7sdeOCh++I47nTSyexwuNn72Mc+gjZ744033nzzTevs5tZGlmcnT53s9/sPPvTgYmJeefWVOInL2fThDz787LMv/c5v/avuoH/s2ImNjc3ZdLp/cNDv9Yjo1KlT168fRFHc7XaNNfk8Z5wX5Sogeu+uXL3i0c0P63yQRokwJhDS2lYsBDAOg0HHuTCqlk1lGGNppkxt7nnknt29q9PpYQihqus0S7c2t994/U0g9sMfPH3nXbc3rllVi+HG+s61neDCxQuXT565TSgppYqSeDKeOOtjLarCEmK5ak6cjNfXNxbLej6dLeZlXfhOLwaixaQS7DBNcq2rctU01UJpgZ5NDlZEYGpfl66qrYws8Mv/9F/8s4P9QxkJhmI+qQC40mI+araPbaya2d61aV2aJJNZntvGeu8xoI5FvTria0YZb5pGxzrvpXtXplGshWTLeck4Zd1YaFgtGinANG441HknLldmWZm8GzcrN4FSaUkipFlCAUbXZ3Xt0iQul3VTOue8C04qQci7nX6axuWqcTbESfLWuXORVlVdCSmiWAopGGMIYTQd1a5eVNNO3pNMAhecCS4ka1vuBQfOhACwZEPwiBqZoBsbPBFZAhKccTpSc+eAjIWWX0cIBEitPi9xzuNEMgbegfNhsaySKHZYjourz5//k8v7TycCr+9ejqOIS5bE8W1nb+MiQoTJaOpMybmUFI8P5iF4YExr6VyIIu0N7c/nUvFuP/XGSC6TQZT00kVYjsbjqqrrSX3oDgZn0t72qfXecGt9fX//+taJLa10FEd5r6cjXVUUcN7gMh/qR+7+gJAqTqKHPnSGMbZcmMls+tILL3zkox/dPnXyt3//D779ne/d9/H7Dw7HZx44de/ZO19//Y2dA54lUZKmWZ6cOnVyMplVZZnn+ZnbbhNC7O4dJGkvTpOss3Hu+VeDw9G0VrHIu/H6xlpdV9evzXp9QseZpwc/uP3WS/vDYykXuH6i88all3UUpf18uVruHh4ornyAg/Fhr9d35FSqzEoWi+V99x3XIn3++Re3ttfreuV8XVVV0xSco+BQFrapvI593skaY4EJFev5/oEUqttLZtOld2G92ylXZjpeWoNcMql4vpZjwHikVnMzmxfOBQHkSr9fuuuXxuXKIIJtfG8Ym7JO4s6xrf71K6ON7eHKlc7Va1sZCNZZ60Spyvt50zSmccEhAaGRAripnW38YJgTYN7JNjc3xuPJwfW51ry/ETMAKaAsy8W4qgrPGLim9I5M5U1lB5vp+eVe3kmjlFsHs1mhNO8PMyHFYl6kSWzqAyEEA5alHfRw7pVdqfjaeocxVtVF0lFKiSiOyrJSOrp+/iCJsuV0XxJxAoHIvAfGmJBHOD/nQqlYCLzZXME4HPX9ELadO3Sjl/ltXa4b1NQjb2EMA2McMJBzlKYdFeG3/vg7T7/wnbcuP1fbBQQ0jbGNu+3sSUS6cO6ikGo+XwaPSmlGwjtXVyYgteIOiMgYU5oDk87i5LAADv21eDYKFJgS8XK5KooyjqOD65PTp9KtYxt3nrmdCfj2t77XGP+Nb3zr7Nmzn/n0Z6qqeuaZ55GZqqrOXzhPFKSWiOHzn30oENu5fh2IP/DwA1Krvavjb37tu8a58XgcZ/LqwcXR6MA2ttPL4ygxxu2PDzpJP81SIgqEZVU1TVNcqxvX6ChaFqtOP06zREZiuSqqlVsW8zhRx892B71OJ49X1SrPs/XtXGuxmNdSS1JQrIyU3FsqsAzOO2uFEIvloqqrc+festZLwS9cuJgmSbeXHxyM0lL3+/04jlsyfaefLSZVnIJSiglmbLNcLpnUjGA+LRfjhgD6a0mcxIf7o6wbRSkbbvSrqiyLOk3Tta1Oy58RgpkyKMW9C4upqQuvY+FtWEyNaQIFipMoIF6/foiBmjrs78yybjTc7JlFE8Wac6k1pIOMMzYZzUIIUayjSDnr55MizeMirhCxN4hbHiU5TOK0mM3qynd62tTeeUy7Ks20c2ExqZOOjxM9WFtjIOaTsY4EELPWASPnXSzjJE6ms+lyUTrnpOJScQCQSkUBvQmuMRhYJKPZZJ5leVGURVFLAu4DBQzMM8YYmJabzW4UBIBzaIVFjlpFORCKGw8CAbX0T8S2AaKtI/OAAYj4DUlSZ71zJDQcHk6eeOJPX3r9+wQrJI/YdtL4+WwZgm8aK6W4fnWWZCrWiTMNITmLGChwBAAMxJlRWkaJTjLmg/cOheJEUBZNFK0ImVI6SbJgXVGsBKc7xVmhJWfywsVzd99972233fbGW2+VZTlcW0MZQMpOr6e0tN5JKZ98/rWzZ87sXT9kjJ04dvLNq5f/8N98e9Bfr331yqtv5mtR0o1jpoeD9Vinta2qqqnL5vruAbaEdQwtIwM5C4QOrXONlACM4lR7rr1HJHIhAEBRFoz5prYmN6dv32YkitWVYMkZu1rWQjAMBFCTR6HEieMnimJlpVysKqWFc2F0eLi2tjZcGxIRMKzKSkkdRzED1ul2u53ecrkw5mjvCAHTOCbNDouVMxiloq6stcZ7qgqzdWzoapRc712bdLu1lCLrRM4G7wIheYfBozMIBMFh3FHeYjE3TeVP3K66a/HO+TmXLOtoa/1qYbiYO0edfsQYCz5EUcSVCgGaOpimTjOM4iiKNPrQVE0U6SzNvfdVVQsSdWHLpRGSDzd7xaqejcsolsONwWq5WswrzlhdGcSZMbY3iLv9vGlMCCHtRJGOpVAAzDRuelCiJwxoAs38Kk51HEfFomEASmpvEUNQwhNCFCkZkN/ALgmIfAhExI+aMxnnTDAKDHnblCsYCwwZhqMGZEQkAMIg3tVd2SI/ANwREZIPLV8aDkbXxvO9pl6ur8dCxNaLEHxZV3XZ6EhvbW1762ZJqbgoFvV0vGKMoUdC4IIFG7wnIZhQLLigNM86iZQy76STycxU9ur8QEciTqQzLo6S6WKBaK/t7+7sXU3z5J777s2y7PDw8OVXXjp9+nRZl4tmURRFVVfD9cFsuVBa/sFXv37m7FkpJGK4eG1vZ2dnZecbm5vX3tjxPjhLYWZWWBrvtYxcE9BDU5m6MJwJYEBISqs4ioXg1jSD/rqMGHHfNHb3ygiRhOLosayDqX2WyU4nlpoXZZXlmeR6MOwyJhfLldYSAGxjk0Ql3fi207dZa1uULU40AKtWRio7nU3zPFdKWWvny1WxbJQWjLHlfJnmiY4UF0xKlSSxilazcYkhSMXXj2VpFi+X5XSy8A5Xc9fp1Qe7S6VEbTx55JzFiY4TPatKzpkzwdQeAjGA4CnJFM9ZtXJ1YYGo04/Wj/dm41WSaR3zqnAEXCrAQFIKAJxNljpSUaRMbaulQ09SqCRJg/eMM/TUBMsZr1YGLZnGlSvHOVutKgAQkjsbVquVtQ4DLecmBGxqUyxdfy0VTFbFInhSkbDSVlXNOa9WZjUzQnIhGCLZhkKgNE28IcYpeCqLWikxM4v+sJsnqWxNE7EVZQAiYsCQGOeMc0bIffCECIwJxlv8n9oBHPSuzsu2enxTCgw4MOLMOUIMhBgojK5fferZx5arMWPIgSkRa5VMZ+NqZTpZJ40zbzwiU0p4h01lbROEOKLNIQEwLiSLdIQUhOScMx88l6AikXfSLEv3d6bF0nDJmOQI5BpTR3I0Gu3uXx9u91HL/f39K7uXD0bjE7edQI7Pvfg6AXofUFOcRtY7COyll18NPnDB1oZ9Y41Be3X/GnI42C23hGTEiXmkot/jnAsdS+NMb9hN00wpbUxTFIUnl8RJ6UJtS+uatBt3B52qPKhWtY6ls0cd/IW3zvnhRn+xXDZNPehnGxvrOzv7prFpFrcSd1KLrBNvbKxfuHCRAMpVHRwCY3kvjWNNRKvVqi6t1lJyZRrrLIsiTYEqRgDAOaeAQDyJ0kNbbG6vD9YH3ts4iU7Krb3dfS6s1IyIlJKLSd3dSLIsK8uqKm1MaGqPBimgd4Q3GnuLuT1+uqeUBAYhhKayg0E+HS0JodPLgJVaSyGZd77VVFjNDRcOApjGtU0j3gVnqxCCUtI0NgTs9jJCcC7knTg4rFZ+Pqq4YEIxzqGpbRTL/nra1LYpfZQI9DgblUrKVsVOSVWuKgKWJnESRypqtBaMgxAcCITkeZ6VeRUweO+VkrNJlXUUADR1I50naDvPiYiOAGM46sUkxpBQAjHOGMKRwjAxhLbVBnjbkM9uyHVxfuQCRIw4Q2QhkPfIGJtOD7/zvT/4/T/8nUCFD353d6KVAi7LsixXVqnFfL7gjMdxvJxW5coxIK0FA9Zby1eLoq48ZyC10JHmscvyNM5i701VNKPRpNPJ8jwH5qvKZnnc6eQIMBnV4/1FL+kBw+F275lXXr90+ZKUcuPketrLp4u5SEhpZQ0wCUmecms6KmGcV1UhtQzoV6uVcyik8Eh14evSLqYminlduOCIS5BCCCVQCAdNFCsGtBzNvce8n64N+js7O8aE3lrMU9o+2Z8mzNkAHGLJABgnyjvZ8RPHs04CxIxp6rpZLUsiCqHVHUVTuzqur13bsc4Kzp0L3mKvn6+vD60z1jprjHPOWUcI3gVnUWmbdWJjHBFKKQkoUumgP9yLRkKyTidbFfNAptNNT/DNoiiXsxXjfLCeYUsI89hGsa2jmpUjolvFUWztOecqEv3NWAi5mtdIJngqVrWOOQGs5rVUHJFCOAqIvQ114YAgTiQQ1GVTldZbZIJjQCGZ0lJrFSey3+9knWR/Z9qsvLPoHJgqqFgAUZyrJJOld03licAabxonhRKMOnk+tVZKqbXudLohYPBYVzaKJWPcNNZ7n6RaRxEics6mo8qZ0DQ1EyARW7VHDkQIiP7oKGAMWoajFJHgMiAxxrD9l9i7hNzbsUxtyezt/KH9gTEi1jTNzrXLzzz13ev7V7aPDUZ7RTU3nWEUPGY9nffiycHSmHDsdK88XC4mtXe4dXy4NugjBh3rgL4qC9sg4xyJhms96y2GoLVuuKtLi4SNbYCQcSpWdWOsjERdWAjBWb+7f7BcTg/HB6ti3ul2O/0sStTo4sHG1rCuax1J78Pu7m4U6+FmJ4qi/euHRHTits3+Ws+7oHRy4a1r27d3Jter42fWGYamaYpFU9c+66hjp9fn07KpJp1+zBhUpdWRWKzma4P1gBglIgTcvTpd2+zEmdKJ6K2LPM+NsYtJMZ8ud6IdxgkD7FyeElHajdM0to0PoVSxiOKok+fnz13WkW61zZTiQrDRaFSs6qZ03uH6dieJk/HBrC3JE4EQgjFqC72ropzP5kSsO+guy3mcyeHGmnVNFMvFzMRJfPmtkdbWmqC1mBzWq7lJMtkfZkhBSIZ4hP/1ejrLsslkFQiBsaZ2aVfEka6LxlqUktVLt98shWLoSSdSJ5IBKC3XNyLr7Nqw661vGtOUrql9MDdcikGcK9u4NE2UpqJcRSrdOrZ2ZXnY2pDQXEeihWWTTG0fX5+M5uP9kgEs56WKlBCsrhtE8LW11m0MVZZlTd0Uy6YuHRHMJ7VScxXLbq8rBK+qcm0rHe0V1vjNY0PJkRgDqZjzXjLggIKDVjJJ1XQ8yvPcBCu1qKpaCV3XjRCaAjAub8Y+RCQ4HKH9wDjn3gdkjJBLYJEKi+La7/3b39m9fu7CtRdjKYLxSaI4A62V5x6QexviRObdaDmp007UHSZS8U5P6ByFkGVZRplIO7Je+f6wQxBM7evaGOWTJAIiWwchuFZccLGa1VknytMMKdTlsin8bn/8rSe+3+2nr756pdNP9kfjKFYHo2mwgNJ2u0lZ+Pl4kmTK1m6kp6tVsVjY4AnY1Fkvo0jphoB5j3GunG+iVCSRLuaGCZb3UwytCBlbTGtEAsasxdmiCATOERAriiY4QoYyElwIpZUxRmp+6q4NKZj1vioaZzAdxJFWtnFKqcWsqJaurrxrQnBBaR0cM94XK5smUb1w44O5bRAAdCSrhbGNS/KojUoJGAYKHgFC8BjpKGA43B/l/bSbZGioMjURscYqAc7Wt53pC66uX52O90rGWHctAgbT60udyE4egYdi2shIrJ/N1za68T73zlvjJtfLyT4cv42pWLrgO4MoTpS1iIjBIxes20sICT2qSFHwpjHeBSBKEikEK4MNnphgSUd1ekmcREDU1A4A0dVxnKpEYOWRwFsMClXEOWOuCbvjEecgJfOOVjPHhRtsJuWyAcaLZa21mtCcKCRpNNjIdy8vOKPgqKmcEPLapT0u2ebW+tpat65s8DS6PpOMMSGOBLkYB8QglQAFgQJTnGsuMXBlU8E5Ixs8UgjAMfj2NOGMB0JCzlnb3satdQAglHIuMAmHo70fPvmdZ176/nx5QBCO3bY+Hc/Srh5sdPauTjgD1ZHWeO9D3km7/U7eSay1bX+Cc85ayzlP08T1gnd1+zaIiEjltPLdICW3JjDBgq82j61lnaguDQCduf3UfFp4i95755wx1qNfzgouuG2Ct8E2Ps5VHEXtgd4qcwT03vs4lVJzKUVVNONR1RlEcaKjhJxFoTgQiyKFHQiIcRyXRe1MWM1NObeMsySTOpbWBG8Wi0kjJItTmeQqSaMoUU1lZqPSNiHvR2maAOdALE0SkQvGmDWu9oaI0iwGgoANekRC51wIGELwjoImZNRqIqQd2emlUorFotCRV1ogkrMh+EZHknHQkWqJrstZHSWy9r5pZkKILEsbweNcoqDhel/LyDssF3ZV2GJRA2OEFCUqiaP8RLJrp03jVlOTxDZYnB7WUSyAyFuaHBSdtahaWUTKO2kU8bqpVRYF9IwBk5wIjaudt+XS1IXnnKlIcMGSTNalj7t681ifMWaM4Yw1lTe1SxJiYL19m1rgTBCKMwbOkjPBGbyZkAjJpeJlVbfVYnsU+ImyWB47sbU2DKP9RZLK2ai2NrSQptbzKFFJKpNEx6k+aolsBdUYY1xqISQD8IGiOCMSztdKMCKy1nFO1EpKIAEBY1wI2eoZCgVKKwLiRJwxKVmsxejg+vd/8I2nX/z24fxKkop+2gHArBOXq1pptnGst5gWTWOqldOxyPI0z/OyXrVdzCEEay0iaa0YQ+/Q1X46XsapLFYsBHQO41SrROpIlAsnld88Bt1e3tTWGF/XTZbHjDMdSSKyxm+fGF67cOiaAAAqEgBQzI3gIkqljmSc6jiJnHUAFCXCNmG2LDiAlLxaWSAWJ9pGvlpY4LCxHSGy+bhhtEBChpzCDbUvJEDyHtteHwykY/A2TPZXW8f7wUFT+sF6rpTY35lGiej2Uq1U8EhEtnFNZRmvtFRZnjjn68K37aCm8SGgd2iNC41zBp1FQmpq05SBWAs0EBeMkEJA2zjGWMVrIUWeZ3GcLGZFXTod861j/SjS0+lMxJkxVstQ+1ppEedysbRNFaRkKha28eODZZxoRPKOZocNA1YtbbmwPuKtCZo6dAh0ImzTCvEEQtBaIwhgIKWUkltrdSTEWkpYWRNCQC543k+iHHUkbrRk+aJwFMjWwTZ1Uznn8EaIBCEQEHHBAShJlW2aW4NvZ9F7BAApjxIPIYK3WK6qujSm8nEshGTeYacXMQ4+eDAkFU+7OkkTCQDeeyQvpGhTV9sELaXWMkokOlIsiXgUEJ1p0qTnTGAcIi4ZA6GAc4ZSEvMq4gyQiJJEe++behEl4s1zT//wqW9eO3iTmOmvbc4nC+vM2toQCbnkaR5jQGNMfz3d2Br2+x3nXNvWyBgn8t5770MSpzKJszxuus6ZgEicQ106ImaNE4oJxaNEENFsskjzOM01Ei3nhY4ixsE6p0glOuuc6C+my9lBVZdOR6q/lper2tvAOMhImNoCULMyxcJywSItgsWicDIWTemlYL1ejhnt78ylEs4527h65eLYcMmkFN1h3N/MgvfOEedAhjEgLhgF4hyAqCnddLKyja8Ll3Wdbdz0oFRa2CZIwRBJahFFKkqUNRYDChCdTspZI6V0zmGg4I5yM8YoSjjnIBTzLtSlVbGwjbNNiDOpIyG15AwCUl05axZrG53hcG3n0qiY2+0zuRRqMV+tFlWcKUbMWlMUJQZKO4oL1pYsffCm9ELx1dS0maxrwmJUW4tE0DTIALKu0olI86ijhPckuChWRQiwXJTt+YMemQBE4pJHSkiZCiGF4CGEKI5AsKqulqtVm1tag1IyoRhjgCHcYuEABN4TIHDO0m5UFc42R09wFsulTXLFBWOMxTFnnHmLGGj36sQ2nhBCICF5kqksT3zwwXsuWBRrj844kEdjdFlgnDlrBQsUAou1sxiWriqLbn/de4p0HMcZAFRlFUdRHEtggIjWee+cw7Ksm6JYcc5Onjw1m45fevXp6Wz38Sd+cHnnwmh0oBMWtjAEH+l4NJpwxrTS13YPu92MKOhY53lqnSmKoixLY6xSR57pPRKRVrrTyZ0No+tLQsh76WpugkNTBR1hGke9Aa8rt5g2IYQkixKt5+PlcLOfddKwXGIIRVF0utnxU5txsjrYmXHB0zQNHouiRAyMRaVxdWmnO2Ub5yjNvUGpeNqJOGfe0+H1adu2pmPujMeAg814Y7NfLOvGWBVzHQtjEI1DBGDEgLk6MEaEkHTjKJHOuSRV0Qk5HVXl3LYaptXSJJniglVL4yPKOlprLYUsiyp4dCYoiSFgCMQFY5xJxcm2LaKsnZPeUoysQVaHdiPUimMIUaS8DauF4QKyLN083ouzMsuT6XS2WlRRIsqizvOccwEAxlhigIGk4gzIOQoAzJOKuE5kubDBkzfIbhFs7vbTvB/HuRRKAwJjEgOtltXssAqIUnIuuUpE1lFRLELwSRa1kt1CiCiKlsUKCEJAAhCC9YaRrb3WotdPnA1CVsuZfRt6qnwJIDXn/N2tKIyB1FwpzgWP44gBwxgLMovdFRcQZ2Lr+GAyXjaVz/IgJA8I3gcheaojrZV0ziOGFgxeLVdPP/PHZTXbOrbZVNVsOmaMPvnoTxaV31zfzNLua6+9/vJLL588tTEcdrz3s/l8NBrVVS01FwJGo8PBYO3HfuwzOzs73/zeVyara8tJ4ZwvptXaZrYYr5AAOCtXhgKlScdbNI3tDboIOF/M6romghbpgxSSJM7y3DsPALP5bD4pMaDSfLjer+tKaYEYVCSSJMYQEClOFCK1kA6AbUpfFY3QTCmhlCqKigmIsygxYu1YYsqwXBQ6Et5jG4hXS2dqv5paqbi3WEyRc8h7sWuCjpV3WK1MnCoiCB6LhfEO045WKpLaCe+alSsmxllkHOJUCsGE4G0mUywMIZNbmam94DyOk0jbEmwL6cSJVEp4H2wTmrry3ulYSREWs5oxqFaujXxCQB0JIZiUajEtnMHWRZ1FAFCSSykYAyEYIbXSUYwxIbnSnACapmkLk/NxUa1c8NTbiIbrgzTNlJJJEi8WC2ObKC69CzcnxPhAirG0q+JcujIsp+aWrRmIBZ0Irqiqq2plkjj23teF9S5QAIdIdWgKxwmCoyjiXPKyrIuViWIeJzGTLEq1igMDJqQQQqAPkjMpo9lk2VtPrEXbhDbWQgJTe2ByOWusCTd12HtriZCsWjouWbcfNbXxIfR6nXse3JbRNWt9cGhsM1jrTEYL55yQmjEWPJnGuXHo9kgyxoUUSvG965dff/OF7z3+tcYstra3CMNyOe90slW92tsZ3X77Hd1O75lnnjn31vl+P8lyTQBNXZdVhYiC8bYoMxyuMV4ejkYHB1dMWHIhggsUyDdUzCvrXJaHTpbNpgvfuLVhp2maOImUUtaaumi8D3maOmcZcMkVF4wDU4r1e5kSvK6Mq91sPAtIaa6SXDPGnAvWGrAsSVSaaSllXTUu+DhVq2VtrM06URIpLdEZ186RjWIBAaplPdxaty4moDTVprbLUQMEQjDeHqMIq0VTlKazFudd3R1EjIlqZevCK8UxwMI2FKZpVwVH88PKVAEIokx6E1Qk2mCsqZ0ziHGoi7quQlM6zsvuIO4PI9sEpTl6qp01dSAioXhVuHLp0CMhEwpCwKbyjLM2CBGpRA8taqdjHjzZhhAh6SsumFLCueAd6pitbfScdYyz9hgpV7VzvmU0eEtRIgjB+7BcrIgwzZOmMTrSvUE83i9uJbY7h3XholhkeeoaKgvTPigU8wHn41JGzNS+KnytrTehXllCkIJ5fwMLB0gSba0DJAbMVB5QFPPV2maOgG2OIRk3lc+6mjEuBQPGMGBvPTKlLxbOOwQARPAOGWNrm90Q3GJSC81PntnEQAd706pqyqVttydGxebWxm23H1/MF03lilXV7aXWGc6Z844LJhQHoqb0C19JoWQIwjTND5/83je/+6/Rr0xTLeZTHStrmsMRHB4eUgDnZ3XVXLlyBT0uFmq5JOdcy3s5EhrlXEgxXx48+/zjHn2WxsX+cjGbLaaGAtVFPVjrrOYVeMo6qWDMGiMlzzvxcj7XSsVJmibxYrZyTQhI6O3CeimFkFxLjJM4OJ5E2aCXjUeza5eK9ROyt5YtZkWxrITiaRKZxlobGFhnvZRcJ9KtQlN5paSRjnOB1jXOxnFcFzUQJrkk5tY2soAhy1IVQwhYzg0XHD1ywYBIaNFW8XSkgWFdmPbyRZH0FoplPa6Xm7JjSm/Ko70xjnhdBVcH8ph3YgbkXUg6KksTrTz6sJoYztnaRhJFytRuOTcYKDjkgiWZasFla0KnlzSlbTuO0o5qClfMLQAjZYOn4BERlOZRKohASN6UnmKGAZ1BFXkfXEsS5pzZOnhLdelUJKJYaU2MU7Vwy6QEwLKwSaa5gF63x2ESKdHYcKTbBEBIq6ktOXR7wG+ZhcQlr1duMW44Z8GTEMwCeI8MQEecPN2cb2fr0BSuriwnHsVSR7zdF6YHRV26wUYqJCglm8pFsUDw2bDTGcQH1xYMIEq091TM7Q04CKNEDDbSqqpWiwYDOW+FEBvHOquVWEwqWwcmGCJOJ7Nut4OBGCepxeFoyoAlWRQlmlgQkheLWioKAaXzlpG2zlZl4bzdHA6uXl26xjkbpWkCxIInrfT+9euT6XQxX0Y6jmPNbtZ+iRCRc66U5FIY00ynU2tNt9eTQgNw2wQK5Gwoi4ozsVo0AORdGO0vvMPNE5120EtZFNZa54NzldaSgFZLl6Ryc2tomlpLHekozzoA4K2fDyxjUCxrQjIGpSetvam8c9Q246PmwEFFHACscbVoOp2OEmJVrJTUnAvgXitR1U0SR0qrFrLoD2NOtJgY1wQtOXCQkXCLEBy26BABhECR5kxAwEBIwdFot7ip/80ZeE+cASLVZUBspObOsmJu4jiKtM4yX8ysrUNT+hb5ASRvEZHQU+Fty/toCm/rILXIukoo3lvLvFkKxZ0LSjFnMHhqpQR1zJXknINrAiL1h4kRLvgwn62IIE10nCipRJTogKFYGPTUXYsxAAGVi0bFYn7YNFlYP5ZORlNnsVWthBviH8EfaXrOp1Ur+5x2pFSiqb2pQ9ZVRFTOrLEgJcu6Kk5iIpqNy7yjlBZ16eqird1SXbg4kxTI1IGQnEOh2GrR9AaxkKI70ICMMSyKSirRG8SLaW0b55p3TPsyTdi/Nm3n2gSPu5fGUSq7/aw/6ASPk7pATxigLMuqKttpEnVhrcVgg45FmiWNsZwJ03hXB51KySAIwRKp41T2e5nUXGm5WqzKUEMQWZKNDyedTrZcLY0xWisGYEyjlGzRCe+9EELHWggOAFGktYrGh9OmDFzyctUQUSsIvJyVKhZJJnUUITaMoXc0G5e9QZqmqRCiLKu69HEirPMYyFQ+SVXe6cwmVV2btcGwqZr5fAHAt09szueL6X6Z5Epqnnej0V7RJohCc8aY95gpKaW01tWFMU1wNvR7GSJZawlRKcE4lwIQUZJgjEklVSSmo8ZWoeVReYNccCCoVtbUvjuMhltdIavZYe0t2iZ4g63UhfNHmB0SlEsHDJJUqoivZgYDAICQjPOVVDzN9caxvFg0s3HjTYhiwQVDJCFY8NQUTiiedZSKhTWBC55kOs5Ep5cupmXSUdXSAUDaVaby7TB0Z8gZH8VCpyJOVLfXmfpFU7q8J41xzoYoioDZqqw63c5iUjPGgsPDg9IZZKC9C96TkoIzefWteVO7gCBuTD6/dSGC1HxtMyUkKUVw6AkjLZDApegdCsmiROtIBe+zns46EWfSVksioEAA4C0W9mgvV4olHaW0WM7twbVisOWzPCZSQkFTmuH6UA7k9cvLuvDwrkVQLCzc6MT1dcg6sXPWGi4VTzu6LlxVuhAQA3X6sZAMEbJcIcrFrGF8xgUvVk0xt8GiDySBhYCNc+ViPq2q1dWr1yOtldb6iOfDiMgHL4TQWhNSU5nZbBnHKk2TpjF1adJMa50rJayzVWm9w8XMCu44Z03t01zrSHQHSb/fZ5xlaQrAl6tFCME0ZjkvlvOqqWzezRhwdmPEghAs6+kkja11zgbBaDGbjw8Xy1ktNK9tsCZ4h1JxIVhwhIGU4OjQeGwlK+rYcuGOZoEgmcasgITgtnHOhjRLTNOAEEpJqZUz1lgnRMuCPZLwBoBy5QAgGAwWm0TYxlMAW3meyvYLyPrR8TM9U/rJ9VW5dIxDW+uJc5V3IwxULBwAMM4IaT5qXBOSjnYWTeGk4sCgqYJtgtRcay5kCwKSECxJ5caJ/NjJzdpWSKgizrisV64uXaejkiy1xtWlF4oppUzthWJEuFws6sKaJiynNVc8OGuNA8bIU9PUeS8ytSciKZhlMJtZJRgcaTJ7IUAK3unKtKOiKKpWTbm0q/ptE2QAkdZVWRWVtSY4i+PrFWNH82mcAVcVjJecMxlzKRkGW5auPRhvzSuSVPQHWeOcNSHL1XzcCM6CI0s+5ooJHnwgoqSjQiDX3DiS3u0IAAAuEHp0DhArDMQ4tHxbRAGMEaFzICTLe3GSxpPRwluSipZTk6SKJ7wsjVSKt8Dw/sGucbV3Pk8yjAmRmAiW6qyTtvoo1jjvHQZqGxE550kSC851pIERMWKMVaUJofYGRSySXA+3ulvH1xiHNEukUG2/LxElqKuqZoKUls4Za72zznvvPTETdCwEZ1GitVZlUfQ6XSmj3Wt7i0lj6lDbAPxoOlU5t0zACiwGQkmmckCQdHS3nzAgThxbKmpA9AiBkkQjkjE+iYkxYYzr5HmapqPRyDm/vr5++k6cjcrpQdk6ABcMGEjFVSIYg/HBqlk5DMQ4oyN9X/QO+2sdIChX0ygSSUcluQoeGWNpV5smBItKcmeCM6FkRAzQYzu4yhlsMzxvMVgkACEhBBoMcyap2+8gBtNY7zwH1nLCm9JrzrPNDBghUmeQDNa608NlXTWItJwZLlgUi2Lp+sOo/ahZHgnOiZjsynK58DYkqQqeAlK3F1kbfAjFspYR946EZEBca00ZKcXqAySg4AgAnMXxwSJJlbNHUyfwprB/Gy9RO/GKrENTeQasZdG9bf0MOGfO4HJVe48ArDeIuWhC4E3VAEAXYx2L8eGMcTbc7PR6ODks6sJ6h+/rBog0m1RxLntrMRC09QEhuY4FBvQeOWctM6+qmigW5dJVhS0XNkmkjuRsVMmXX3pxc+PE+QtvvPnma0GUvW4PgOV5zgUIJRbzBTq0jfU+mMYgYCftKCU4B0SK4zhNM2tNXdfCg+Aqy2LBZb2a6EScPLM5WOt1ex0bjJR8Nps547kQAIAsCA3Cce+DlBwJvEfOhNI8eETPVqUHxrI8YwyiKCvLIvgQp1IpjksyDlvrNKVnklFoJSzAN8g5Y0BJlJpQ61iHEBrjgicuBCE1tWWcOeObxiZpbCvrvAcApZVUqtfrVkubZlnwB9PDUkU870WtjruKBACtZtY1oTOMsq6uCufq4C0eXFu4dR9FWkjW1MF7CkhC8mJRCMGFYJ6gqXyrc4+OirmVkvWHSVO5unA3v1YCEJwxIgykI4kMy6KczxaIFMWSCJrCcQ6Mg3e4mBYq5t1hMlzv5Z2uq7BY1gBQlyHJBCFEmjeV947664ngvFgaREIP3bWoXNhi6azDKJGDzcw0Ns2SujZNZYVCa7AqqhAC56CV2jrRQ6T5pKhL375+8BTcuzUQ3rtCAHh3GAU6Fmmu5qPGLx0AcAHFslKRKFcNegyevAtScyZY2lFJqriU3UESJ9LUrljaNiF59xt5qkvfWwPZtvx6DK0Mj0UiyLs64lwKWZtGcGaa0JROSN40XqfSuyD/p3/132xubo0nh2W5KzRtne1mWWoaS8jKsl4tCkDOOUgp0zwmBkmqkyhijJVlyQTknbSpWVl7BrwurLdYF40zIclVby0frA9MU5vGWAZJnAI1iCilIjJIKLWM06gqGgYEHBmAToSpKAQKHmeHdVOGu+892wQzmS8qG7r9VEdyVU+5Q4SjyJICAQEjcHU4Ehs1WBcVjzE46xxmmcaY4iRqVpV3mHeS7jD3wdmqSZK4Lq0QFRAP3k8m8+l0fvzE9saJDvDQfh9McDRYrSzcmENoCo+Oer2UdaFpXFP4iS+2T/eGx9JyYcuFK+ZWChbcEYn4RjM1aMFCIPSUpVpLdvNsbyMEwZnkLCC4yu9fnnLJ4kSqWMSZ1Fxa9KbwzoYskYRkas+l9CaQ501hy6piDEwVopjbliXB4I47T45HhyHgdFx6F+ZTyyXr9DQJJiJOJgSL83HVX8vRU720SCglt00IntpQTWrFkIDRsZO96biYTwwAWIPvtcK/yBIMBEJoghLMBRKSqZhzcTTFMe3oqnABKU1lf5Alqa7qyju/ttmfTqcy5fkw2T0/f9+pkehovl9rKZgjAayuPWPABVOaN5Vv6pB1AnDqdjMGamc5yXqq048Fk4Qgd6+fK6qD6XTsXJXl3YDWBtGY2tRhfDAloKauvce8kwIjKaVUwlijlEyzJISwKpbOOaW0FLKY14tJ2dSBcdg81ldKFsWqHfHrnJVCVaUpixUwJrgQnAckAEwyHUVaCFHXdZsiSS1NFVTEGaeqbmSMNvg4VyoWXPLhiXT3rSXcHOhENwC7NmjhrO0HWDVzixQ8MSacDd5WLBAilauasqCUIiIhRONsWVZSCO+8s1ZGwAWleRKn5XLalEsX5YqQvKe2cAsAtgm2CaEJPqA/6qYAH1x/Pcu6uuiYxdh4E961RUrBolgYg8GjKYKpQmPfMYExtCrFAABgmhApEQQKyeJIpUni60Jy8AG8RR8wTmQUK2f8dLzgjJdFnWQRYrOa28Yio1brknHOsiybjpaTcYMI4IBL313TpmEEYD2Ox7U3aB1WjQOAQV+3/YBIhCE455SU1rkoVVvHOkqwo9f5n79ixTdOZEmu69pWS1vMnXGogelYmDpUK9eUTmmRdmSbC8Vx5NET+TRLGp82dUPhBjT7fquqfMN8rEWSCsZkVXkViTghY71tQpwKpYT33nurYqG0cBaReUKS1pqmaZxzXIi1tQGGMB8vTOObys4nZZrEWmvOfRzHxBCAjgbUOU9ITdMY49Is4SmvbWUaY5pAAIONtNfvzqZza62UsmkaYEwJhR5W89pUQWouBPOeolgIIVoFaCllkrJisSJ0xKDXzxhn1hqQTAqed1MlVdPUx49vXz+3JADBICBIyb1/x3fSNiYoJbjgLGZSSQx1Xfq1tYgx1pTOGh8nkSCGATmQrSxpGUIgTVmeFEVhjLU2SMXzng4AzqNSnHPWVG9nhI05Ml+lWKevGbA40mkaaxWZarps3mHcAK2PHkmmNu8cPvreaEIIpmMuJQse69IKpqqqaUt41qAPpPo8z/PVspweLoExb6nNOjjnQDhY000dDg73lVJJlBIuW6tlDLhkcRytJu7mtSoK6284nrdEAQjBWzIs2Dqsb/UZZ4RBR7rXz5YLa/5SJ0Dj0LkwyGU+1N4HU4e9yytncDW33mA7PMV7DA6rlSsWc7NppeKredPU15xrlRBE2lO+RH+jTPGuz4EEIZD3pBRTKJTmZeGAmI55tXIpwLyurAnHTveEYsWisY0jAhnQx7GO4g3rTN7JHTlnvanrclkRkam9imQrDIeMENEYAwhN3dSlbbkcUjrGwRprLNLRXEGazRZSQbfXa5qmWDVZmtTGNKX1BoMnIcEYX1ch5FLp0JYUtJY6ivpr2WxcMABjbFM7zpmMIh3LEEIcRUSwnC85Z0iARLe03xytEGg2Lpu62TjV4ZxLJaUQUayCp+BQKJ7kWkrOGDDOGxcElzYYMo6ANbW97Y6TpjGHB2Mi6K9nwVNRNuiJcyAAek8MygWLUsUAFpPG2hDF8tZRCbcuj1TV7/GK9kUYaMGNR8bg5uYtFReKOxvmo6aYWWcDBeKcqYhjQ86id8E7rIuQdnS3H03HK85ZFHFjmPewfixrKn/i5NZqUU9nNQDEqUy7mnFwNgREuBF63ZpdNjf81trgHTIGM7lIsljGvKoqZ0O3E41M/T/H8t9eB3uVMWHjRNZdS+MU9q8UtvFSi6SrAMnUIXgKnqTiy2mNgfobERErl845yntKq0hpY8vwjsDynct6tCvkDITmnEFVhrSruv1kOW9UJDAgIu900+WiaPXqAEASYRRHvX6vMbVUgoPo94Wpw2hvBgggWAgBfXDOIkPEAEAU2sGA4DwGR8EHIuk9Bo9EIBUngKqoBsNeGmemcZwx70JZGFPZth2WEITkKqIjDrZgrewEZ2xtvQeAB7urqrAAYJ1B0oLzsmiiKGKMHezOw83Rly39GABuAMME4B2WC+ysOy5YwiD4wDmPEhmMB8a6a6lUcrUsgg8egJRCJOeClKJpzGQyiSIdfFCR6PXzyahgjAnFCAlvEHSFYC1GlGaq00+FZMtFXSxMsbQ6EnlXv2+uBgCBiL3f/UjABROB3XyC81gULomljjl6XM1t2w4mFKiIMwPF0ocwJU/GBdkEIlvWQQkmJQcGZenSrhoM8yROz725FwJJwdKOHm50Dvbm5dw6E+DGyXPrEF8b8FblY8FYVfiAdS6iFhDLuvFo/Jd0ACKYj42pfNKp+utxr597j3XpOWdRIuJUF3MDBGmqC9nUhUsyqZSKE0VAcaKrwhRTG9yPOn8IQAnGOAueqsJHsSCkpgpKc0SKU8V54JyHQHEig2PAQBKhc8Z567zlQnsKwKDb63T6eVOZ4DCOYwJSWntvAwXGgBApYCvpmnXV+vqwO8ga00z0YrS3aBmqwWGS2tHhpKoqU4fSWCF51o2tdS21S0jW7cdxEhljOOc6ipSUAMA52zq2sZjXUvK0q9fW+gGtNQ4ArLVccKn5zT3raATBzfOdMQJinAnJqpWLEhlp9AGVklKK/rBDRHGk22lNzgUbyDskomrlBhsRA3DB95Ju3s10FKdxur8zbyrPbxgFE4zCTREA8B5DCKY5angNlmrrfYM/AiH5sx5Isyjv8PGkUIK30bmxyCmkuSLNcOWISApORxiRWBbOLVFxhgSN9YEQAFygsvTt7rCcmV6nM58v6tpsbmVJEtXBGGvLpQ3uPefYLeEE3UyuACQ7qqabxutIMGBVYX6E/f25iwCqKlRVsFXob3SU5tWKmtJbE7KOBgZ16bOOA4DgqJhbYi7OFBdMKlGX5kdbv2AMiQYD3RisG+8cJSm3DqejMusqnco0TcvlvCobRGxn+wKA9CEsVyvjGuvs5uZmZcuqbob99dvvOH24P716aS8QMgAuOAECIyFEvbLlrLEWdSJOnj6xubnRuFIqvr6x1tRuOatUxIGDaUxd14Rkax8C9Yc5ExAlkoiZxjAOeZ61jWhxnERRZKxp6roz6HU6neq2ejqZB4+9Xn86mzS1z7ux9z7S0fFT66vxrmkCABw/OSxXZjYr4GhSOTEGnDMu+XJski4KyUwdpPKcs0E/QQzz+VIqEScREVWTxmKQijWVV1JKKU1jyqKoqkqrqCiKsmzqpY0yKSXngqmI2zrczAKtCZPDAm4RAgMA9yO/pPddHGBzY73TzY05p6UCTrNZ45Gk4ozxprKeCAikAiGYdzQYpnXtfSCtOXNEAJy/Lc3dJoroiJBlWRbFsjdM8jybLXlZVu+1fnhPMH1zMcaWK9fJlVt6n2Cex+j/khDQu1axclU9a4uGrgnoqd3+CcB7FJxziYjUyigFi0KyONVCmUiJpnqfD5HHUijR1C5O9GJetlIPTe3jVDIA04TYBcZYsbRJGqJYVoW1BoFA9jvb3ob9/YPNrY29vVGss6tXDvV9Wkd6PBvXSye4CwT3P3zHwWg83l9sbq6Z1So42t7qbG6v6ZhX1ZSpoBNKBrFOB9evQFN624SyMKfPHCurglh9/NSm4vpwf+S8LxcNF1wo1svVYr401gw3ZFsBZhwqs5wtD3WqtvPBbFLsH+5GOrJNmNuKArlmuZw7AaA4c0iKsyzRsxkAAAPY2krqJiwWVgIjIFeH2X4tJKeIR4kej0rTOCFYmmdKcYA4UsF5n8RJ/+zgyrn9zWNrUY+KZVOtjOrGdWnRIQVoll5yFinuHL5rD3/fOeWaM0/05wHlAADrg2iw1r906fDSxd3bzm4O19f7/ej8m7sBiQHce//pg/2RVgLAMYBI87WNzFv9kz/16Wefee6FFy8jgW9nht74GC5QL1dl6WobkihbHw6lvJSm+ur5fWdpWdgf+XHevUxAAJi1XLQljA8a8Z4YTrB3BFHvvhSCI5F/z7UggOAp3HI1b24i3oS8H7kxmirkmWQBVhZHV4pI8mNbWVFY3dPeoCdqTDhz+8A0cH1vVjU+IuKcJZ300bvvmM9nB9dHiJj3knJlAmKwuJiukkQuZ8XaenfQj01UkfFSxUyKaDyB2WwmhLAasyypq8Y0Bi0CABJIzWezeZKpY6f6HCUxQCQucFHM/dRHSbSxPdSCe4eciayjI6XmsxoJjG0Gwx6XcHh93O/34jRWPiCi9xg8lVVZV9Y0fsrnnW7W7XZCQGtdFMVta3K3l4SAZVkN1jOG/PD6wtQBAJQU7T58cLC8eQXTVPZ6XYBitbBS84SxNssJAUNgRFCVBoDVlbdmqWNRFa5eOUQ4cTodH045595ZafmyKk3lshSdcTc3e4/kzfunsO9d9i9i+wCcwWJh63qcZVpxSNP00iuXru8xDmw4SIiCkqqq7HTRtJa0LFwcuxDsm6+/laUZA4gj7YMBYEIIBkd7e2MC55wFnM8XnW7iXIAAa1vppTfnf8HP/2ctAnhvdvMjrB8APL5PBZcBSM78+9d2YTm3YmnbVJcLJjWT5qgejwRJqvNe5KxfLYwxoVzWxhIACMGkYCriaZJGUZQkmY5ncRx1ep3V8vpsbJKuqivnHapIVGXd623GEe/1uvLUbdtVWQ+KTlnU8/GKaLV9cpCnGRION7um8hhIRmK5XG1ur6edfDpaaC1EpozxTeOjVJw5eypO4r3ruy644LGpHDqigB5gOlkKxUKgcuWiuGacMc7STmyNs8Z7dIwDF9zWoeINY2y5KIQQaaaBwSDJ8kGHM7Zr9jnnJ06cnE/q5dRIwQioLSJheHsHDh4X82K1agAgTkXjkAsWPBFScIgBZcSjSEUxCc654DXzQvJYS++BMaEjSLNcR7ioS/REgdWl+wtt43/ZlSZSSzFbmXtOH/eurus6TrSQspNFSZpNJ7NTJ89c25nQtOEMlOYK+Onbj0/Hs6IoO51cSd7OaFZSRFq2HBMAMA5bC2vqerFYVIW7cmnMOLTbcLcTOx/q2v2v93fdut73+t3kT0jOWh6udz7c8AfBmY5EQPIueA9SyiznSgupeJxmTVMEhxSIM6YUL1cOgGnJWw6VrcPB9fHB/rQqa615HEfO2SgWeUeRYNaE4BADrazJ8pUUsL62Lg8PrhdFFWule9IUNoqijbXhsL82mY4319clk7PZ0roAAKa2QZCpLQcmFC9X3jlUFd+5OOqtZU1lVCRdCE3lGYEP1FjUiVwtS+9RR7xcNQSgI5FmsdKCgNo/I04l5yxJoiROTWOJYDmrheJxVBNimmV5N6uKajQaO+cFZwTABUMPAJDE2joE8ADgHZUrAwSRFsGhNUFHouUOEID3wQdgxDq9TClVVbWQvK68EGx/d8wYsyYIIU5219GVTe1n08X4YPW+ETP/s4PmH71uLeMowR+4/+7BoPv1bz25vbVBFC5eunTfffd84QufffbZZwlhbdAty+rsmdMH+xMteZqqXr9z//33TUaTw8PRlStXs1QhMSLgnCklGD+SLWstzCPVtS2WJRLM529HPmdu214syivXRpIzKVgIRwM8keBdpLObI4JaYigDkJJLxW0TjjTwWauIBkrJdoZ5O+wDEQlIcCGVPGrpBWBc3jIyGjgwxkAJBgC9Xnc6mQXEKGmbhhkTRzPlBOetSqQQAgmlUqNDa42VQvZ7vc31pBUicdYBIyKs66pqqvm0IqKged7zGrWUAhhgIG8RibxFAFjOiyjiHKby4PqhMyHvZBiQc7DGTMZjYHR4OD52fCvvxgg4Xyy1UnVlBPNSyrqx4KhxgQB8HS5e3O9NozgV3fXEu1AVnhMEIgzEOVstbFM6rYVpQhQL2wQlpXPBGm/q0KwcF0xoAcS01kJIDFQVTigu5aqqas4EA7ZaNtVqaSrPGPhAdKMzNU0jrBzUAACeqGy84EwKXhU+MAqSS8mU4gAQPNaVt01IskQpqMoGAxJSXXgVi2ppOWdV2cQ6jeOqrhpn3ftaPwBoxUMA/+eyYd651gb//9beK9jS7DoPW2unP510z419O01PQA8GOYNiAEiKlF1FiaKrRFIlvdhlyUF6ssqhXGXLtt5cKtm0bD/Idknlsk1RiZQt0ZYpUSIAkgAIAiQGE7ondbrdN5/0p53W8sM+t6cngXjwfug+96/znz/stML3fassczk776yPgXg0yL784z966dKlr3/996uqmGxMbt26vb9/9ed//he3tnamG9Nbt1795V/+ZaX0pb2JMfrS/u7GdPzFL3yxKIrf+H//+cMHj/b2tg6PZwBQ5tn+5Su9fWu+6OhJ34OZiEeVRgRrKS+k0hIQiiK7tDtChCIvu7YDhDzPAdFai4Cp7kmqfSIQjTHeu6ZtbW+zzIxGQ0SZ5HCEQBQCEZVSiRElEOumns9mxDwej3d3d5VWAoUQIqJ8WzYz9V2m63r18OCgLMsQ/HRz8/Ll63lRSin63gKz1rqzlomlkkqqGKMxBohPjx9lOt/Y2Lp27ZpADQB93wqJRLHt6rPzU+8edK0nBu9DjKGsir4PZye9d1EqVFoMJ4VSgomqqlJsucrycVWt6nqyUZ4frSh68n53e/rRjzxPFG6/eddF37fO22iMAUYfCJ9YLiIxIqMGbZSQYryZMXNWZCrXUoK14dTVi1OLAmIgJpASg6MYKHgSCplBKXDOr1ZNCD44QgTXh7bGwUgCiK61fePKgXZdDJGVAOsp+V5pVQcAIwUAu8hAbAwqJR5XMUsa2UQ8GBuTSW0UAJhMouByoH0fq0GeVK6VwuPjk7btbRuTEiQAZEoggI8UGQRAbuR4XCXZvMgkEAUKQA4U1sIkAqUUScxdCJE4GUKI3Z1NIVjL40RTzIvs67/7O1lebEyqN958I2lW3r/72n/1V//a4eHhlStXjo6OxsPJwcGB0pjnhijeunXrrbtvAYPrw2rRTybTzY3hxnCQFYUPfjSqiiIzWTaoquOj47bti0JPJpOyLJ3zSqmsyLRSPoTxZDTd3GCirrXMZDKzt7tXlKVzrsjzdNtCyFQNUUjZdd3R0dHJ8XGe55ubm6PRSKxniRBSChR0EQrwzsejeHJy4r3f3d29du3acDiUUkopO88hxkQgSVTpUZUvZrNHDx/2vUXE4WBQ5GVmcimVEoaInHMCpDI6xth1tu96bXTXWmdDDL2Wbd+GZrUABBd6IiIOzORddCEKjUpgW7u28dPtMit0OYzL80gRxpt5NcgFolJxb29HCZCZyfOi6q1FCrqQOtN1U082JnmRS4X7+7tE9PDBMWWQZdq58OFPXN6/vJMZw4y268uyMsasmmU1KKXGtu04gpQmywsUoLV58/U7f/CN153zHFlKERxFT0rLGNB1TmkhhaTI7coRgTFqNM7ms6ZvQ5b75WLZ9+3GZsUEWRYyKRHFtRvbUojFYjUejZqVReKi0BvTYcpmKK2IyBMk9jRKYKYY43CjMMYIxBgpM1mMlOVaCKyXXTXIVss+y7X3LjPG5A4Ih0PI82xjNDAmU0oy80Ux+hQylckCUFJoo5nJOU9E2uiqrJL+LSKiQKUUInrbn58dmyy7fOVynudd10mplVJf+KEf6rq2aVpmfnD/4e3btxDx8PCRde7KlauX9i8Jidb2kfzW5nbv+jdeu5/l2dWn9rY2txBFcDHEGKLf2tpO5oVSMsSglADgwaACGNarZjQcsSBmrpTMjIkxamOWy/tEQaAxmRlUZcwzpUzCeMcYk/SxECgQmMn6XihBFBeLJSAjCiWl1loI6XyftAsYwPa9VCJEYCCi2PVdCCHGANL0zterVdt1SRdaI+RGr7knwOfnZ03jQqCu60IIeZY571ZNA0LESCF4H3xmsr5ZSWTv4xzmDw8Ojo+PEYCAets5541RILhvgslk3YayUsMNrZUhcju7mxRPk/CE7bqsMCYzBw8e4s/+uR8tq6rI87ZtY6Sz0zOVyc3pRllWUgqtTd/31llmVlJpowEAGEOIUkopRNu13ntnvRRqsVgopYzRq1Wdm7zvnTFGSpnnuZTy3t0DZhqNBwnlu7m14Ww8eHAYQ2SCwbAs8mJQVWfzs65zwfsYeDQpULARqqutFFgNB5kusizLTHF2ejoaj0ejEQJmWZYK2x8cHCDC5tZ2ZjKmtWbvql6cnB67YLOJ7tq+a3qtMwFydr5MIhQxkjFCahEDX7++qbU5P5k9vLu8dmNrWI739/eJWClZFIW19uTkdLVabm5uTqfTpChTVVVVVTHGk5OTw8PDGOMzzzxTlpUxmffOWmuMEULU9erBgwd93+/u7OZFHmNMZCMAiDFaa/u+b9tusZgPh8PhcEQUlVQhBu99DCFVDes765wn4jzPhqOKiYnJGGOtDT4KgUopYoohMkci2trZTulFa51SWistpFhn3RHrfqaVLsrCO9/1nVb60u61pNO2WCxSgrIc6jRd67pO9VcG5aTrOu89M+VFAQCL1VnXdQKFkIKIsixL2wMiJqeHiJiRKIYYgk/6+xAcBb8OEq0BASgB0VnvnFdS8oW3zAxJvNBajyi0Tp4GJMQeMYXITIwCBUKM7D0lGQEpMc9lRC4KA0BKpxIWoI0wmYmR+saqrZ1plmVt2+pMKpBlWRqVRScOZydt26aHt84JFMZoISWF2DRd1zptpDE6vQghZPCxaVptFDDEGE1mnPVKySwzm9PNra3tra0pxYhCxDxmWbdc1PWqF4gusBSCmeumadu+t13fh9Eko8jOeaVllmfBBGDQShd5URRl8EFKKVAggBBrYzR4jyiYKYZASnkXhRTJScrzXJPqfcfEIZCzLQB4F8bTMgTqWleUWd/ZduVjjEoxEY3GZjAYChCz2RwApBRN04QQuq4FgK7rz8/P0zLvnDs7O1NKpT+994eHh2kChOC7rkMUUkrvXdL4Pzs/r1crIlZKRYprcKHz3gcE1Jlsmrqpax9C3zlEUEo4F1KCLyGfEJAoLubLGIkiJdM6RhYIUonEQdVaAoBWmohms1lT98QwGQ8iRdsHKaVSoutbpWVemOCj7b2Q4uRoiQDeR+dcCBERy8okjQapQAhsWy/gRCqRZWq56nKjrXVCovMhFaeJREr2WSaTQMNF1hB7G6QAKYTzkZOKW2DnKYFPhQAiEAIZUl1dTtQ8gHXcAAUmRxY4ovDMECMRg0AEhHcjbwHkhVSztdE66uvIyHkhGYAijDdMUajZ6cK2Uf3Ov/pOXpjz41VWKq3V/LQRQphMogBi4gghhBAjQhK6gRjI25B0aUyhUsqmKLNm2cdAOheuiyaX2thIpIxoZde1/enpeep+7z0gxBARcXHeuj6aXG5uDbMse3Dv2HZhslXsXZ4Cku1spBgDpTJoTOB6b2SQwi+X86ZpYox93wkpM2MWiwUAdF0HAKvVSgj0joQUeZ6HYLu+FRJr3+tMMoP3RJG8S0Yw9q2XQkTP2ghrXZ4XXRvrxt+/cywlaiUQQQgpBMZIMQZjTFM3kYhiFEJkWeZD8DYQsLPBGDw8PGNGrRQzuxAQIDMqy5T3ngEEQl3bEElKyUwxJnTFWvVtWGXM1nuSApveGy1zLTobiAHXxELOjSyUqWvbuZBcsaST83bRWgZpY2Qez2ZEcHi08IGYeVn3APwYOcKUSoMiMxDx49MvilwxACwby8wAqCQKBBcIAVEAIvpASvQCMRARv43FAvBK4lpv/2Jk8kVY6WKsPpFUeefwveBPMnxQ3uWJ46lQy/t8hdf/KSUGQ6W06NtQrwID5JmQiH0XVnMXIqvVee3zfHHSTLcrVWhkjt63ziGic9F2YTAulFTWOhsDEoRAFDlGZmLmJNUCQNjWAZiZuO+iVCLLZDHIE9R5teiOHiwYYDjOgSMKQZGUVhQTqpFWRas21cZWuZy3plST6aDvLcUognDRHz6YJ9nhxczm2Vwq1XfW+qiEQEREUErWrQUAKUSSLV2viAKLTDGzD5Rl0hIVA8XMwbOUmJUSAISEotTExMCbO8ONjQmibFvXW+ptrQQm3N0TvQuFViFSigKliiCps9fdjMDv6ZLU90+EZ97TkxdtvuwfDxcG6Gzo7Xu6mOJwgEQUPjgLlaL+pycLadRj4sH7ABniH5XKukAdurdzYGlo8pVL48Oji5TVO2FO73tjT6KMPqhdv7xZDaq37j7q+v8fMhWRubdBRxkDayUZohRY5Go5c3XXpjCecj6G2PpIbW89xa53wECBbE8MYIxAAOeCbWO4iPxplYrHQHQUPDEABZuqIThLDACRlVRam7punHVdE2wXhcRQRJPrLDPOueDXCo/MMD9tlZZXr1/av4KHx4eL5Tw3ucmyPtrJeOP04CDtccGG1r6NyHdvh+O9kiJECvROiklk365D4NZHEMDITIAIxTQfjLIQolZ6e2dnPps/vH+KApbLZdcE28bJIF+29nEO/8mOa93b97A2UQEAYFRoRDEcFweH83f19A/S9++9kJEIiO49ozYQW+fhiZDiBzUiyJVMc2ljXH3oueuv3X7zfNn/kSf+kW0yNJ/+zKfu3b3/6q0772L2vG97MgfyZCLl8XEEEAhlVZZlmRvdpwnwHgZMnkkm6H1817nwHqChEliVSgi0LrZdSJKKkXi2eAceRNkmxMgc2bUUrEdAZuYIKAABUrVAAJYahUzq20mma3259CRpxjNAJJYILCAS2c4tThu4WB2VxG7lusaNJiylSKql6Udi5PlZMxjNJ5vDp569zBHOT+d913kfiww2Nsp61Vv3gSsVAnzyEzfffPNe0/bev1/yHYABskzmuYwEQBwD1ct+Z2/z8OBsUHWr1cr10WRGKTAZjyb6U5/66Muv3J6dddZ+QDrgnTcAACbTm5uTp2485d13F3VvbWBY1xcEAOa1qapkKqFAF7XY1psGMyTPLyWVkGE0ymJEbnol0EcmZoEoJMbIy6UVAmVCv6a0lFj/SPqshPCBtJFlmRvd+RAzrYw2V69djncftV0fAmkphAAfOXGH0qgSAgViupaU0jrPzFoKRIzMRgoXiYltH1/63qvTzdHl/end+6cCMFkjSooLvai1CcQAzFwYFYlDJIGAQiR7L91/ygFrKQLRG28cFLlkgtIoISDx2YPnCxcIkkZ0Aoc/FptI6dGkoColAkDrolGiGmihZRZCOLaR6MkJo6UgosigIAARCwDJqFGyIGSwglOZMI4gUXrnyLNUmK53UQAGLuojvWPfR4FaqxRRznLVdyFtkiGQySQwN6s+LzJE+eRKYLv48N5Zs+qeurk/Goy07ojqLDN5me1emRbz1eHBIgRmAAGYIGmPqbTM3LZuYzy6duXy7dtvuhAzYwJRCAEAjDEhBEg9KmReqOB9Evxpmtb1oa5rBMxyHYIHktVguDjvHzw4oYDXr15+4879GCkzyl0QpxBACCRad4M2WkuhlLrx9PXFfH7w4OFgONja3n7l1ltFnmmJznslRQjkPSGCUUIpaRmEFKnQslSCIoXAeW6ICJj9WtHAONsPq1xJ0VtPkYUAk6m+9zGy1oJdHFZV3/VCIiKESBQ5KS8IKQKxdSH6qKUYFHndtN975bWnr1/d3to4fHQcIymFCAhMQiAIlIjGKKkEERGRFEJpHXwgACFFknUGgUYIIh6U5Zt3DnvriiJTUghEiMQMiWxExKm0DANnRgspnbMIKCWmN6iVYMBUYzHFixhACMyKgoht6JgACSIAM6eFIyVmyEUEUBrThBRS5Ma0XU8MFJmYMYlmAbhA84U1WkYmWheBBABQArUS1q/dB8XAElFKBKAY2VkqMoWIiQWbKZTMPoLzlIEYVsVy1Ya4NovpYia8PfoB0tUSnC548heCFknbUSlsax8CSYkpdvn43K4OmXEP3nqUF/PBoPKWLHV5mRNGkvwYK5K8Hq0lx3ghIwSvvPrGxmhw80Mf/t7LrzFDJCIiBMhz4xIgizlG6moPgCFSrrQyYnHWKiParhsOB0SAiKtVU1WjEPjWrbuZ0aNqc53Mf+eukrw7YkZEo1WIcZDrj370Y9/+9rdvv36nLPLdfEAMUkgC6GyU61pqjIydi2wjIowKE3zoXBAOKSkiho4ZhBQxUm6MVuVJu0xiZPFClrb3FInSW3CBqqqo6zaGpDF34boCJAcjBMrrnhjG4+GdB0fU+dlwuVjVTe8ZoLMXyg0XVlZljHW+7R4bCesPwYaEN1n3MsJwKBng+HQxnQyfNIF8fLfBphiM1qvmXTSa97eaNrcGRLysm/XfH4C+fnxBJaHI7l+h/AAAMzxJREFUVfsETvGx1RqIQxf7PhKDuBhrkOimWnYXP6EEoiNCBufJEyHApb1pnhfW2qZpELEsy02ZnZyezZeN7l0inUgBj5GS7wbEMqwWtgabpuOTLQROLHLbR3yPeQcAJtNd406PmhvP6hiwbfxoEpzr4SLI8PZrFcKFyMnnBUCEru/Pz2fp+aNbu1BKqbpdv81oGYCICCVqzUpBvbDjzUJJVVUD2ztg7Nowm52jYARwzq/qVZre/Tvt/vWUZkBgIuqtd275nW9/+96Dw6533odk9zjv8cL0fOJsgBTbViaG5Mi+0ymmCABZlhdFwQDWvb87iCECQIzxffHGjy8WGbQUUso0PVarVby4m/eeo5RKuK8/ol2YtYiYF/n3/+4P4Kq83VJgTQp4zzz64Bv5QJYRwMUanXoqHYmR3RMzVmktGCEQVGXxsz/9Y3/pL/3lz33hcywMArf1MnifZUVebsxnZ//L//Q//vW//kveBYB33N+Tox8FSIH+ImLwfW7tfZ3C1bILgbyls+PzYMHWfnG2BCHKIjeZ7Lr1iiUQvA9FkXXW/+k/9TMnJydf/e2vS6myzBRa2hCNFChlb70Q4r3XxQjko+WolFBC5aZwXURWrncCMYToQ2QAJeVoODqdzeD7ot7TDu5DfO2NuzESABijtzanp+eLFBr/oDcQY8B3vqF3rAnMadU3UgjEd/HoEUBrGVz0Ibx39D/5O4kkFEOQAiPxYDCIDPNVA+/XYow/yHiVSmijlAApxNbW1r37R8D8GIz3Lh04KVAK8cF6Du9oIQRjTGZ0+wNHgR5zgP6IexaYXhQxhyeGrxpPt5566uof/4kf/7l/4+c+dPMFQA0XXl012H78vcnG5l/5j/6zX/yzf+6X/ptf+me/8S8eHR7WTfs+d0Pwbs7ID9bWUb8maCMQoa09RVRKdI1XWq5cm1Q4jZYA3DsChLq1f+yHvvhf/Jd/LS+yP/+Lf/YPv/vd4XAEiMQQiEPwUqC176aAcOQA7GwACzHy/LwJMbT1yWCYex+Kga6q8vy4AQApZVEUaQxrLen9vHBmcM4zEQIMq7Lpbe98jDHPcwBILOcPemRr7bt2yHfEmrpWaw0ASgopxLsmgLhwCim+31098TlEUgKts5lSrfNa60KbD7ol5z5Age2dLQaqV00gwBAQkm7g2zbNu+Zj7wKg/QHHhPdeqSQs8ANNAGbmSO8ben5XU1JkWjTWA4AUwl8EDNVf/c//45/66T+xs3stZd4YCJkA1fv+yuWrT//Xf+O//fnf++ZXv/ovf/M3v7KqV8wgpez7zjoLgMykpFJKhRhsb5kZEPq+jzEKIVK+J4QghBBCJFxU+neNnEERQ8QcBArPXpvMaLO3Pz05nmstYugZUQqlVMgz03X9pz718bpZSSU/99nP3L51azgclkUppGVi9j4FMdIDPybqJgdGuEjEG9tV37huZds6CLTexbbxVVkVhYmh11qmN8wXhUzet1nrCUAiaqPFhaUUkjAaMeEH9gwiaoXJzJaIQiaOPzAwcYppRIBUiO3d+1hkSJqK32eHSY0BEME5n26p67qhyT7oy855caFqgQhSiCzPmCgBOZ333l88YAgIQMxpln7fO2D8gdfEVNHwB/nm430G+f1tthRt8369QKDA0ajsT5cMbDJlL1IV6pvf+MbpyemVa0+NRmMpRds0bVMPR5MEBdnZ3W2bdrFYjsfjyWS8XC69DxvT6Re+8MXhcCSlHI/HXdedz84YWUqZEIXj8dg5N18spJR5ls0XC2dtVVVZnlGk1WqVZZkxxjk3GAzOZzPvPTBXVaW1mZ8v0hown82FlKPRcGtn8/j4mInPz862drb3L1159PDw5OTEO//MM8+cnhwXefYzP/tzn/zUp69cu/6v/8yf9LYnAOeDlPKll777t/7W/4yIIYBAGWIQAJE5EjOx66KQslk4AOjqQMSTnaKsqrBBIQQjpNb6QgX+3e8XEZSUMUaBSMSRubd+rZhJlMRRmIne7by83XyIIQAAIMCwyqVEZ10kTl67ViqNrRTofO/pj/v1+48SiaiUfBwbjjFK8f7CLeufvXhUgWC02tvZDiEkiOj5+Wzha14H/ThFyaV6/7XyyR8M8QfwKy5uL4Q/GmkuADIpbYzI70+6QYDpeKCUOjlfPNbuLssqz9re+jwzq2bN7lf/+//xDwdFqfO1NnEIxBw//vFPxhg3ppM8K5h5sVwG75966qn5fB5CKMqcge8/uG+0ufn8zUcPH83n87IqL+1dunv3LjPv7u0abU6Pj/uuv7S/P5/PVqt6NBpeuXLlzbfeCt6PRuPRaBQi/eiXf8I6fXBwQMSXr1zZ29uTlADGkIKYUkiKcXf76fsH9yebl77w2U994hOfPj46eunlF09Pz4qimM0XymRf+vKPw5OogPQB+Dvf+vrf/7u/XDd9lus8V03bEZFAMZmOnXVFqZQumuVDYi6MjJGHhZaRYhd9F3VORS4RU44GFUK4GBwIgAwKAUVCowADF4UJKTIghFYGAIyUSogP8mLhImbCAJ11SomEgEibTaTYtiuBICTS+1GPlRIuUtv077K5n2wSsSyzGGKMfo1SiF6ZDxyyUqzJKLA2vZh9rPIihNB1Xdf16TrEIKVkiCmM/0G/BgACARmcfY/K+Qe0EKKUQXzfWQ0ABGBjTK7tqnfvXZ4YIMvMoKrmq8YHBwDWBSGpGmRt7/veFrls+wgASrJgAt+H1WoGACrLe+ceHR7XdbO1aph5d3e3a/vVajUYzM7Oz2KIRZkR04MHDwFgOBofH580TeN8GAxGZ+czItIm01LVqzXmTOtMSXt0eCKlnp3NpZLexRipafr5vG5bi6jm87P5oh4N+52NrfQMmQGABBIUjuKqaU/Pjs6Oj26/8vLDo9Ovfu2rtutHo9H5+fnzL3z4V//+/zaZTDY2pufnZ1LKvb3977363cloomU23Rw//+Gb3oWub5kgQdKHo6FA0XZzJbONce58HA1zpZUpVJUXfhSY3Hi4sb9/aeut1xDLsiwRwXsfY/QuZHnWta0QEhHquifisiymGxsAs+j7vMiHg1IJdN4FFACwMSx7FzrrHucsE2Yj9ZyWKISIMdXaWdtMROydl4hSiPdYQKAFZgZDwBDeXz08tUjctD0RPWZmEdP3sZq0wkCAALmWu7tb1TAbltOmaY5PziPFJCS8jgdwSsUgAiGAFsIRZVIk1ZjEdZRijaSKkYnWseNIHN+u8/vuFgIB2CzLkn7o+85thSCF4LT/CCEFAkQX+cn0FgDMZ8sYvBGIRua5JqaN6WRjOjb6ETNRZIVWKqG+/JM/MR5PyqKYLxaZMSfn8+OT042NDe8PtDbOuePj00ePHhJzXpRHR4d9b3d2tvu+e+uNe4NBtZzX56eLs/OzybgfVOPZ+bLv+2E1jiG8+frrWZ4T42KxOD466vreB3r1lZe1NlVVXr5ytWk7b0Pb9jHy8dHp3u4CCF6/9fqTTyuE2JpuXrlxfTAYWNeOykxrNR6N2rqZTDeS6u/zzz9/cO+Vull88tMf623tvb9ybe+1Oy8PRsXZ2WyxnKHAsiyVUkppbpmYnLVFUXrvi6IcjspUm7UoCmGgKAomIYSoytFoNLpx44bWOp2eHJW27aQUbdsqrRGwbRvnQp7nVVVtbIxXq5UQYmM6+sgLz6ainKn434bSKBOXShJR13WRKDM5AGithJAh+DzLUmBTKYXrjAcm32mjaZI7IqRgDvWqllJONzeCD94HeNtMYgAUUggUABBCqOu+KEyRZyFwjHG6ubG7Pd3fmYQQTKaCDyGwlGgyrbU6PasLI/e2tr/4hS/83J/5uT/2I1/kCL/8y7/8N//mL3Vtf2lnkmWZEDJVRWmadjgcbG1vXd3fllIkSyn5LUqDUjKhJ5MIn3ectrEEKAwxeh/4onJCJEpqYol3UVXVYDBYLpfGaNs7BDBaKi2ZsSwzKRL+KunBpHoovrceAYxRKERCXBdFLqQYjgdaayGwrld912e5Kcsi+JDl2cYUUaD6kS99SaLsbZ8dHVlrt1VWlMM8z2Pk4XC4Wq2cc0Lo0WAwmUyt9W3bTqfbdV1vbe2Ox+PJZGu5bFerJjGftDYhRG2y4XBUjcaIUA2Gxycnq7oZjUfVYNhZ2zufl2WW5c5TluVSSO9CjFSWJRNY9864DcOibq4IkRfFaDC8urd97fLe3YdHg8FgOBy63iLgeDTSN66fnJz8yI/+8FNPPxV9+Ognv7C1t1nk+Te/+a3JZCqVkAZ9R3U9b5t1BLDruvl8MRgMiFJu3xJRgcY6F2OIMfa277qua1unNSAarRMRajgaSiGzLAOA5XJVFMXGZmW0UVJMxhOjNQDnZV5W2WK5tNYm/H0IXNddb3ulVJ7lzNz3VgjZtm0IQWtdVdXm5oZAFkKWZRm8jxSNSbmCAMAxUqpxC0BvvvlW13aXLl0CAGOMUsKYTAiMRDFGgUIpRURt2zx48KCqqo2NDe9Ya5Vl2Yc+9CwwtV03GBbrpK8USimpVG9dpkogcfXatUv7+5ONS4D43PMfuvHMtenGtChLipGicNaH6Nu2G4/HN27cyExOHL33trfOO4qEMiQ/IQU88jwH1sCJXJMCCxSZiZge026E6No+RkpjOpVJB4jLxTyGOB6PtTHGmLLMETjSmm8EAIl6kKafUlpplbQA8zxfLBdMVBSlUmq1Wp2dnyqptra3lZTD0Sj4ECkqJZVUKke4fPlyCKFufYxcFMXepct5ni8W86qs5vO51GpzOn1qtSJiY7KmqW88/Rwwb21tVdXo6WeejeSn02leVgAwHo+lEEVROuc2NzcBxHS6LYS4evXqZz7z+aSEtb29bbLFalkDCwSxs71blUPvfZaX79ryUKqTk1Mp5Qsffv7K7rbkeO169rM/+7OIKKTo+/7mzZvOXrHOZmZy7dpAK2Vk9YmPfQEAh9Xk/PTcmLxr+6995Xfn81kIIcszrXSMse/W7p1UcrVaee9ZhDwvKFywophRIDNTpIAhLcaQgD0xeO+Pj4+yPPuhT3z86Wee2RiN88yMB4PxcGjKQfC2t8F7D4gx+LpuFotV2zbWuqZpTk6O7917MDufxRibphECi6LMM2O0yvOM1tqdQqBEtV7RQwhsdPBBKjBG911XVZUQwhhtMl1VVaopH0NMnjEza6NOT0+UVuPxONVzEEJsb28uVztd15lMC0Qh1sEuYh6CEGy8DVlmovdpP1HKTMabN29+uCzLvu9t7621ztm27QaDajIZJ/3jpBtLRN75rBAUow8++KC1LooC0SR0UAwxRB9CiMTeB2sdAxtj8jx31hOt+T1t20opKYZMG2vt1tYWMWVZlmWGKKSC6hdJxuCDY2attExIISWyLAPgzBhjjNa673sA8M5jKYaDoXOWYjSZoUjKes/WhhiZITN6c3OipJZKbm1tSym3d3YHZeW8D94LKbe3SQgBzN6HLMuaphFC7O3tF2Xe9U2W5VevtmntQQCjtbVWSPnssySkWC6Xo+HoueeeT/ObmOq6VUrleZ7n+aVL+3mea63z/B1BOgYIRIdHh3luxN5Ws6rPTx5NLl1+4SMvpL2yLEtmvn79s2myPD4xM2MAuHb16cloczze8C4MBt9NezcAlGUZY8wKwcxlWQ6Ho+VqqZRSWiOiEKi11lrnRa60AQZmSpJvKbOWxNwBMM9zRPyd3/u9h+dnly/tHT44MEJMx6MbT92sV6um7dumTeuWyTKhpDGGiJqmOT46vn/v3unpGSKmQHCMRDFMJkMGjjFKJZVSve1jDFoZT957L5Xo+i7LVILTeR/SbPHBOi8wiBijEKiEbtoGhXC+DzHaehmiFaxS4acUGsq0BoiIQggkohhDCKEox13j6mXdNE3TNEwsJCphtMgE6662XdfrTAOAlEoI4azrut5aW69qKQUgpAfU0kQkYKkkKCERpHMuRXhs7/q+d96FSD74NHOMyYo8z/Ii5fWdc8xrUKDWynmntbbWxhi7rrPBut5FiskQiuRisAmyEDMTfeitBYTcZMPRyOSqa5tVXRf5gAFCDFJJdty0DTNQJPW97720XC6aulmuVqPh8Etf/unJxqZ1XmtNIWZZ3nQdIgqVuORZCEEpQySkMkWB2pgYAkpWwY8nG0qbGKOU0mgVnI+RBsNB8MEYszHZQMS2bZm5KIq+77e3dhEVM+RZYYxZrVZlWYJ5d1xZEhnWRP7B/QerTAsIUkofwtbmZhqRUin4gGijENWgHG9v7vVdVxSFUkpr7b3Pi0JKeXZ22Pd9luXTzelrt18vSjMcDIosD56DT44bGG2YWUgZQ7IvIgAIKVerFQMMB4PZfH5w7/6sq5fN8vbLL2MgifzstTcf3T+sm2Y2m0khx+NRgNjZLgYWApWWiFjXXdPa8bCsqsp7X9d10zR5prXW3vmizKWQxBEBTaatdSjQGOOsWzNxbbC2r6pSGxXJeu+Tk5DnudbKWau1JopSKdv2DOxcD0ha6xCs95aBZQJ+UqRIMYYYAxENh0NkkUQieA06lMDCWuesIyIC6vtOCOG969o4GDRCCuKIjErKRMEjEkAohUhCKcGHs9NzH1yM5Jxz1jnvUEgiss7GEPu+77tO67bv+7RNpXUBgGzfdW0bNr3zFpBjjG3fdl0XKQoUkYnJETlEVFpKKbq+c8FPJxvD4XA0Giml8jybTjfzrDo6PmqaZroxTWWQTk5OAECRcL2vb7/5ct/3zz77HEj71r1XPvqRjxwfH4/H40dHD3Z2d6TMvPXnpzOdK6GgygpmmM/nmTExolIq+jgel019rpTWEr23MZCUqqoq73xZlmlzLMvKGNX7VshcKQ1MSngpVQhIFLLcsBD8ngIMAgSgkFL3HnoPALp+7WA4qsaTna3NjRA8M7XNQqoMkYV4LFC+5r7+2T//byZv8sbT13/xF37h9PhkMBj8ws//mZ2dnX/73/nLl68UVVUxBYHSdfbe4fFoUo5Gw5P21Oj81B51sjs4eDAejoo887bf2pxuTyfDyfTlN26fn9WjjWxSldL645fvnt26FwL1gQDgzhsnTz7CrG2fTNcrXKN0ACBY11IYDIrJoBJSjMeqbU+11kwDa9sYAcmApTIvEWA2WwQOsca67pvOn5/VRHo4KE3OpsxiDNY6BFEWVXR9V9dAYjoYj8zo6s7Ti1V7cnJSDVTTxbPZMs/zgZkEEQm9817LfLVYzJdnwR9aZ4URNoQYSUrQubbRLeoVMK7qmsBprRi47jqlZBRck12QQ/Khj3meBe912+ZZHkLorQ0hLBfzpV9FjkrK3lpEtMEuZ63RmRDCWYuIG9NpsFZLDYwUWWutlWBmUei+j9ZxCKLvLVFsu56IldKIUjDFABBhPNnoV9Y1vXVuNBoK1lplWhlrewCuqkobLMv8/p2HVV7t718F4KLMpESlpcxM9qEP3by0t/eZz3z2zt0Hb77x1o/+yI+89tprq9Xq1q1bRB/+6Ec/8Y3f+b1vf/s7Bwd3N3e3fvSHfuTg/sPvvviiMeba1as3b958+dWX+75DxE9/5tN33rqzXC2rcnjt6vXhYHjr9i2tdAj+C5//4v2zByfnD7uu3ZxuXrvy9K1XXgUMSpmt7Z3pdCdGAkE/CBZlsVwuV4vo3enmxtHR4Wuv3d4YD5h479IexfjMM886b29+6JlqtJ0E9+vlSdv7e/fubEwnSsm9S5f29/dfeOHDf/pP/YSzdjgeDwcDrXWWZb1c9NYOh6OtrSrLc23i5UuTwgQCFMqMRntbW9sPHtz1vX7m49eu9G55Pu/O2xSIjJGJ34nneaK9A57wxB+NC+CAgUfjbHMyuH55C2GLiLI8DyFExpOz1cOTAxDKBw9I42GRZXp3azQclDeuX9nY2BiNR7qQRZ73fb9crqbT6XQ60Toanbd113dua2v3Yx/72Gtv3Nudbe3sbt14+sZkOnj48OCVV17p+qYcFFoZJfrT0xNCcXp6WpYVE52cHDtnjcmIo43tsjsniidnJ6JQRmkhcNXXAKAWUufah1XTNiEE0xkhhApytop5nmdZ1nWrVb84X5xHosxki/nSOZeXed84iz0wWOsAMIZY6HxQVFKKLMuUUl3XNU3jnJ3N5mVZaK2ZY10ve9sKIYh1nmV5nhWTIQUfiYzRRVnKVsboGcJ0Oi7LcjbziRnbNG0IntIW5NxiMdeZci6onZ09RJnVq43Jxs72ztnZcna+OD05O3jw6Pq1a4vZ8t69+zduPMvM52cnb71xe7Y4/9ynP/vo8PDu3TtKSaXUzZs333zjjRADEX3oQx+6c+fO6ekpEQvEra3Nr3/9dwBhdn62u7v74ovfe+mVPwzRf+i5mz/1k9X/9U//ibWrohh++ctfnm5uZ5lRJrP23QLc70l2smQRo+9tb629c+etX/vHv/bU/pXjk+PPfPqzX/naVz/58Y/fuXv3v/8f/sbTo62LnJX4w29/a76Y/eQf/4lIUSnlfDdfzq9dudL1/bPPPptl2Xg4/OznPvfyqy8eHDzUWo2f+cRytapXq8nesN+9Zn04X9UglfPoyCyasLV9FQL1s1tRRCUtESNiJoUPFCJdBN0B1hCPBJGHJ1iywGugGCqFUqLSYmtz9Nz1vaIomqbJ89x7r7P8xVdef+XlIyxUnmWaI1k/2Bp/5MMfv3zl8vVr1xGFzjIwZj6bzReLvuuGo2EI4YUXnldKexeLvADE4bjYv7xTDYyQsKxn1TDXmRxsZqonFAKZjw4f3rv38PmPfIyZP/PZz1hrX3vt9oP7d25++GMETqgI0hUDbTpaunlAjYx1WAFzHbL+pImR6nolpXRRGmNCQwhoyiko0bnFbHm8nLXVsATmZtmHGEejQUu9tT2FNcXKO6ekNNKUZV4NyjzLV3VNMRZFUZZZ3zfWYl4Ubdf2th0NB0WR5XlRFDkCz5uVd344HOaFiqQY4ng6HE2GiDgcDaSUzNB1Xb1aZbli5hD8arUaiHHfe7VcrE5Pzl577bU/+M53X3rpleef/+iL3/3u3/yl/y7EeP3a9bt37965+8Zytri0c5mCUyrr6pV3ru977/oYxXK5SEuyECil1FrneV4UxXw+D9H74OeLmRCi7+q2bx4+epj46V3X5HnW913T1L11XdcggnX9+xeQeE/r+14IUFJNJpPNzc0sy5TWAsXOznYMIQF09/b2Ek4LUQzHW888++ztWy9/5rOfpki97eu6fnjwYGtrqyzLj3/s41LJ3/7q14IPP/HHfzi47urVq08//fTBwUFRFNuTK0U1qNvmH/zqr/7zr/xWIC5Go0hWxFIytHMfO/KeQqCE/TRaSgFEjAipIDsCCrlOT6dCYMCACIEYEYwWWmGMXK+64GyZm82NSWG0Nqapm9FwdHV76+rudP/GtatX9gvJAolltrGxIZBu33756PCwd2HW2IcPHvV9P9kYlVV18OBBkWeIjCi+8MXPXtq/9MlPfbzu3BtvvnZpf+/w6OHe3u50unH9uS/54Jq61SL72m/97qP7p/fv31FKS4SNyfhb3/rWxz7ygsng9ddfsq51XlajMchQFloKQUxakpCyKPRq2WVZVpYmM6a3lsjmRZFp41y7WJ53fZsXOto4uTwaDoez05ntKTqrJItcBRc5cCAWDM6FLvq6bc1iUZXG2hAib23G3b0dADg5Ol4sZkcnC0QGImLvfRtigQh1s6wXvXW9j/14PBlvbFy+tjccF2dnM2Vknhf1snbOohCXr+x7H6y1RVkwRWeD2tvbG4/Gu7u7McQQw5XL1z7/uS/2th+Px5PR5PKlq+eL4/t37129fH1ra6eshqt6JoUwxmiTCyHyokh6IXW9mkwmQgiTmSzLRqMRIPS2DzFEG1N2RmkBAgBJGx2i10bmlKFQIYQYXYhBMQG8O+353sxlWZaRfAhBSHnjxtM//VM/PRoUFOPP/Mmf2bu8+/nPf+H8/DQvihjsa7deeurG048ePbp0+SqxffTwETNdu37VezeZbFzZ23npey994+tf/8QnPk4h3H711f/gP/1Pvv71bzlHv/21b7Rd+8ILHxFbjCLmhdrcHF27skuM5009Oz2tmzlHPjs/KaQQAo1RIcQQIjM/rll2sdq/LVeY9Bf44iET3y8GRgRnw7Lu6oYuX928fuPDu3t7FGNZFJ/65OJTn/mxaryhtIiuZY73j84eHhy88cb3Xn3lzYOjcyaurQ8hCoSnru9UVf7WGw+lRKPEpStb164+9bFPfPTG058n3tjfu/zc85/8v//prwRyq1X98PDBaDwcjce2c+cnS611jOH8fPHVr/2ryXgDgN+68/qjo7sPDw+GZbk53tjZ3qEQffRaKQZY5UMp5ZXdy2CjyYwQMs9z51wIfnO0raQ8PDxqV/clQ671tRv7165ejTFKIYyRxpi+TaFMEAKS2AKs675xb4NgZgYf6Ph4VlVmNBqWlQHAxXwVIze17TuX5XIwMiY3LKIqICuVyfXTzz61vbOZD3Q1qOaLRfRRa40CHz58FGOcTqevvHzr/r3D0bBgpmXj1NGj4+l0+uzTz+V5HkIQIv+pn/4TKfSRZdnP/umfY7Deut3tSx/+0E2U2Pb1eLRx7eqNL3z+88aYoihGo9Ev/PwvdLalSNPpdHd3lyJtbk23djalEB/7xEeCDz74qiqvXrnc2qXUYnNn83R2qrTK2BiT++hCDNqooizb5gegbCMCYAgheH/jxo3d3Z3xJBsOx0U+vvH0zfQVgjA/O335lZf3L+/PZ+e7e3uX9nebZrW1vbW3t3dychJCuHbt2nK5/P1vfYsZfuzHvnR6evLKN15dHIXYzL/73Zfu37//6//ot2p31nd9UZVay9FkEmOcjschr+4ePOqtD84LqYRcKwVa64kosY+EQGZO0iMJZPXkE0ghFEKMrBRSZGOkMerg4Pyf/ebvfuUbf1gWZZ5nq2UdKToXm9qHGBfLZdO2IOF8YY0SValXrX+SMq+kqIpBcKHtwnSUecfRQfDs+rha3dmYbG5ORkVZPXX92eF48PGPfvpf/uZXHh09+Mkf+6JzfnnaPbh3uGrm1aCqyurKlSvGmO2d7cGwuHr1KjNLKbe2N09PTs5OH5VlaYxpuxYIdvd2n7323GpVh+Ctc0xkrfUuQoT93ctX968liGQk3NraGg2HN566dufOna7rwn4UUkghUwSWiLWSRusUAFVKueCjD13XPvvsc5PJ5PDwMMRQjjKllBSyrMrRaFSWFSB774jiaDRGIW7evFlU+v7DN4lCUeXtqnPODQbDy5cvb25uf+oTnzY6+8pXv3l4Or++N4yZxr/4F/7i1tZmluVSycwYYiWESgU7rbMbk4nSbPv+/Gx+ef+yVNJH6z0NqlHKOy4XCyHEYFhVg6rrOoEolQSAru+ISSvNAJkxfd8VRbVarkyuUhgs08XDg4eDKm/7rsirS/uXF4tVVhQUBb5TRVXIdfoJL9DJSjFFr7S8fOnS/v6loixsmF26tD+sdvGJeGizOv/6b//WZz/3w1JKipQPqt/73d+Yz+chxOVqub2zrVHeeevO3/t7v9I0jTGmyIv969dHw+GVq1evX3+qLAoUAmPunV8tFw8PDiSKxXx2en5Wd/3R2bmP3DbtfHbe2kYJCCH0LqxLSBFxynSumeEsBEolcO0rk9EqRO6tL4wOMSqNmVK9C7lWKxuYSCsZiGOkC049rznvCMBAzJkW7p24SaP1l374cwLxrbsPOPrdvZ1L+zuTjXHkcOOppy7vf+j05PSVl1/8d//9v/SxT34OAL79rW/+6j/4lb/w7/1b29vXXvzD73zrG18XOnjvNzen9+4/UEoLIYNvjSmkUF3rppubXdeNKqWUGo1GiMLafjwegxanp6fW9l3bCSljDMyiqVtj9MbGRpLGqdtWGbO/f8n7cHpyIoRgIiFkwj547ykSAA0GAyGktS6GeHp2OjufnZ+dbW5uZoVpmnq6OXXOFUWe57mSKsQYQ+hSVNXb0XCotX7u5s2iyl6+9aK34drV68t5XdfNdLIJBM2q+dznPv/662/+w3/wa1/7ytfGhekCKQkxeksCgYT1zgcQUsUYm6YlJoju+ZvPfe/+i4dHR5PxoCzKxWJurYXgiNg6OzufCYHm2lXXL1OqQildFAUT33nrrjHm6rVr3keI4fjsYDKeaFLITCF4113Z3TNa+xDKsuybVgQHPUZOYm/i8RwQLFLWQ6CIMQTvUYUYgqkqdl09P7e13rs0sqvGNQ8TqQCAI8VuNbP1/J/83b89KMuuaa6/8PHf/ef/4vD4hIgOHj0cj8fRmKNHh+fn877pmTkGuvvGXWImRkZVlmU1GGzu7BZFPqyqsiwHVTUYDvaqS0x88/lnszxn5uVyOVuehxhSqFcp7b3vOkvEPgQmIiLvow8+8SedDyFEgei87/o+wT8TIHwjM8MqA4S+s8ZoYuraTkoJCEQcffQhMjGDCCEqiW1n67aNiQwOEIJ/cPDgM5/99E/89E/+zje+cePGjR//8R9/8cUXf+3Xfu1LP/6vPf3ss+23VvfvvuVtl9QjVGy/+OmPvfW9l+7hKy9973uXtretAhCRIW7vbr704u2jw7NM+aefefb69af29ysfQpYro8Nrr72WZdmHn38+sLWhhUiDgS4LOaiMc84HlMJMNwYAEEKIwQohhlUJAIvTU0BR5TkiSsSk68QMlIAb1gLg0eHJvbv3+85/78UX7755DxnKYfH0c9eeefb6wf07CHJzY7sy1dnp2a1bt0PwIITJ8nJQzs/m2qhHjx6y0L3HrmvbzpydnTnnlDqan5xe3ttumtXt22/UbdvYWCiqO6fKYnBp78p4PI4x9F2ns1xpHWNMMdc8z1HiYFhdVvu7u9ta6SzXMRITtW1LMWSZLsoSAIBQSyMgUuRm1Trv2q4hpnq1RCEQoG1r56w2Jnjf9T0TCSG0NhsbE8b85PTIh6C1CTEBCcVaoVsICRhiAAZiCiE455C7lPFpuzYpHjN3fd+HGLRUxhghRW87ZOi71jVds1otZrO/96u/pjINQszn86ZpameVzurVCiIpKYEBKdgQAnHnQuvabNWMmubO/QdN2yPCsMyN0c6FCFBmpiwLISSjEFIqJZUSxJDnemMy1kYblWd5jgjGZCYzsC4CaxiYYky6YGmflFIak3VdJwSORqOUJhdCAoD3znsvhExqm977rmuDj0plCZh0cHDw0ksvHR+fLJcrqQRFphgeHRwogc3h0UyqV775e91quVtWr37r91/8/W/b1erZ3b23vvMdWNYmz/2DOzsU+8NjEjhluPX1b9yu66xQWa6tj6/fvnt8dN71/ujEnZx2k/EQgLyz165fV2ryq//413/91782GpZ5UW5uj5L5kOd5KnY4rAZpdAshtNZKClRRCExoICEEIggJF/rqwCyJhDDGO7537+G3fv8PvAurZa11RiFqnSPok5OFj/2gHObGZVl7ejq/d/fg/Px8MBls728fnj0ipr39vSLPXn/j/q3bD4INCei1uT0ZDIZv3nq9yPPhoDo7m7VdAtipgZD4Yz/2w+PJuKoGSilEECClUAljmpBSN55+imLIi/z6tesmMwKFybK2bb1zzrkYSRuVm3I0HAkhnHPL5fL8/NwHZ70dDgc7OztK6Swz3nlEKYRo6ubs9HQ2n3vvlFLj8Xg0Gr388ssJrQkoQMgEpWIiBJFK0jMDE3nvvXfA/cOHD4P3G9MpM8/nc+eaGAMRy4tkZFYVG5OxkfL87OzenTuPHhyVVbazu9vZ/mx2bkxelgW7aG1PPgqBEjDGGAV0vTuf1fPaaiW2p2NtzOHxifW0t71RFMXh0UnduWFh8sx0va17DwCZFkqIEEkIrCojhLA26dOh1tIoCQCMImXoEtxfK2m09JEQsCx1pPQhz/M8iU8nNqVW+vGRGMl7z8RG59poo83x8fHrr7++mM8hBqWEdzHLtCcwWhlgKZWQyijhnavKou7tRpF/5Nr1YZ5tTjauXL5cFJnKMpLysz/8w9lg8Lf/zt/5X//R/ykMKC0ZcLWwfeue/vAPPffsU/PZcbM8Gw+Lh48ebG5fzfP8//mNf7aqV1pLIjZGpbGePCEUYmdahUDBMyBoJQFRGZRKCJGwa0IgZnmWemrN22YANHlWPTx49Prrb1GMAmUMRMRFbsaTEQuO5MfDUVlUQoimrk9OThBgOB6Z0gDycFRVw8FgWNWr7uWX3prNZhSjlKoYFINqYIQ6fPggMyrBVbe3d7vzR4veqfF2aQyCdhE9EZ0dL5aLVV3Xzrk0fV986Q+c74FZSd3ZTgixvb1NgbLMJCfYGBMClUWVckkXzaDkvsflcqa1DrEw2uRFAcCR9Hg6NIUior7vZ/MzH/tAbm9nJ89z59YIHyklEXnvm6aOF5WB0wRYzvu+71arVRKXPT8/r6osIUP6vieKzHB1Ojk4PLr16iuPHhwLgQigG3G+XPoQCViY1j5ye+NJvWq71iJgbqQ2UpcGJRaV6WxoXTg4nq0L9CLOZsvFYskMAqHuXN05RMiUlAJtiCGuWZPMzkeSApOlnnb5ECMDSFyr2QCAEoKSgjODQKwKxcxtHzKtylLPlzYyC7jQSLzwa5BBS0EAgTjFkSJRrkSuVd/EEMn0PtF3hABmCMQCQQqkk3lhJDq3WixMrBpisbc3m822Ll0CIeZ1PTCmnE5iJC2yLMu6vu/7/nC2sK++3vf9yeE91y+fe+b6arb63d//daUKJtaycr4RqJ+QUVm3blVb/32EGy8CGe93rMyyzloBEpEjsAAVunDePEw1lDM5i0yR2QghAPsYHp0v0rlaZIEdAGxONpTJy3yYMDje+kezE2byzjobMmU8U4jYe7i0e0ldf/pGDBGAkwjw7vZ+DOSdJyIUqKQKwXlvvQ/Oub7vEEWMYbWqbXAuepCIEhbL5cnp0RpUEmPCeCTobwK7S5lqtitvPXHMsmw4GJosq8pyujl96unPzWbn3/r9b969c48ibW9v7e7ujcYjJRUI1FmeTORI0Tlne8veGmPKsuj7zlpHRHXbMlOCT2Umy/L8/v37dd0cHy2sx7XrjLSoQ4I9EvcAsDo/EgKVFFqibSO34M7qNcubOdNCKgEETElWiYmQmItMeU+RGREI2LooEbVCgRAZiC/kmVLEE0EgE0NiEIrH/DKJgTih9iNxnhtEdL4dDPOqKprWsadMSaFEnsm+Cz6QlFgUuipLRHF2Nrc+emIA6AN1YT0EOXHnmWMSw0FkZoGYaRkiBeZ535ejITG/cXpaertcLBzA62++2VN88627IIgxCKWVkSbXCHB2duvs7DYC5lq9/qZnACm0ljIrs1WzMqoQAhGztBIRR2AChM4TgEBMeUAphERAXo/5lJzBEB1DegMpukEMhEIGlkLkiEIKJRhMnjFR7AiFUDIbDiopxHwxH43Gxpj5fM4EAnUkb0MtQAGKs9mC+NzI0sUmXU6KJA2jbIguekSyfbRoeo9KcUHRIaKUEiQ41wmBWWEQEhMPlTZlaYQQKbkDyY4RMsSQEFdKKec9rmkKQDFxHiLFtYSTlBIFBh+bpqnrOiHgV+0SO7Fqlm/ceWNZL+/fv3d2du66qJVEBGut0opidN43vSWitMGGEHzw1Lepa51ziaUVkbWWyR6vyqqqKuSghHjho88Bc4jEgAMjQoghhM72dWt9CF3jI4QYPXgKfQyBq0pZS0mGkRGcC6UxIYZIrJKQoKfeMwMokVDKjwnfCAgSQGshBQKCD5S0+FGAQkyCMcwQAgUiCCAEJqw1IterPi3Y83nb1F2MnJxjjuQsJG0BIrZ9EGizLPORUyKZaC1XCABJeyTVRZACUgBKCmQCpdARLa0/c255eCSk/O7Dg4EUvQuO4sls3rZdPiwGw9JH13YhBNYG13MamIE777rTcwAYVMO6WQo5NFq1XT2ohraziMJIiaiT/g6zAFzD+pkIxTomnFaWZFoLIdeUMgCmCIhSaokSGLXOABE5CR6iQJObMVOQKmc23nsA4T0xRGSpjE4EgKrYYA6dbYWQmPLvqJQwAKyE9tENy1HTrhgFgECRRdTH8wX+lf/wrzJzckYoRk8d4DqEB0yIgjlpEyCnmhPrMK1MwjWYCqkJRglEkYgBGDHJZ3HKdKAQAKCETCL6FIkosdJJCOj7fnNzq+97BpYoIQglpVQSGNJ+Ysky8eM9KsbQ1csQYow+JoAmUW/7osiqqsryPMtyY7QgSgNXSKm11trEEIjIB9/1tut7a60Lseu61XLZd31STtZCBEoVHJDT4CaRtoQU20SEEC7un1I9uDVzIBIxrUWjtBKAkHgfRMDEMfBjxREESNywdcz24n+thZQYIyND9OQCIWLSfnys0iswDQtWKllZa32EeMF7R8THaz8iZlowgNaiszHTYjIsQ4gE0PfeZPq5m8+88cab57NWApDEYa5iIKmRAWOE+bL/QTR9FcoL6QAmZgIWFySGFAZGIQSs9cTXcWEARJRCpIdfCymmpCcKJc3ahgNkIimUEJI5CKFSCQiiqLQBgOCdUNo5G6JDVJEcMxld4HorDlIooihQChQMhABGmkCUmRIz4V2vVDa60NRjFBC9JI6IcKGOAbwWI1xrgAKA4AgcAeExV5UxMgQUTxwhYoiAzAAUmQGIIHIEBmZkkIwMgIFClle9czrLlVICBfLblG0JAEAG3g2QjtMRMzAkSqiQUiHEoiyG1aAsS200oojeMlPTNElqJsZ47+CQPIfUQ1LkRZ5DLEu9sTFIiHwA0BKJ4lqeFoUQAtCkUi7M9JjSwU80AE44KCKOKchPrBWjYKaE8idmCD5SUo1MAwJFZF6T6JNRACAFCAQiCj46570LwUffR7rQPkAQUmKS9mdmIhCJhY8AiMlVWOsFEUuBUgmpUGohBOxsDFPIRTMGHzIhqtK88OGno683p72S0nk3rxtF6dVCtL4sZNteyCc+7pT32u6CeC1CAEiMDMQeo39bq5veoYR4MZc5EguEVLKG5cVRDiEGJJQSEaRATMK7gMgQYlwbutGutRZ936TiBghRCUBAIAuAMt0qe0Rgjm79AsFHhyh8b8ExMCtmBEQCAkAmFlIhvwOMkFDFTx4hCPwunYJk/D15AGPkpKvMjMBECIiEAABEF8oNJEQQQiILjjKuDeV3KwigfA9DABXgOl2glBRCjgbGmCzPc2NMkv2QmQRmYiGdZ+DIPoTkntDjvRgAldRCC1Gk1BsaCY+/AIhCYCB10TPrCfDY5kn1CQCg7doEpk9TgojT/gFPyKcTB6IYidLCBslLfudbVFIoKVLWK4SQ9jdg5AuVuJQMEWJdsMyHEEJIfJ1EbRFSapUKJ3ZKSiGVUlIqJaUwRqYxl/ZMIBoMqi70O1f2nhuNAbjruoeH5+t3ROSs622/XCZ97yQJTszs36Od6PuYBkgkpgAc+L0sfhQoFCot1iwWx85FYEaBKJLjAOnDWnqZOUZWClAhEKwPM4S4Zg+/PdLenlHrI4nxg8kOWbt8/C71TgCQBMzw/wH24Wl7HlBM9gAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": null,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Display resized image.\n",
+ "PIL.Image.fromarray(resize_image(transformed_img).numpy())"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v2/notebooks/5_DataManagement/load_data.ipynb b/tensorflow_v2/notebooks/5_DataManagement/load_data.ipynb
new file mode 100644
index 00000000..18c725cc
--- /dev/null
+++ b/tensorflow_v2/notebooks/5_DataManagement/load_data.ipynb
@@ -0,0 +1,530 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Load and parse data with TensorFlow 2.0 (tf.data)\n",
+ "\n",
+ "A TensorFlow 2.0 example to build input pipelines for loading data efficiently.\n",
+ "\n",
+ "\n",
+ "- Numpy Arrays\n",
+ "- Images\n",
+ "- CSV file\n",
+ "- Custom data from a Generator\n",
+ "\n",
+ "For more information about creating and loading TensorFlow's `TFRecords` data format, see: [tfrecords.ipynb](tfrecords.ipynb)\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import numpy as np\n",
+ "import random\n",
+ "import requests\n",
+ "import string\n",
+ "import tarfile\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load Numpy Arrays\n",
+ "\n",
+ "Build a data pipeline over numpy arrays."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create a toy dataset (even and odd numbers, with respective labels of 0 and 1).\n",
+ "evens = np.arange(0, 100, step=2, dtype=np.int32)\n",
+ "evens_label = np.zeros(50, dtype=np.int32)\n",
+ "odds = np.arange(1, 100, step=2, dtype=np.int32)\n",
+ "odds_label = np.ones(50, dtype=np.int32)\n",
+ "# Concatenate arrays\n",
+ "features = np.concatenate([evens, odds])\n",
+ "labels = np.concatenate([evens_label, odds_label])\n",
+ "\n",
+ "# Load a numpy array using tf data api with `from_tensor_slices`.\n",
+ "data = tf.data.Dataset.from_tensor_slices((features, labels))\n",
+ "# Refill data indefinitely. \n",
+ "data = data.repeat()\n",
+ "# Shuffle data.\n",
+ "data = data.shuffle(buffer_size=100)\n",
+ "# Batch data (aggregate records together).\n",
+ "data = data.batch(batch_size=4)\n",
+ "# Prefetch batch (pre-load batch for faster consumption).\n",
+ "data = data.prefetch(buffer_size=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "tf.Tensor([ 9 94 29 85], shape=(4,), dtype=int32) tf.Tensor([1 0 1 1], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([68 57 88 41], shape=(4,), dtype=int32) tf.Tensor([0 1 0 1], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([51 19 18 56], shape=(4,), dtype=int32) tf.Tensor([1 1 0 0], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([70 84 99 32], shape=(4,), dtype=int32) tf.Tensor([0 0 1 0], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([40 0 25 28], shape=(4,), dtype=int32) tf.Tensor([0 0 1 0], shape=(4,), dtype=int32)\n"
+ ]
+ }
+ ],
+ "source": [
+ "for batch_x, batch_y in data.take(5):\n",
+ " print(batch_x, batch_y)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "tf.Tensor([ 9 94 29 85], shape=(4,), dtype=int32) tf.Tensor([1 0 1 1], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([68 57 88 41], shape=(4,), dtype=int32) tf.Tensor([0 1 0 1], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([51 19 18 56], shape=(4,), dtype=int32) tf.Tensor([1 1 0 0], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([70 84 99 32], shape=(4,), dtype=int32) tf.Tensor([0 0 1 0], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([40 0 25 28], shape=(4,), dtype=int32) tf.Tensor([0 0 1 0], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([20 38 22 79], shape=(4,), dtype=int32) tf.Tensor([0 0 0 1], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([20 22 96 27], shape=(4,), dtype=int32) tf.Tensor([0 0 0 1], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([34 58 86 67], shape=(4,), dtype=int32) tf.Tensor([0 0 0 1], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([ 2 98 24 21], shape=(4,), dtype=int32) tf.Tensor([0 0 0 1], shape=(4,), dtype=int32)\n",
+ "tf.Tensor([16 45 18 35], shape=(4,), dtype=int32) tf.Tensor([0 1 0 1], shape=(4,), dtype=int32)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Note: If you are planning on calling multiple time,\n",
+ "# you can user the iterator way:\n",
+ "ite_data = iter(data)\n",
+ "for i in range(5):\n",
+ " batch_x, batch_y = next(ite_data)\n",
+ " print(batch_x, batch_y)\n",
+ "\n",
+ "for i in range(5):\n",
+ " batch_x, batch_y = next(ite_data)\n",
+ " print(batch_x, batch_y)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load CSV files\n",
+ "\n",
+ "Build a data pipeline from features stored in a CSV file. For this example, Titanic dataset will be used as a toy dataset stored in CSV format."
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "#### Titanic Dataset\n",
+ "\n",
+ "\n",
+ "\n",
+ "survived|pclass|name|sex|age|sibsp|parch|ticket|fare\n",
+ "--------|------|----|---|---|-----|-----|------|----\n",
+ "1|1|\"Allen, Miss. Elisabeth Walton\"|female|29|0|0|24160|211.3375\n",
+ "1|1|\"Allison, Master. Hudson Trevor\"|male|0.9167|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Miss. Helen Loraine\"|female|2|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Mr. Hudson Joshua Creighton\"|male|30|1|2|113781|151.5500\n",
+ "...|...|...|...|...|...|...|...|..."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download Titanic dataset (in csv format).\n",
+ "d = requests.get(\"https://raw.githubusercontent.com/tflearn/tflearn.github.io/master/resources/titanic_dataset.csv\")\n",
+ "with open(\"titanic_dataset.csv\", \"wb\") as f:\n",
+ " f.write(d.content)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load Titanic dataset.\n",
+ "# Original features: survived,pclass,name,sex,age,sibsp,parch,ticket,fare\n",
+ "# Select specific columns: survived,pclass,name,sex,age,fare\n",
+ "column_to_use = [0, 1, 2, 3, 4, 8]\n",
+ "record_defaults = [tf.int32, tf.int32, tf.string, tf.string, tf.float32, tf.float32]\n",
+ "\n",
+ "# Load the whole dataset file, and slice each line.\n",
+ "data = tf.data.experimental.CsvDataset(\"titanic_dataset.csv\", record_defaults, header=True, select_cols=column_to_use)\n",
+ "# Refill data indefinitely.\n",
+ "data = data.repeat()\n",
+ "# Shuffle data.\n",
+ "data = data.shuffle(buffer_size=1000)\n",
+ "# Batch data (aggregate records together).\n",
+ "data = data.batch(batch_size=2)\n",
+ "# Prefetch batch (pre-load batch for faster consumption).\n",
+ "data = data.prefetch(buffer_size=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[1 1]\n",
+ "[2 2]\n",
+ "['Richards, Master. George Sibley' 'Rugg, Miss. Emily']\n",
+ "['male' 'female']\n",
+ "[ 0.8333 21. ]\n",
+ "[18.75 10.5 ]\n"
+ ]
+ }
+ ],
+ "source": [
+ "for survived, pclass, name, sex, age, fare in data.take(1):\n",
+ " print(survived.numpy())\n",
+ " print(pclass.numpy())\n",
+ " print(name.numpy())\n",
+ " print(sex.numpy())\n",
+ " print(age.numpy())\n",
+ " print(fare.numpy())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load Images\n",
+ "\n",
+ "Build a data pipeline by loading images from disk. For this example, Oxford Flowers dataset will be used."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download Oxford 17 flowers dataset\n",
+ "d = requests.get(\"http://www.robots.ox.ac.uk/~vgg/data/flowers/17/17flowers.tgz\")\n",
+ "with open(\"17flowers.tgz\", \"wb\") as f:\n",
+ " f.write(d.content)\n",
+ "# Extract archive.\n",
+ "with tarfile.open(\"17flowers.tgz\") as t:\n",
+ " t.extractall()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with open('jpg/dataset.csv', 'w') as f:\n",
+ " c = 0\n",
+ " for i in range(1360):\n",
+ " f.write(\"jpg/image_%04i.jpg,%i\\n\" % (i+1, c))\n",
+ " if (i+1) % 80 == 0:\n",
+ " c += 1"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load Images\n",
+ "with open(\"jpg/dataset.csv\") as f:\n",
+ " dataset_file = f.read().splitlines()\n",
+ "\n",
+ "# Load the whole dataset file, and slice each line.\n",
+ "data = tf.data.Dataset.from_tensor_slices(dataset_file)\n",
+ "# Refill data indefinitely.\n",
+ "data = data.repeat()\n",
+ "# Shuffle data.\n",
+ "data = data.shuffle(buffer_size=1000)\n",
+ "\n",
+ "# Load and pre-process images.\n",
+ "def load_image(path):\n",
+ " # Read image from path.\n",
+ " image = tf.io.read_file(path)\n",
+ " # Decode the jpeg image to array [0, 255].\n",
+ " image = tf.image.decode_jpeg(image)\n",
+ " # Resize images to a common size of 256x256.\n",
+ " image = tf.image.resize(image, [256, 256])\n",
+ " # Rescale values to [-1, 1].\n",
+ " image = 1. - image / 127.5\n",
+ " return image\n",
+ "# Decode each line from the dataset file.\n",
+ "def parse_records(line):\n",
+ " # File is in csv format: \"image_path,label_id\".\n",
+ " # TensorFlow requires a default value, but it will never be used.\n",
+ " image_path, image_label = tf.io.decode_csv(line, [\"\", 0])\n",
+ " # Apply the function to load images.\n",
+ " image = load_image(image_path)\n",
+ " return image, image_label\n",
+ "# Use 'map' to apply the above functions in parallel.\n",
+ "data = data.map(parse_records, num_parallel_calls=4)\n",
+ "\n",
+ "# Batch data (aggregate images-array together).\n",
+ "data = data.batch(batch_size=2)\n",
+ "# Prefetch batch (pre-load batch for faster consumption).\n",
+ "data = data.prefetch(buffer_size=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "tf.Tensor(\n",
+ "[[[[-0.90260804 -0.9550551 -0.9444355 ]\n",
+ " [-0.9538603 -0.9715073 -0.9136642 ]\n",
+ " [-0.41687727 -0.37570083 -0.25462234]\n",
+ " ...\n",
+ " [ 0.4617647 0.422549 0.3754902 ]\n",
+ " [ 0.4934436 0.45422792 0.4071691 ]\n",
+ " [ 0.5530829 0.5138672 0.46680838]]\n",
+ "\n",
+ " [[-0.9301815 -0.98563874 -0.9595933 ]\n",
+ " [-0.9379289 -0.95557594 -0.89773285]\n",
+ " [-0.68581116 -0.6446346 -0.5305033 ]\n",
+ " ...\n",
+ " [ 0.46960783 0.43039215 0.38333333]\n",
+ " [ 0.5009191 0.46170342 0.4146446 ]\n",
+ " [ 0.56071925 0.52150357 0.4744447 ]]\n",
+ "\n",
+ " [[-0.9480392 -0.9862745 -0.96889937]\n",
+ " [-0.93367803 -0.9485103 -0.8916054 ]\n",
+ " [-0.9224341 -0.9033165 -0.7915518 ]\n",
+ " ...\n",
+ " [ 0.48045343 0.44123775 0.39417893]\n",
+ " [ 0.51623774 0.47702205 0.42996323]\n",
+ " [ 0.5740809 0.5348652 0.48780638]]\n",
+ "\n",
+ " ...\n",
+ "\n",
+ " [[ 0.0824219 0.37201285 0.5615885 ]\n",
+ " [ 0.09744179 0.3858226 0.57758886]\n",
+ " [ 0.1170305 0.4023859 0.59906554]\n",
+ " ...\n",
+ " [ 0.02599955 0.65661 0.7460593 ]\n",
+ " [-0.0751493 0.6735256 0.7022212 ]\n",
+ " [-0.06794965 0.73861444 0.7482958 ]]\n",
+ "\n",
+ " [[ 0.10942864 0.39136028 0.5135914 ]\n",
+ " [ 0.18471968 0.4658088 0.5954542 ]\n",
+ " [ 0.21578586 0.4813496 0.6320619 ]\n",
+ " ...\n",
+ " [ 0.22432214 0.676777 0.8324946 ]\n",
+ " [ 0.10089612 0.73174024 0.7959444 ]\n",
+ " [ 0.00907248 0.74025357 0.7495098 ]]\n",
+ "\n",
+ " [[ 0.15197992 0.43433285 0.54413676]\n",
+ " [ 0.20049018 0.48284316 0.60343134]\n",
+ " [ 0.2664752 0.5252987 0.6713772 ]\n",
+ " ...\n",
+ " [ 0.24040669 0.6644263 0.8296224 ]\n",
+ " [ 0.10060894 0.7192364 0.78786385]\n",
+ " [ 0.05363435 0.77765393 0.78206575]]]\n",
+ "\n",
+ "\n",
+ " [[[-0.49571514 -0.2133621 0.6807555 ]\n",
+ " [-0.52243936 -0.2322433 0.66971743]\n",
+ " [-0.5502666 -0.24438429 0.6732628 ]\n",
+ " ...\n",
+ " [-0.61084557 -0.22653186 0.7019608 ]\n",
+ " [-0.60784316 -0.21568632 0.65843004]\n",
+ " [-0.6197916 -0.22585356 0.6411722 ]]\n",
+ "\n",
+ " [[-0.5225973 -0.24024439 0.6538732 ]\n",
+ " [-0.54144406 -0.26501226 0.64094764]\n",
+ " [-0.56139374 -0.27119768 0.6341878 ]\n",
+ " ...\n",
+ " [-0.6186887 -0.22824419 0.67053366]\n",
+ " [-0.59662986 -0.22015929 0.6358456 ]\n",
+ " [-0.6119485 -0.23387194 0.6130515 ]]\n",
+ "\n",
+ " [[-0.54999995 -0.26764703 0.61539805]\n",
+ " [-0.56739867 -0.28504562 0.6056473 ]\n",
+ " [-0.58733106 -0.297135 0.5988358 ]\n",
+ " ...\n",
+ " [-0.62097263 -0.22653186 0.62466395]\n",
+ " [-0.60171235 -0.21739864 0.5984136 ]\n",
+ " [-0.614951 -0.23063731 0.579271 ]]\n",
+ "\n",
+ " ...\n",
+ "\n",
+ " [[-0.49420047 -0.25567698 -0.29812205]\n",
+ " [-0.5336498 -0.31243873 -0.34749448]\n",
+ " [-0.5600954 -0.35433567 -0.38869584]\n",
+ " ...\n",
+ " [ 0.4558211 0.22837007 0.47150737]\n",
+ " [ 0.49019605 0.24705881 0.4980392 ]\n",
+ " [ 0.5021446 0.25900733 0.5099877 ]]\n",
+ "\n",
+ " [[-0.50617576 -0.29696214 -0.31009734]\n",
+ " [-0.47532892 -0.28324962 -0.28901553]\n",
+ " [-0.45759463 -0.28628123 -0.28675795]\n",
+ " ...\n",
+ " [ 0.46366423 0.2362132 0.4793505 ]\n",
+ " [ 0.4980392 0.25490195 0.5058824 ]\n",
+ " [ 0.5099877 0.26685047 0.51783085]]\n",
+ "\n",
+ " [[-0.45882356 -0.254902 -0.26274514]\n",
+ " [-0.4185791 -0.23034382 -0.23034382]\n",
+ " [-0.37365198 -0.21194851 -0.20410538]\n",
+ " ...\n",
+ " [ 0.46366423 0.2362132 0.4793505 ]\n",
+ " [ 0.4980392 0.25490195 0.5058824 ]\n",
+ " [ 0.5099877 0.26685047 0.51783085]]]], shape=(2, 256, 256, 3), dtype=float32) tf.Tensor([8 8], shape=(2,), dtype=int32)\n"
+ ]
+ }
+ ],
+ "source": [
+ "for batch_x, batch_y in data.take(1):\n",
+ " print(batch_x, batch_y)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load data from a Generator"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Create a dummy generator.\n",
+ "def generate_features():\n",
+ " # Function to generate a random string.\n",
+ " def random_string(length):\n",
+ " return ''.join(random.choice(string.ascii_letters) for m in xrange(length))\n",
+ " # Return a random string, a random vector, and a random int.\n",
+ " yield random_string(4), np.random.uniform(size=4), random.randint(0, 10)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load a numpy array using tf data api with `from_tensor_slices`.\n",
+ "data = tf.data.Dataset.from_generator(generate_features, output_types=(tf.string, tf.float32, tf.int32))\n",
+ "# Refill data indefinitely.\n",
+ "data = data.repeat()\n",
+ "# Shuffle data.\n",
+ "data = data.shuffle(buffer_size=100)\n",
+ "# Batch data (aggregate records together).\n",
+ "data = data.batch(batch_size=4)\n",
+ "# Prefetch batch (pre-load batch for faster consumption).\n",
+ "data = data.prefetch(buffer_size=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "tf.Tensor(['snDw' 'NvMp' 'sXsw' 'qwuk'], shape=(4,), dtype=string) tf.Tensor(\n",
+ "[[0.22296238 0.03515657 0.3893014 0.6875752 ]\n",
+ " [0.05003363 0.27605608 0.23262134 0.10671499]\n",
+ " [0.8992419 0.34516433 0.29739627 0.8413017 ]\n",
+ " [0.91913974 0.7142106 0.48333576 0.04300505]], shape=(4, 4), dtype=float32) tf.Tensor([ 2 10 4 1], shape=(4,), dtype=int32)\n",
+ "tf.Tensor(['vdUx' 'InFi' 'nLzy' 'oklE'], shape=(4,), dtype=string) tf.Tensor(\n",
+ "[[0.6512162 0.8695475 0.7012295 0.6849636 ]\n",
+ " [0.00812997 0.01264008 0.7774404 0.44849646]\n",
+ " [0.92055863 0.894824 0.3628448 0.85603875]\n",
+ " [0.32219294 0.9767527 0.0307372 0.12051418]], shape=(4, 4), dtype=float32) tf.Tensor([9 7 4 0], shape=(4,), dtype=int32)\n",
+ "tf.Tensor(['ULGI' 'dBbm' 'URgs' 'Pkpt'], shape=(4,), dtype=string) tf.Tensor(\n",
+ "[[0.39586228 0.7472 0.3759462 0.9277406 ]\n",
+ " [0.44489694 0.38694733 0.9592599 0.82675934]\n",
+ " [0.12597603 0.299358 0.6940909 0.34155408]\n",
+ " [0.3401377 0.97620344 0.6047712 0.51667166]], shape=(4, 4), dtype=float32) tf.Tensor([ 4 10 0 0], shape=(4,), dtype=int32)\n",
+ "tf.Tensor(['kvao' 'wWvG' 'vrzf' 'cMgG'], shape=(4,), dtype=string) tf.Tensor(\n",
+ "[[0.8090979 0.65837437 0.9732402 0.9298921 ]\n",
+ " [0.67059356 0.91655296 0.52894515 0.8964492 ]\n",
+ " [0.05753202 0.45829964 0.74948853 0.41164723]\n",
+ " [0.42602295 0.8696292 0.57220364 0.9475169 ]], shape=(4, 4), dtype=float32) tf.Tensor([6 7 6 2], shape=(4,), dtype=int32)\n",
+ "tf.Tensor(['kyLQ' 'kxbI' 'CkQD' 'PHlJ'], shape=(4,), dtype=string) tf.Tensor(\n",
+ "[[0.29089147 0.6438517 0.31005543 0.31286424]\n",
+ " [0.0937152 0.8887667 0.24011584 0.25746483]\n",
+ " [0.47577712 0.53731906 0.9178111 0.3249844 ]\n",
+ " [0.38328 0.39294246 0.08126572 0.5995307 ]], shape=(4, 4), dtype=float32) tf.Tensor([3 1 3 2], shape=(4,), dtype=int32)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Display data.\n",
+ "for batch_str, batch_vector, batch_int in data.take(5):\n",
+ " print(batch_str, batch_vector, batch_int)"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v2/notebooks/5_DataManagement/tfrecords.ipynb b/tensorflow_v2/notebooks/5_DataManagement/tfrecords.ipynb
new file mode 100644
index 00000000..a72cffcd
--- /dev/null
+++ b/tensorflow_v2/notebooks/5_DataManagement/tfrecords.ipynb
@@ -0,0 +1,244 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Create and Load TFRecords\n",
+ "\n",
+ "A simple TensorFlow 2.0 example to parse a dataset into TFRecord format, and then read that dataset.\n",
+ "\n",
+ "In this example, the Titanic Dataset (in CSV format) will be used as a toy dataset, for parsing all the dataset features into TFRecord format, and then building an input pipeline that can be used for training models.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Titanic Dataset\n",
+ "\n",
+ "The titanic dataset is a popular dataset for ML that provides a list of all passengers onboard the Titanic, along with various features such as their age, sex, class (1st, 2nd, 3rd)... And if the passenger survived the disaster or not.\n",
+ "\n",
+ "It can be used to see that even though some luck was involved in surviving the sinking, some groups of people were more likely to survive than others, such as women, children, and the upper-class...\n",
+ "\n",
+ "#### Overview\n",
+ "survived|pclass|name|sex|age|sibsp|parch|ticket|fare\n",
+ "--------|------|----|---|---|-----|-----|------|----\n",
+ "1|1|\"Allen, Miss. Elisabeth Walton\"|female|29|0|0|24160|211.3375\n",
+ "1|1|\"Allison, Master. Hudson Trevor\"|male|0.9167|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Miss. Helen Loraine\"|female|2|1|2|113781|151.5500\n",
+ "0|1|\"Allison, Mr. Hudson Joshua Creighton\"|male|30|1|2|113781|151.5500\n",
+ "...|...|...|...|...|...|...|...|...\n",
+ "\n",
+ "\n",
+ "#### Variable Descriptions\n",
+ "```\n",
+ "survived Survived\n",
+ " (0 = No; 1 = Yes)\n",
+ "pclass Passenger Class\n",
+ " (1 = 1st; 2 = 2nd; 3 = 3rd)\n",
+ "name Name\n",
+ "sex Sex\n",
+ "age Age\n",
+ "sibsp Number of Siblings/Spouses Aboard\n",
+ "parch Number of Parents/Children Aboard\n",
+ "ticket Ticket Number\n",
+ "fare Passenger Fare\n",
+ "```"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import csv\n",
+ "import requests\n",
+ "import tensorflow as tf"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Download Titanic dataset (in csv format).\n",
+ "d = requests.get(\"https://raw.githubusercontent.com/tflearn/tflearn.github.io/master/resources/titanic_dataset.csv\")\n",
+ "with open(\"titanic_dataset.csv\", \"wb\") as f:\n",
+ " f.write(d.content)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Create TFRecords"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Generate Integer Features.\n",
+ "def build_int64_feature(data):\n",
+ " return tf.train.Feature(int64_list=tf.train.Int64List(value=[data]))\n",
+ "\n",
+ "# Generate Float Features.\n",
+ "def build_float_feature(data):\n",
+ " return tf.train.Feature(float_list=tf.train.FloatList(value=[data]))\n",
+ "\n",
+ "# Generate String Features.\n",
+ "def build_string_feature(data):\n",
+ " return tf.train.Feature(bytes_list=tf.train.BytesList(value=[data]))\n",
+ "\n",
+ "# Generate a TF `Example`, parsing all features of the dataset.\n",
+ "def convert_to_tfexample(survived, pclass, name, sex, age, sibsp, parch, ticket, fare):\n",
+ " return tf.train.Example(\n",
+ " features=tf.train.Features(\n",
+ " feature={\n",
+ " 'survived': build_int64_feature(survived),\n",
+ " 'pclass': build_int64_feature(pclass),\n",
+ " 'name': build_string_feature(name),\n",
+ " 'sex': build_string_feature(sex),\n",
+ " 'age': build_float_feature(age),\n",
+ " 'sibsp': build_int64_feature(sibsp),\n",
+ " 'parch': build_int64_feature(parch),\n",
+ " 'ticket': build_string_feature(ticket),\n",
+ " 'fare': build_float_feature(fare),\n",
+ " })\n",
+ " )"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Open dataset file.\n",
+ "with open(\"titanic_dataset.csv\") as f:\n",
+ " # Output TFRecord file.\n",
+ " with tf.io.TFRecordWriter(\"titanic_dataset.tfrecord\") as w:\n",
+ " # Generate a TF Example for all row in our dataset.\n",
+ " # CSV reader will read and parse all rows.\n",
+ " reader = csv.reader(f, skipinitialspace=True)\n",
+ " for i, record in enumerate(reader):\n",
+ " # Skip header.\n",
+ " if i == 0:\n",
+ " continue\n",
+ " survived, pclass, name, sex, age, sibsp, parch, ticket, fare = record\n",
+ " # Parse each csv row to TF Example using the above functions.\n",
+ " example = convert_to_tfexample(int(survived), int(pclass), name, sex, float(age), int(sibsp), int(parch), ticket, float(fare))\n",
+ " # Serialize each TF Example to string, and write to TFRecord file.\n",
+ " w.write(example.SerializeToString())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Load TFRecords"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Build features template, with types.\n",
+ "features = {\n",
+ " 'survived': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'pclass': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'name': tf.io.FixedLenFeature([], tf.string),\n",
+ " 'sex': tf.io.FixedLenFeature([], tf.string),\n",
+ " 'age': tf.io.FixedLenFeature([], tf.float32),\n",
+ " 'sibsp': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'parch': tf.io.FixedLenFeature([], tf.int64),\n",
+ " 'ticket': tf.io.FixedLenFeature([], tf.string),\n",
+ " 'fare': tf.io.FixedLenFeature([], tf.float32),\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load TFRecord data.\n",
+ "filenames = [\"titanic_dataset.tfrecord\"]\n",
+ "data = tf.data.TFRecordDataset(filenames)\n",
+ "\n",
+ "# Parse features, using the above template.\n",
+ "def parse_record(record):\n",
+ " return tf.io.parse_single_example(record, features=features)\n",
+ "# Apply the parsing to each record from the dataset.\n",
+ "data = data.map(parse_record)\n",
+ "\n",
+ "# Refill data indefinitely.\n",
+ "data = data.repeat()\n",
+ "# Shuffle data.\n",
+ "data = data.shuffle(buffer_size=1000)\n",
+ "# Batch data (aggregate records together).\n",
+ "data = data.batch(batch_size=4)\n",
+ "# Prefetch batch (pre-load batch for faster consumption).\n",
+ "data = data.prefetch(buffer_size=1)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "[0 1 0 0]\n",
+ "['Gallagher, Mr. Martin' 'Fortune, Miss. Mabel Helen'\n",
+ " 'Andersson, Mr. Johan Samuel' 'Jensen, Mr. Niels Peder']\n",
+ "[ 7.7417 263. 7.775 7.8542]\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Dequeue data and display.\n",
+ "for record in data.take(1):\n",
+ " print(record['survived'].numpy())\n",
+ " print(record['name'].numpy())\n",
+ " print(record['fare'].numpy())"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.15"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/tensorflow_v2/notebooks/6_Hardware/multigpu_training.ipynb b/tensorflow_v2/notebooks/6_Hardware/multigpu_training.ipynb
new file mode 100644
index 00000000..53d664f0
--- /dev/null
+++ b/tensorflow_v2/notebooks/6_Hardware/multigpu_training.ipynb
@@ -0,0 +1,371 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Multi-GPU Training Example\n",
+ "\n",
+ "Train a convolutional neural network on multiple GPU with TensorFlow 2.0+.\n",
+ "\n",
+ "- Author: Aymeric Damien\n",
+ "- Project: https://github.com/nebulaai/TensorFlow-Examples/"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Training with multiple GPU cards\n",
+ "\n",
+ "In this example, we are using data parallelism to split the training accross multiple GPUs. Each GPU has a full replica of the neural network model, and the weights (i.e. variables) are updated synchronously by waiting that each GPU process its batch of data.\n",
+ "\n",
+ "First, each GPU process a distinct batch of data and compute the corresponding gradients, then, all gradients are accumulated in the CPU and averaged. The model weights are finally updated with the gradients averaged, and the new model weights are sent back to each GPU, to repeat the training process.\n",
+ "\n",
+ "
\n",
+ "\n",
+ "## CIFAR10 Dataset Overview\n",
+ "\n",
+ "The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images.\n",
+ "\n",
+ "\n",
+ "\n",
+ "More info: https://www.cs.toronto.edu/~kriz/cifar.html"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "from __future__ import absolute_import, division, print_function\n",
+ "\n",
+ "import tensorflow as tf\n",
+ "from tensorflow.keras import Model, layers\n",
+ "import time\n",
+ "import numpy as np"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# MNIST dataset parameters.\n",
+ "num_classes = 10 # total classes (0-9 digits).\n",
+ "num_gpus = 4\n",
+ "\n",
+ "# Training parameters.\n",
+ "learning_rate = 0.001\n",
+ "training_steps = 1000\n",
+ "# Split batch size equally between GPUs.\n",
+ "# Note: Reduce batch size if you encounter OOM Errors.\n",
+ "batch_size = 1024 * num_gpus\n",
+ "display_step = 20\n",
+ "\n",
+ "# Network parameters.\n",
+ "conv1_filters = 64 # number of filters for 1st conv layer.\n",
+ "conv2_filters = 128 # number of filters for 2nd conv layer.\n",
+ "conv3_filters = 256 # number of filters for 2nd conv layer.\n",
+ "fc1_units = 2048 # number of neurons for 1st fully-connected layer."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Prepare MNIST data.\n",
+ "from tensorflow.keras.datasets import cifar10\n",
+ "(x_train, y_train), (x_test, y_test) = cifar10.load_data()\n",
+ "# Convert to float32.\n",
+ "x_train, x_test = np.array(x_train, np.float32), np.array(x_test, np.float32)\n",
+ "# Normalize images value from [0, 255] to [0, 1].\n",
+ "x_train, x_test = x_train / 255., x_test / 255.\n",
+ "y_train, y_test = np.reshape(y_train, (-1)), np.reshape(y_test, (-1))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Use tf.data API to shuffle and batch data.\n",
+ "train_data = tf.data.Dataset.from_tensor_slices((x_train, y_train))\n",
+ "train_data = train_data.repeat().shuffle(batch_size * 10).batch(batch_size).prefetch(num_gpus)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "class ConvNet(Model):\n",
+ " # Set layers.\n",
+ " def __init__(self):\n",
+ " super(ConvNet, self).__init__()\n",
+ " \n",
+ " # Convolution Layer with 64 filters and a kernel size of 3.\n",
+ " self.conv1_1 = layers.Conv2D(conv1_filters, kernel_size=3, padding='SAME', activation=tf.nn.relu)\n",
+ " self.conv1_2 = layers.Conv2D(conv1_filters, kernel_size=3, padding='SAME', activation=tf.nn.relu)\n",
+ " # Max Pooling (down-sampling) with kernel size of 2 and strides of 2. \n",
+ " self.maxpool1 = layers.MaxPool2D(2, strides=2)\n",
+ "\n",
+ " # Convolution Layer with 128 filters and a kernel size of 3.\n",
+ " self.conv2_1 = layers.Conv2D(conv2_filters, kernel_size=3, padding='SAME', activation=tf.nn.relu)\n",
+ " self.conv2_2 = layers.Conv2D(conv2_filters, kernel_size=3, padding='SAME', activation=tf.nn.relu)\n",
+ " self.conv2_3 = layers.Conv2D(conv2_filters, kernel_size=3, padding='SAME', activation=tf.nn.relu)\n",
+ " # Max Pooling (down-sampling) with kernel size of 2 and strides of 2. \n",
+ " self.maxpool2 = layers.MaxPool2D(2, strides=2)\n",
+ "\n",
+ " # Convolution Layer with 256 filters and a kernel size of 3.\n",
+ " self.conv3_1 = layers.Conv2D(conv3_filters, kernel_size=3, padding='SAME', activation=tf.nn.relu)\n",
+ " self.conv3_2 = layers.Conv2D(conv3_filters, kernel_size=3, padding='SAME', activation=tf.nn.relu)\n",
+ " self.conv3_3 = layers.Conv2D(conv3_filters, kernel_size=3, padding='SAME', activation=tf.nn.relu)\n",
+ "\n",
+ " # Flatten the data to a 1-D vector for the fully connected layer.\n",
+ " self.flatten = layers.Flatten()\n",
+ "\n",
+ " # Fully connected layer.\n",
+ " self.fc1 = layers.Dense(1024, activation=tf.nn.relu)\n",
+ " # Apply Dropout (if is_training is False, dropout is not applied).\n",
+ " self.dropout = layers.Dropout(rate=0.5)\n",
+ "\n",
+ " # Output layer, class prediction.\n",
+ " self.out = layers.Dense(num_classes)\n",
+ "\n",
+ " # Set forward pass.\n",
+ " @tf.function\n",
+ " def call(self, x, is_training=False):\n",
+ " x = self.conv1_1(x)\n",
+ " x = self.conv1_2(x)\n",
+ " x = self.maxpool1(x)\n",
+ " x = self.conv2_1(x)\n",
+ " x = self.conv2_2(x)\n",
+ " x = self.conv2_3(x)\n",
+ " x = self.maxpool2(x)\n",
+ " x = self.conv3_1(x)\n",
+ " x = self.conv3_2(x)\n",
+ " x = self.conv3_3(x)\n",
+ " x = self.flatten(x)\n",
+ " x = self.fc1(x)\n",
+ " x = self.dropout(x, training=is_training)\n",
+ " x = self.out(x)\n",
+ " if not is_training:\n",
+ " # tf cross entropy expect logits without softmax, so only\n",
+ " # apply softmax when not training.\n",
+ " x = tf.nn.softmax(x)\n",
+ " return x"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Cross-Entropy Loss.\n",
+ "# Note that this will apply 'softmax' to the logits.\n",
+ "@tf.function\n",
+ "def cross_entropy_loss(x, y):\n",
+ " # Convert labels to int 64 for tf cross-entropy function.\n",
+ " y = tf.cast(y, tf.int64)\n",
+ " # Apply softmax to logits and compute cross-entropy.\n",
+ " loss = tf.nn.sparse_softmax_cross_entropy_with_logits(labels=y, logits=x)\n",
+ " # Average loss across the batch.\n",
+ " return tf.reduce_mean(loss)\n",
+ "\n",
+ "# Accuracy metric.\n",
+ "@tf.function\n",
+ "def accuracy(y_pred, y_true):\n",
+ " # Predicted class is the index of highest score in prediction vector (i.e. argmax).\n",
+ " correct_prediction = tf.equal(tf.argmax(y_pred, 1), tf.cast(y_true, tf.int64))\n",
+ " return tf.reduce_mean(tf.cast(correct_prediction, tf.float32), axis=-1)\n",
+ " \n",
+ "\n",
+ "@tf.function\n",
+ "def backprop(batch_x, batch_y, trainable_variables):\n",
+ " # Wrap computation inside a GradientTape for automatic differentiation.\n",
+ " with tf.GradientTape() as g:\n",
+ " # Forward pass.\n",
+ " pred = conv_net(batch_x, is_training=True)\n",
+ " # Compute loss.\n",
+ " loss = cross_entropy_loss(pred, batch_y)\n",
+ " # Compute gradients.\n",
+ " gradients = g.gradient(loss, trainable_variables)\n",
+ " return gradients\n",
+ "\n",
+ "# Build the function to average the gradients.\n",
+ "@tf.function\n",
+ "def average_gradients(tower_grads):\n",
+ " avg_grads = []\n",
+ " for tgrads in zip(*tower_grads):\n",
+ " grads = []\n",
+ " for g in tgrads:\n",
+ " expanded_g = tf.expand_dims(g, 0)\n",
+ " grads.append(expanded_g)\n",
+ " \n",
+ " grad = tf.concat(axis=0, values=grads)\n",
+ " grad = tf.reduce_mean(grad, 0)\n",
+ " \n",
+ " avg_grads.append(grad)\n",
+ " \n",
+ " return avg_grads"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "with tf.device('/cpu:0'):\n",
+ " # Build convnet.\n",
+ " conv_net = ConvNet()\n",
+ " # Stochastic gradient descent optimizer.\n",
+ " optimizer = tf.optimizers.Adam(learning_rate)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Optimization process.\n",
+ "def run_optimization(x, y):\n",
+ " # Save gradients for all GPUs.\n",
+ " tower_grads = []\n",
+ " # Variables to update, i.e. trainable variables.\n",
+ " trainable_variables = conv_net.trainable_variables\n",
+ "\n",
+ " with tf.device('/cpu:0'):\n",
+ " for i in range(num_gpus):\n",
+ " # Split data between GPUs.\n",
+ " gpu_batch_size = int(batch_size/num_gpus)\n",
+ " batch_x = x[i * gpu_batch_size: (i+1) * gpu_batch_size]\n",
+ " batch_y = y[i * gpu_batch_size: (i+1) * gpu_batch_size]\n",
+ " \n",
+ " # Build the neural net on each GPU.\n",
+ " with tf.device('/gpu:%i' % i):\n",
+ " grad = backprop(batch_x, batch_y, trainable_variables)\n",
+ " tower_grads.append(grad)\n",
+ " \n",
+ " # Last GPU Average gradients from all GPUs.\n",
+ " if i == num_gpus - 1:\n",
+ " gradients = average_gradients(tower_grads)\n",
+ "\n",
+ " # Update vars following gradients.\n",
+ " optimizer.apply_gradients(zip(gradients, trainable_variables))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "step: 1, loss: 2.302630, accuracy: 0.101318, speed: 16342.138481 examples/sec\n",
+ "step: 20, loss: 2.296755, accuracy: 0.108398, speed: 5355.197204 examples/sec\n",
+ "step: 40, loss: 2.216037, accuracy: 0.299072, speed: 12388.080848 examples/sec\n",
+ "step: 60, loss: 2.189814, accuracy: 0.362305, speed: 12033.404638 examples/sec\n",
+ "step: 80, loss: 2.137831, accuracy: 0.410156, speed: 12189.852065 examples/sec\n",
+ "step: 100, loss: 2.102876, accuracy: 0.437744, speed: 12212.349483 examples/sec\n",
+ "step: 120, loss: 2.077521, accuracy: 0.460693, speed: 12160.290400 examples/sec\n",
+ "step: 140, loss: 2.006775, accuracy: 0.545166, speed: 12202.175380 examples/sec\n",
+ "step: 160, loss: 1.994143, accuracy: 0.554443, speed: 12168.070368 examples/sec\n",
+ "step: 180, loss: 1.964281, accuracy: 0.597412, speed: 12244.148312 examples/sec\n",
+ "step: 200, loss: 1.893395, accuracy: 0.658203, speed: 12197.382402 examples/sec\n",
+ "step: 220, loss: 1.880256, accuracy: 0.672363, speed: 12178.323620 examples/sec\n",
+ "step: 240, loss: 1.868853, accuracy: 0.676025, speed: 12224.851444 examples/sec\n",
+ "step: 260, loss: 1.837151, accuracy: 0.705322, speed: 12101.154436 examples/sec\n",
+ "step: 280, loss: 1.799418, accuracy: 0.736816, speed: 12185.701420 examples/sec\n",
+ "step: 300, loss: 1.790719, accuracy: 0.755615, speed: 12126.826668 examples/sec\n",
+ "step: 320, loss: 1.732242, accuracy: 0.807861, speed: 12229.926783 examples/sec\n",
+ "step: 340, loss: 1.732089, accuracy: 0.806885, speed: 12167.651100 examples/sec\n",
+ "step: 360, loss: 1.693968, accuracy: 0.835693, speed: 12060.687471 examples/sec\n",
+ "step: 380, loss: 1.665804, accuracy: 0.862305, speed: 12130.389108 examples/sec\n",
+ "step: 400, loss: 1.627162, accuracy: 0.890381, speed: 12152.946766 examples/sec\n",
+ "step: 420, loss: 1.594189, accuracy: 0.920654, speed: 12057.401941 examples/sec\n",
+ "step: 440, loss: 1.575212, accuracy: 0.929688, speed: 12196.589206 examples/sec\n",
+ "step: 460, loss: 1.569351, accuracy: 0.942383, speed: 12147.345871 examples/sec\n",
+ "step: 480, loss: 1.520648, accuracy: 0.974609, speed: 11998.473978 examples/sec\n",
+ "step: 500, loss: 1.507439, accuracy: 0.982666, speed: 12152.490287 examples/sec\n",
+ "step: 520, loss: 1.495090, accuracy: 0.989746, speed: 12071.718912 examples/sec\n",
+ "step: 540, loss: 1.490940, accuracy: 0.989502, speed: 12049.224039 examples/sec\n",
+ "step: 560, loss: 1.476727, accuracy: 0.996338, speed: 12134.827424 examples/sec\n",
+ "step: 580, loss: 1.475038, accuracy: 0.995850, speed: 12128.228532 examples/sec\n",
+ "step: 600, loss: 1.469776, accuracy: 0.997559, speed: 12113.386949 examples/sec\n",
+ "step: 620, loss: 1.466832, accuracy: 0.999756, speed: 11939.016031 examples/sec\n",
+ "step: 640, loss: 1.466991, accuracy: 0.999023, speed: 12095.815773 examples/sec\n",
+ "step: 660, loss: 1.466177, accuracy: 0.999023, speed: 12035.037908 examples/sec\n",
+ "step: 680, loss: 1.465074, accuracy: 0.999512, speed: 11789.118097 examples/sec\n",
+ "step: 700, loss: 1.464655, accuracy: 0.999512, speed: 11965.087437 examples/sec\n",
+ "step: 720, loss: 1.465109, accuracy: 0.999512, speed: 11855.853520 examples/sec\n",
+ "step: 740, loss: 1.465021, accuracy: 0.999023, speed: 11774.901096 examples/sec\n",
+ "step: 760, loss: 1.463057, accuracy: 1.000000, speed: 11930.138289 examples/sec\n",
+ "step: 780, loss: 1.462609, accuracy: 1.000000, speed: 11766.752011 examples/sec\n",
+ "step: 800, loss: 1.462320, accuracy: 0.999756, speed: 11744.213314 examples/sec\n",
+ "step: 820, loss: 1.462975, accuracy: 1.000000, speed: 11700.815885 examples/sec\n",
+ "step: 840, loss: 1.462328, accuracy: 1.000000, speed: 11759.141371 examples/sec\n",
+ "step: 860, loss: 1.462561, accuracy: 1.000000, speed: 11650.397252 examples/sec\n",
+ "step: 880, loss: 1.462608, accuracy: 0.999512, speed: 11581.170575 examples/sec\n",
+ "step: 900, loss: 1.462178, accuracy: 0.999756, speed: 11562.545711 examples/sec\n",
+ "step: 920, loss: 1.461582, accuracy: 1.000000, speed: 11616.172231 examples/sec\n",
+ "step: 940, loss: 1.462402, accuracy: 1.000000, speed: 11709.561795 examples/sec\n",
+ "step: 960, loss: 1.462436, accuracy: 1.000000, speed: 11629.547741 examples/sec\n",
+ "step: 980, loss: 1.462415, accuracy: 1.000000, speed: 11623.658645 examples/sec\n",
+ "step: 1000, loss: 1.461925, accuracy: 1.000000, speed: 11579.716701 examples/sec\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Run training for the given number of steps.\n",
+ "ts = time.time()\n",
+ "for step, (batch_x, batch_y) in enumerate(train_data.take(training_steps), 1):\n",
+ " # Run the optimization to update W and b values.\n",
+ " run_optimization(batch_x, batch_y)\n",
+ " \n",
+ " if step % display_step == 0 or step == 1:\n",
+ " dt = time.time() - ts\n",
+ " speed = batch_size * display_step / dt\n",
+ " pred = conv_net(batch_x)\n",
+ " loss = cross_entropy_loss(pred, batch_y)\n",
+ " acc = accuracy(pred, batch_y)\n",
+ " print(\"step: %i, loss: %f, accuracy: %f, speed: %f examples/sec\" % (step, loss, acc, speed))\n",
+ " ts = time.time()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 2",
+ "language": "python",
+ "name": "python2"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 2
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython2",
+ "version": "2.7.18"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}