CIFAR_10_vs_MNIST_Autoencoder_End.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "28c458b5-b229-4a20-952d-1f8e493125c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.metrics import classification_report\n",
    "import tensorflow as tf\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import cv2\n",
    "import os\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "494f15b8-fd7d-4bb7-9f8c-0d78fcf82ee6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Metal device set to: Apple M1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-11-01 16:57:56.019756: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:305] Could not identify NUMA node of platform GPU ID 0, defaulting to 0. Your kernel may not have been built with NUMA support.\n",
      "2021-11-01 16:57:56.019852: I tensorflow/core/common_runtime/pluggable_device/pluggable_device_factory.cc:271] Created TensorFlow device (/job:localhost/replica:0/task:0/device:GPU:0 with 0 MB memory) -> physical PluggableDevice (device: 0, name: METAL, pci bus id: <undefined>)\n"
     ]
    }
   ],
   "source": [
    "(train_x, train_y), (test_x, test_y) = tf.keras.datasets.cifar10.load_data()\n",
    "(digit_x_train, digit_y_train), (digit_x_test, digit_y_test) = tf.keras.datasets.mnist.load_data()\n",
    "(fashion_x_train, fashion_y_train), (fashion_x_test, fashion_y_test) = tf.keras.datasets.fashion_mnist.load_data()\n",
    "\n",
    "digit_x_test = digit_x_test.reshape((-1, 28, 28, 1))\n",
    "fashion_x_test = fashion_x_test.reshape((-1, 28, 28, 1))\n",
    "\n",
    "train_x = train_x.astype('float32')/255\n",
    "test_x = test_x.astype('float32')/255\n",
    "\n",
    "digit_x_test = tf.image.resize(tf.image.grayscale_to_rgb(tf.Variable(digit_x_test)), (32, 32))\n",
    "fashion_x_test = tf.image.resize(tf.image.grayscale_to_rgb(tf.Variable(fashion_x_test)), (32, 32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e80ed423-4509-4f62-b05c-e77de427c3cf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            [(None, 32, 32, 3)]  0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d (Conv2D)                 (None, 32, 32, 32)   896         input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, 32, 32, 32)   9248        conv2d[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, 32, 32, 64)   18496       conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, 32, 32, 64)   36928       conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d (MaxPooling2D)    (None, 16, 16, 64)   0           conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, 16, 16, 128)  73856       max_pooling2d[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, 16, 16, 128)  147584      conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_1 (MaxPooling2D)  (None, 8, 8, 128)    0           conv2d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "flatten (Flatten)               (None, 8192)         0           max_pooling2d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "dense (Dense)                   (None, 128)          1048704     flatten[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_1 (Dense)                 (None, 128)          16512       dense[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "dense_3 (Dense)                 (None, 128)          16512       dense_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_2 (Dense)                 (None, 10)           1290        dense_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_4 (Dense)                 (None, 3072)         396288      dense_3[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 1,766,314\n",
      "Trainable params: 1,766,314\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "input_layer = tf.keras.layers.Input(train_x.shape[1:])\n",
    "\n",
    "main_x = tf.keras.layers.Conv2D(\n",
    "    32,\n",
    "    3,\n",
    "    activation = 'relu',\n",
    "    padding = 'same'\n",
    ")(input_layer)\n",
    "\n",
    "main_x = tf.keras.layers.Conv2D(\n",
    "    32,\n",
    "    3,\n",
    "    activation = 'relu',\n",
    "    padding = 'same'\n",
    ")(main_x)\n",
    "\n",
    "main_x = tf.keras.layers.Conv2D(\n",
    "    64,\n",
    "    3,\n",
    "    activation = 'relu',\n",
    "    padding = 'same'\n",
    ")(main_x)\n",
    "\n",
    "main_x = tf.keras.layers.Conv2D(\n",
    "    64,\n",
    "    3,\n",
    "    activation = 'relu',\n",
    "    padding = 'same'\n",
    ")(main_x)\n",
    "\n",
    "main_x = tf.keras.layers.MaxPool2D(2)(main_x)\n",
    "\n",
    "main_x = tf.keras.layers.Conv2D(\n",
    "    128,\n",
    "    3,\n",
    "    activation = 'relu',\n",
    "    padding = 'same'\n",
    ")(main_x)\n",
    "\n",
    "main_x = tf.keras.layers.Conv2D(\n",
    "    128,\n",
    "    3,\n",
    "    activation = 'relu',\n",
    "    padding = 'same'\n",
    ")(main_x)\n",
    "\n",
    "main_x = tf.keras.layers.MaxPool2D(2)(main_x)\n",
    "main_x = tf.keras.layers.Flatten()(main_x)\n",
    "\n",
    "main_x = tf.keras.layers.Dense(128, activation = 'relu')(main_x)\n",
    "main_x = tf.keras.layers.Dense(128, activation = 'relu')(main_x)\n",
    "main_output = tf.keras.layers.Dense(10, activation = 'softmax')(main_x)\n",
    "\n",
    "ood_x = tf.keras.layers.Dense(128, activation = 'relu')(main_x)\n",
    "ood_output = tf.keras.layers.Dense(32*32*3, activation = 'sigmoid')(ood_x)\n",
    "\n",
    "model = tf.keras.models.Model(input_layer, [main_output, ood_output])\n",
    "model.compile(\n",
    "    loss = ['sparse_categorical_crossentropy', 'cosine_similarity'],\n",
    "    optimizer = 'adam'\n",
    ")\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "13c4c88d-ed2d-4998-816d-576c01d92e82",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-11-01 16:57:56.908165: I tensorflow/compiler/mlir/mlir_graph_optimization_pass.cc:185] None of the MLIR Optimization Passes are enabled (registered 2)\n",
      "2021-11-01 16:57:56.909167: W tensorflow/core/platform/profile_utils/cpu_utils.cc:128] Failed to get CPU frequency: 0 Hz\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-11-01 16:57:57.110802: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:112] Plugin optimizer for device_type GPU is enabled.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "157/157 [==============================] - ETA: 0s - loss: 0.7690 - dense_2_loss: 1.6860 - dense_4_loss: -0.9170"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-11-01 16:58:22.417341: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:112] Plugin optimizer for device_type GPU is enabled.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "157/157 [==============================] - 28s 174ms/step - loss: 0.7690 - dense_2_loss: 1.6860 - dense_4_loss: -0.9170 - val_loss: 0.4897 - val_dense_2_loss: 1.4165 - val_dense_4_loss: -0.9268\n",
      "Epoch 2/100\n",
      "157/157 [==============================] - 27s 170ms/step - loss: 0.3031 - dense_2_loss: 1.2327 - dense_4_loss: -0.9296 - val_loss: 0.2373 - val_dense_2_loss: 1.1687 - val_dense_4_loss: -0.9314\n",
      "Epoch 3/100\n",
      "157/157 [==============================] - 27s 170ms/step - loss: 0.0545 - dense_2_loss: 0.9867 - dense_4_loss: -0.9323 - val_loss: -0.0035 - val_dense_2_loss: 0.9315 - val_dense_4_loss: -0.9350\n",
      "Epoch 4/100\n",
      "157/157 [==============================] - 26s 167ms/step - loss: -0.1202 - dense_2_loss: 0.8141 - dense_4_loss: -0.9343 - val_loss: -0.0013 - val_dense_2_loss: 0.9335 - val_dense_4_loss: -0.9348\n",
      "Epoch 5/100\n",
      "157/157 [==============================] - 27s 171ms/step - loss: -0.2534 - dense_2_loss: 0.6827 - dense_4_loss: -0.9361 - val_loss: -0.1216 - val_dense_2_loss: 0.8168 - val_dense_4_loss: -0.9384\n",
      "Epoch 6/100\n",
      "157/157 [==============================] - 26s 167ms/step - loss: -0.3802 - dense_2_loss: 0.5573 - dense_4_loss: -0.9375 - val_loss: -0.1798 - val_dense_2_loss: 0.7585 - val_dense_4_loss: -0.9383\n",
      "Epoch 7/100\n",
      "157/157 [==============================] - 26s 166ms/step - loss: -0.4842 - dense_2_loss: 0.4540 - dense_4_loss: -0.9381 - val_loss: -0.1113 - val_dense_2_loss: 0.8276 - val_dense_4_loss: -0.9390\n",
      "Epoch 8/100\n",
      "157/157 [==============================] - 26s 167ms/step - loss: -0.5929 - dense_2_loss: 0.3457 - dense_4_loss: -0.9386 - val_loss: -0.0593 - val_dense_2_loss: 0.8801 - val_dense_4_loss: -0.9393\n",
      "Epoch 9/100\n",
      "157/157 [==============================] - 26s 169ms/step - loss: -0.6870 - dense_2_loss: 0.2520 - dense_4_loss: -0.9389 - val_loss: -0.0223 - val_dense_2_loss: 0.9167 - val_dense_4_loss: -0.9389\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x288d85a60>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x_train_output = (train_x).reshape((train_x.shape[0], -1))\n",
    "x_test_output = (test_x).reshape((test_x.shape[0], -1))\n",
    "\n",
    "digit_test_output = digit_x_test.numpy().reshape((digit_x_test.shape[0], -1))\n",
    "fashion_test_output = fashion_x_test.numpy().reshape((digit_x_test.shape[0], -1))\n",
    "\n",
    "model.fit(\n",
    "    train_x,\n",
    "    [train_y, x_train_output],\n",
    "    validation_split = 0.2,\n",
    "    epochs = 100,\n",
    "    batch_size = 256,\n",
    "    callbacks = [tf.keras.callbacks.EarlyStopping(min_delta = 0.03, patience = 3, restore_best_weights = True)]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "ab8a67cc-bf56-43be-822e-48255435e76f",
   "metadata": {},
   "outputs": [],
   "source": [
    "cifar_10_class_mapping = dict(zip(\n",
    "    range(10), ['airplane', 'automobile', 'bird', 'cat', 'deer', 'dog', 'frog', 'horse', 'ship', 'truck']\n",
    "))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "6066a025-97d0-4967-ae22-806e433939dd",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-11-01 17:01:56.620448: I tensorflow/core/grappler/optimizers/custom_graph_optimizer_registry.cc:112] Plugin optimizer for device_type GPU is enabled.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.9380527\n",
      "0.03908347\n",
      "-0.8794275093823671\n"
     ]
    }
   ],
   "source": [
    "preds, autoencode = model.predict(train_x)\n",
    "preds = preds.argmax(axis = 1)\n",
    "preds = [cifar_10_class_mapping[pred] for pred in preds]\n",
    "similarities = tf.keras.losses.cosine_similarity(x_train_output.astype('float32'), autoencode.astype('float32')).numpy()\n",
    "print(similarities.mean())\n",
    "print(similarities.std())\n",
    "\n",
    "threshold = similarities.mean() + 1.5*similarities.std()\n",
    "print(threshold)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "1820b163",
   "metadata": {},
   "outputs": [],
   "source": [
    "preds, autoencode = model.predict(test_x)\n",
    "preds = preds.argmax(axis = 1)\n",
    "preds = [cifar_10_class_mapping[pred] for pred in preds]\n",
    "similarities = tf.keras.losses.cosine_similarity(x_test_output.astype('float32'), autoencode.astype('float32')).numpy()\n",
    "trust = similarities <= threshold"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bdc28eae",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True     9317\n",
       "False     683\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(trust).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "7dc49f5e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "    airplane       0.75      0.82      0.78      1000\n",
      "  automobile       0.87      0.85      0.86      1000\n",
      "        bird       0.67      0.57      0.62      1000\n",
      "         cat       0.57      0.58      0.57      1000\n",
      "        deer       0.63      0.76      0.69      1000\n",
      "         dog       0.64      0.65      0.65      1000\n",
      "        frog       0.79      0.79      0.79      1000\n",
      "       horse       0.83      0.74      0.78      1000\n",
      "        ship       0.86      0.83      0.85      1000\n",
      "       truck       0.83      0.84      0.83      1000\n",
      "\n",
      "    accuracy                           0.74     10000\n",
      "   macro avg       0.75      0.74      0.74     10000\n",
      "weighted avg       0.75      0.74      0.74     10000\n",
      "\n"
     ]
    }
   ],
   "source": [
    "print(classification_report([cifar_10_class_mapping[val] for val in test_y.flatten()], preds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "261bbfc7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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G9zHcEx3DsKq+qIddX4ug03jpPh7CQn70CKqaqupf5fvt5dXmYnE2whPPj7Gwn/aMiDQQRgj+EsBB+bn7Gnq/jveGlyG8ewfCA8rZCPqLFQgjEujaf+EalfDLk39CeOe+Orf35r2xV1XvR3hd+1iLeD+EcBxPzu+TvwVr73z3bLNOVf8LYRTjOQh9uKDoUR/9BdKsCBQI+qiTZ+vk94uj83KvjRtV9bmqulpVX4gwCvHjfPWN3jY5xyKc2+/n19iVANbnD7hHzGUyHu2nGzF/H8237Z4y17avRQgUujkF4c3F9XmQcx2AHyH4M1R1h6q+RlWfoKonItxnZvvrFgBHRdfxyZij7xFGidbBBjb+Qah+XlVPUtXVCEHJ4Qiv5Wf386950N5R1UsRXg2f4LcWmDdIUdVdCNHO34nImSJSy0/u5xCio4WVuYHPA3iJiDxTwi+C3oe9P5nDCEPn4yLyRAD/s9cNNbx3/TyA/w9hKOtq4JGfp71GRFbkkftuhNEKj9fm9p/S9fdyAC/ONR23Izyxvjh/Ev0TBAHSLFsAHJHrImZvWj8E8CERaYrIkxGG8mafsP8vgA/mN8rZn8Sd3eMhfxzAn4nIsRJ4cm7j1wAcJ+FntFUJPzU9AcBXVPVehHee78v75dkIQ/ezXI5wLl+YP5E2JfyM9pAetl1MhhG+QLcBqIrIe1C8kK4A8C4RWSlBR/PGrnU/BrBbRN4pIgP5cZwkIr8MPPqzYG+n+TXxHgB/L0FjMJhfF2eJSK/vboGF/cjjIgDvkEd1N48JIrJKRF6D8GX6F/nT4kJ+uifUEa6JbQA6InIWwjD+opKf1yMl/HTzdIT+BoLvzCCMig0ijMZ2swXhi3CWZQhfItvydn8bXUGGPPpz8SMcG1aKyPtE5BgRSST8suV3APzXIhzifAwjPDWP5v7/9j3cvnCf6uKTCE/KHVX9wV7a9kUAJ4nIy3Nffg+AG/MncUN+32rm19rbEEZtL81Xfw/hVf278nvZsxDO9TcRAslD8ej19Yb8uE4BcH8+yvOs/F7VFJG3Izz9/2eXnStF5Lzcl16BMCL3n7ldrxCRofy8vgAhELyqy+56fnwCoJbvI8nXnSW5Pin/HvtThFGP7uN+Zr6/z0Vdch2A5+QP2xCRpyAEjjfmy0eLyOrc5rMQhMofAABVvR3hVeV7c3tehqDx+kK+7W+IyPH5Ma1F0Cv+dz6qMntNNRGClyRv45HRXRH5H3mdtQgatH/rOq/XIYzCH5S3fy7CyPC8OrsFf4Ksqh9GGK34S4Qv7x8hPImesdBQX1cbtyAMuX0W4Ql3DEE419P2EW9DiOLHEJ5u3J+uzcOnESLOz2mXWAzhyXajhKHR30eX0HIWCeLFIwD8vao+1PV3FUJHn5N/if0BQoDwAMLISvdv82cdbruIzP407Zy83QcRLoz3qurV+bq/RXD8b4nIGMLN7Wk9HutHEL6sv4Vw7i4BMKCq2xFEi29FuFG/A8Cvqers67tX5/vYgRANPzI0nX9ZnY3gE9sQfOHteNSX5tx2kfkmgqDwdoTXDtMoDl+/H6Hf70HQfnweub/lryBegnCzugfhteXHEZ6qgXBju3auHavqRxBEyX+CR/vgjQgjcAvSix/NselXEXQAv9vLfvaCn0kYkr8T4Yb+h6r6nq718/lpz+SvjN6E4Js7EXzmqnk32jOekR/HbgSdxnKEXzvclK//JILPPIAwHB0HDJcAOEHCq50vqerPEfRR1yJ8yf0SHv0iA4K/zLYX00Los3/P7bkZwQ9ft09HuDDvQ9BM7ELwmyvnr27w7lNAeDA9CV0PqBIS0o2jR1R1G0JA/kGE8/80BL3HbHvvFpGvd21yLsL3xlYEkfvzZ7978ofKsxFeF+5C+E54rarelj+tP3J9IdyTsnw5RQjkPpbb8ACCbums/P44+7rj1xG+c3Yh/MLr7K775Jvz7UYRHnx/V7t+Roxw351C+AHKxfnn/ydfdwaAG0VkAuGh8UrYYPk8AFdq8RUr8ldaFyL8dHgMIcD4c1WdzfHyPxB+XTeGMKL2mvw7eJZXATg1P+6LALwiPydACIq+gUd/oZchjELOcm5+HB9DCIym8j6f5W/z/vhF/r/7XvUXCCLdG/J1fwjg5ao6inmY/UnTfkVEhhCMPLb7XRshjxUi8j8RBMXP7aHuxxGC2G8+9paRpY6I/AmAbar6jwtWXuJIeFW/FUFjdUe/7SEHPvstSBGRlyBoWAThqeRpCI6+/6MkcsAj4eehRyE8/R6L8DT5UVX9m37aRchSRkIiw19T1V/tty3k8cH+zDR4NsIQoSDoFl7FAIU8htQR3okeiTBq91mEXD2EkL1ARDYi3L9f2l9LyOOJvrzuIYQQQghZiMdsFmRCCCGEkH2BQQohhBBCSgmDFEIIIYSUEgYphBBCCCklDFIIIYQQUkoYpBBCCCGklDBIIYQQQkgpYZBCCCGEkFLCIIUQQgghpYRBCiGEEEJKCYMUQgghhJQSBimEEEIIKSUMUgghhBBSShikEEIIIaSUMEghhBBCSClhkEIIIYSQUsIghRBCCCGlhEEKIYQQQkoJgxRCCCGElBIGKYQQQggpJQxSCCGEEFJKGKQQQgghpJQwSCGEEEJIKWGQQgghhJBSwiCFEEIIIaWEQQohhBBCSgmDFEIIIYSUEgYphBBCCCklDFIIIYQQUkoYpBBCCCGklDBIIYQQQkgpYZBCCCGEkFLCIIUQQgghpYRBCiGEEEJKCYMUQgghhJQSBimEEEIIKSUMUgghhBBSShikEEIIIaSUMEghhBBCSClhkEIIIYSQUsIghRBCCCGlhEEKIYQQQkoJgxRCCCGElBIGKYQQQggpJQxSCCGEEFJKGKQQQgghpJQwSCkxInKmiPxCRO4UkQv6bQ8hiwV9mxDSC6Kq/baBOIhIBcDtAJ4PYBOA6wCco6o/76thhOwj9G1CSK9U+20AmZPTANypqncDgIh8FsDZAOa8kS8bHtBVa4aLhbJ3O1f0Grz2sgOvrV7L9q51t9CY2tv+RJ1jFLutqeY0L15/OUXew0MvJf7ZsKW9nN94q9Ftk5gYm9lLjyqwR769fPmArl27olDmnt74nHjnradehDm/onbQudcHPNeKqH11bE0cH/OOKS5yT5Bja+ZU84bWNWpR/AOy7Yvdg9ePZstePawnO7yLsFhn84M7MDXV+qaqntnjnsl+hEFKeTkYwP1dy5sAPG2+DVatGcab3//KQpk4dxRJimXezTbTjrMH74KvRMvel0Bq289smSYztvn4e8exoeN9oWfOTb9aLMu0bepUxd5Ek7RiyrTqHFNSvCmLY4N4l1zi3OAd2zpxPzrH7d/f7TFlWXx+bVtJUtzuH//4O27re8Ee+fbatSvwoQ+/tlDWdvq2WmsVC9o121hmfUwTJwCpFPs/6TRMnbbpQ/9L3noPkFaK5zJt2S3rNedLvm1bSyO/rng+nFl/mkrtOa87xqZZ0WcrNcevW9avZ+pTpqzaHrC2xQFh3QlknPtF0nD6YqZYloh3nRbrvOsdl+KuOzczQCkp1KSUl54eA0XkfBG5XkSuHx+zNwVCSsiCvt3t17t3068JebzCIKW8bAJwaNfyIQAejCup6sWqeqqqnjo0bJ9SCCkhC/p2t18vX06/JuTxCl/3lJfrABwrIkcCeADAqwC8er4NOmhhtDCKDvfFczUrDndWKs7rDOdZ132HLcUhdaMLmGPLzKlXdd5XI4nqOXZ1Jp2ycVuxMRQd96B1f63YIfx2pWXree/WI1vjZQBQZ9jae1Rw3kCgmhULxXlFk6lna922H70GdN4QWO3BYqhRAnvk2ypAGr1KQzZh6rXGi+e3WrGvOFI4r4BSxz/Hor5NrJN1nNd01cx5Hem8Hsmmin4gjhO0nFc73usLReSzmW2r3XFeHVVsvanUeU0avWZsOT5cS21fJ7YIWcP2Y6rFc1Kxb+QA7xXTtD2mSvRaK6s676/MYfPHI2WGQUpJUdWOiLwRwDcRXmt/QlVv6bNZhOwz9G1CSK8wSCkxqvo1AF/rtx2ELDb0bUJIL1CTQgghhJBSwiCFEEIIIaWEr3sOICRLkEwWfwlhRHUA0npRXKmJreNpWJ10J4BE23q5yhxVZtsRvXUmrKhxxerBYp3MCkNrnhjSyaOR7SiK6iqT1v2TZU7OjJqTo6FjxahxfopO21EOOsJEdQSYUre2xYng2pVpU6fjnaMZJ29GLFyOhamwuTu0s3jK2T1Cgaxd3Hen5eQt6USiSXXyaKjts6TlCJy1qN5MnTpesrJUrF3ZmN2nRkLQZmLP95Qj/M3atl49ErJKzfqmp9cWtfZr3RNZF/sia9vtprxsMM63S2Xc3muyyNeTtuNnTSePT2r7uh7ljOlk1tZaWtwfk66XG46kEEIIIaSUMEghhBBCSClhkEIIIYSQUkJNygFE1hJM31c8pbVBJyHU8uJy2nQ0KY7Mo5bYwkr0Ptck3YL/zlc7TtKrGWtHvbW2sLy80jR1dqc7bFup1a60Z4plHdg6FWeuI68vhpIhu21WrDgzsdu2lTrzvTj6E02tNiCVorYhrdi+brUcnYST+KwSaVJSb36lyeI7/8xJerZ/UFSic9VxEuU1It9LU6sFqTjz+WSOzimLtQzOPD2po82oOv047c0RFWmaJpNxW0dspt2s5SSVqxfPU9pxdDepfR7tONeqONfgTHRMmZOwriqOD1dtWx2112+jE+vaHE1K20li5yShnIgS2Q04uqHpSBemzvGQ8sCRFEIIIYSUEgYphBBCCCklDFIIIYQQUkoYpBBCCCGklFA4ewCh0sFMsrNQljmJziSaEVWnHdHkjJPArGZj2iwSoaVO3NtpW2GiOLOmqqNQ3T01VliuDdk6bbViwmzQ7rM6XDymqiO8G64vs9th2JQtr600ZZVKUcC4e9CKX8emtpuy3dNWYDs9400FWzxviTN7a8fJ2uXonc0Mvq3MEXfWi22pI7TcX8SzcquTiKwT9Y+XwKyjU6as5giCp2aivnXEtYmTMHDS6Uc4ic6yaDbjSuoki6tbH+iIPZlpJAhXsfurOucui48RQOYJu6N+FUewPe30T9UR62rd9n+UNw+VmhXXpjNOEruaIxCOZnaeVpvwrWpmOqdwtsxwJIUQQgghpYRBCiGEEEJKCYMUQgghhJQSalJKjIhsBDCGMLVfR1VP7a9FhCwO9G1CSC8wSCk/v6KqD/dSMUUHY1IUZiYtZ6bfaJbRxJuF15nUdKptRW/pTDQzr9XdoVmzjXllG9avN2XHHHFcYXl1Y4Wp007XmbJWxwoY05miwDabdoydtGrL1pSTkbRj+6LSKArwlg8uN3Wqq1eZso7afW6fsQLbe8c3FZZ3tq1btOPsnQBqHesDFXOCrQ0dxMLERRcY9ubbqtAok27FiB+BNBKfth1xduJk5HWSrKIdzZactBzRuDhZUJ1MyuoIzjvTxXrL6lYQ23GmtK44GVQ1TunszLSdqZP9NbF2NVp2nxNJ0f+Tacef6k7248weU+Jk3601igJzcbL7OpNEI205s1wPFG0dFCtet+1TOFtm+LqHEEIIIaWEQUq5UQDfEpGfiMj5/TaGkEWEvk0IWRC+7ik3z1LVB0VkHYCrReQ2Vf1ed4X8Bn8+ACxbYYc2CSkp8/p2t1+vWW0ncySEPD7gSEqJUdUH8/9bAXwRwGlOnYtV9VRVPbU5yJiTLA0W8u1uvx5ebmcDJoQ8PuC3WkkRkWUAElUdyz+/AMD7F9pOK0XhW7tlRWhx0s3agB2BmclsNkeNp68HUIuyrFaHbFtas0K+g1cca8qecdTTTVmjUnRRcYSPk+PWjbfd95Apk6QotBsattllm46AtOqo9nZO7DJlO7ZsLSwniRXkHXv8MaZMnenrx7Zb0eEJq48qLG9fPmLq3LbrHlPWTm3m0jh7bKVqRYhJs/gMI4v0SLPnvi3IouzAqSMqrcWukVmDW45wU9v2PCXRZSOOuFLbjuDcEbYmTubVSjXK1Jza861VW1bvWBF3O/JPbzy149iwrGPLZpytByNhbrthjxtOWyq2rytO+uNOdI9qO0LjStvpV6ev62nxfpQ6Ausk7ldxjoeUBgYp5eUgAF+UcAFVAXxaVb/RX5MIWRTo24SQnmCQUlJU9W4AJ/fbDkIWG/o2IaRXqEkhhBBCSCnhSMoBRLVewZoNxWRhifO+tRIlcVI4ibHU6jXqNStgrFaLLlR13ieLo+k4duAoU/bAHXeZsqnJaIZjJwFV4ugplg/bX4QMDY8Ullstq9WoVL3ETlb/sPaQJ5iyqXuL7+B3j42aOtt22rLpaWvHzu07TNmy3cX+f9LJJ9g6y21iu9t2/NyUxfn7KhXnVhDVSbw6+wEVQKOZdxNHa9WKkrelzjTImaMjMQcKIItmWXby7bk6jCyerhlAY8D6lETbJo5uqwFn1mkn6dtANHu41G3fZE4yOk9jVk2cA82K573pJAdMK84syM7sz97U1Fka3UMcGzJHE1SrOfq3KJtkVrW21lpRX/dvcm/SAxxJIYQQQkgpYZBCCCGEkFLCIIUQQgghpYRBCiGEEEJKCYWzBxBJRdBcXhTRpY44DlFirGrmiMvimVUBiOMtGolKO44It6FOLOzMtmpmcwVQqxeTMw2tGDF1lg0PmrJm3Yrq4rK03TB1pibGTNnwypWm7KAn2BmbD9pwaGH51ltuMnXaHXs+1m+wIty1a0bstpE2USatiPKpR59qypBYAePtDxfFtDPTzkzPkXg0S/ukMFQFZor+kqXO1MVZURDZcWYDbjkzF2eZM2N25IuJrYLUmfG46uhyEzthNtJI0FlzbKg2rFC9XrV+XasWr6+ZGaetujWs4wjH1UmAFyeyS5vOvSG1dnUcRaqoLWu0o3uIo7etVGyhOjN+TzeK9nsJ68y3HnO5lRqOpBBCCCGklDBIIYQQQkgpYZBCCCGEkFLCIIUQQgghpYTC2QMIVUAjcWOcWTRQFKqJODPgelPeZl42Vo2qWGFcxRH7NRObEXbMmaF2y/btheWT1h9i6iwbssLZhpONMm0XZ3bOnP01Bq1YcWBouSnLEjtzcaTbRHPZClNnwhHm7h6zAsahAdu+StH+baNbTZ3h0bWm7OQNVkz70OT9heWdE9tMHcliP/HO/2OPAIglwl4C2Jn4BDhiVCfhKdLU+n8WiTK1bW+V4ghDa5kVY6Nu26/Viu3XazbD82DF+rA0rR1JZH+94cyo7M0YXLE+lmZW5Rtr7xNYf/XuIeLcLxytMWaiLNLeLM6Jd49KnIy5kUhfHKG68zsBUmI4kkIIIYSQUsIghRBCCCGlhEEKIYQQQkoJg5Q+IyKfEJGtInJzV9kqEblaRO7I/9tsYoSUHPo2IWRfoYSo/1wK4KMAPtlVdgGAb6vqRSJyQb78zoWbUnQiMWicLRIAEAnt1MsM6aSXzVIn06REYsXE1kmcbJTtCZst8s577jNlt9++sbD8xCceY+pUHYFhrWZFgfVGUdQ4NmZtbc9Mm7K6IwaenrLiwbvv3lRYvvPOTabOuoNGTNkvbtloyjpxelkAQ8NFQeTIsBUfNwZsH9ZhxcDVKAttxRHFSiUq2/PMnJdiEXxbAbQj3aROWwVsJcoSO+NkW47FwAEvM2p07BVnf8526mRcbqr1z7oWfXEgseeoYvWvqDuC9qwZteVk2k2dlLmZY3+7Y+2YqUaC8xl7bTUyez20HH/pOGWVSGCbZk7KWee0zTg+W4sy5lbrTmZik3W4P4Jw0hscSekzqvo9ADui4rMBXJZ/vgzAS/enTYQsBvRtQsi+wiClnBykqpsBIP+/rs/2ELJY0LcJIT3DIGWJIyLni8j1InL95G5nFjRCliDdfj025szQRwh5XMAgpZxsEZH1AJD/t1m7clT1YlU9VVVPHVzuvMQmpFz05Nvdfj08bHUShJDHBxTOlpOrAJwH4KL8/5d72SjLFK1WUXCZqVWcJUkxmPESiSZqhZviiPaSKFtkpW7r7Ni2y5Rde9d/m7J77nrAlFUjAe/uneOmzkDTZpytr7EZPGuRwLY56IgQM2trq2X7cOuW+03ZjTfeXFi++ba7TJ0jjz7clO3aabPQ3nefbX/5iuJxjqyywtnakBU1TjRsNtndSXGflcQRK0aOIYszp/0e+7ZAkKRFP+jEwlYAaXSeEsf3O04K5rrJZwtMR9mJvWzLAptdVhpOltjEllXrxbK6k2fVzQQNJ3ttlHnVO08VtX7Rdp5ppGqF4zJT7MdMrBhVPddI7fVVr9qymazYnhEtA+hU7SixxhmGASCyTTInf20sLKZuttRwJKXPiMhnAFwL4HgR2SQir0e4gT9fRO4A8Px8mZAlBX2bELKvcCSlz6jqOXOsOmO/GkLIIkPfJoTsKxxJIYQQQkgp4UjKAYZGL4edfFYmeZuTfw1e5q6kB02COomkdj1gf51x+7Ubna3te+cX/uqvFJZbLVvnrnusfmNklf1lq0TvsMVJApc4ZaM7tpuy22693ZTdfffGwvKOHaOmTqttT8iqNTbp6uSM1VPM7Cz245STp2pn2+pbpsSWdTpRPzoJ6+KZc7VvL+8zICkmC0viJIIANLqbtVvOjMRO/6cdm4isUi0KNhInkWHqZBgbdHxYKlb4W4sytWVNezxNR6dSqzj214papVrb2tVOvVmQrb5lxtHnoF30u6qXBM7JPJd6Cd6mrNYNkaYmqzjPzs70yVVHn5NJnBjO9kUti7VWpMxwJIUQQgghpYRBCiGEEEJKCYMUQgghhJQSBimEEEIIKSUUzh5AiAjqteIpVXXEZVhYOCZO/FpRK45LatHWU05SsN22KGtZIdy6J6wyZcccdWhheXS3TeY2PmEFemMTk6ZsZGAkssEqTx980CaUa7es2G9ifMKUVaUomjxklU2gNd2ydm14wpG2rart69FdxWNfs9ImrKsOW6HgdNv2T3x+08xL0BUJZ/uY9CpOOCiOILwVHUPWcSpNW2Fr28lEptG2iSMWrTm3T3USvNUcM9JoVuVGy0k65olk4+mgAVSTYlvuLMKO6LkNK2ivOTMQzESJ9KrOTM+ZOIJYp68l8Tqj2P+eINlzPjWzGQMSJZd0JnM3PcFcbuWGIymEEEIIKSUMUgghhBBSShikEEIIIaSUMEghhBBCSCmhcPYAQkRQSxY+pR1HcGba8sqcTJaValEo2OhY8euOSTuzcFaxbQ0M21l9O5Fg8eHRnabO7XfajLP1hhUPHnFUUaA65mSS3XT/L6xdy+0sy9t2WDtmIjHwspo9xrojOlw96MyAe5DNUjo5XRQnHn7wQabO4KCVAWbODL6x6DB1ZgzWaDvto3I23nfq2JK1IjGwWuFm5vi+J0aVSFStXobbim0/dVI8dxp2n9Wpov0zNSs8zap2nw2n3kyrKLKuVGydRJ0ZzB2B7VRit+1EsxlLYkXdrXHr1y2nz9oz9ryZBLOOiFsGnIy2jsA2zuQrTgZsHYzukY6dpDxwJIUQQgghpYRBCiGEEEJKCYOUPiMinxCRrSJyc1fZhSLygIjckP+9qJ82ErI30LcJIfsKg5T+cymAM53yv1bVU/K/r+1nmwhZDC4FfZsQsg9QONtnVPV7InLEorSVKWZaRTGfOuKySi0S2lWdzJmpI6R0RJ91WV5YTrdagdtgbYUpSwasWPSnN91syoAoi+thh5kandSK/TZvus+2/8NrC8tbtj5s6gyNrDZlhx9+qCnbutUKZ3VmtLC8apk9xom2tXXbQ5tM2ZrDjjNld0aCwobziNFo2HPZmXCEiNXixq641pnmfk9YLN9WBTqReU7eUiDKrNtObS1JnePsOBl5K0UxpbZsZ2eJPb+q9vy2p+w5qTeLmYfbdSsab6bWrs60IxiW4vntTDlC0GU2E27m+GI7c5wq6tep9rSpMtnxBL3WfzqZrVerxft0bJiy21Wde4hJRez8kKDaLtaJsxmTcsGRlPLyRhG5MR8yX9lvYwhZROjbhJCeYJBSTj4G4GgApwDYDOCv5qooIueLyPUicv3kuDN/BiHloiff7vbrsTH75E4IeXzAIKWEqOoWVU1VNQPwTwBOm6fuxap6qqqeOjjkDH8SUiJ69e1uvx4ethM1EkIeH1CTUkJEZL2qbs4XXwbAE2t426EuxRt6B8577U7xXXGn7cy26ryn9d4nr2wXE51tWHOUqXPHTptsrVl1Epg5EoiNd95TWJ6csNO0rt9gNSMPP7TFlN1//13FguXW/UedBF0YtzMvH/zkYVOWaFF7s3WLnf552yZr/+Q9d5mykZXLTdmha4v7HN1itSyNCfv2ZGrajkQkkSYlcSbOTSqLP1/s3vi2AsgifYynl8myaDZdZxbktjczslOWRLPpxontAGDQ0WF4CczEmVp4olPUoAw5Oo9dzozKjdRJyhbNgtx2ki7Wxhwti5PsbtpL2KdFzcuEk5Ct7WzWVme2ZCdNpHTic+ucI6NbATrOTrVTrFer2u3SaOZ2ZxJsUiIYpPQZEfkMgNMBrBGRTQDeC+B0ETkF4f68EcDv9cs+QvYW+jYhZF9hkNJnVPUcp/iS/W4IIYsMfZsQsq9Qk0IIIYSQUsIghRBCCCGlhK97DiB0WjBzR1GQmjatIrKyvijk66TOTzydJEiSOKK3djHOHW7YX2L80onHmrKZGSuqe+B+K3aN80Ht2LLV2qDW1mWD1taVJxeFp2tOtOLXoZVWrChmmlZAHQFgosX2Vk/b2ZOTm+zMyxM3WGHuvZvvNmUrm8VEc03nHHVaVihda9p68RGlTkYrL8FbPxAASSRIFUfsmsViYGdm3qzjCDAdgWdluliWwlEWO+JdZ5JiaN3px0ZRVN1Jra9U646Iu+bcsqMZjrOmPcZpb2ZhJyWel+xuWov1kuqkqTPTdmaEdmZx9kTKLSna6yXhiycuBoBqzR6TRsLi1Em4V43Pdx9n9yYLw5EUQgghhJQSBimEEEIIKSUMUgghhBBSShikEEIIIaSUUDh7ANHRFDtaRWHmzH1WhLauWRTppauswG1ArVBwaHLElO3aURRq6hE27j3mKDtz8YMPj5qy5SN2tuRl64r2DzesXZ2xCVOWrLOCucOftq6w3Ko7KsfEyehZsZdJ6ggR4+lUB4etrclhNpPs7lutAHPGmeJgG0YLy6Pb7IzTB22xwt+hI60osyXFY1cnS+lMVNYvfaHCZjTtqD1PEmVOVqeON5N31TmVnWq0QycbcqvlZDytOrOHOyLxSuQrCax4XWHP73hq24r9M9ll/U4rNutt4mS07TgZl2MB9cSkM6NyxxGxOg7TdrIWVyOhbN0TGif2PhaLZAGgEovcHSGwVON+ZcrZMsORFEIIIYSUEgYphBBCCCklDFIIIYQQUkoYpBBCCCGklFA4ewBRaQArji2KwCZaNg5tbSuKJg9Zd7BtbMqKyR66ZdSUVbOiCG3oidalxkYfNmXqTBN/3BOtHetOLba39aFtps7dV1u7sMIK5pZFmS1riRUAampFh6kjAEzEHmc7LR5T2nLEfkNWWNl2hIITo1ZIufapQ4Xl+zePmjpbf2TbP7iyzJRla4uCZ3GeVxJT1h+BYaJAs1Pso1bF9u10ZF7qZQpu2+2qNXtcaXTdZE5WWnX6rOWpi5teNt/ieap6QmxHGJqqtTWLMscOO9lxM7Ui3KnECsc7ThbdSha156TVrTj7lMz2taM/RhYdU9try/NP51rNogyzWc25Bp3syqS8cCSFEEIIIaWEQQohhBBCSgmDlD4jIoeKyHdF5FYRuUVE3pyXrxKRq0Xkjvz/yn7bSkiv0K8JIYsBg5T+0wHwVlV9EoCnA/hfInICgAsAfFtVjwXw7XyZkKUC/ZoQss9QONtnVHUzgM355zERuRXAwQDOBnB6Xu0yANcAeOe8jYkilaJ4s7nBEU0+UDzt6V2OAC21rrF9y4wpa0pRCnfT9T8xderLbFsjq6xI9qSTjjdlo0MbC8utuhUYTrZsWWO3Ffe1pgcKyxWrJcRUx8nM6ehFE0fU2G4V+yJz9HniZfR0ppyfGLVlh60eKSwf9JRVps6mH+ywdo3b/m88oXjOa+L4QCTI9PphLhbTrzMBWpG4VSetvbVIgJlVrMH1qpOx2BE4xyLhinOrlMTLOuyIPuN0uQBQLbY/7Qh6k9T6cFK1dgxE2V6dhLOQAdt+JbFtVZ2LQmNFcmKzIXuZditq7xc1R+yqUXbfAU/w7GSqdRLmQqJMyknHVmpViv3ltk1KA0dSSoSIHAHgKQB+BOCg/EY/e8NfN8+mhJQW+jUhZG9hkFISRGQIwBcAvEVVd+/BdueLyPUicv3UmH1KJ6SfLIZfj4/Zn2MTQh4fMEgpASJSQ7iRf0pVr8yLt4jI+nz9egBbvW1V9WJVPVVVTx0Ydt5fENInFsuvh4ab+8dgQkjpoCalz4iIALgEwK2q+pGuVVcBOA/ARfn/L/fQGpLonXJ9wJ7iyZniO+a7b73P1Ent62RUKvbLYuvDxVmXH37oflPnWc88xZQddfywtcuZzbjVjkaHnGxQmdj37TMtewASzYqbiNUsNGu2vzrOPmfGrR4hmywuDwzbd/dVR1NQr9mRgqRpnx9qkW0HHW3bH7vbmRE6sTqA4aGiVqk9bfsrnv12T1hMvxYFkniQ0JmtuhF1R9vRPyQ122fTA3YEshLrVKatj0nNPhR4ydbg9H8n0kEkmdWfSJxEDYA68pnpZrRPRwtSaTtaGSehovfYKo3iTivO5OHiHGPqaF48X5RohuN4AmoASKqOTiVxkixGepaKo62ratEHhLMglxoGKf3nWQDOBXCTiNyQl70b4SZ+hYi8HsB9AF7ZH/MI2Svo14SQfYZBSp9R1R9g7nzjZ+xPWwhZLOjXhJDFgJoUQgghhJQSBimEEEIIKSV83XMAIZ0E1W3FmXLbW+yI+9jW8cLyw1ttArBOx4rqDl5/mCnTaGbhzBHLjY9Zkel92zebso3ZHXZbGS0sp46KNfVmkHUSTjUaRdtqTtKobMaK8WoNJ4HW8IAtW1YUFlea1tbJSSuS7XTsOTriSatt+81i+0ndqigbq60wcWrK2qFRgrFW6iT7MiLf/ggMFUAnyiSnzp2rFYlpqw3rw221/dOcscceTe6NStX6U9sRFtdgfbHi+GcWz6LtiGQ7cJK5OYLhJDK24SSxSx2NrFS9/rFi4EYn2mfFHnfVmVlYnUdgb+boSuSemZfMzSin/ZmRNSsmb2s5LltzBPOkvHAkhRBCCCGlhEEKIYQQQkoJgxRCCCGElBIGKYQQQggpJRTOHkBkLWDqvqIKLZ1yUsdGurGWk8Z1eIUVhh5/zNGmrLZpS2FZW1aEe9TRh5qyu2Y2mbKp+i5TFqvq2l4mWS/UdmaCRVoUMCaJnSE1adrj9gSA9eW2cDDOpuno83bucGZxTm3ZwAa77UynKE5st6wIdyJ1ZnGessLQdKIoBK05gkypFY+nn3rDKCkpqs5Jr0QzHE93nIywTjpTbXoq3GK9NHEywk4701A4WWgzJwttNRIqp04mVtTtMaaptb8didw7juMNOiLiNBbvAqiL9cU0OvGVirW17WV/dUS4lYojIo5E0UniZGAWm+1aao4PRLMgV+AIntNi+5wFudxwJIUQQgghpYRBCiGEEEJKCYMUQgghhJQSBimEEEIIKSUUzh5AVKsVrF27olA2vt0K1XbvKopdT36mzSQ72FllytatXmfKxieLwtYtm7eaOkOrrJCv2ZowZQNOeshGdXlhuWN1rRhZ52T+dIStSRqJRWXQ1FFPQ+eWOQLG6HKSihWsPvygI2SOU24CqNQcAeNUUfzYdES+jYoVGGpmL/N1g8WMtlOZFYbuTiejhkyV/YZG2V17OU3iiIGrjqK6nti+nmgUW8tS21ataf214ghbPSFrJpEo2RGUIs70CkCdbKxxYuCsav2u5Yhka06W2FbmiFGjbLipo/F1ktxCvMy0ji9mkSq6nVrBrdbsDmrOOUkaRePUU3uLp6onZYUjKYQQQggpJQxSCCGEEFJKGKT0GRE5VES+KyK3isgtIvLmvPxCEXlARG7I/17Ub1sJ6RX6NSFkMaAmpf90ALxVVX8qIsMAfiIiV+fr/lpV/7KPthGyt9CvCSH7DIOUPqOqmwFszj+PicitAA7em7ba7RSbHxovlFV22cGyQw9eWViu6oipsywSVgLAz+/+uSnbdOc9heWTTjzW1OkkVryWDNhsr4MNR9QoRRHd0HJTBbWhcVPWUSsenBgvikOzmhX2TU1YAWkiVsjXbDrivqwoNE2cLJwP3W1tPeSgEVO2sm4PdCrKgrqsuczUadRths2xSXtMkyj2z0xq+6tqjrv3lLOL6dcAkEQi2Kpa/4k1n5WKkyV2mRUpT047ftcuNpY42X1dHGFrktm+zZrFfVamrD91HAFsTZ1sr1I8pqTjCHWrVpjbajtZYgcdgW0l7ntTBR1rKtB0hL9O+uZEi/ZXnGzCiSN4FieTbxrVqzsaWTEi4j6mUiYLwtc9JUJEjgDwFAA/yoveKCI3isgnRGTl3FsSUl7o14SQvYVBSkkQkSEAXwDwFlXdDeBjAI4GcArCE+lfzbHd+SJyvYhcPz1tnxwJ6SeL4dfjYz2OYhBCDjgYpJQAEakh3Mg/papXAoCqblHVVFUzAP8E4DRvW1W9WFVPVdVTm0071E9Iv1gsvx4atrlfCCGPD6hJ6TMiIgAuAXCrqn6kq3x9/l4fAF4G4OaF2qo2Eqw5oviufuIOmzys2SjqTbZttzqJls1zhge2PmDK1owUA6ORFXb0/u6H7Hab63a25HZm9QJDtWLCsh3bx+x203a71ox9cT6+PXoirzvv6Z2H9pqjLWnDjlo1asW+2PWAtWviYbvdcSesMWUzzqDYZFSoU/Zdeqdj95k5SfLGposH6m6XFpPHZVnv2dwW069FBEmlqNmopraDsihGbzlJu7Rlb3kDak96LBFxJsxGx9FEJE6ZOnZUokRtmZMYzohsAHScJIJplJSt4WlgvPxlnvbDKUuj7G2a2hmVE2cmaXHsT5wEcu0oyWLFSa5XcWY8Tpz7RZpF/ejMMJ7WPAENKSsMUvrPswCcC+AmEbkhL3s3gHNE5BSERJobAfxeP4wjZC+hXxNC9hkGKX1GVX8AX17+tf1tCyGLBf2aELIYUJNCCCGEkFLCIIUQQgghpYSvew4gFCmmUZxdeMqZNXj39qKQNXMEaKM77GzGY5O7TdmGdcX8XLfccY+pM7Fypylbdrj9JVKrY8WQ7Ugo2B6zor3KjJOAKhbQAUijGZsHxHZO1Uk816ha1eFgwyopx0eLIr2xB6xoeWTEJmBrVewxjbdscq8sSlA3Mz5l6rRHrSiwYzXKaI0WxaKpkzhM4r7o0yzIAnteOp6otFY8J4MdK5qcccTS4swcLdHP+Vs16yuS2fPmzbCr6ghBK0WfTewliLYztXDVeawcaBf3OdNwfNgRf1eqzq8BHUNqsR1it0uc85E5M0JXnReA7aiwEiugAShsH6pzrVaq7WjZmXU5vs30cXZvsjAcSSGEEEJIKWGQQgghhJBSwiCFEEIIIaWEQQohhBBCSgmFswcSokC1KKasb3DqTRRFklO7bcbNWsUKABvOTKR3bt5SWG7N2Lh31Wq73bKGFYbWHSGcpMV6Omnbag5YAWN9lRXhDo0UbWtWrfi1BisgTZxYvuNoJqdmiv04st5eXiMHW5Fmc7mXudRJORtlEp3a6fRFzc6eXFkzYcqSSFhccWbXjfWeTrLQ/YLCioYTJ/Nqo1Ks02nY/m862XdbsCez2SwKZRMnw22nbfssnjEYAKZTm765EonEqw3rF6knFhXrn2l0rS5LnNmHE2t/NbH9kzjXRHwrqDgi3Pj8AEAts+3X69a2eILmjjN1sTptoWL32Yx0vy1npvO4jnAS5FLDkRRCCCGElBIGKYQQQggpJQxSCCGEEFJKGKQQQgghpJRQOHsAIRA0pCg0lZoV32G4KDhLnWnQ0XGmbJ+wQrV7txaz0DYHbLbI1dUVti21mS3bLdt+aywWGFrB7dA6K44bXOsIfyP9YnvaZoR1NXSOGDJ1so0OR8LcurNd5mTmVGev7WnbP1mr2LfVdMjUWbPO9v+ygSNN2eBgMfOt97TSmposLFfwM6fWfkCANBJJOvpRIMrSK4k9R21H/Vt1spKKFnsks+6EAeuKAGyhONlksyhjcVKzB1R3xKLtGXs9DyyLsjI7ttY6TnZZ51qqwcn2msR9b72lZvW2SNTWE3HuR5GAt1K3HRaLawGg46TfTZrFtmot5zpyBPqkvHAkhRBCCCGlhEEKIYQQQkoJg5Q+IyJNEfmxiPxMRG4Rkffl5atE5GoRuSP/v7LfthLSK/RrQshiQE1K/5kB8KuqOi4iNQA/EJGvA/gNAN9W1YtE5AIAFwB453wNJYmgGb0oz2bsu+5qpSjOqHTse9uOk0iqMWBfdq85stjWshX2PXdzyL7nbnecBGaZTWg1GM24unyVk0BLrOZFao42IDrOmpOcrtm0NiQVq2OYTu0MxBmK7TfUtoWO3WciTgKtqt223igmaqut8BJv2b4eqNgZfFWKzyfebLHJiuI5alS/burMw6L5tSjQTIv2ziTWryuRrkM97YSnI0mtL2q9eM4HnH6Vti3zrpt6w5mBODI/U+9cOlqruq3XjhL/eYn5qs5s6BUvO5+jI0mi9sQ5nrRi7yGa2XriaF6a8XmDTX4X3CnaThx9V5Tkz5ngGhWJZqCmRqXUcCSlz2hgPF+s5X8K4GwAl+XllwF46f63jpC9g35NCFkMGKSUABGpiMgNALYCuFpVfwTgIFXdDAD5/3V9NJGQPYZ+TQjZVxiklABVTVX1FACHADhNRE7qdVsROV9ErheR6yfGnfleCOkTi+XXY2P21Roh5PEBg5QSoaqjAK4BcCaALSKyHgDy/1vn2OZiVT1VVU9d5mg/COk3++rXw8OOoIIQ8riAwtk+IyJrAbRVdVREBgA8D8BfALgKwHkALsr/f3mhtjJVtDqRWK3jCEijKlVH9Ia4HQCrl9kvi1VPKiYU07Z1qYHMzsxbn7Ri15GBVaZseLj4449qxXFZbxpTR1SHeCbdxBGxOiK6mbYV7S1zBJKdaNrg1JkZFk77w4O2L5Y1nNmMK9GM0M6MzV6OM8mc8xs5QeLMep1Es+nKHkwXu5h+rQDa0b7rifXrLPLZxLE3FgwDQK3qTe9c7LPM8TuNp4kGUHdmIK6mtm+zWlTm2JA5wtMEtqzWKSbmcyZ/hsLxAbV9GIuPASDVYlK8xJnVWeCM4tadxHlOX6gUy7xZxzMnW1ymNlmfSYyYOQGuEVTzWb3MMEjpP+sBXCYiFYSr5QpV/YqIXAvgChF5PYD7ALyyn0YSsofQrwkh+wyDlD6jqjcCeIpTvh3AGfvfIkL2Hfo1IWQx4DgXIYQQQkoJgxRCCCGElBKJM/SRpYuIbANwL4A1AB7uszn7wlK2fynbDsxv/+GqunZ/GgMU/BpY2v27lG0Hlrb989l+LIBrVfXM/WgP6REGKQcgInK9qp7abzv2lqVs/1K2HSi//WW3bz6Wsu3A0rZ/Kdv+eIevewghhBBSShikEEIIIaSUMEg5MLm43wbsI0vZ/qVsO1B++8tu33wsZduBpW3/Urb9cQ01KYQQQggpJRxJIYQQQkgpYZBygCEiZ4rIL0TkThG5oN/2zIeIfEJEtorIzV1lq0TkahG5I/+/cr42+omIHCoi3xWRW0XkFhF5c15e+mMQkaaI/FhEfpbb/r68vJS2LyW/Bpa2by9lvwaWnm+T+WGQcgCRz5Py9wDOAnACgHNE5IT+WjUvlyLMjNvNBQC+rarHAvh2vlxWOgDeqqpPAvB0AP8r7++lcAwzAH5VVU8GcAqAM0Xk6Sih7UvQr4Gl7dtL2a+BJeTbZGEYpBxYnAbgTlW9W1VbAD4L4Ow+2zQnqvo9ADui4rMBXJZ/vgzAS/enTXuCqm5W1Z/mn8cA3ArgYCyBY9DAeL5Yy/8U5bR9Sfk1sLR9eyn7NbDkfJssAIOUA4uDAdzftbwpL1tKHKSqm4FwswSwrs/29ISIHIEwod6PsESOQUQqInIDgK0ArlbVstp+IPg1UM6+nZel6NfAkvJtsgAMUg4sxCnjz7ceY0RkCMAXALxFVXf3255eUdVUVU8BcAiA00TkpD6bNBf06z6wVP0aWFK+TRaAQcqBxSYAh3YtHwLgwT7ZsrdsEZH1AJD/39pne+ZFRGoIN/JPqeqVefGSOgZVHQVwDYKGooy2Hwh+DZSzb10OBL8GloRvkwVgkHJgcR2AY0XkSBGpA3gVgKv6bNOechWA8/LP5wH4ch9tmRcREQCXALhVVT/Star0xyAia0VkJP88AOB5AG5DOW0/EPwaKGffGpayXwNLzrfJAjCZ2wGGiLwIwN8AqAD4hKp+sL8WzY2IfAbA6QgzlG4B8F4AXwJwBYDDANwH4JWqGgsQS4GIPBvA9wHcBCDLi9+N8P6+1McgIk9GEA9WEB5WrlDV94vIapTQ9qXk18DS9u2l7NfA0vNtMj8MUgghhBBSSvi6hxBCCCGlhEEKIYQQQkoJgxRCCCGElBIGKYQQQggpJQxSCCGEEFJKGKQQQgghpJQwSCGEEEJIKWGQQgghhJBS8v8DJnC6IjzXGBgAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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Oqv5xtt2VXEBXi0sQ7tRuwPJxumJEpIrwhOCPEB6XjyM8Ql7peXwsvATAv2V/vxJh356HkNhuX3At+x2doxL+8+SvEXQGGzJ/bz0Wf1X1AYRH3o+0iPf3EfbjKdl18idg/V3qmm0+U9X/RHiK8WyEMfy75ZxQK9QEwpffeQttsuvF4zO718fNqvocVd2gqj+I8Hr2huzj5wJ4Q3bTug/hPL9aRN7ibSv7e2E7jwPQUdUPqGpbVXcD+ChCwrzcfh1BuMYs1jdU9eOqeq6qbkDQfpyBIDFYjvXZfrxbVRuqegjA3/b4dT7Cm4udqtpV1a8D+BpCPC+3zwC+8x38MoTEs3e/uqr6dlXdrqqnZevtwcPn+XkI2pjZLLn5Syw9XmWEcR5FeJLy99lxWhiH3dm1fFGWTFJUdRIhU/0zEblYRMoS/g3rYwiZ1bJBmvFxAC8Wke/N/iPonTj2C9IIwqPzGRH5LgA/t9IVswzu4wgipPUIj6ogIhUR+XERGcsy9ymEpxUeP5n5f37Pz0sBvEhENiBkmTUReVF2J/obCO9zF9gPYHuWWS5ctL4K4PdFpCYiT0F4lLdwh/2XAH43u1BCRDaJyCUr3OW/AfDbInKmBJ6S+fgZAE+U8G+0JQn/ano2gH9S1fsQ1PbvzMblWQiP7hf4IMKx/MHsjrQm4d9oT1vBuqvJCMIX6AEAJQn/Oth793A1gF8TkXWZGv71PZ/dAGBKRN4iIgPZfpwrIk8HHv63YG+j2TnxNgB/LiKXishgdl68QET+8Cj8Xy6OPK5A+A+C2lFs56iR8G+GP47wZfoHqnpoBXF6NFQQzokDANoi8gKEx/irSnZcHysif4Zw1/nO7KMRhJuvQwg3FL+XrLof4cK6wBDCl/aBrN//hZ4kQx7+d/Htjg/rROSdIvIEESlI+M+W1yLoTh5JRhDuqCey+P/Vo1w/uk718AGEpwNtVf33Y/TtkwDOFZGXZrH8NgA3Z08fDNl1q5ada7+C8NT2quzj5yIci/OznwcRXtv/eY+/vywi20TkVIQnMQvr3hW6l1dmx+YUBL3RTT3bruHh63c1Ofc+AOA3smP8XQi6q6t61n1aFoObELSE/7iwj9n1uIZwLiDbvyoAqOpBBD3Xz2XX53GEpx4Lfn0dwLOzm22IyFMREsebV7DPC7wE4VXyl3qN2bn/+My/sxH0hb+lqt2ebf9Udt0cQBBB35St+wwReVZ27R+QkChuQUigJhGexp6f/SwkNk/LPl+UZf8FWVX/EOFpxR8hfHl/DeFO9LnLPerr6eM2hHepH0XIPqcRBGErWj/hVxCy+GmEuxv3X9eW4MMIGefHksdOrwKwS8Kj0Z9FuPOIEJFnINx1/bmq7uv5uQbhveYrsi+xn0dIEPYgPFnpfcT3sez3IRH5r+zvV2T9PohwAr9dVa/NPvtThPeCnxeRaYSL24Ur3Nd3IXxZfx7h2L0PQSR3CEEA9SaEC/WbAfxQdnIAYXwvRHg8/nb0PJrOvqwuQYiJAwix8Kt4OJYWXXeV+RyC0vwuhNcOdcSPr38LYdzvRXiH+nFk8Za9gngxwslyL8Jry79BuKsGwl3M9YttWFXfhfDvf7+Bh8fg9QhP4JZlJXG0yKr/jKAD+OmVbOcYuEnCI/m7Ed5N/5Kqvq3n86XidMVkr4zegBCbRxBi5prjcz3ie7L9mEJ4bD2KIIa8Jfv8AwgxswfhEXyaMLwPwNkSXu18SlW/iaCPuh7hy/vJCBqKBU7v6S+liTBm/5r5cytCHL7muPZwed4J4LsRvhz+GeHVwdHgXaeAcGN6LnpuUCUUpOt9ZbAkqnoAISH/XYTjfyHCf7gt9PdWEflszyoLAvOHEJKS5y9892QJ9HfOIYSbyyM9rzD+CkGUfgvC2P9zZoOqTiG8JfilzI8bsza/27PteTz8aucOPPzaEgjXt28jHPuvAPg/qvovPZ//KUIicGf2u/e8PSPra+EJx3zWboEfQdBRHcDDmplfyvz+CrL/qM2+Ez4B4PdU9fPL7XMPrwbwAecV0EaEm9hZhOvrlar63p7PX4sQz7sR4v1xeDiWqwjJ4aHssxciaGUe1EDvcTqQrbNfVZtYArE+PvKIyDDCQTtTF3+XSMiqISI/hyAofs4K2v4NQhL7uUfeM7LWEZHfAHBAVdMvgpOO7O75IQSN1bf67Q85+TlhSYqIvBhBwyIIdyUXIgT6ic+SyEmPiGxFyPKvR1C3/zPCO94/6adfhKxlJBQy/CFV/f5++0IeHZzISoOXIDwiFATdwsuZoJBHkArCI87HIjy1+yiCupwQcgyIyC6E6/el/fWEPJroy+seQgghhJDleMRmQSaEEEIIOR6YpBBCCCEklzBJIYQQQkguYZJCCCGEkFzCJIUQQgghuYRJCiGEEEJyCZMUQgghhOQSJimEEEIIySVMUgghhBCSS5ikEEIIISSXMEkhhBBCSC5hkkIIIYSQXMIkhRBCCCG5hEkKIYQQQnIJkxRCCCGE5BImKYQQQgjJJUxSCCGEEJJLmKQQQgghJJcwSSGEEEJILmGSQgghhJBcwiSFEEIIIbmESQohhBBCcgmTFEIIIYTkEiYphBBCCMklTFIIIYQQkkuYpBBCCCEklzBJIYQQQkguYZJCCCGEkFzCJIUQQgghuYRJCiGEEEJyCZMUQgghhOQSJimEEEIIySVMUgghhBCSS5ikEEIIISSXMEkhhBBCSC5hkkIIIYSQXMIkhRBCCCG5hEkKIYQQQnIJkxRCCCGE5BImKYQQQgjJJUxSCCGEEJJLmKQQQgghJJcwSSGEEEJILmGSQgghhJBcwiSFEEIIIbmESQohhBBCcgmTlBwjIheLyJ0icreIXN5vfwhZLRjbhJCVIKrabx+Ig4gUAdwF4PkAdgP4OoBXqOo3++oYIccJY5sQslJK/XaALMoFAO5W1XsAQEQ+CuASAIteyNdv2KjbTt8e2dwkVJJlL08Va0xX83C78hrKSnpb6VZXr6eVpuzH2pd2rbXb7R6TJ+KMobvWCm5EvL7SY/TgA/fjyOGDq3FAjiq2R8fHdfPWrbHRG7LE34LjqTsUfoCmazqb81b0bMd2LnWdVv56uuQigEUGYwVOANDkWuBcGhY57739tn50kfbvxLV3PXLapc65l7/Etmf3/Zibnf2cql5sW5N+wyQlv2wD8EDP8m4AFy65wunb8ckv3hDZ2q2WbZheXL0zudA2pqJ3oUv68pIi78JaKNg3jZ4NKMeL7oXJWc3hhCcpTmfz83Vja9Tnja3T6dhtJmNdKtnTt+tstNO2xzI9buWy7UtKxWj5FS/4H7afY+OoYnvz1q1415VXRjZtOpeuYrxPNadJq2ONhbLNeATxvqvY86hcqtr1ukVj6zhRVUoCSAq2zbzzNr6q3jFvxH21neRmqGxsaDoJQ9fGSqcU+1ZsOTFWsmNYVmsrdKwf8xL7X+lWTJt22bketexYSzE+b1odu16hFY/hG177Stx1xzeZoOQUalLyy4puyUTkMhHZKSI7Dx86cALcIuS4WTa2e+N66siRE+QWISRvMEnJL7sBnN6zfBqAB9NGqvpeVd2hqjvWb9h0wpwj5DhYNrZ743p03boT6hwhJD/wdU9++TqAM0XksQD2AHg5gFcuvYpCk8e1qvYxdXobK85rHO/xc6drX0Goxnluseg8VvZeojiPgr1mkogPuo6mA7CPdFfy3tzVdLiv7m0uL2Jtqbak1bR+TU9MGNvEYfukwHttU0yebje79jWRN/7lsn18LhKf+gVnvVKyQfe10bFxVLGt3S7q9WZsc15pFDT2r1lwXhvopLHVKjXbF+LzpuO8NmhW7PlQFe81lH0t0U5iSp3+UbDnyJzzWq6YvBosOceyM9c0tor7atZus6XJK8qOHdeuE+sN51LQac3ZdZPXL1p1fJi3Y10peq+rkmU79Oi242ObamJIvmCSklNUtS0irwfwOQBFAFeq6m19douQ44axTQhZKUxScoyqfgbAZ/rtByGrDWObELISqEkhhBBCSC5hkkIIIYSQXMLXPScR7U4HE4kwc3r6sG0oschtYGDANKkUrOqt1bLiuFSE1mo2TBvvP049gWe1ZgWMQ2PDsV8162vBybW9mi6mDoujl6t3rMCw3nJEe2XrayqcnZicsn3NWOFgKnYGAFVHqJkIlydmDpk2AwOj1uaIgWvV+NQvV6wYUjtexbR+ICh2452Y69hxLLXj2Jt3hNFStXHXnZmwm0xCRRyRaallL5+lsq2dMg8bK5rWHmnbuNOqjeuBuvWjnRzgVtuK5Qtd21ezbeO6ULR+NBuJgNqpWdJtOH3NWT+aTv2fbiE+llq3cVdxxnq26tRJSa5tHecrroTYB3WLKZK8wCcphBBCCMklTFIIIYQQkkuYpBBCCCEkl1CTchIxNz2Jr3/ls7Ftdsa06yRzfXjvZItO0TRP+1GuxCHkFXzz3pGroxeoVq3epJy84y8NDDo+2Hf+60asNmPLli3RctHRwEzOTBvb9JS1jY+OGVuqcZmetrqJZt1qdsTRpMxOWz3L/Q/cHy0Pjg2ZNqed9jhjazn7VE+KgknXHo+JiVjPVJ+fNW1OBKqKelKUsOAUHUvDuOMUDCzDHpOZptU2DEhSmM8RMJUHrI6n3rLHd9CZL6hUTYrFOedWwSme57iK7kxSUNHRWrVKjlbMqR/XcHRIpcQ2N29XbDvF1sRxpOmMTyqX6XacsXDmLKpY+QyqlTiO553idwPl+DrjXYtIfuCTFEIIIYTkEiYphBBCCMklTFIIIYQQkkuYpBBCCCEkl1A4exLRas5j/wPfjGyFgneI49y02bBitoIj0KtUrVCw3ImLY3XdAmBOISyn2Fq7ZZVw08nsqjMzVgg8OGgFsBOjVmC7595EhFtyZnN1RMQdx3ZfxymYlRSL8/R4DWesG/PWdve37jG22269NVq+cMd3mzaleVu8b6puZ0suJAX2Cs4+NpLCfM16v4SzXXSSMSp1nFm6E3FtxRFboukUTXPatSUW2ErJirqb0zYWvWNer9ptzs/F2xyqOrNeOwXYigVHoJqc46p2e+2GE9ctp8hix+7TVDLWTWdG5VbLKcDmKHPbTmHENuKLTckRkqf7CACtmj3HW8mYFZ3ZpevJ9rrejOwkN/BJCiGEEEJyCZMUQgghhOQSJimEEEIIySXUpOQYEdkFYBpAB0BbVXf01yNCVgfGNiFkJTBJyT/fp6oHV9w6EYG1mnXTpKPFpI0VblaKVlTnyctSIWjdEWl6sw2PDg1bo1OhslqMfS0PWbFcpWRVvmVHDNeej6u4zjiVM2fnbEXSwWFbvbZQsrPpdlLBn9oxnJqylWTvuOMuY9u1635jm5+Px/ZrO//btGk5AtjTTj3V2FJN4/ycrUpbLCf+O1WIj5MVxrYChVis2fDEobOxEFoLdp/a6sRK18b/XCMe607VCqXLBSvYroiNqflpu83KhjiOG3O2zeiItbWLThXdtIqrI2LterOC1+34zDjidU1Ft20bBw3ntG8WJo1NnFmck0mW0U1nKwcwXLFfVdK217bx9rpouV2z52kxqYAtjgib5Ae+7iGEEEJILmGSkm8UwOdF5Bsiclm/nSFkFWFsE0KWha978s0zVfVBEdkM4FoRuUNVr+ttkF3gLwOAsbGRfvhIyLGwZGz3xvWGTZv65SMhpM/wSUqOUdUHs98PAfgkgAucNu9V1R2qumNw0Oo1CMkjy8V2b1yPjFlNECHk0QGfpOQUERkCUFDV6ezvHwDwW0ut0+10MTOZKNicCphpBdV2y4oCm22nQmXNVt1MS2x6FVs920TTVrYcGhoytlqyzY5TsdKbXn521qkGmogOG8708vW6HYtu1woAy06V23vueSBafmD3XtNm0BEMT03Y/kuOMLdSif3fs2e/aTM5+R/G9n3PeZaxjSdjXZ+2PoyMJFPar1JlzqONbe0qOvX4WIlz7NrdRAgqniDS7sPknBW7Vkvx/Vt3zlbbbdes4Ha+ae/7qk4F1e5MHGfqxNP0nI3hcsc+LdUkLppFOzbqVGqedc77siMmn2vE7dqOXx6NhhW2NrpWDFxE7G9Z7BhOD9sbsNF5+/U1MRgL38sdq+gtDsY+KOx4kfzAJCW/bAHwSQlJQAnAh1X1X/rrEiGrAmObELIimKTkFFW9B8B5/faDkNWGsU0IWSnUpBBCCCEkl/BJyklEp93G5OG4NpY6s4AWk3e+pbINg2K1amzNli10Njcb6wAaTUfT4cwyW65YzUUhLR4GIK3T1nJmER4YtFqWrjqzyiY2p2aUWxiu6BTCeuiArUF2w86bYh8c/cMTn3imsU1OWT3IzJQttKWJ/55GZP9+q1P5t69+1dgufNrTouWhih2MejM+3qulSTl6ukA71oR4s+5qMY51Z6Jq1MXqJKRrj6/MJZoRJwbEmb26U7QbbRTtbNvVVhz/7SO2iFpz0Inhku1fZ2I9S1Od2Yfr9txtOzNCT85bvUlpPm4317DrwSkC52ljxFm1nUy5Pl+05+BA2/Y1UbXXlcHkoMvgmGmjiUaof3FNVgKfpBBCCCEklzBJIYQQQkguYZJCCCGEkFzCJIUQQgghuYTC2ZOITqeNqYlDkU27VnDWSoqfpcXdAGDTtlOMbbBiC04VCrG4r+FMh7r/sBWBDg7awnCDJSsUHFi/PvbVEaM2OzaMZ2dt8a2R0XibxZLN0eecol3qFI269dY7je3QxES0vH3bNtNm6tARY9t9v53xuOMUqEsrCrecYlwiVuD5wAMP2r4qsTD6qU/+LtOmmgg+HS3yCUGgKBRikWrTKZBW1zjWWzPe+NhxbTWdGbOTnW05M+56IllxZggWp0hhITkvO017bpUaVlwuJbvfrXS2YXGKMzoF61ozTrE1RxQ7mcSZNm1fla49751abiiX7XnfqMX9VZyvpbYjbi44x7LeivsqYsK0kU48zYJ6FS9JbuCTFEIIIYTkEiYphBBCCMklTFIIIYQQkkuYpBBCCCEkl1A4exJRKpex+dRY8FpxKsfO1WNx3OycrUY5MrbO2GolWzmzWYr7H686IkFn5t9ayYbe0DpbHbI2Fs/6Kk4Z0a4j6PTEcOVELFqsOFV1xVa7vP32u4ztwb0HjG0wqXx78KCtStuYt2Ndq9kZXr0qmK12su+OSNartFtwZpWdmonFzPv27zNtBk/dmjpl2pwIugrMdeJ9mO3aaq9IqsS2nOqpdWcW3qozI3cqn+461VmnWnY8hr0qxvNWVFqvxbGiaoWz3ZYz6zisH1pJ/OhawW173hPJWpH4bN2OazOprFtoWDH+bNnueMGr5KrWf5mNz3sdtOvJoBXrYt5ejwqDsR/NeaevaiLkZ8XZXMMnKYQQQgjJJUxSCCGEEJJLmKQQQgghJJcwSekzInKliDwkIrf22NaLyLUi8q3stxWIEJJzGNuEkOOFwtn+cxWAdwP4QI/tcgBfUNUrROTybPkty3VUrVbxhMc9NrKlVUoBQFMBpFNwsViwAsOmU+F0OBHFdmHFhE6xSNRKVtw3NTlpbOVyLI6rVhzxrlMBU7c4otKksm7LcWzfASuivOPu3caGghXdpqJeT5hYdvyv162Y8Gnffb6xbT/j1Gj53l22Uu0Du62vc7NWDCnF+P6k4sTJulPiypzF8lFfLq7CKsR2t6uoT8f7oE4F1XoiSta2U53YEYk3HeV1oR4LTeuOuLLTnbJ9ObHebY/bdkmV5HLZnluVrq3U3ICNn+JcUhm45VR/7dgYmG/a/r0qxjqfnjd2vZl5ez4POmJaiPUf5di3Ytm2aTXtPlUGrIA3PUoVsYLktJhzvyopk5XBJyl9RlWvA3A4MV8C4P3Z3+8HcOmJ9ImQ1YCxTQg5Xpik5JMtqroXALLfm/vsDyGrBWObELJimKSscUTkMhHZKSI7Z2fto2xC1iJRXE/bV3CEkEcHTFLyyX4R2QoA2e+HFmuoqu9V1R2qumNoyOoKCMkZK4rtKK5HbDFAQsijAwpn88k1AF4N4Irs96dXslKj0cDd3747somjih1KKqOqU7m07IgkxRHFjiZ9jYzaqrEzDSt6S0WsoX9LJakA23JEdZ20EiuAVssKK9MtHpiyfn3xi9cZ26FDh4xtbHy9sU1Oxnf8tZIVH4+OjhrbfGO/7X/I7udZp2+Llp/8pMeaNkWnkm+95YiIk2O+ZbPdn3Y9Fv5Wq1aEeAwcfWxrF91OfKzEEYJqKxF4zjnC0LpXsdgKMCURn87P2zYo2BibcwTnxbbNw6pzG6Ll5rgjOO/Yc6kttnLsQFIxd6ZsfdWWtTUcwXl93qlo24ptdTjj5QiLGyXnHrhh47qUiIa1bduUazauO84hKQ7Ex1yc61gV8X571zWSH/gkpc+IyEcAXA/gSSKyW0Reh3ABf76IfAvA87NlQtYUjG1CyPHCJyl9RlVfschHzz2hjhCyyjC2CSHHC5+kEEIIISSX8EnKSUStVsVZZz0+ss1N2ffyQwPxzMJNtZqFRtP+p9DspC1edXging34wLRts3vvhLEdOZKWz/ALzw0k75THBu376prz3rk2YGdjPjITv7u/5a5dps3+g3Z243XrbFFUr7BdO3l331J7DzDpFKzrptWlAMCZubiZtGs0rKZAHO1BbdDOpjtQifUlU5P2eJeLccE6deLkRCBQVArxfs11rb+lZqxTmXJmHy60rOai3nT0FJ04jjvOuGrX2lrOJXVAra1Ri+OgeMCO7QzsPhaLVvMyi/hYdp24KBStrTlr9S2dtt2nw0lhu2rVjpfC+tV17oFLY3b8S8V4fLRrjxvEFosrDlhBdbkYX9vKYvUmrUSdptSk5Bo+SSGEEEJILmGSQgghhJBcwiSFEEIIIbmESQohhBBCcgmFsycR5VIRG8fHI1t10ybTrtOJRXSFihXtaXejsd2zyxaluue+fdHydMOK/Xbvs8XK7rnzbmObODJhbKNJcbizn/gE02bDuC2QNle3vk4kwtmJGSvQO+Mxtn+v2NfBQweNbWAgFjC267b/OUe4OTw0YmzbH3emsRWGYjFwx5m915MAtluOMFdj30pFRzzaiEXXqlZ8eUIQoJsIZ7VjhZrtQjy2HbXC0DlnLBoNK/ZONbFzjgi323REslU78/VUwRbBG55LZv6tWWFot2LvIbslKxYtIBbhekLQ9oxTpM3Ww0Or4wiS23F/XSfu2hVrG5i3+10fdCqwdeJ9Lztx1mzb8ak5xfSqZnZpGyfVcjwWhQKFs3mGT1IIIYQQkkuYpBBCCCEklzBJIYQQQkguYZJCCCGEkFxC4ezJhFRQqm2PTC1HXNatxbauUzlz1z27jG3nztuMbd+BeIbg0VFb6VXrVky4fsiK6ipqBaTrN8TVXtttKwCcSgSxANB2ZlnuJOtu3WzFwVu3bTO2+++7z9hqzgyvpzzmtGj50EErrt23b5+xDVTtafjQg7uMrayxQHJw0I5hs2kFnuqMRbkYCxHFEc42k9mlWy1HaXkCkC5Qno/HaNYRIKcTFTcbjiCy4cRKx1YPbs7G41FvWnGtNK0os+VUly2r9fVgLa4CXJyz52CpYcWiaNkK0uWkmmzXzPcNNJyZsHXeOZ5DTrt2HFNFsXHXcmZSb47aca0VnMqx7fiYlJ0KyXDEuqW23WapmohiHUHyQCm2Fdz510le4JMUQgghhOQSJimEEEIIySVMUvqMiFwpIg+JyK09tneIyB4RuTH7eWE/fSTkWGBsE0KOFyYp/ecqABc79v+rqudnP585wT4RshpcBcY2IeQ4oHC2z6jqdSKyfTX6ajRmcc9d10e2VstW3Uz1ZodnrLj2ppvuNLZv3fktYytVKtFys7HOtGk7wtnTTzvN2AYHrei2OFCNllsdKzCsVavGVi5YUePMdCw6HHCmete6FROOjzjt1BGjlmNBXmnLFtPmgQceMDZU7Gm459CksY2Mb4iWCwN2v+95wApzi46ocSBZd2TUipaHhuJqvyJHd7lYrdhWUXQqifi06FS/bSZj5ghW57t2vVbTCjwbSTsRez/XdgSXUnf6qljxpk7FvlW8KrFiq7+WC/aYN+vJOVGw50jTKfQKcSoWz9pztVOMz6WqI2ItOLHR7thzpN21ottSEp/e8RhwNMQN2wydkfXxcqqmBtCxLpAcwycp+eX1InJz9sjcfvMTsnZhbBNCVgSTlHzyHgCPB3A+gL0A/nixhiJymYjsFJGds7P2zouQnLGi2O6N65kZe3dPCHl0wCQlh6jqflXtaHin8NcALlii7XtVdYeq7hgaGjxxThJyDKw0tnvjenjYvgYkhDw6oCYlh4jIVlXdmy2+BMCtS7VfoFGfx9133x7ZRhw9xWiibZhwZvS97957jW3GKZo2Nh4/re+2nJlJyzbMaoPWdujwAWNbv+WUaLnjvLuvOzPU1p332vv2x7MxVyv2/b4679vn23af1m22epNyKd6nI0eOmDZtp6/qgP0SfsJZ5xhbqv+ZmbN91UY3GNu88/J+uhvrAOamnFlsk2JoLU/XcJQcS2yLANVEZzHpFPIqFOMiYCWx41Pq2Puyuaq1leqxDqOQjD0ATHfsmLWc+Cm27cB1m7Fv9aLVUKFlj1vL8bWcFCnUohVwNLpWa9VpOAdU7H5WkpmL286t7Zije4JT2G6g6BTOK8ciEU9D1VQ7PgPO+EuiJSo5hRJL7bgvYTG3XMMkpc+IyEcAXARgo4jsBvB2ABeJyPkAFMAuAD/TL/8IOVYY24SQ44VJSp9R1Vc45vedcEcIWWUY24SQ44WaFEIIIYTkEiYphBBCCMklfN1zElGqDmDjGWdFtuEBO6Po2GhcpOvmu/aaNrOzVow6Pj5ubI854zHRcqdpBXrFri0od+DBPca2b98hYztyJC7QVR20/8E0MuT894cz8+/BA7EwVx0R7ob1Vnh64LAVwD7k2DZt2hQt79lj99ETzhbV3itUHAHjurTgmlNQTp1iX4Wy/RfedHhajuC5pbHIUdWZVfhEoHYS3G7Vma03KaTWKtl9koIVbg61rShzfjARYDZsm8GqI7IWK0atztvLbHMwPuYCz1dbYK8Le15KLe6r07K+lsWKaTuwxe4cLTnKhTgWy8NWjF+u2XgdGbN+dIdsrI8kx3Kw5BxbRwzszXBcaMeBXfIKt5WT4HeK2pH8wCcphBBCCMklTFIIIYQQkkuYpBBCCCEklzBJIYQQQkguoXD2JGJooIoLnvLEyObVUmwmIskpRwRa6Fgh36hTvXbdurji7AP332/aSNcREzqzFM83rJBPE+Fsc8YKB5s1Wwm37FS5rSTbbKj1a3Jmythm563wdLZuxcDTMxNxmxnbZtAR+V76gucZ29Oecq6x1duxKLkOK5x9YsHud6tlxcyNejzW8w3bppvM/Pv5ASuOPBEUIRhBvO1ZsfuO5PjW1alc6sRFoWxjfXAu3ve6I+asOSLTQtuOUWnYEbJ24v46ThnXgjOLMMq2f0kqrzrabLSadr+HnWqsbUfEXU5EvgNjVrA6NmwF7SXH1+GCU903OSalolW71gac6rJFe73oIP5HgULRma08+dpjxdl8wycphBBCCMklTFIIIYQQkkuYpBBCCCEklzBJIYQQQkguoXD2JKJYLGJsNBawdZxp4uePxELQQ0ceMm1m5qdt/wdsuKQCzIOHbdXY2VkrPN2yebOxnfaEJxnbRNLfdCKkBYC2V+W2ZAVzA0Px2HSdqeT3PXTA2NqO8LdUsuLBubm5aLnZtArGC556jrFtPeMUY3vg4H5jm5qK913VEzdbNWerbceim9yflB0hc01iW6FfFWcLXUg1FiEPOJVdG4n+sVZ17sFa9phPOtV2ZSAWbw45Iuty1VHOFq1YtFK1toFKIgSet/13S9Y2LF4J1bivGbXn29ycFXHLhK2+2ynZ8ZFKfNw3rbfi78GaFc7KoO2r6IhUN5bj49Qq2jZF53zz7rGLicC21LLHqDiY7jcrzuYZPkkhhBBCSC5hkkIIIYSQXMIkpc+IyOki8iURuV1EbhORX8zs60XkWhH5VvZ73XJ9EZIXGNeEkNWASUr/aQN4k6qeBeAZAH5BRM4GcDmAL6jqmQC+kC0TslZgXBNCjhsKZ/uMqu4FsDf7e1pEbgewDcAlAC7Kmr0fwJcBvGWpvlptxe4jsQiw6Agij8zENnHmZx8asze47bYVmD344IPR8uy8rQi7ft2Ysf3YSy82tic9yQpnZ+fiarL79uwxbQ48uNfYpo5Y4e/UbCwenHUEtyjavP2gI9YV2HGdno73vVS2bc455wxjqxbnjG3eqXI7UImP7eSU3Uct2arAQ44fkogTZ6bscZtoxNvrtK3QcjFWM64FgkoiDm11HXFlIqYtOBV5Hf0rBgtWjFpOum/X7KWyVnMEsWNWEF4o25hK19xYsMJQGbQC1VrB7nc3OS717ohp05m2Y9HYYuNnftoe46GBpOLs6HrTpjzoVNV1qu92BmyVWHTidWtq20jVHqOiUx13IInr6tCAaVNLDm5BWHE2z/BJSo4Qke0AngrgawC2ZBf6hQu+vfoRsgZgXBNCjhUmKTlBRIYBfALAG1XVTiCz+HqXichOEdk5NW3vjAjpJ6sT1/apEiHk0QGTlBwgImWEC/mHVPUfMvN+Edmafb4VgC1mAkBV36uqO1R1x+iIfcxLSL9Yvbi2rz0IIY8OqEnpMyIiAN4H4HZVfVfPR9cAeDWAK7Lfn16ur2ajjr333BnZugWrI9mzLy5YNjNhZxHevGGLsU3P2Cc1jaQQ1pBTiOnpFzzZ2MZHrQ5mz/13GZsks6YODdp399UzTjW2zunGhHonftfdcTQpu3cfNLYvfuUGY2s6+oxiois4ZZN9dz/mzCS86w67312nwNjGzZui5Q3OjMozR+yM1pX1NnktFuNTv+oVv6vG+1N0ju1irGZcowCkNcxKTt6ijVjb4NX/qo54ReucTZbi+BxwpjyuDFu9w3jZOtZab9sNdmNbyZmtt1CxjlWcWa47iaai4cyo3Bq1Oo/mlO1rbtSYUCnEvumg1YeMlOy4FpwiaRVH/5NMCI2uE4vttj1XK85syd1qorerWhFSpRSPDyUp+YZJSv95JoBXAbhFRG7MbG9FuIhfLSKvA3A/gJf1xz1CjgnGNSHkuGGS0mdU9d8Bp1Z04Lkn0hdCVgvGNSFkNaAmhRBCCCG5hEkKIYQQQnIJX/ecRIh2Ia24MNjkpBXF3n3bHdHykUPOzMXzVqjWdmZUTm0X/8DTTZsf/eHvMzb1Zp51Xg60knZVZ0bZatmKGsuOkA+JOLHszPh6y233G9uXr/uGsY2PWzHqgWQG5e+94FzT5uLnPdPYug0raiw6osNiKR4g711Kp7nB2AqOglRl+YJWxaSwnVe87ERQQAEVxMe47BSoqybFvZqO2HWwYOOu3bYz+I4OxeMxOGrbDI5YlamWbTG98WEbZ0PJDNN1dQThzngXYdt1O/G/aA85sz/Xqzae5h31cbVuY1E7sf8VZ6bn6oBzPJzZw7vOJM6tZtx/yRH+ThedvtTGbDUpODlYc2Y47ia2fs3uTVYEn6QQQgghJJcwSSGEEEJILmGSQgghhJBcwiSFEEIIIbmEwtmTiNpAGWeftS2ydd3ZeuMpVG765t2mTXPKzpfSalpR3dPPOydafsUPv8C02bbFzqhcdGZz9eRr3U4ys23B5tXiiD7TSrUA0O3GwtmiI67dstFWiR0csmLIU7adYmzzc/FMwmeccZppMzZi+5pXO9YiVuCJZJZfEef0dca11bQVPLudpIqoIx4sVuL+u30TGCpQjCv8DjozHNeHk4qzM1bgWfJE1k4l3XLS13DVimTHhpzqqc4hqVStsVKN/ah0rK/loh3vrqMHLyGO2YYXT7P2fNABWzW56ghzS4NxddyuM0vxsDPbuhbtWKczVQNAqxTb2s75PDxv/S+0ra/FRFCtRafCcHI8Cs45Q/IDn6QQQgghJJcwSSGEEEJILmGSQgghhJBcwiSFEEIIIbmEwtmTiEKhhIHBWETXdQRtw+s2RstTU3OmTcepLrvBEZW+7CUXR8ubxjeaNnNO9VqncOwiArbY/5Z1C6WSI6ZVK6y069mxKVasbd3YmLENDdgKpKkflaIj3u1Yv2oDVoCpTrVORWwrivW17QhuneFBoxUfE3ELcyYVbp0KnyeEgqCUiB0HhmzF38H5eHxKw3asy0V7yWurEweJJnNk3YBt4/iw3qk4Wxq0x6RTio+5NOzYdot2mwOw51InqcZacMSvECuSLU7bk7A9YMdnVOL+ukW73+WCFdN6FWG7jhi42Ip9a85aH2pij2Vx0G6zkRaTdYailVS01X7FNVkRfJJCCCGEkFzCJIUQQgghuYRJSp8RkdNF5EsicruI3CYiv5jZ3yEie0Tkxuznhf32lZCVwrgmhKwG1KT0nzaAN6nqf4nICIBviMi12Wf/V1X/qI++EXKsMK4JIccNk5Q+o6p7AezN/p4WkdsBbFt6LZ9CsYqBdY+PbIcnJky7tsaiva43pXrXCtW2bNlsbVtjoezE1KRpU3SUmx1HqOlVgC0n67YdQW/XEckWnPq1nXYsYOx0rPButm5FxKWC7X/jeiuQHE4qkA7XbMXN5rzdplMU0/jq0XH28dChw8Y26wiXy9V4o9UBqzDsduPLQ2cFYuQFVjOuBYJSIt4cLFl/54dj21DdDmzTCbzRkhWQylC876WqjeGRsiPYrtkxKhWt8Lpciv2QmlM1uWljoOVUx60l53OzOW/aVFtW7FpxqugWnGqymlQerhTsGErR9lUUG3c67yjfk8NUqDiVZIcdkWzdtqsmIuKiIyJOtfFOgVuSI/i6J0eIyHYATwXwtcz0ehG5WUSuFBFbW56QNQDjmhByrDBJyQkiMgzgEwDeqKpTAN4D4PEAzke4I/3jRda7TER2isjOiQn7FIOQfrIacT05OXOi3CWE5AwmKTlARMoIF/IPqeo/AICq7lfVjqp2Afw1gAu8dVX1vaq6Q1V3jI/bx8qE9IvViuuxMftqjRDy6ICalD4jYQrf9wG4XVXf1WPfmr3XB4CXALh1ub6ajTncd/d/x8aS1UUcPnIgblJ23sk7xZ8Ga7bd0GD8PnykYts0W/Z9cskpmlZ1ipqJxu+Yq86Msp22o5Xo2vy7lczi22jbfRwZsYne2Lh9n+9IIiBJcbV77nvItJmY/E9ja7Trtv+qPW6zc3G7RtO+339ov93mzJztf3Q03qfRsSHrQyKWmXRmxl6M1YzrQkFQHYjHoztn970yFGs4CkVH/9OxcVFyCvMNJNMNi9q4Vue8KXftcSs4+q5SISmQ5rQpODOYixOz3WTmX3GKCJYrdryajual6+hNyokWqehocVod21fZmTW7U3ZmnG7FtkbV7mNrztHsVOzxrSZV+EoVezwkLTxHTUquYZLSf54J4FUAbhGRGzPbWwG8QkTOB6AAdgH4mX44R8gxwrgmhBw3TFL6jKr+O/xc/jMn2hdCVgvGNSFkNaAmhRBCCCG5hEkKIYQQQnIJX/ecZJSSB+yVms1DN6yLhYKDg3a2VXVm662WbbgMDcTrlpzpdKs1+98ZFUdg23ZmQT588Ei0PDtt/x1VnJmeG04xtMOH475aLSvQu3f3PmM7MmWLY83M3W9sE4enouWb7rzXtNng/KfK9NSUsc02rNCx1Y3Hp9t1RJROYT7vpcuefXHRt44jyKwm6uCZWTsOJwaBJJeq8ohTlG0qts07+y1OUbay2v3qJLFecmJfW1aQrGVH7Np1ZqtO4tPTfhe7zuzJzmzAmhbra9n9aThC8kLT8d8R2qcj3W05s0s7BQ+la9XlBXVmXDdFA6dNmwqc86FpfUU1EeG2bZwMDCXXO+G9ep7h0SGEEEJILmGSQgghhJBcwiSFEEIIIbmESQohhBBCcgmFsycRAquRbNftTKSdZCbezeMbTJuzv+fpxnbv7j3Gdtu3d0fL485suiVHmNZsWb+aaoWC05NxldNSwYbs5s2bjM3R8WG4Fgvm1m+x6007VVzHNhw0tmdecJ6x/f2hT0XL33uhHcMLnvoEY5udsP231Y7Z4elYdDgxaQWG01NWWJwKhgGgk8wmPTpiq+qOjcZVaA983M6wfGLoAqVY5Kkdq4otJLFRcETj6DpVYls27gqVWHBZcmbTLTox5sW1o3VFEbEfUrTCZbUmqCNGbXfiONCyXVFadrzqjqi0CFtVuFKIhfYdtULgrnO/6wmS1dF1dxAPkDix3xTnuJUcEXFS+bbifMNpI+nfqYxL8gOfpBBCCCEklzBJIYQQQkguYZJCCCGEkFzCJIUQQgghuYTC2ZMIhaKTVBwtFWweuuOpT46WazVbcbYoVkw4OzdhbLfcfEu0/NhtVox65umnGtt4UvUWAEZGR41tcCAWbw4O2oqt4lSj9KqxTiUiXHUEc2c4lV6/XrjN2LZv22Jsz3rm06LlmRkrbJ2ZnDC29U4V2pmGFWCuTyrAnrbF+lAubje2IqzQsVSMT/35uq0+OjUbi3CrVStePDEUUOzGMVruOmrUWuzfYMsRRLacyrHDtnJpqRSLy1Gx51GrY2NsoGzbqThq0VYcG92iM7ZlK5Ltdpy+EgGsztnjrWKFs5WiHYt2ycZdqmMtadO0kZZT0dZRDHcL9ph0JY69UrtmfUiPB4CSU0q5KPG6XiXfQqp49qbBJLmBT1IIIYQQkkuYpBBCCCEklzBJ6TMiUhORG0TkJhG5TUTemdnXi8i1IvKt7Pe6fvtKyEphXBNCVgNqUvpPA8D3q+qMiJQB/LuIfBbAjwD4gqpeISKXA7gcwFuW6qhYKGJ0JNZ17D+w37QrJPOaPv2cM0ybjlPo6annPtHY6vW4YFPNeXc/Pm41F4MDVn8y6eg1Jurxu+gZp1hZpebMtuq8+9794N64rxk7I2tb7Qvqiy48x9juuvVmY9u6PtbPbNi43rTZu+9BYxsdfKyxrR8aM7ZGO9ZOVAqOFserS+XoEdqdWAdQdPQDtbQ4mtP1EqxaXAvE6mqcgl9SjAvSFZzigLMFq20oVq0mpVKMtQ3q6J68YnHlgu2r0LLb7JTiWHHqkqHrVIsrOMeyUIm32XQ6KzkarXbNtqt0bdwVNNapdMvWh7JTbA1OATk4mhdpxWNdcArKlar2GtKCUwCvG/cvntYnjR3Wcss1fJLSZzSw8M1bzn4UwCUA3p/Z3w/g0hPvHSHHBuOaELIaMEnJASJSFJEbATwE4FpV/RqALaq6FwCy35v76CIhRw3jmhByvDBJyQGq2lHV8wGcBuACETl3peuKyGUislNEdk46r0II6RerFdfeHEWEkEcHTFJyhKpOAPgygIsB7BeRrQCQ/X5okXXeq6o7VHXH2Kh9b0tIvzneuB4fs5MfEkIeHVA422dEZBOAlqpOiMgAgOcB+AMA1wB4NYArst+fXq4v1S5a9Vh05ujs0E5mfS0O2sJqUrKhMd+wBb+aibC1WrLCwbk5OxvqzLQVrTacAmaddiyY1K4jVnSmOlVHVKpJYbutW08xbbwicKd07Jfk9EZrS4vDDQzYolTlst1myRlrcYSsQ+VUPGqLdrUcFaCKtQ0kYsvBDTbBXbc+Lsw3OGTjZDFWM65FBJVyLICcF+tLWket27aC6nVdu17HiR9JiqaVYeO6O2Bjsdiyx6QzZGOxnMyqXHQE295xK1ZsXHQqSV/OzOe1jj2+DTizFItzLkncv1NjDt229b9bsOdSuWDHv6LxdaVbdMS7zkzq3pdXqRTHSbvgFDJMriGeGJnkByYp/WcrgPeLSBHhydbVqvpPInI9gKtF5HUA7gfwsn46SchRwrgmhBw3TFL6jKreDOCpjv0QgOeeeI8IOX4Y14SQ1YCaFEIIIYTkEiYphBBCCMkl4s0ES9YmInIAwH0ANgI42Gd3joe17P9a9h1Y2v8zVNVOc/0I0xPXwNoe37XsO7C2/V/K9zMBXK+qF59Af8gKYZJyEiIiO1V1R7/9OFbWsv9r2Xcg//7n3b+lWMu+A2vb/7Xs+6Mdvu4hhBBCSC5hkkIIIYSQXMIk5eTkvf124DhZy/6vZd+B/Pufd/+WYi37Dqxt/9ey749qqEkhhBBCSC7hkxRCCCGE5BImKScZInKxiNwpIneLyOX99mcpRORKEXlIRG7tsa0XkWtF5FvZ73X99HEpROR0EfmSiNwuIreJyC9m9tzvg4jUROQGEbkp8/2dmT2Xvq+luAbWdmyv5bgG1l5sk6VhknISkc2T8ucAXgDgbACvEJGz++vVklyFMDNuL5cD+IKqngngC9lyXmkDeJOqngXgGQB+IRvvtbAPDQDfr6rnATgfwMUi8gzk0Pc1GNfA2o7ttRzXwBqKbbI8TFJOLi4AcLeq3qOqTQAfBXBJn31aFFW9DsDhxHwJgPdnf78fwKUn0qejQVX3qup/ZX9PA7gdwDasgX3QwEy2WM5+FPn0fU3FNbC2Y3stxzWw5mKbLAOTlJOLbQAe6FnendnWEltUdS8QLpYANvfZnxUhItsRJtT7GtbIPohIUURuBPAQgGtVNa++nwxxDeRzbJdkLcY1sKZimywDk5STC3Fs/PetRxgRGQbwCQBvVNWpfvuzUlS1o6rnAzgNwAUicm6fXVoMxnUfWKtxDayp2CbLwCTl5GI3gNN7lk8D8GCffDlW9ovIVgDIfj/UZ3+WRETKCBfyD6nqP2TmNbUPqjoB4MsIGoo8+n4yxDWQz7F1ORniGlgTsU2WgUnKycXXAZwpIo8VkQqAlwO4ps8+HS3XAHh19verAXy6j74siYgIgPcBuF1V39XzUe73QUQ2ich49vcAgOcBuAP59P1kiGsgn2NrWMtxDay52CbLwGJuJxki8kIAfwKgCOBKVf3d/nq0OCLyEQAXIcxQuh/A2wF8CsDVAB4D4H4AL1PVVICYC0TkWQD+DcAtALqZ+a0I7+9zvQ8i8hQE8WAR4WblalX9LRHZgBz6vpbiGljbsb2W4xpYe7FNloZJCiGEEEJyCV/3EEIIISSXMEkhhBBCSC5hkkIIIYSQXMIkhRBCCCG5hEkKIYQQQnIJkxRCCCGE5BImKYQQQgjJJUxSCCGEEJJL/j/0BJjJk3hIMAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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9q9hvL1Obi8X5ADoIWpj5/LRnRGQAQQ/0TgBHFefuavR+HR8Iz0MYlQDCC8r5CPqLFQgjAujaf+kalfBrkX9GeBisLuz96YHYq6obEN4wH2wR798iHMeji/vk78LaO9c923vY/heCVuXJCH34ifmMUCvUBEKg8MCoXnG/OAXRVElXGzer6m+o6mpVfTrCFO6PDqQthOnLmXvirQBOjnz6zK5tb8Y8I/4icgnCs/BpqjqfGLpe2L4cwDoAny2u/euK7zcW97X57I6ZsVEAQFV3qupLVfVhqvoohPvMj7o3KJ7BL4Sd6jkPwD8UgwAzLwbXishL5jm2mXZXIjxnr1LVv+llm/mYM0gpoqlLAPyTiDyjGG47EWEodyN6cNKCzyFMJTxBwi+CLsGB35CWIQglJ0TkV1BEl71QRK2fA/APCEO/1wCAiDRE5KUisqKI3McRRis8Xl7Yf1bXv+cDeLYETccvEd5Yn128if4lwjTEDFsQhr2TwqYNCELRvxWRQRF5NIL6eeYN+/8A+JviRjnzk7jzezzkDwP4KxE5VQKPLmy8GsBpEuZqaxJ+avpIhKHbexCmby4p+uVJCPPiM1yOcC6fXryRDkr4Ge2xPWy7mCxDeIBuA1ATkbeg/FZ0BYA/F5GVEnQ0r+767kcAxkXkjSIyVBzHGSLyWGD/z4K9nRbXxFsAvF+CxmC4uC6eKSJ/vwD75/Mjj0sB/Jns1908KIjIKgm/Ong/gL/TMKU2n58uhAbCNbENQEdEnokwrL6oFOf1JBH5J4RRqEuKr5YhvHztQHiheEe06RaEh8kMIwgPgm1Fu69AV5Ah+38SeqJjw0oRuUREHi4iiYSpgt8H8F+LcIhzsQxhpGB34f9vWOD2pftUFx9H0DZ1ijf8A+GLAM4QkecXvvwWADer6s+9ysV9a7C41l6PMGr7sV7aEpFXiciRxd+PRBByfxMAVPWXAG4E8Nai/ech6J0+39X2ShG5sPClFyCMyP2gaO/PEYK1p2qkuxCRcyRodRrFPeaNCCO1P0R4mToa+6/7mZejXwfwQwmjYC8WkdFiv09HeKn+VtH240Tk9MKfViNMZX9nZvRDRE4RkdXFts9EEBfHP6l/HsIPH74dlZ+GEKjN2AaEe/gXi7bTop9rAJKi3+rFd8sRprt+oKomXULxDBpEuP5RbDsQ14uZ9yfIqvr3CKMV70R4eP8Q4U30vPmG+rrauBXA/48wL70ZYThtK/bPsS2E1yM4xl6Etxv3p2tz8CmEN6gro6G2lwFYL2Fo9H+iS2g5gwTx4okA3q+q93f9uwpBHHdB4Sh/iBAg3IcwstI91HZl8f8OEZnRvVxQtLsJwRneqkHrAYRfsFwF4Bsishfh5va4Ho/13QgP628gnLuPABgqLqjfRhg63YHwy5ffVtWZ6buXFPvYiSBAfWBounhYnY/gE9sQfOEN2O9Ls267yHwdQbPyS4Rph2mUh6/fjtDvdyMo+j+Hwt+KKYjnIFyEdyNMW34Y4a0aCKMu1862Y1V9N8Jc619ifx+8Gj3qRXrxo1k2/SqCcPp/9LKfA+AmCUPydyDomf5EVbvnpufy054ppoxeg+CbuxB85qo5N1oYjy+OYxzhFy/LEX7tcEvx/ccRfOY+hF/qxAHDRxD0abtF5Euq+jMEPcK1CA/vX0XxoCo4rqu9mBZCn/17Yc9PEfzw9w7qCOfnEgCPQXggfhXRjx96wLtPAeHF9Ax0vaBKSEjXPWUwJxo0Ms8H8DcI5/9x6NKDSUju+bWuTV6G8NzYivCm/9SZZ898bSFMzdwiIvsQXs6uRrh3zfBihFGNXQgvAS8o2oQG/dPvIDxz9iD8wuv8rvvkOxBGE2+X/VNaM20PIAT5OxD84lkAnq1B16Td1z2K4BfAFg2aTUV4+d5Y2PVOAK9V1Zmf856MoDvZi/3+1H3P+HWEX9ftRRhRe2nxDO7mQgAfj6enVHVrZBsQpm1npmtfhjCV9EGEEbUphOcwEAKfxwJ4hZTzsMyMpp9Q1J+xZQpBmDwn4kyhPeiIyChCFHeqqt59yA0gDzlE5H8BeLGqziuylpD9+EpV/fp8dQkRkb8EsE1V/++8lZc4EqYJtiJorG7vtz3k8OeQBSki8hyEYTZBeCt5HIKjH/ooiRz2SPh56MkIb7+nIrxNvk9V39tPuwhZykhIZPjbqvpb/baFPDQ4lJkGz0cYIhQE3cKLGaCQB5EGws/TT0IYtfsM9qv6CSELRETWI9y/n9tfS8hDib5M9xBCCCGEzMeDtgoyIYQQQsjBwCCFEEIIIZWEQQohhBBCKgmDFEIIIYRUEgYphBBCCKkkDFIIIYQQUkkYpBBCCCGkkjBIIYQQQkglYZBCCCGEkErCIIUQQgghlYRBCiGEEEIqCYMUQgghhFQSBimEEEIIqSQMUgghhBBSSRikEEIIIaSSMEghhBBCSCVhkEIIIYSQSsIghRBCCCGVhEEKIYQQQioJgxRCCCGEVBIGKYQQQgipJAxSCCGEEFJJGKQQQgghpJIwSCGEEEJIJWGQQgghhJBKwiCFEEIIIZWEQQohhBBCKgmDFEIIIYRUEgYphBBCCKkkDFIIIYQQUkkYpBBCCCGkkjBIIYQQQkglYZBCCCGEkErCIIUQQgghlYRBCiGEEEIqCYMUQgghhFQSBimEEEIIqSQMUgghhBBSSRikEEIIIaSSMEghhBBCSCVhkEIIIYSQSsIghRBCCCGVhEEKIYQQQioJgxRCCCGEVBIGKYQQQgipJAxSCCGEEFJJGKRUGBF5hoj8QkTuEJGL+20PIYsFfZsQ0guiqv22gTiISArglwCeCmAjgOsAXKCqP+urYYQcJPRtQkiv1PptAJmVswHcoap3AYCIfAbA+QBmvZGPDA/r2NiKUpl4FaVcKm6g2lvwqtEO1Nmu5+YdY+P2pMe2vODbltk67VanJ8PS1A5Cqualz1mWmzptp6yT2/Zz55gSzaId2ra8Y/J8IMvK9bLcayu2KUeujrELZ0G+vWx0RI9YvSoq9U569LHHFzCvmsS95jme2K7wrzdvp9E16LTln8seri/xBsh77Qtvn7FtPV68PRP3tVOl13N5AHu/f9s2TE03v66qzziAzcmDDIOU6nIMgA1dnzcCeNxcG4yNrcAfvfIVpTJJ7A0rTdPyZ22bOuKUeY+nPCnfFlrOg7PlPP/Sji3MxXmoJ+WymjULaDvbdWyw0YnK1Kmz+b6ttn21l8nYymWmrNWaKH3evWfS1Ll/17Qp2z5pz1Ers2WN1u7S5ySzbSGzHZTC9s/Evlbp85691tb4ubk7Or6DYEG+fcTqVXjHX7y2VNZx/CdyRbTaTVMndWa4223rB3Wtlz5rIzN1RAasDaYESOtOYJGVfSptWB9LnMAxEXvOs6x8PWutYY2IA1x4wQeQdWyfJRLZ5kXQcR3YoB0AwiBaVBYFbOq+AFi/TtTWa0a7TGHPbZ6W9/fmv3sv7rp3AwOUikJNSnXp6dVKRC4SketF5Pp9++yDhpAKMq9vd/v13ol9h8gsQkjVYJBSXTYCOK7r87EANsWVVPVDqrpOVdeNjAwfMuMIOQjm9e1uv142OnJIjSOEVAdO91SX6wCcKiInAbgPwIsBvGSuDQSCtFY+pd5cdzzdkzh1Os60yt6pKVOm0bZbdtjh6A332SFkaY2bsnrDDs2OjJUDr6NWDpk6o4N2eFucefk0KfdNx9EZjK1cbcqOWLPWlGV5y5Stv2dP6fOO3XtMnT3jdrt2Zu3PUTdl8YhCDfYkrXAe6LkzhN+MTnCsLQIObH6/Rxbm2wrk09GUQMv2YzOeC2zag9qX277InYGdVjQ9UnemLGvOFESn5vhdy05x5I3ydSL7nOkSZ361Hs9pAciid80ks9eptJ0plMROAdUc7UdHyseZeFou2Os+d/aZNJxjysplbThTUzXnUeVM07Wj/s+c40nNtcUfj1QZBikVRVU7IvJqAF8HkAL4qKre2mezCDlo6NuEkF5hkFJhVPVqAFf32w5CFhv6NiGkF6hJIYQQQkglYZBCCCGEkErC6Z7DCBErivVIo9wpO1tWzHbzHdtN2cZNW0xZhvL+8mkrQquP7zVlqwatuC+pW1Hj3omyi47fb1122TKbs2RoyP7SaXi4LLodHBy0bY2tNGWnnHq6Kdu0eYMpu/2u9aXPGzfZnCvNjj0/tcEVpqwxOGrK0lpZ8OeklYE67x3q5KboRIJCN0VbD8nvDg0KJGWRZEesuLLZLpdp01F/e4pwJ8fHdNSPLSfXjJfQD/scoaaTJ6XRLPtiW6wIVMTa2lQrqE4iAbhYt0aaO+1n1i8yxw6NEhA2MytaTp1cQqjZ9tNJe0xZ5J9OiiBIx+7TE/AKyiJ0cXIhyYDJ+md3SCoDR1IIIYQQUkkYpBBCCCGkkjBIIYQQQkgloSblsEKQRHoTb7o1jeaK799k9Sc3/mK9KfMSjElaXr9kAHbuWNL7TFlbbDK3miOyyFrl9ndut/Pcm+6zWplGw9o6MFBu62HH2CRta9ceb8paVv6AyabVz0xOl4+9ldnO95Y98Wz11uCJeyep2e2cJW3QdLQZnciQzF25sUwfFSlox33ZdkQ0ketl3lqRjuCh4yR4i9eB7DjZ7mrO7VOcZGuTLVuWJGWd1oCjj/L2mWZOYsQ4gZwjMJK2tbUxYB07czrNXPfxAjkA8gFnzShnsc5W4mwbnZNBb/2v1B5To+ac4EgT12rYvh+KurDXhShJf+BICiGEEEIqCYMUQgghhFQSBimEEEIIqSQMUgghhBBSSSicPZwQZ0XjxBHRRau+ji23or2Vg84KspNWtBeL+6Y6Vow3vsfGwlunbVt1J2GWRoJJzW37XlItdWSecdnuCZtkbv29m0zZ7j2TpmzVKpuAbXC4nFSu2d5hbXVWzl01ahPP7XT2qVn52NtOoqrpCeccte0KtZ1IIJnntu+dxbH7gyokTkbm3Lk0j0TjzjFlYoXdme0edPKyQLvTtv06ldr+rzkiWSd9HBrRityZ4xe5c4yDNSdTW3QNinM83orHnbazT3VWFM+dBiNSb1XqjiMIT20/plECuSnn3VlyW9ZyhLm16IcDXsLDdmQWZbPVhiMphBBCCKkkDFIIIYQQUkkYpBBCCCGkklCTUmFEZD2AvQAyAB1VXddfiwhZHOjbhJBeYJBSfX5TVW1KWAcBIJFwLM5AGyqWhXbLhqwbDKoVuI1PWAFdMxLCtR2lWiwSBABp2NWGs7YV3yFOMOtknhQnY2unY+3XaOXc2tCQqbNsuSNi3bXNlG3fbk/Jrj3lfWZO5s8TVtvVjQc6dkVoZFbo2IjOSeKsWNtJvNV0ncyiKJfljiDZ9Z3FpSffFjiCcGc14EYS9X9m/S53+tXLspq1ym21nCyrWWKFp20n5W/T6cd2dJ7EyXo6kNvsylNtJ8tqdE0ksHXa5kIC0qbtC1V7DdYjX8nUbieO/DSxGlzAWXm5E9lbc2x1ktBC40y7ANpJ+R5V6zj3nvixR+VspeF0DyGEEEIqCYOUaqMAviEiN4jIRf02hpBFhL5NCJkXTvdUmyeq6iYRORLANSLyc1X9bneF4gZ/EQCsHLO5OwipKHP6drdfr15JvybkoQpHUiqMqm4q/t8K4IsAznbqfEhV16nqutGRkUNtIiEHxHy+3e3Xy+nXhDxk4UhKRRGREQCJqu4t/n4agLfPs5URO3rLkGukQus42U0HU5vZUgesEDRrldsacsLe3BHTJnWrqmu2rNg165TFiTJgH1jekvbtliM8jYR2u3aOmzqnnPxwU3bCCaeYsh9871pT1myX93nKw081dY5sWLu2b9tlyvKOPW9ZVj5PjZqXEtbJ2usIHdNIiFofsud7+fLlpc/NLfc7+1s4C/ftBIKBUknHSava6ZTrQOz5zdu2f9qOWLQTncs8s9vt61gbnCS0yGTAlHUa5f5PHVF6PmDPiTjHbXTpnrh80trfsvpUCOw12O6U28sct6vHGYEBpI6IOHVEvVor3ws6Tiem8O499hpJI5F46mSq1ZRK2aUEg5TqchSAL0p4mNQAfEpV/62/JhGyKNC3CSE9wSCloqjqXQDO7LcdhCw29G1CSK9Qk0IIIYSQSsKRlMMJASTSGmRO8qqYqUlnldMRm3Ss6cyt61R5flcmbWIycVZuzZ057Exsgq48ml8fHltl7Zp2tAGZM18dJSwbH7danJt/doe1C9b+KWcF4k6k9RkdWWbqtNt25eWOM8ef1rwEbFFFZ/VnZ+oe6YDV/4w0yknr6o5GyFsZuR+oKDomIZ3jP3lZT9Fxkum1nRWhm452YjLSrrSd5Ib5tKNv6TjnpG5tTSJbp9W5thJHf5JaTVYt1tTEy/wCqHurIDv2q5N4rpbE9ey1lTuO13b0cImjT9Ppsu5syNO+daxuSGpO0reoq6VujyeJfMlbMZ1UB46kEEIIIaSSMEghhBBCSCVhkEIIIYSQSsIghRBCCCGVhMLZwwm1YsfMSUIVJ3PbMWnFnOOOUDAZtSsEN4bK4rWWI0ysw6423Gk5K//WrXhQ8kgEWLN1PC9OnGrtqbJteWrt2rpjnynb/cMbrF3iJFvLy2X3b9lq6qwctQLVhpNR9eRjbCr4eqPc12lqhYPeKr/TTXsut2zaUq7jiKc7kTi4X0JagaAm5fepjtr3qzxazThr2VWK3WRuTuK/OIlga9r2YctJFCZwEuc5ScdakZC17iTmazki3MGak/QtWllY6s7+xLG15ghbnftFHq0knIkVsbYckfJg2xHrNuw+a5GgvTXpiHetdh3iJDwckOiacPq1rlF/eWpzUhk4kkIIIYSQSsIghRBCCCGVhEEKIYQQQioJgxRCCCGEVBIKZw8jFGrEjbFIFgDa7bIocHzcrsK7zNmuZnWI2DVVFsBOeElQ61agOjJoRbhwMrRKZEfqrII86KwsnDkC3mSsLLTLpu0BqSM8HRiyl0kns0LKWMZay+12k227zxXLbF/86pmPMGVrjjiq9DlzhKz79lnh7x23327K7r5jfelzu+n0hfGlPmXmVIVGglcnASnakZh20lmuN/NWKXb0wPEKu7lz6B1HhOv2UeJkS5XINxIrgu44wtlObusNDJTbUk9U7NiKmvXPJHf8AFGZ02GJk7U18zLTduw+syh7cOZkx0XbEdPWbWbdLMq4PVi3PpBHIl/mm602HEkhhBBCSCVhkEIIIYSQSsIghRBCCCGVhEFKnxGRj4rIVhH5aVfZKhG5RkRuL/5f2U8bCTkQ6NuEkIOFwtn+8zEA7wPw8a6yiwF8U1UvFZGLi89vnLcltWLKjiMEbUdlkts6Y0YGCoyJFaqlWVmgWnNEb4OjVjibOBkqc9hsrLmUy0Rs6klvqfUOrLA1iwSAdUe7Cyc7aM3JzFlXT2gaCSTjdeMBqCPm3LPXil1/+Ys7TdlwJDZevmzM1BlcsdqUNc6w6XfXrC6LcHds3W7qbNu2rfR54qe3mDrz8DEshm8LkEauJ01H7hhlgE0Te46mUk+U6QhgoztjJ858DKDmtOUkr4U6vj5UK9taczKj1hqeCt0rK39MHRFufdDanzsZW9XJopvF2aEdMWqnbfeZOseUeIrntNzZiTqd6Nx7cscHjK7YaSofiCsx42yV4UhKn1HV7wLYGRWfD+Cy4u/LADz3UNpEyGJA3yaEHCwMUqrJUaq6GQCK/4/ssz2ELBb0bUJIzzBIWeKIyEUicr2IXO/lyCBkKdLt13sn6NeEPFRhkFJNtojIWgAo/rfL6Rao6odUdZ2qrhtxVtMlpGL05Nvdfr1slH5NyEMVCmeryVUALgRwafH/l3vZKFfFdJTRdNs2+wxot8uCziSxbrBrYo8pq49YAWYjWhb+qLYVrK520nxqzba1PbXC2W1S3lZy25YkVlTXEvtgiyV79dQTyXpCY7vPxFHkpZ1yWdq0IsGOY3+7NmrK1m+xGXNHfnxT6fPpp9ustCuOPt6ULV9uf0CzavURpc9OgmG0W2X77954r620cBbu2yqQSBGZiDU4i85J3nLEnGrV0q18ypRlUVbVVOx5y2tWEN4wXgagZu2Is8LmmRWEp2qvh1rdlml0/cbXJAA42m+Mi9P+gLU/ia7VvGP73kn+CnWE4+JkuU1jlbKT0Vad811v2H4FYkOcDL1aLqNsttpwJKXPiMinAVwL4HQR2Sgir0S4gT9VRG4H8NTiMyFLCvo2IeRg4UhKn1HVC2b56rxDagghiwx9mxBysHAkhRBCCCGVhCMphxGTk5P4yU9+UirbuTNOU2FXyq3X7ITy1p17TdnwcjvHfMxRDyt97rTtPPf9mzeYspGGnYNfu2aVKTtqtFxvc90m6NrdsW1BbVuqK0qfp1OrRUDD/pJEOl4iLDtHHktcHCkC2mq1Ji21Op5hZzVd3XRf6fONO3eYOkc/7vGm7OQTTjRlnaysPfC0AqPLyqtSJ6mnATgEiCCLfDRJnHOeTEV1nISBbaslEk+b1Clvmzt6qcRJ/Ieafe+Tuu03ScrtDTnJ1mo1u8+6o+VaFtVzpCzoOAkPB9X2j3jHFOk6Ok7CN3H82mZWA0S8bHdRckl1tlN7viWx12CjEa1e7ejtspHouPmqXml4egghhBBSSRikEEIIIaSSMEghhBBCSCVhkEIIIYSQSkLh7GFEu93G5s2bS2WDg1Zw1miUlXUT+yZNnaztJCKbtAnedm0vi9Ca046wddIRHe6yYtHluzabsuOPKCfMOme5bUuG7TFuH7DC352ROHRPbrdrtu0l4a2yrLkta0t0TENWhDvmCDdXT9q+XumsFjscpZ36wfYtps7Gm2+w7Y/ZZG6rV5RFxLkj1G1FydzUqXNIUCBe0LjtrHIdJ+madOzNHO2vdpzVeqMEgbXEisZrDbtd2xGVNpxkg0k9SsDmCGfrqW1rZMD6ZxLZ4SW6SzMncZuToC5rOGLdtNz5U3Ay/4m1K2/ac5TkzraxuNVZBVmcFa3jVa8DZfsbzhOubpK5MZ1bleFICiGEEEIqCYMUQgghhFQSBimEEEIIqSQMUgghhBBSSSicPYxI0wSjo+UVdQcGbIbKFZFostmygtXBhiPcdJZSnYpWS96918komdrsrxOpFavt7lih3f33j5c+37Pbtn/sMmvXyWNWoHda1BUDA7tMHaR2O6k7x+QIKWMtbWPIrsQ8MmRXzm3us329a6fNhnvP3rLgL8+WmTqb7rerXt98682m7L+d84RygZOdtW9C2ZgEQHTu0qYVeE51yn2WOZlLk7o9zrqTeTVJohWtvSyozgq7ac36ReoIZ4eGyrdecTLJ1p2Ms17m23okFoUjiE1s85CmPb/13MlCG628XMvsdSqO+HjKyfaqbevX8SWnjjBXO9bWfNheSxot513PnJXbEwpnlxIcSSGEEEJIJWGQQgghhJBKwiClz4jIR0Vkq4j8tKvsbSJyn4jcWPx7Vj9tJORAoG8TQg4WBin952MAnuGUv0dVzyr+XX2IbSJkMfgY6NuEkIOAwtk+o6rfFZETF6ctIMsckWfE8PBw6fPKVattHSfzZD5lM6g2p8uiz1bmZIZ0Mq+21GZBreXDpizrlLPC/rxl69w9YW29bcrJ4lor983RNZtp98hBK9qr15wl4R0x7fBI2bbpSSvI27x1pym7Z/e4KdsybvssqZWFuKOrjzJ11jiixrs3rDdlxx93TOnzcceeaPeXlN9hFiqkXSzfFgCJlG1pq32/SpKyH9TrTqbgjvXPTs2ep1oeiSvFimQdDS4EViSbDjgC2+h4ROzx1MWxK3FEpfXpclu5k1bXuS84iWmhg44gfLpcsZbY9nN1xLqZ4y+OSLml0TlxxLuoOe/TTvbaoUjgrA3nIGPxsdPPpDpwJKW6vFpEbi6GzO0TnZClC32bENITDFKqyQcBnALgLACbAbxrtooicpGIXC8i17fbzigGIdWiJ9/u9uvxiYlDaB4hpEowSKkgqrpFVTMNP/r/ZwBnz1H3Q6q6TlXX1et2qJmQKtGrb3f79fIo9w8h5KEDNSkVRETWqupMhrXnAfjpXPW7tkOaxoGKF4eWy4YG7GrANWe+t5nZsmSivNpwI5+2dZxET7kuN2WtxNGkDJTntZc7qzOvXWE1KUcdYxPIja4oP+yGamOmzr1b7zdl4xPbTNnmTbYsjxJOtaas/qTVtn2YqbV/2h4mhsbK53Yosee25mgPppq2sZ//4vbS5+Ehez5WrCiX5d4KtgvkQHxbIcjTstag7qxAHAfpbacvaoNWJyFOX3cGyu0Pi92u5mgnvIV5cycpW60W6TqcxGdJ3Vuy2dGpxJoKR2KhdSebm7OSdO5c483I/tqU1XJNq5MEEXZkd9ppX1E+T56sLV65GADE0Zu02+XzlGX2hIizgjmpLgxS+oyIfBrAuQDWiMhGAG8FcK6InAVAAawH8Af9so+QA4W+TQg5WBik9BlVvcAp/sghN4SQRYa+TQg5WKhJIYQQQkglYZBCCCGEkErC6Z7DCiucTRxBXj0S0QmclUmdlVsbQ3bV3cF6WXx35BFWsDq09hhTduste02ZwAra0iipXNtJvNUUKwA8+cTjTdmq5WVhbiO1vxpp7bOiQIVNVLXBEQDu3l2O+dPU9ld9wEna5WQF6+yzCd7ak2VF4X33bjB1hoecPlTrA5s3lIW/u0+0+8vzSNDYQ6LAB4NEBINp+Riazq2rFq3Snab2vLU7zjE4/d+Ixd5D9rx5QuJE7XUjjmY1riVOgrQsdW7Pjv1Zu7xtzVkpOXUE7VNOcj7JnH6V8j6nnXfbTG37rdz2v7btPrNoRfGOkxDPE/JPdZxrqVG2tZ04+5O4DymkrTIcSSGEEEJIJWGQQgghhJBKwiCFEEIIIZWEQQohhBBCKgmFs4cTErLOzsfAQFnJ56XT91ppOCsjN6fKottlq1aYOkee/HBT9vNbrzNl7bZd+TfvRLbVrApxomWFb7fevsmUPSzO2Nqwwtnb77Ri1FZmBYDDg3bb9nC513InI6nAydrqiCEHoxWPAaCdl4WzuSPSnJ626TrVydLbGCiLjcf3WCHzypVjpc+9+NaDgyIWN9YazirIzXI/Oklivd4HWrY0T8rHOtixt8qsbjM1p7DnMnGEy5LEvmJtqMWrAwNoOUL4XMr1EmelZC/7bse5ygcGrAh9el/UkW3blia2LWdhZLRSp16UFbaWOO07q1DDuS7jvq5nzjVoBMlcBbnKcCSFEEIIIZWEQQohhBBCKgmDFEIIIYRUEgYphBBCCKkkFM4eRggEtVr5lCaJs1R5JIAcWWZFoNPTNoNkXWxbGmVeHRwdNnX27bWC2EbdySA5ZcWb9aTcXk2tcDbvWLHu+s1WVLdrd1kUOLbcCub2tKw4uF63mWOl5ogmo6Xjs46T0dNZ0l6dtelTOBlIpXxuO217Ppxdoub4QKdTFtPeccdddsOIZtMKcA8NCSRO2+qoMpNauW8ltdmDneSyyFJPOF5uv+mIhlPHhix3BJ51RwialetlNXu95S3r60ndnuD4GvR8AGrtShwZcbtpfaWdl6+bzBGsdjw9uHO/EHEy00bvyjUnw3PmXG9Ss8ek9eiR5gisG1F2377pwUlPcCSFEEIIIZWEQQohhBBCKgmDlD4jIseJyLdF5DYRuVVE/rgoXyUi14jI7cX/K/ttKyG9Qr8mhCwGDFL6TwfA61T1EQDOAfBHIvJIABcD+Kaqngrgm8VnQpYK9GtCyEFD4WyfUdXNADYXf+8VkdsAHAPgfADnFtUuA/AdAG+cq60kTTA8XBaapqkj5IuoO5lkM0fg6QlnhyPR7dq1R5s6e1tWODg6Yu3asXOPKUujZdVXOMK7dtO6cXvZcabsvrws4L130zZTp55bEa5MO6JDRyCZ18r903Kyj4ojOqw57wpullKUBYw1kzkTqCdDpqzRsMLcNauirMPOnWDDhvtKn1st285sLKZfiwC1ermP6jWrDk3zct/W6tav0bEqyVZmBcEaqSk9caUngm47duVtx3+SyA+cjLZNR0CatKytaSQqVrF+5wmNs45tq91xxPFR5mTHNZE4GW1rjhmdxIqBhxtlO6Rmz1ujZk/A4KDt18ZgWQTdaDj3vzQ+RipnqwxHUiqEiJwI4NcA/BDAUcWNfuaGf2QfTSPkgKFfE0IOFAYpFUFERgF8HsBrVXV8AdtdJCLXi8j1zaZdd4OQfrIYfr1nr/1pOiHkoQGDlAogInWEG/knVfULRfEWEVlbfL8WwFZvW1X9kKquU9V18cKBhPSTxfLrFctsnhpCyEMDalL6jITMah8BcJuqvrvrq6sAXAjg0uL/L/fQllnR2NOkxKsZZ7Dz6B21E8qpE9PGuaXiuXwAqJk5YF8DYebpAdST8nz1406zgdi+UTuHfVNm95muLutUhvV4U2di4w5TljmrLNedZGvtKClbmtmRLW1aTY07n59b/YdESbvaTVun7aymm4otGx0pr7I8NODoeiL7vcSAs7GYfg0BkrR8DhJHR5UMlvuj4a1I3HZWxVVHm5GVtT25o4XKnf6oO36nTtK0JEq62PQysHWcpGl1R78UXTeJs6pzLXOSA9ZsW7Xc9sVktOqx5LZfHRcGHB1J4mhjUimfy7Thaa2cZHrOitADSbmtxKmDWKfCV/VKwyCl/zwRwMsA3CIiNxZlb0K4iV8hIq8EcC+AF/bHPEIOCPo1IeSgYZDSZ1T1+5hdXn7eobSFkMWCfk0IWQw40EUIIYSQSsIghRBCCCGVhNM9hxECQCKhrCeKjesMDVgRYqttRZmecLIRrUS6ZedmU6edWBsaNucYhhIrNM1QXv30YSfYLOpPOHedKXvkDrsa83fv2lX6fNTxp5o6U0dZ+7dunTJl28ZtX2Tj5V/YanPC1Mkz2xetzK4SrU7St4FmWZ2YJVatOA1npeIpuxrw7vXlxHlrf9X2RWsoSgzoCC0PBQIxq0InuZ1JGohWt80TKxZNh5z+EeuMGiV46yR2pWRH520S+gFA7gh40SmXDTqrFLecPGQdRxgt0TWepdbHnPxoGHR2sE/ttklUpjX72Eica9yb7Bt0t436TGydISdJ3qCzMnJtqHxMqZPMLRbhCpO5VRqOpBBCCCGkkjBIIYQQQkglYZBCCCGEkErCIIUQQgghlYTC2cMJEUic3dURwiESjg0NWeHg5KQVW3acDJix6C1zUk+2JmxbxwxYQduZD19lyjZtK4tWf3nbelNn+Mh7TdnaR51rylbcWRaLrlG76vJj1tn17jZsssLWK79+oylr7SyvqjzkZBrNHOFj7qxam6WOKHawfJ5qbSs0PllsXz9ihe3rgUgUmyVOVtRoldkFJJxdVETsqscDTjbTTpSpdCi3YtcpZ2Xh+qA9dm3HZc6K1jXbvmRWcD4tNktyEq3YnLUdH3D0nAOe/0SrgCeDdsN4JWMAyMVZkdvJ7CpRv6aOb7YzJ/vrgHPvUWeF4+geVXPEtTXH+VIn++5gdE4azkrYcaZab4VrUh04kkIIIYSQSsIghRBCCCGVhEEKIYQQQioJgxRCCCGEVBIKZw8zYiGrehkkozrDwzY7qyec9crSKHtt3ckCeefdd5uy00esWu3px1mRW+2Isrjv5nErHLzhBz82ZXvuMkUYR1nAODq2zNTZuNWKTLdst8LZ6WkrHuxEptVjETMAcQSY3jL0A07m0pF6uf9P7ti2zmxYMedJK60P/EzL7W8Uu7/mZDnrqpct91CgAPIo4ywGbJ/Vo3euTsseU71u/TNxspmiXm6/Nm3rpKkVnjZhRegD2bQpy6L+ryeO4Dazvt7KHYFqo2xHmlihbs3JTtx2slEPNm2ftaL7Rd3JCBtnegWAemp9sZ7a81YbLNcTR3DuteUJXtNIKNtwrrfUbEjlbJXhSAohhBBCKgmDFEIIIYRUEgYpfUZEjhORb4vIbSJyq4j8cVH+NhG5T0RuLP49q9+2EtIr9GtCyGJATUr/6QB4nar+WESWAbhBRK4pvnuPqr6zj7YRcqDQrwkhBw2DlD6jqpsBbC7+3isitwE45iDaW/A29boVpXlZaHMn22USidBqa1abOunYClOWDdhsqe3aTlO2dkW53nNWWXHt6t1WwPi5e28xZbVVJ5U+b7zLCuZ2/HLclE1OWFsbaoWCy1eURZlDardb5pQdWZsyZQ8btsd0bLK39Hm1I2T1JICbxQo3J0dWlj6nA1ZQmk1Fdi3AtxbVrwXIG+UjS5xB4DQrn5MBJ3OpOiJlOJl7B5Kyn+UN24ft1LbviaVrbeuzrUgcOtWx1+Bwbvu7M+UItqOzPpBbEW7uqExrmfWxltM/I4Nl+xP1BMn2GKXu7HPI1qtruS8Scdpy7G8ktn8ajXJZnDUZACTKriyOgJhUB073VAgRORHArwH4YVH0ahG5WUQ+KiIrZ9+SkOpCvyaEHCgMUiqCiIwC+DyA16rqOIAPAjgFwFkIb6TvmmW7i0TkehG5fnravu0R0k8Ww6/3jO/1qhBCHgIwSKkAIlJHuJF/UlW/AACqukVVM1XNAfwzgLO9bVX1Q6q6TlXXDQ7aIXtC+sVi+fWK5TafDSHkoQE1KX1GwmTrRwDcpqrv7ipfW8zrA8DzAPx0vrZUFe1OeT56ZGTE2+e8djUadl642bRz93EytwEn7H30Y84wZTVnteT7W3Y142ZzV+nzSfluU+e0sZYpe2rTlm0bKm/baW0zdU5fZvUhMmTnrHcvs324MuqyYThaB0eTMpzbZHF1dZJ7dcqduyOz52hzYh/o2wetFKQzNFb6LG17jPVWNHfvJHybjcX0a6giic5n2rFag2akLbEKKqCW2n4VZ7nhJC33R8dZUbnuaBnadVum6qyg3In26fRt5qyOLQ173A0pH1MOm8xN1Fnx2Ln91wedRHD18j4HG44mJXGSudVsWTpgfRZRor40s0kjM2fF6VScfUb6OkdGB5XyOaIipdowSOk/TwTwMgC3iMiNRdmbAFwgImchXEPrAfxBP4wj5AChXxNCDhoGKX1GVb8P/0cZVx9qWwhZLOjXhJDFgJoUQgghhFQSBimEEEIIqSSc7jnM0CgB1NCgXeE4TviWO6ut1h2hmiecjMsaYts6cshZZVlGTdmepk0gt2+oLPibaG43dY7LNpuyJ5xkxXdT0aq17ba19bi6/Rl3zZFgTmWOKLBdFsC2nX7dk1vh4Pb2KlO2V+wvtbZECca21Wxbk7D92sitmDY3YkvbXwMD5fOxEOHsYhPnD8ucVYPTKOFb3rKSyMxZRTheFRwAJC/3hzorJbed5HYaL4UNoK3erFdZFJt2rKDaE86mzjlI43dNcfrGmXmTIdtWwxPADpb7rOG0ldRtv6Z1737hbJuXr0tp2PuA96ASpzSLBPk1J1GlRIkYhasgVxqOpBBCCCGkkjBIIYQQQkglYZBCCCGEkErCIIUQQgghlYTC2cOIPMsxPVEWfg48zGaQjIWzjdTWSZ3MllMTVlSaxyuYJlbMmTrCwRFHq5YMLbftRzrEXQNenTWmbLXY9V5Go8yZQ6kVPu5qTZiyTttmr221rThxKj2i9Hl3x2b73e2snrxn1Ipkp5xzkpkVap2VYa3WEknLSbvZjgSGNcdP4tVivRWEDxWR4FIcn4pFq4nYLKsDzsq57cSe37xTvjXWcuv76rzjZY5QM3GE1/EeE2e7hrPacOa8VsZFXiZcgbMasJP91VtYQ6I+S52Ms0lq2/ey6IqTSbkWCcDdDL25I1R32soiP1ZHHI9G7BfMOVtlOJJCCCGEkErCIIUQQgghlYRBCiGEEEIqCYMUQgghhFQSCmcPI7Isw+5de0plXjbZOMOml112dNRmLp3Ya0WlzWY5U2aSWJfyskwOOUK7JLF2xJK2lrMM/T4nO6umVkw7bjJxWsFcZ9gRHTr2Z7kV97Umo/Zb9h1gOrftJzXbZ8OpLdNOeZ9tR7zrlTVzm81U8rJtkjnHGGdUdTKsHiokK+9bnHOXRELTXJwsqIm9HvLcyYIaiW5z5xw5ulYkjl9kjmg19vSaY0PHsX/Ee63MytdEltpjrDn+lHpCaCfj7EAklFUnQ2/N2S5NnX51lL9ZWu6zuuOL4rTfSawwOk3LkmTNHfEurGCYVBeOpBBCCCGkkjBIIYQQQkglYZDSZ0RkUER+JCI3icitInJJUb5KRK4RkduL/1f221ZCeoV+TQhZDKhJ6T9NAL+lqhMiUgfwfRH5GoD/DuCbqnqpiFwM4GIAb5yroTzPsW9feSXeeFVQAEgjPUgeZ0wDMDBgtR+Nhp3LjTUQNWfu3sPTecRJ5gBAovnvmpMzCo6WpeNoXjTS3iSZY2vbmUd35uAHB5zVVWvlvt8zucXUaTbtPHottW15ZR2U+7rlJJlzV5l17K9HycNibREAdNplWxcoSVk0vwYAk8urY/sxSWPdiqNHcDRaqaPhiHUqiaNjEEff4q2o22rYjqtFt16t2e1yR8tSc9qP5Sypc1tPYPtLGtbHULe21qPrq5Z4K6vbZHdwVun2VmPWSF+UO0kW49XdAaDhaF7ilZHzhrdScqSxcVepJlWBIyl9RgMzitR68U8BnA/gsqL8MgDPPfTWEXJg0K8JIYsBg5QKICKpiNwIYCuAa1T1hwCOUtXNAFD8f2QfTSRkwdCvCSEHC4OUCqCqmaqeBeBYAGeLyBm9bisiF4nI9SJyfbtjf35KSL9YLL/eM27XYSKEPDRgkFIhVHU3gO8AeAaALSKyFgCK/7fOss2HVHWdqq7z8p0Q0m8O1q9XLF92qEwlhFQMCmf7jIgcAaCtqrtFZAjAUwD8HYCrAFwI4NLi/y/P11ae564AMsYTxcZ4IlZPODs9XRbMecLNgyFubdTJoJVbTSByJyFUEqkvxRPqii1z9HmQ3I5amUVfGzbJXOqs8Fozqb0AzawdcWI+T6QZi6IBK5IF7HnyfCKPxIoLWQV5Mf0aqtBo1WZvVd9YVK3qJBZsOCt+O+eyheg8OaLhmpcYbsAR5jqaUo3rNawYFR17Lau3mnFkW+LU6dTttetq3HNbOBBdAOqsJJ2qt4q243eJPaZ4BeWacw9puysVW1vzaJVxdX44kNSivneueVIdGKT0n7UALhORFGFk6wpV/YqIXAvgChF5JYB7Abywn0YSskDo14SQg4ZBSp9R1ZsB/JpTvgPAeYfeIkIOHvo1IWQxoCaFEEIIIZWEQQohhBBCKol4AkmyNBGRbQDuAbAGwPY+m3MwLGX7l7LtwNz2n6CqRxxKY4CSXwNLu3+Xsu3A0rZ/LttPBXCtqj7jENpDeoRBymGIiFyvquv6bceBspTtX8q2A9W3v+r2zcVSth1Y2vYvZdsf6nC6hxBCCCGVhEEKIYQQQioJg5TDkw/124CDZCnbv5RtB6pvf9Xtm4ulbDuwtO1fyrY/pKEmhRBCCCGVhCMphBBCCKkkDFIOM0TkGSLyCxG5Q0Qu7rc9cyEiHxWRrSLy066yVSJyjYjcXvy/sp82zoWIHCci3xaR20TkVhH546K88scgIoMi8iMRuamw/ZKivJK2LyW/Bpa2by9lvwaWnm+TuWGQchhRrJPyfgDPBPBIABeIyCP7a9WcfAxhZdxuLgbwTVU9FcA3i89VpQPgdar6CADnAPijor+XwjE0AfyWqp4J4CwAzxCRc1BB25egXwNL27eXsl8DS8i3yfwwSDm8OBvAHap6l6q2AHwGwPl9tmlWVPW7AHZGxecDuKz4+zIAzz2UNi0EVd2sqj8u/t4L4DYAx2AJHIMGJoqP9eKfopq2Lym/Bpa2by9lvwaWnG+TeWCQcnhxDIANXZ83FmVLiaNUdTMQbpYAjuyzPT0hIiciLKj3QyyRYxCRVERuBLAVwDWqWlXbDwe/BqrZt3OyFP0aWFK+TeaBQcrhhThl/PnWg4yIjAL4PIDXqup4v+3pFVXNVPUsAMcCOFtEzuizSbNBv+4DS9WvgSXl22QeGKQcXmwEcFzX52MBbOqTLQfKFhFZCwDF/1v7bM+ciEgd4Ub+SVX9QlG8pI5BVXcD+A6ChqKKth8Ofg1Us29dDge/BpaEb5N5YJByeHEdgFNF5CQRaQB4MYCr+mzTQrkKwIXF3xcC+HIfbZkTEREAHwFwm6q+u+uryh+DiBwhImPF30MAngLg56im7YeDXwPV7FvDUvZrYMn5NpkHJnM7zBCRZwF4L4AUwEdV9W/6a9HsiMinAZyLsELpFgBvBfAlAFcAOB7AvQBeqKqxALESiMiTAHwPwC0A8qL4TQjz95U+BhF5NIJ4MEV4WblCVd8uIqtRQduXkl8DS9u3l7JfA0vPt8ncMEghhBBCSCXhdA8hhBBCKgmDFEIIIYRUEgYphBBCCKkkDFIIIYQQUkkYpBBCCCGkkjBIIYQQQkglYZBCCCGEkErCIIUQQgghleT/Ad4OGCqTnFrgAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for random_index in np.random.choice(test_x.shape[0], 10, replace = False):\n",
    "    fig, (ax1, ax2) = plt.subplots(1, 2)\n",
    "    plt.suptitle(f'Original vs Autoencoded Image, CIFAR In Domain Data, Similarity: {similarities[random_index]}')\n",
    "    ax1.imshow(test_x[random_index])\n",
    "    ax2.imshow(autoencode[random_index].reshape((32, 32, 3)))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "eb566890",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jwrenn4/miniforge3/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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oL1hE8s53Adx7BoQf9oABQhGiY09g+fLlNDc3e12NiIwgvg1g55M9YIDYuJNIOXjkkUe8LkVERhBfBrCFIrhQqdel9HIlFcRrpvHEk0/S3t7udTkiMkL4MoBTJd6fgtZfbPwpRHt6ePTRR70uRURGCN8F8DvbtpOIeH8KWn+pUWNJVE9iyZKldHR0eF2OiIwAvgrgRCKRPgXNR/O/fUUnzKezs4Nf/epXXpciIiOArwK4paWFVDLpnzMg+kmNqiVRPZmfL1miuWAROWa+CmA/ngHRX3TCfLo6O3VGhIgcM18GsF/3gCEzF1wzmSVLl2ovWESOie8C2IJhXLjM61IGFJ0wn+6uLh566CGvSxGRIua7AE6VVvnuFLT+UuVjidfOZOnSpezYscPrckSkSPkqgLdt9+cpaEcSnbiQlAX5/j33eF2KiBQp3wRwMpmkeffu9IcwioALl9PdMI//XLGC3//+916XIyJFyDcB3NzcTDKZ9PUZEP3F62dDWTXfv+ceYrGY1+WISJHxTQBv2bIFgGTZGI8rGYJAkK5JZ9K8ezc//vGPva5GRIqMbwJ406ZNYEaqrMbrUoYkObqRWN2JLF26VJ+QE5Eh8U0Ab968GUpHQzDkdSlDFp3yHhI1k/n+PfewfPlyr8sRkSLhmwDesHET8dLi2vvtZQG6p59PqqKev73zTt544w2vKxKRIuCLAO7s7KS1pZlUeZEGMEAgRGfTRSQilXzta3/Nxo0bva5IRHzOFwHcewCuvIgOwB1JqITOpovpTgX40pe/3PvRahGRI/FFAG/evBmAVDGdAXEUrqSCzpmXcKizhy9+6Uvs37/f65JExKd8E8AWLsFFRnldSl6kyqrpaLqIlta9fPVrXyMej3tdkoj4kC8CeOPGjSRKx/j+GhBDkaqop2vq2axft44f/vCHXpcjIj7keQAnk0m2bNlKspgPwB1FYsw0YvUn8cgjj9DW1uZ1OSLiM54H8K5du4jFosX1CbghiE46nVRFPdu2bSMajXpdjoj4iOcB3HsArtjPgDiaQJCu6eeTcrB5yxZaW1u9rkhEfMIfAWxGqqza61KGjSupIFlWQywW5y9vu03XEBYRwC8BXFYNgeL7CPJQuGCEZPkY9h44xG2f+Sxbt271uiQR8ZjnAbxh48bi/QjyELlAmI5Zl3Gws4dbbr2Vn/3sZ7qMpchxzNMAbm9vZ++ePSN3/vcIUmU1tM++gu5RE7jvvvu46eaPsWLFCpxzXpcmIgXmaQCvWLECgOSoOi/LKDgXGUV30wV0nXApuw90cPvtt/PFL35R148QOc54GsC/evRRKKsiWTneyzI8kxzdSPtJV9Mz6UzeeGsNn/zkJ7njjjvYsGGD16WJSAF4duRr06ZNrFm9mp5JZ4yoT8ANWSBIfPzJxGubiOx+ixf//Xe88MILnHrqHK655moWLFhAdXW111WKyDDwLIAff/xxLBAiXjvTqxL8JVRCbNJpxBrmEN67gbc2ruWtO+4AoHHiJOacegqNjY00NDTQ2NhIU1MTodDIPnNEZKTz5Bnc0dHBs88+R2zMNAiVeFGCf4UixMefQnzcSQQ69hDqaOGd9hZ2Pb8cF+vuXay0tIx58+aycOFCzjnnHMaPPz6ncUSKmScB/OyzzxKN9hCbMduL7ouDBUhVjiNWOQ4aoBsgGScQ7SDQc4DYoWZeWbmWV155hXvvvZfZJ53EhRdcwOmnn87kyZOx43laR6RIFDyAnXM8+uhjpCrqSI2qLXT3xS0YJlVeQ6q8hsSY6UQB6zlE+MBW1rzzNmt/8AMAKiurmDPnVCZMmEBNTQ01NTVUVFRQUlJCaWkpFRUVVFVVUVVVRSQS8XZMIsexggZwa2srP/rRj9i+fRvRqWfn3E7JtlcIdGV5ofNkDEvEcKEIBIceNqnyMUQnv2fI6xWKK60i1jCXWMNcrOcQwfZm4h0tvPz6auyVFbhkYsD1S8vKGTt2LHW1tdTWjqWuro7a2lrq6uqor6+nvr6empoa7VGLDIOCBHAymeT+++9n6dKlJJIpog1zSNQ2DS1I+wh27cOS2V3kvLS0lMVXLmbZsmX05NCX69qXU439Bbv2AVC27jdZrzPU8HelVSRKq0jUnUDP4TuTcSzejaXikExgqQSWjGGJKJaIEot3097Zxba2nYTWbcLFuiCVfFe7gWCQqqrRVFePpqqyklAoRCgUIhAIkEqlSCaTOOcIh8OEQiEikUjv3nZZWRnhcLj3FgwGe9d1zvWun0wmSaVSpFKpd30oxcwwMwKBQG/bh2+D/j4y7R8WDAaz/l0eq74vWP0/ZHP4MX34pnhUVFRw2mmn5f1vaNAANrNbgFsAJk+enFMnr732Gg8++CAAnadcW9AL7yxevJjbbrsN5xyPPPJIwfr1jWAYFwyT9VPdOSzRQ6DnEIGOVoIdLQQ799J2YD9tB/TvleT49dnPfpZrr702r20OGsDOuR8BPwI47bTTcnrJnjt3LmeffTYvvfQSozY+Q/eEBSTGNuX81r5s3W8ItTdnteyyZctwzvHrX/86p76S5WPpPnFRTuu+q503VwLkpa0hcw5cElLJ9B5wZu83fevGYl1YvJtAvJNgvJtAvAsX7/mTZoKhEKNGjSIYPNoecIhQKL2nW16W3vstLS0lEonkfQrDOTds0yJmpr1TeZeGhgYuueSSvLdbkCmIkpIS7rzzTv74xz/yg3vvZcP639EVLCFZk9sedap8DAPPbP6XjmSMpU8+gwuVQ2V1Tn0VjVSSQOdeQh0t6b3XeBfBRHf69DWXOupqZsbo6hrq6sdSXz+V2tpaamtrGTduHPX19dTW1lJTU0N5ebnmgkXyqKAH4ebMmcP/vvdePnj99ST3rKUrxwD280GxgkslCB3cQWj/ViIHt/cedJvQ2MikiTP+5CyIkpISKisre8+CqKmpobq6uqDzoyKSVvDT0EKhEFdfdRX3338/1nMQVzq60CUUt1SSQM9Bgod2E2rfRbijBZeIUVlVxfsvX8Tpp5/Oqaeeqo8vixQBTz6Icfnll/NvP/kJkdZ1RCef6UUJxSHRQ6i9hWB7C8GuvYTiHbiejt6Hxzc0cPo5l3Luuecyf/58fTRZpMh48owdO3Ys555zDv/+8n8QbVwIQQVHL+cIHtxBSesaggd3AumDXyfMnMmkSXN6rwUxZ84cffxYpMh5lnxXX301y5cvJ7R/C4m6E7wqwz9citC+zZQ1vwXdbdSMGcOVN93EwoULmTVrFiUlumaGyEjjWQDPnTuXSZOn8M6edcd3ADtH8NBOyna8inXtZ0ZTEzfecBvnnXce4XDY6+pEZBh5FsBmxrXXXM33vvc9Ap17j8vrQljPQcq2vULw4E7GjRvPrV/6Bueffz6BgOf/qk9ECsDTZ/q5554LQLC9xcsyCi+ZILLjNSpWP8ao2H4+/elP87Of/ZQLLrhA4StyHPH06NfYsWOpGj2aePd+sruyQ/GzeDejNj6Lde7j4osv5lOf+hRjx471uiwR8YDnpx/MbGri4Lq3vS6jIMwlqVj/FOFkF3d85zu8973v9bokEfGQ5+93m5qasO62AT8qOxKYSxDs2k8pUf75rrsUviLifQDPmDGj99NdI1YiSrDrAAFz3P3d7zJnzhyvKxIRH/A8gJuamgDycs1dX3KOsrd/By7JjOnTOfHEE72uSER8wvMAnjx5MsFQaMQGcLhlFaED25gwYQKjRo3yuhwR8RHPAzgUCjFlyhSCIzCAg+0tlO54lbPPPpu6ujqvyxERn/E8gCF9JkS454DXZeSVRdsp3/Ii48aN4/bbb0dX0RWR/nwRwDNmzMBl/ivDSGDxbio2PsOocIB/+M53qKys9LokEfEh3wQwjJADcck4ozY+RzjZwz/90z8ybdo0rysSEZ/yVwB3F3kAp5KUb3qeYPd+7vj2tzn55JO9rkhEfMwXAVxdXU3NmDHFfSDOOUq3/pbgoV3cfvvt+qCFiAzKFwEMMLNpJqHu4j0QV7L9Pwnv38ott9zCpZde6nU5IlIEfBPATU0z0h9JTiW9LmXIws1vEWlZzbXXXsuNN97odTkiUiR8E8AzZswAlyLQ0+Z1KUMS6NxH6Y5XOffc87jtttv0b9tFJGv+CmAg0FVE0xDOUbb9FSorK/nyl7+ka/mKyJD4JjEaGxsxMwLRQ16XkrXQ/i0E2lu49ZZbdK6viAyZbwI4HA5TXz+ueK6KloxTtvNVZp5wAosWLfK6GhEpQr4JYIBJkyYSjLZ7XUZWIrtWQrSTz3/uc5p6EJGc+Co5Jk7MBLBzXpcyIIt2UNK6mksvvVQfthCRnPkqgBsbG3GJKCSjXpcyoMjuNwkGjI9//ONelyIiRcx3AQwQ6PHvgTiLthPZu4krFi+mvr7e63JEpIj5M4B9PA8c2bWSUDDIhz/8Ya9LEZEi56sAbmhoSJ+K5tMzIaznEJF9G7nyyit0gXUROWa+CuBIJMLY2joCPf7cAy7ZvZJwKMSHPvQhr0sRkRHAVwEMMHnSRIIx/80BW7Sd8L5NXHnlldTW1npdjoiMAL4L4MbGRl+eCxxpXk0gEOCGG27wuhQRGSF8GcAu3gMJH52KlohSsm8jF114oeZ+RSRvfBnA4K9T0SKt63DJONdff73XpYjICOLfAPbLRXlSSUr2rGXhaaf1XrFNRCQffBzA/pgHDu3bDLEubtTcr4jkme8CuKSkhDFja/0xBeEcpa2rmTptOgsXLvS6GhEZYXwXwACTJk70xRRE8NAurOsAN95wvf7ThYjknS8DeOLERkIx76cgwnvWU1lZxfvf/36vSxGREciXAdzY2IiLdUMi5lkNFusi3PYOixZdRiQS8awOERm5fBvA4O2ZEOG9G8A5rrjiCs9qEJGRzZcBPHHiRMDDAHYpSvZtZP78Bb21iIjkmy8DeMKECYB3H8YIHtwJPe1cddWVnvQvIscHXwZwWVkZtXX1BLrbPOk/smc9o6ured/73udJ/yJyfPBlAAPMmD6NUE9bwfu1aAehg9tZfPnlhMPhgvcvIscP3wbw1KlTsZ6D4FIF7TfSsoaAGYsXLy5ovyJy/PF1AJNKYoW8OHuih5K967nwwgtpaGgoXL8iclzybQBPmzYNgGD3gYL1GWlZg0vG9R8vRKQgQl4XcDSTJ08GIFCoeeBknNI9aznrfe/rDX8RkeHk2z3g8vJy6urHESjQHnC4dR0uHuUjH/lIQfoTEfFtAMPhMyEK8B+SUwlKW1ezYMECZs+ePfz9iYjg8wAu1JkQ4T0bINalvV8RKSjfBzCp5PB+Ii4Zp2z3SubOm8f8+fOHrx8RkX78H8AwrJ+IizSvwsW7+dStt+qavyJSUL49CwJgypQpwPCdCWHxbkpbVnHOuedq7ldECs7Xe8BlZWXUjxu+MyEiu1ZiLsknPvGJYWlfRGQgvg5ggBnTpw/LmRDWc4jI3nUsWrSo95xjEZFC8n0AT506Fetug1R+z4SINK8iFAhy880357VdEZFsFUUA41L5vTh7IkrJ/s1cfPFF1NbW5q9dEZEhKI4AJr9nQoT3bMAl43zgAx/IW5siIkPl+wCeMmUKZpa/A3EuRenedcyZM5empqb8tCkikgPfB3BpaSlTpkwl1NGSl/ZCbdugp53rrvvzvLQnIpIr3wcwwMKFCwh1tkIqecxtRVrWUFdfz1lnnZWHykREclcUATxv3jxcMkGwc88xtRPo2kewvZkPXHstwWAwT9WJiOSmKAJ47ty5mBnB9uZjaifcspZIpITLL788T5WJiOSuKAK4qqqKadOnE2rfnXsjiSglB7ZwySUXU1lZmb/iRERyVBQBDLBg/nxCHXtyngcO792ESya46qqr8lyZiEhuiiaA58+fj0vlOA/sHKV713Hi7NnMnDkz/8WJiOSgaAJ4zpw56XngQ0Ofhgi274bug1x7zTXDUJmISG6KJoArKyuZMaMpp3ngcOtaKiorOe+884ahMhGR3BRNAAMsWDCfUOceSCWyXsdinYTbtrH48sspKSkZxupERIamqAJ43rx5uFSSYEf288DhPesBuOKKK4arLBGRnBRVAP/XPPCu7FZIxihtXctZZ51FY2Pj8BYnIjJERRXAFRUVzJ03j5L9m7O6PnCkZS0uEeWmj360ANWJiAxNUQUwwPUf/CBEOwgd2Drwgsk4pa2rOeOMM5g1a1ZhihMRGYKiC+AzzzyTiZMmUdqyCpw76nLh1nW4eA833XRTAasTEcle0QVwIBDghuuvxzr3Hf3aEMkEZa2rWbBgISeffHJhCxQRyVLRBTDAxRdfTFXVaCLNq474eHjPWlysi5tu0tyviPhXUQZwSUkJH/jAtYQObv+Tf1UUPLiT0p2vcfrppzN37lxvChQRyUJRBjDAVVddRTgcpvTtl3r/XVGgcy+jNr/A1MlT+MY3vuFxhSIiAyvaAK6uruYLX/gCFckORq1+jJKtL1Gx8Tlqx9Zw113/U5ecFBHfK9oABrjssst4+OGHuObqqyndv5lRpSH++a679K/mRaQohLwu4FhVV1fzuc99jg9+8IOYGePHj/e6JBGRrBR9AB/W0NDgdQkiIkNS1FMQIiLFTAEsIuIRBbCIiEcUwCIiHlEAi4h4RAEsIuIRBbCIiEcUwCIiHlEAi4h4RAEsIuIRBbCIiEcUwCIiHlEAi4h4RAEsIuIRBbCIiEcUwCIiHlEAi4h4RAEsIuIRBbCIiEfMOZf9wmZ7gHfy1HctsDdPbXltpIxlpIwDRs5YRso4YOSMJZdxTHHO1fW/c0gBnE9m9qpz7jRPOs+zkTKWkTIOGDljGSnjgJEzlnyOQ1MQIiIeUQCLiHjEywD+kYd959tIGctIGQeMnLGMlHHAyBlL3sbh2RywiMjxTlMQIiIeUQCLiHikYAFsZteZ2WozS5nZUU/hMLM/M7P1ZrbJzP6qUPVly8zGmNlzZrYx87XmKMt9zsxWZcb8+QKXmZUhjOV/ZMaxysweNrPSQtc6kGzGYWazzOzNPrdDftwuQ9gm1Wb2SzNbZ2Zrzey9ha51MEMYy9tm9lZmu7xa6DoHk+04MssGzewNM1uWTduF3ANeBVwL/PZoC5hZELgXuAw4CbjRzE4qTHlZ+yvgeefcTOD5zM/vYmanAJ8EzgDmAovNbGZBq8xONmNpBD4LnOacOwUIAjcUtMrBDToO59x659w859w8YCHQBTxa0CqzM+hYMr4HPO2cO5H039jaAtU3FNmOBeD9me3jx/OEhzKOzzGUbeGcK+gNWE76yXykx94LPNPn568CXy10jYPUvx5oyHzfAKw/wjLXAT/u8/PXga94XXuOY2kEtgNjgBCwDLjE69qHOo5+y18CvOx13cewTaqArWQOovv1lu12Ad4Gar2uNw/jmEg6oC8AlmXTtt/mgA8/2Q/bkbnPT8Y553YDZL7WH2GZVcC5ZjbWzMqBRcCkAtaYrUHH4pzbCdwFbAN2Awedc88WtMrBZbNN+roBeHjYq8pNNmOZDuwB/m/m7e6PzWxUIYvMUrbbxQHPmtlrZnZLwarLXrbjuBv4CpDKtuHQMZfWh5n9P2D8ER76a+fc49k0cYT7Cn6e3EDjyGZ959xaM/tH4DmgA1gJJPJXYfaOdSyZ+a6rgGlAG/ALM/uIc+6BvBWZXR3HNI4+7USAK0m/u/JEHsYSAhYAn3HOrTCz75F+W/z1PJWYtTxtl/c553aZWT3wnJmtc84ddapyOOThebIYaHXOvWZm52fbb14D2Dl30TE2sYN37ylOBHYdY5tDNtA4zKzFzBqcc7vNrAFoPUob9wH3Zdb5e9JjK7g8jOUiYKtzbk9mnV8BZwEFDeB8bJOMy4DXnXMteS8yS3kYyw5gh3NuRebnXzLwvOSwydNzZVfma6uZPUr62ElBAzgP43gfcKWZLQJKgSoze8A595GB+vXbFMQfgJlmNi2zp3ID8ITHNfX3BHBT5vubgCPu2WdezTGzyaQPPvrxLW82Y9kGvMfMys3MgAvx3wGfrLZJxo34c1scNuhYnHPNwHYzm5W560JgTWHKG5JBx2Jmo8ys8vD3pOfnVxWswuxks02+6pyb6JybSjq3XhgsfA+vWKiJ7GtIv3JHgRYyB9uACcBv+iy3CNgAbCY9deH5JHy/cYwlPdG+MfN1zFHG8TvST4qVwIVe132MY/k2sI70E+NnQInXtec4jnJgHzDa65rzMJZ5wKvAH4HHgBqva89lLKTns1dmbquL+TnfZ/nzyfIgnD6KLCLiEb9NQYiIHDcUwCIiHlEAi4h4RAEsIuIRBbCIiEcUwCIiHlEAi4h45P8DHA6sjk/J02UAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.Figure(figsize = (20, 8))\n",
    "plt.title('Similarities for In Domain Test Data')\n",
    "sns.violinplot(similarities)\n",
    "plt.axvline(threshold, c = 'red')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1d7b8f27",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.59761256\n",
      "0.09487512\n"
     ]
    }
   ],
   "source": [
    "digit_preds, digit_autoencode = model.predict(digit_x_test)\n",
    "digit_preds = digit_preds.argmax(axis = 1)\n",
    "digit_preds = [cifar_10_class_mapping[pred] for pred in digit_preds]\n",
    "digit_similarities = tf.keras.losses.cosine_similarity(digit_test_output.astype('float32'), digit_autoencode.astype('float32')).numpy()\n",
    "digit_trust = digit_similarities <= threshold\n",
    "print(digit_similarities.mean())\n",
    "print(digit_similarities.std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "48c6eefd-ca20-41db-8f4e-f02552c2111c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    9996\n",
       "True        4\n",
       "dtype: int64"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(digit_trust).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "875dd2b5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "    airplane       0.00      0.00      0.00       980\n",
      "  automobile       0.02      0.01      0.01      1135\n",
      "        bird       0.06      0.15      0.09      1032\n",
      "         cat       0.01      0.01      0.01      1010\n",
      "        deer       0.00      0.00      0.00       982\n",
      "         dog       0.05      0.25      0.09       892\n",
      "        frog       0.00      0.00      0.00       958\n",
      "       horse       0.03      0.00      0.00      1028\n",
      "        ship       0.06      0.08      0.07       974\n",
      "       truck       0.00      0.00      0.00      1009\n",
      "\n",
      "    accuracy                           0.05     10000\n",
      "   macro avg       0.02      0.05      0.03     10000\n",
      "weighted avg       0.02      0.05      0.03     10000\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jwrenn4/miniforge3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/Users/jwrenn4/miniforge3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/Users/jwrenn4/miniforge3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n"
     ]
    }
   ],
   "source": [
    "print(classification_report([cifar_10_class_mapping[val] for val in digit_y_test.flatten()], digit_preds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "15f9311d",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for random_index in np.random.choice(digit_x_test.shape[0], 10, replace = False):\n",
    "    fig, (ax1, ax2) = plt.subplots(1, 2)\n",
    "    plt.suptitle(f'Original vs Autoencoded Image, Digit OOD Data, Similarity: {digit_similarities[random_index]}')\n",
    "    ax1.imshow(digit_x_test[random_index])\n",
    "    ax2.imshow(digit_autoencode[random_index].reshape((32, 32, 3)))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d5c02e66",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jwrenn4/miniforge3/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.Figure(figsize = (20, 8))\n",
    "plt.title('Digit Similarities')\n",
    "sns.violinplot(digit_similarities)\n",
    "plt.axvline(threshold, c = 'red')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "141f4ca1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-0.79730517\n",
      "0.08872931\n"
     ]
    }
   ],
   "source": [
    "fashion_preds, fashion_autoencode = model.predict(fashion_x_test)\n",
    "fashion_preds = fashion_preds.argmax(axis = 1)\n",
    "fashion_preds = [cifar_10_class_mapping[pred] for pred in fashion_preds]\n",
    "fashion_similarities = tf.keras.losses.cosine_similarity(fashion_test_output.astype('float32'), fashion_autoencode.astype('float32')).numpy()\n",
    "fashion_trust = fashion_similarities <= threshold\n",
    "print(fashion_similarities.mean())\n",
    "print(fashion_similarities.std())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "fc9820be",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False    8586\n",
       "True     1414\n",
       "dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(fashion_trust).value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "4e8143df",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "              precision    recall  f1-score   support\n",
      "\n",
      "    airplane       0.00      0.00      0.00       980\n",
      "  automobile       0.02      0.01      0.01      1135\n",
      "        bird       0.06      0.15      0.09      1032\n",
      "         cat       0.01      0.01      0.01      1010\n",
      "        deer       0.00      0.00      0.00       982\n",
      "         dog       0.05      0.25      0.09       892\n",
      "        frog       0.00      0.00      0.00       958\n",
      "       horse       0.03      0.00      0.00      1028\n",
      "        ship       0.06      0.08      0.07       974\n",
      "       truck       0.00      0.00      0.00      1009\n",
      "\n",
      "    accuracy                           0.05     10000\n",
      "   macro avg       0.02      0.05      0.03     10000\n",
      "weighted avg       0.02      0.05      0.03     10000\n",
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jwrenn4/miniforge3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/Users/jwrenn4/miniforge3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n",
      "/Users/jwrenn4/miniforge3/lib/python3.9/site-packages/sklearn/metrics/_classification.py:1308: UndefinedMetricWarning: Precision and F-score are ill-defined and being set to 0.0 in labels with no predicted samples. Use `zero_division` parameter to control this behavior.\n",
      "  _warn_prf(average, modifier, msg_start, len(result))\n"
     ]
    }
   ],
   "source": [
    "print(classification_report([cifar_10_class_mapping[val] for val in digit_y_test.flatten()], digit_preds))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "d8c4bfff",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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ZJ8xsbGwuXEW46s7y6Rj/1MTfPwEfNLPNCBt7lJl9MN4u+AahEpQsBabEjB93f45w7+3fzWxUbKY6mt4WhwuBc2Klxcy2MLODa1zli4FvmtkOFuwWY7we2NHMPm5mw83sY4R+HNe5+zOEpv4zY7lMAz6UWOblhG15oJl1xZinm9k2NczbSGMI92CXA8PN7N/omylfCXzNzMaZ2STCV4lK/gqsMrNTzGzDuB67xhMgcX1qOviY2SZm9o+Eg9/l7v5AxmRXAp81s53NbCNCM2QlS4HNzGxsP9OcChxlZl8yszFxHc8mfJugdGVxGWEf/bmF77+PMLMDCbdIZsV9eyDrkp5nIzPbj9Ay9ldC3YLq++lSwkmExPRrgRXxKvOM1OfMMrN5FWI42MyOiOVgZrYX4aq2YrLTACMJ+/Vy4HUzO4jQ0ase6TIgnvh7gO9Q+/E1y0+Ak8xskplNJCRasytMeyewT6kFwMz2IDQrl07ElwKHmtnUeEw7HbjN3VcQjncWjyXDzGxrQufP++KyppvZtnG7TCb0JbgmFec34rZ7K6HPxuxYFk8QEsuvm9kGZrZzXPZ1cdmfSCx7O8LtpDcuTuOxbRSh30PpWDU8jptESBa/7+6lVhQS8x5jZlvG17sAX6PvhS/AoYQ+DDenhv+UcIzcx0IifhbwS3dfHcvouFRd/WJi2fMI554vxXUuHbf+mCivo81sFzMbRzi/zI5xbhn3g9HxmHYg4YK3NG9lXlvHk6OBB+ltqv0R4SqsNH4W5R3g+gwjNNU9S++3Bp6nt3PeG9OS8RUd+n5daV/ClUY3oZKcRaiUmZ2QMtZlnzjN9xPDRhKalV6mt3f6tIx530XoSLRFxrj5wPGJdV1M6FjzFfp2FtyMcKX1MnBPHLYNoXK/RGjK/1xiucOAkwhfBVodx59bY1l1ESrKU3HeO+ntlDKN0GFuZfw/LbGMN8ey7Sb7WwPvJHQuKn0H9zfEzkPV5k2V2XTKOwsek3jfp5MP4Qrl8cS6/Thur8WEJsdkOW9MOJCuINxO+Qahv0FpWRMJ9zmXxG3xl8S8nwL+3E8depre796vJFyhfxHoSkwzm77fGvha/KxFhJOi0/sNjvS0lxD2kxVkfGsgsf3mxXJeFbfBrqlpxhP21aUx3vmU9/avui4Znz2P3ucIlL7b/XViR80a99PPxe22gtCSMTGxPo8S+sa8Ubfjtj6nQjz7Eg6kL8R4HiXxfA/66YxJuGJy+n4b5Tbgk9WOTbGclsZ1uIyQQFXs9Jnx2QcTjokrSHxLiVBXndhhMQ67ELiwv+N06rOM0Nz/Uvzr8xyBWBc+kXh/PKGjbukbECenlvd5wjH7ZUK/n8mJce+l9xtISwj9bTaK406K860htMR9j0Tvefo+R6DPV1vj+EmEY3M35d/MOIeQ7L4S/19E305zs2I5Jv9mxXFnxPd9ngeQmPfSGM8rhH3k2yTqd5zm94TWhKzy/3jctq8QEp/SN72GxfV5id66flpq2+xBOCavJXT22yO17JNibKtinKWvC25BOC6viOMeIPENtP7+LC6gqcxsdAx2Bw/3jUSGlJl9nvANkf1qmPZi4Ofu/vshimVnQmK9gWd3xJUUM7uX8E2aan2L2p6ZfZrw1b9peccixdC03xowsw/FZsSNCffVHmAAPTxFamFmE8zsPbEpbidC0+ivapnX3Y9pdBJgZofG2yXjCF8p+7WSgNq5+9SCJAEbAV8gXN2KNEUzf3ToYEKz6CJgB8LVWfObI6QoRhKaxVcT7pFdQ3av32Y5jnAb5QnCPcCa+7ZIMcR7ussJzb5zq0wu0jC53BoQERGR1qCfIRYRESkwJQIiIiIFpkRARESkwJQIiIiIFJgSARERkQJTIiAiIlJgSgREREQKTImAiIhIgSkREBERKTAlAiIiIgWmREBERKTAlAiIiIgUmBIBERGRAlMiICIiUmBKBERERApMiYCIiEiBKREQEREpMCUCIiIiBaZEQEREpMCUCIiIiBSYEgEREZECUyIgIiJSYEoERERECkyJgIiISIEpERARESkwJQIiIiIFpkRARESkwJQIiIiIFJgSARERkQJTIiAiIlJgSgREREQKTImAiIhIgSkREBERKTAlAiIiIgWmREBERKTAlAiIiIgUmBIBERGRAlMiICIiUmBKBERERApMiYCIiEiBKREQEREpMCUCIiIiBaZEQEREpMCUCIiIiBSYEgEREZECUyIgIiJSYEoEGsjMZpjZI2b2uJmdmnc8Io2iui3Suczd846hI5hZF/Ao8H5gIXAncKS7P5RrYCKDpLot0tmG5x1AB9kLeNzdnwQws58BBwMVD5Zm1tZZ2Pbbb182bPXq1X3eT548uVnh1O3uu+/u837s2LFl00ycOLFs2IIFC2pa/s4779zn/aJFi8qmWblyZU3LGih3twYspnB1W1pfg+q2oESgkSYBzyXeLwTemVMsTXH++eeXDZs3b16f99/97nebE8wAmPU9jkyfPr1smlmzZpUN22OPPWpa/ty5c6su65prrqlpWTkrXN0WKRIlAo2TlZ2WXRWZ2bHAsUMfjkjDqG6LdDAlAo2zEEi2g28DlLUFu/tFwEWg5lNpG6rbIh1MnQUbxMyGEzpUHQA8T+hQ9XF3n9/PPE0v/B133LHP+4svvrhsmpkzZ5YN6+7uLhs2ZcqUqtMtX768zgibJ31rYJNNNimbZuutty4b9uijj9a0/HRZL1mypGyaVatW1bSsgWrEfdR2qdtSLOoj0DhqEWgQd3/dzI4Hfg90AZf0d6AUaReq2yKdTYlAA7n79cD1ecch0miq2yKdSw8UEhERKTAlAiIiIgWmzoI5yqNDVbpD3LRp08qmueGGG8qGrVu3bshiamXpDoXtJq8OVS3RWbArY9j6jGE9bykbNMYeKxu2OvU+jxXM+sxhWcfwYZ1/jafOgo3T+bVFREREKlIiICIiUmBKBERERApMfQRylMd9VG3v5mmF/gVF7iMwbMQDZcPWv7ZrDpG0plaon4OhPgKNoxYBERGRAlMiICIiUmBKBERERApMiYCIiEiB6bcGRIZIumNmu3fOanXe09N3gMq7X1kdhzMfWKRy7HhqERARESkwJQIiIiIFpkRARESkwNRHoIHM7GnCb5OsB1539z3zjUikMVS3RTqXEoHG29/dX8g7CNBTBFtN1vZosw6ELVO3oad8UHuVZUvKKsENM+rtWpV1R9GtARERkQJTItBYDtxgZneb2bF5ByPSQKrbIh1KtwYa6z3uvsjMtgRuNLOH3f2W5ATxIKoDqbQb1W2RDqVfHxwiZjYL6Hb38/uZZkgLX9u29Q11H4Gh+IW2VqjbWX0E9GN0Q2OjjGGt0EdAvz7YOLo10CBmtrGZjSm9Bj4APJhvVCKD15J1u2dY+Z8MiTUZf+HLI8k/aWe6NdA4WwG/ild4w4G57v67fEMSaQjVbZEOplsDOdKtAWnHWwO1GPJbAxnfHvShvhshbzBLb4CupsegWwONo/Y0ERGRAtOtARFpP1mXMGoQaJ71qQ3Q/AYBaSC1CIiIiBSYEgEREZECUyIgIiJSYEoERERECkydBUVEpD66hOwo2pwiIiIFpkRARESkwJQIiIiIFJgSARERkQJTZ0ER6Qjp39YY6t9xKLRxf8s7AmkgtQiIiIgUmBIBERGRAlMiICIiUmBKBOpkZpeY2TIzezAxbLyZ3Whmj8X/4/KMUWQgVLdFikmJQP1mAzNSw04FbnL3HYCb4nuRdjObNq7brz6yuM+fDKEVV/T9k7amRKBO7n4L8FJq8MHAnPh6DnBIM2MSaQTVbZFiUiLQGFu5+2KA+H/LnOMRaRTVbZEOp+cINJmZHQscm3ccIo2mui3SntQi0BhLzWwCQPy/rNKE7n6Ru+/p7ns2LTqRgVPdFulwahFojGuBo4Dz4v9rmh3A6aef3uyPlGLIvW7XasOdJ/V57z1ePpEeNtgg38s7AGkgtQjUycyuAG4HdjKzhWZ2NOEg+X4zewx4f3wv0lZUt0WKSS0CdXL3IyuMOqCpgYg0mOq2SDGpRUBERKTA1CIgIh3JrbyPgA1xJ4GMXgkd2i3h73kHIA2kFgEREZECUyIgIiJSYEoERERECkyJgIiISIGZe1b3FmkGs4zeTAOk7diezIa485p7Ln3VGlm3G+mtPTuUDfvUVx8sG3bat0eWDUuv0PqM5Y/I6C6YuQnavAeh9aRWoKv5MeRVtzuRWgREREQKTImAiIhIgSkREBERKTAlAiIiIgWmzoI5UmdBUWfB5toqY9jSjH2nJ2O6dEHWXLBHZQyb0/dtrYXVKk8uXJravFvncE2pzoKNoxYBERGRAlMiICIiUmBKBOpkZpeY2TIzezAxbJaZPW9m98a/mXnGKDIQqtsixaREoH6zgRkZw//T3afGv+ubHJNII8xGdVukcPQzxHVy91vMbErecYg0WhHq9tLXy4f9NqML3uyMLnifreUDbskYNidjWEpWr7daOizmZct0P71WCUwGRC0CjXO8md0fm1fH5R2MSAOpbot0MCUCjfFDYHtgKrAY+E6lCc3sWDO7y8zualJsIoOhui3S4ZQINIC7L3X39e7eA/wvsFc/017k7nu6+57Ni1BkYFS3RTqf+gg0gJlNcPfF8e2hQPnPmYm0oY6r215+533GAG9wZz4EaN8BLartlJVYRt8LnV3ahzZVnczsCmA6sLmZLQTOAKab2VTCseFp4Li84hMZKNVtkWLSI4ZzpEcMix4x3GTrylsEfLi6vA+Wrc8owyG+zNQjhhtHfQREREQKTImAiIhIgamPgIh0pB7WlA/rUmvyUPCu8lsupuvMtqEtJSIiUmBKBERERApMiYCIiEiBKREQEREpMHUWFMlR1vMfhvrZAh0rfVnz8KiySbL6CmY98EBboF7lJaaHDbYPtQiIiIgUmBIBERGRAlMiICIiUmBKBERERApMPzqUI/3okGRpZGfBIv3oULpzWpf2iVx16g9qdSK1CIiIiBSYEgEREZECUyJQJzObbGY3m9kCM5tvZifE4ePN7EYzeyz+H5d3rCL1UN0WKSb1EaiTmU0AJrj7PWY2BrgbOAT4DPCSu59nZqcC49z9lCrLUh8BKZNXH4FWrdu1Uh+B1qI+Au1DicAgmdk1wP/Ev+nuvjgeUOe5+05V5lUiIGVapbNgq9TtWvWkfwn39fInC3YPX1s2bIxOJw2wadmQF21l2bDNG/iJSgQaR7cGBsHMpgB7AHcAW7n7YoD4f8scQxMZFNVtkeLQo58HyMxGA1cBJ7r7qlqv4szsWODYoYxNZDBUt0WKRS0CA2BmIwgHyp+6+y/j4KWx2bR0r3VZ1rzufpG77+nuezYnWpHaqW6LFI9aBOpk4fLox8ACd78gMepa4CjgvPj/mhzCExmwdq/blrqs2dT/XjbNiuaEUji+4dD2B5Chpc6CdTKzacCtwANAqXvSaYR7qVcC2wLPAoe5+0tVlqXOglImx28NtGTdrlX6AzfNiGBF5o8Oy2D5huXVbFh5HtbYz1RnwYZRIpAjJQKSpVW+NTAYSgSKRYlAe1MfARERkQJTIiAiIlJg6iwoIh3hz6kHCq3MajhOP3QIQA3MdfNUoQ0f4tsAMrTUIiAiIlJgSgREREQKTImAiIhIgSkREBERKTA9RyBHeo6AZNFzBIaOZ3YWbMlQW4Zn1MdWuILUcwQapxW2p4iIiOREiYCIiEiBKREQEREpMCUCIiIiBaYnC4pIcbyWMWyDpkfRsnp6yvvfdeUQhzSXWgREREQKTImAiIhIgSkRqJOZTTazm81sgZnNN7MT4vBZZva8md0b/2bmHatIPVS3RYpJDxSqk5lNACa4+z1mNga4GzgEOBzodvfz61iWHigkZfJ6oFCr1u1G8qxfydugJUPNRWYfgRbtJKAHCjWOOgvWyd0XA4vj69VmtgCYlG9UIoNXhLpto8qHZZ9POj85OCDjpP/HFj3py9DSrYFBMLMpwB7AHXHQ8WZ2v5ldYmbj8otMZHBUt0WKQ4nAAJnZaOAq4ER3XwX8ENgemEq4qvpOhfmONbO7zOyuZsUqUg/VbZFiUR+BATCzEcB1wO/d/YKM8VOA69x91yrLUR8BKZPnjw61Yt0eatm7TtuEP2DtfmtAfQQaR30E6mThKP1jYEHyQGlmE+I9VoBDgQfziE9koIpQt7s2LB+WdTox3zhj7lcaHs/QSa1URl5zcxud9GVoqUWgTmY2DbgVeAAo/ajpacCRhKZTB54GjkscPCstSy0CUibHbw20ZN1upKxEYN3a8mHmG2XM3VmJwLCMG8MtudEqUItA4ygRyJESAcmS562BRlEikDclAlI7dRYUEREpMCUCIiIiBabOgiJSGOszbgNkXQ05a4Y8loHJag3vKR+SauNv1acDSmtQi4CIiEiBKREQEREpMCUCIiIiBaZEQEREpMDUWVBEJC3rEqlnp9SAh2tcWEYHP1/f9/1D5YfirIc4Z3UVtKxgL0svrGJwImoREBERKTIlAiIiIgWmREBERKTAlAiIiIgUmH50KEft9KNDWT+E02l1p9Yf+8mjrAdKPzrUOOmn9dmhGRP9qnxQVkEM08/lDJp+dKhx1CIgIiJSYEoERERECkyJQJ3MbJSZ/dXM7jOz+WZ2Zhw+3sxuNLPH4v9xeccqUg/VbZFiUh+BOlm4gbuxu3eb2QjgNuAE4CPAS+5+npmdCoxz91OqLKut+wjsv//+ZcP23nvvqsvq7u4uG7b11luXDXvkkUdqjG5gli9f3uf9Qw89VDbN008/XTasU/sItGrdbhXp3/gbdnT5NH5x+bAGbk5JUB+BxlGLQJ08KJ3JRsQ/Bw4G5sThc4BDmh+dyMCpbosUkxKBATCzLjO7F1gG3OjudwBbuftigPh/yxxDFBkQ1W2R4lEiMADuvt7dpwLbAHuZWcZTwbOZ2bFmdpeZ3TVkAYoMkOq2SPEoERgEd18BzANmAEvNbAJA/L+swjwXufue7r5ns+IUqZfqtkhxqLNgncxsC2Cdu68wsw2BG4BvAfsBLyY6VI13969WWVZbF36n1Z2rr766bNihh2Y9NaZ91NlZUHV7kLJWel3GsJFDHUgBqLNg4+hniOs3AZhjZl2EFpUr3f06M7sduNLMjgaeBQ7LM0iRAVDdFikgJQJ1cvf7gT0yhr8IHND8iEQaQ3VbpJjUR0BERKTAlAiIiIgUmG4N5OsF4Blg8/i6rSSegNeW8Se0c/z9xb5dMwNJaeu6nVBX/C3We62Tyz7Put1x9K2BFmBmd7XzV64Uf35aPfZWj6+ado6/nWOH9o+/nejWgIiISIEpERARESkwJQKt4aK8AxgkxZ+fVo+91eOrpp3jb+fYof3jbxvqIyAiIlJgahEQEREpMCUCOTOzGWb2iJk9Hp/j3tLM7BIzW2ZmDyaGjTezG83ssfh/XJ4xVmJmk83sZjNbYGbzzeyEOLzl4zezUWb2VzO7L8Z+ZhzekrGrXjdPO9draL+63YmUCOQoPtP9+8BBwC7AkWa2S75RVTWb8It0SacCN7n7DsBN8X0reh042d13Bt4FfDGWdzvE/yrwXnffHZgKzDCzd9GCsateN10712too7rdqZQI5Gsv4HF3f9LdXwN+Bhycc0z9cvdbgJdSgw8G5sTXc4BDmhlTrdx9sbvfE1+vBhYAk2iD+D3ojm9HxD+nNWNXvW6idq7X0HZ1uyMpEcjXJOC5xPuFcVi72crdF0M4KAFb5hxPVWY2hfADO3fQJvGbWZeZ3QssA25091aNXfU6J+1Yr6Gt6nZHUiKQr6wnkuprHEPMzEYDVwEnuvuqvOOplbuvd/epwDbAXma2a84hVaJ6nYN2rdfQVnW7IykRyNdCYHLi/TbAopxiGYylZjYBIP5flnM8FZnZCMLB8qfu/ss4uG3iB3D3FcA8wj3tVoxd9brJOqFeQ1vU7Y6kRCBfdwI7mNmbzGwkcARwbc4xDcS1wFHx9VHANTnGUpGFX0n6MbDA3S9IjGr5+M1sCzPbNL7eEHgf8DCtGbvqdRO1c72GtqvbHUkPFMqZmc0Evgt0AZe4+zn5RtQ/M7sCmE74ZbClwBnA1cCVwLbAs8Bh7p7ueJU7M5sG3Ao8APTEwacR7qe2dPxmthuhw1QXIYG/0t3PMrPNaMHYVa+bp53rNbRf3e5ESgREREQKTLcGRERECkyJgIiISIEpERARESkwJQIiIiIFpkRARESkwJQIiIiIFJgSARERkQJTIiAiIlJg/x80BgTABnHUPQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Clipping input data to the valid range for imshow with RGB data ([0..1] for floats or [0..255] for integers).\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for random_index in np.random.choice(fashion_x_test.shape[0], 10, replace = False):\n",
    "    fig, (ax1, ax2) = plt.subplots(1, 2)\n",
    "    plt.suptitle(f'Original vs Autoencoded Image, Digit OOD Data, Similarity: {fashion_similarities[random_index]}')\n",
    "    ax1.imshow(fashion_x_test[random_index])\n",
    "    ax2.imshow(fashion_autoencode[random_index].reshape((32, 32, 3)))\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "5ef23134",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/jwrenn4/miniforge3/lib/python3.9/site-packages/seaborn/_decorators.py:36: FutureWarning: Pass the following variable as a keyword arg: x. From version 0.12, the only valid positional argument will be `data`, and passing other arguments without an explicit keyword will result in an error or misinterpretation.\n",
      "  warnings.warn(\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.Figure(figsize = (20, 8))\n",
    "plt.title('Fashion Similarities')\n",
    "sns.violinplot(fashion_similarities)\n",
    "plt.axvline(threshold, c = 'red')\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
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