Merge pull request #12 from tensorflow/master

Merge changes from tensorflow:master

Author: lamarrr

.bazelrc

@@ -1 +1 @@
-2.0.0
+3.1.0

.bazelversion

@@ -10,32 +10,30 @@ labels: 'type:bug'
 we only address code/doc bugs, performance issues, feature requests and
 build/installation issues on GitHub. tag:bug_template</em>
 
-**System information** 
-- Have I written custom code (as opposed to using a stock
-example script provided in TensorFlow): 
-- OS Platform and Distribution (e.g.,
-Linux Ubuntu 16.04): 
-- Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if
-the issue happens on mobile device: 
-- TensorFlow installed from (source or
-binary): - TensorFlow version (use command below): 
-- Python version: - Bazel
-version (if compiling from source):
-- GCC/Compiler version (if compiling from
-source): 
-- CUDA/cuDNN version: - GPU model and memory:
+**System information**
+- Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
+- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
+- Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
+- TensorFlow installed from (source or binary):
+- TensorFlow version (use command below):
+- Python version:
+- Bazel version (if compiling from source):
+- GCC/Compiler version (if compiling from source):
+- CUDA/cuDNN version:
+- GPU model and memory:
 
 You can collect some of this information using our environment capture
 [script](https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh)
-You can also obtain the TensorFlow version with: 1. TF 1.0: `python -c "import
-tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"` 2. TF 2.0: `python -c
-"import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`
+You can also obtain the TensorFlow version with:
+1. TF 1.0: `python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"`
+2. TF 2.0: `python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`
+
 
 **Describe the current behavior**
 
 **Describe the expected behavior**
 
-**Standalone code to reproduce the issue** 
+**Standalone code to reproduce the issue**
 Provide a reproducible test case that is the bare minimum necessary to generate
 the problem. If possible, please share a link to Colab/Jupyter/any notebook.
 

.github/ISSUE_TEMPLATE/00-bug-issue.md

@@ -38,6 +38,9 @@ state what is wrong:
 - Producing correct results, but the model is slower than expected (model generated from old converter)
 
 
+**RNN conversion support**
+If converting TF RNN to TFLite fused RNN ops, please prefix [RNN] in the title.
+
 **Any other info / logs**
 
 Include any logs or source code that would be helpful to diagnose the problem. If including tracebacks, please include the full traceback. Large logs and files should be attached.

.github/ISSUE_TEMPLATE/60-tflite-converter-issue.md

@@ -11,32 +11,29 @@ As per our
 we only address code/doc bugs, performance issues, feature requests and
 build/installation issues on GitHub. tag:performance_template</em>
 
-**System information** 
-- Have I written custom code (as opposed to using a stock
-example script provided in TensorFlow): 
-- OS Platform and Distribution (e.g.,
-Linux Ubuntu 16.04): 
-- Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if
-the issue happens on mobile device: 
-- TensorFlow installed from (source or
-binary): - TensorFlow version (use command below): 
-- Python version: - Bazel
-version (if compiling from source):
-- GCC/Compiler version (if compiling from
-source): 
-- CUDA/cuDNN version: - GPU model and memory:
+**System information**
+- Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
+- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
+- Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
+- TensorFlow installed from (source or binary):
+- TensorFlow version (use command below):
+- Python version:
+- Bazel version (if compiling from source):
+- GCC/Compiler version (if compiling from source):
+- CUDA/cuDNN version:
+- GPU model and memory:
 
 You can collect some of this information using our environment capture
 [script](https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh)
-You can also obtain the TensorFlow version with: 1. TF 1.0: `python -c "import
-tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"` 2. TF 2.0: `python -c
-"import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`
+You can also obtain the TensorFlow version with:
+1. TF 1.0: `python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"`
+2. TF 2.0: `python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`
 
 **Describe the current behavior**
 
 **Describe the expected behavior**
 
-**Standalone code to reproduce the issue** 
+**Standalone code to reproduce the issue**
 Provide a reproducible test case that is the bare minimum necessary to generate
 the problem. If possible, please share a link to Colab/Jupyter/any notebook.
 

.github/ISSUE_TEMPLATE/80-performance-issue.md

@@ -0,0 +1,116 @@
+# Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ============================================================================
+#
+# THIS IS A GENERATED DOCKERFILE.
+#
+# This file was assembled from multiple pieces, whose use is documented
+# throughout. Please refer to the TensorFlow dockerfiles documentation
+# for more information.
+
+# A list of assignees
+assignees:
+   - amahendrakar
+   - ravikyram
+   - Saduf2019
+# A list of assignees for compiler folder
+compiler_assignees:
+   - joker-eph
+# filesystem path
+filesystem_path:
+   - tensorflow/c/experimental/filesystem
+# security path
+security_path:
+   - tensorflow/security
+# words checklist
+segfault_memory:
+   - segfault
+   - memory leaks
+# assignees
+filesystem_security_assignee:
+   - mihaimaruseac
+   
+tflite_micro_path:
+   - tensorflow/lite/micro
+   
+tflite_micro_comment: >
+   Thanks for contributing to TensorFlow Lite Micro.
+   
+
+   To keep this process moving along, we'd like to make sure that you have completed the items on this list:
+      * Read the [contributing guidelines for TensorFlow Lite Micro](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/CONTRIBUTING.md)
+      * Created a [TF Lite Micro Github issue](https://github.com/tensorflow/tensorflow/issues/new?labels=comp%3Amicro&template=70-tflite-micro-issue.md)
+      * Linked to the issue from the PR description
+      
+
+   We would like to have a discussion on the Github issue first to determine the best path forward, and then proceed to the PR review.
+
+# Cuda Comment
+cuda_comment: >
+   From the template it looks like you are installing **TensorFlow** (TF) prebuilt binaries:
+      * For TF-GPU - See point 1
+      * For TF-CPU - See point 2
+   -----------------------------------------------------------------------------------------------
+   
+   **1. Installing **TensorFlow-GPU** (TF) prebuilt binaries**
+   
+   
+   Make sure you are using compatible TF and CUDA versions.
+   Please refer following TF version and CUDA version compatibility table.
+   
+   | TF  | CUDA |
+   
+   | :-------------: | :-------------: |
+   
+   | 2.1.0 - 2.2.0  | 10.1 |
+   
+   | 1.13.1 - 2.0  | 10.0  |
+   
+   | 1.5.0 - 1.12.0 | 9.0 |
+   
+     * If you have above configuration and using _**Windows**_ platform -
+       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the %PATH% environment variable.
+       * Refer [windows setup guide](https://www.tensorflow.org/install/gpu#windows_setup).
+     * If you have above configuration and using _**Ubuntu/Linux**_ platform -
+       * Try adding the CUDA, CUPTI, and cuDNN installation directories to the $LD_LIBRARY_PATH environment variable.
+       * Refer [linux setup guide](https://www.tensorflow.org/install/gpu#linux_setup).
+     * If error still persists then, apparently your CPU model does not support AVX instruction sets.
+       * Refer [hardware requirements](https://www.tensorflow.org/install/pip#hardware-requirements).
+   
+   -----------------------------------------------------------------------------------------------
+   
+   **2. Installing **TensorFlow** (TF) CPU prebuilt binaries**
+   
+   
+   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
+   
+   
+   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
+   
+   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
+   
+      * Try Google Colab to use TensorFlow.
+         * The easiest way to use TF will be to switch to [google colab](https://colab.sandbox.google.com/notebooks/welcome.ipynb#recent=true). You get pre-installed latest stable TF version. Also you can use ```pip install```  to install any other preferred TF version.
+         * It has an added advantage since you can you easily switch to different hardware accelerators (cpu, gpu, tpu) as per the task.
+         * All you need is a good internet connection and you are all set.
+      * Try to build TF from sources by changing CPU optimization flags.
+   
+   *Please let us know if this helps.*
+   
+windows_comment: >
+   From the stack trace it looks like you are hitting windows path length limit.
+      * Try to disable path length limit on Windows 10.
+        * Refer [disable path length limit instructions guide.](https://mspoweruser.com/ntfs-260-character-windows-10/)
+   
+   Please let us know if this helps.

.github/bot_config.yml

@@ -0,0 +1,39 @@
+    # Copyright 2019 The TensorFlow Authors. All Rights Reserved.
+    #
+    # Licensed under the Apache License, Version 2.0 (the "License");
+    # you may not use this file except in compliance with the License.
+    # You may obtain a copy of the License at
+    #
+    #     http://www.apache.org/licenses/LICENSE-2.0
+    #
+    # Unless required by applicable law or agreed to in writing, software
+    # distributed under the License is distributed on an "AS IS" BASIS,
+    # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+    # See the License for the specific language governing permissions and
+    # limitations under the License.
+    # ============================================================================
+    #
+    # THIS IS A GENERATED DOCKERFILE.
+    #
+    # This file was assembled from multiple pieces, whose use is documented
+    # throughout. Please refer to the TensorFlow dockerfiles documentation
+    # for more information.
+
+# Number of days of inactivity before an Issue or Pull Request becomes stale
+daysUntilStale: 7
+# Number of days of inactivity before a stale Issue or Pull Request is closed
+daysUntilClose: 7
+# Only issues or pull requests with all of these labels are checked if stale. Defaults to `[]` (disabled)
+onlyLabels:
+ - stat:awaiting response
+# Comment to post when marking as stale. Set to `false` to disable
+markComment: >
+  This issue has been automatically marked as stale because it has not had
+  recent activity. It will be closed if no further activity occurs. Thank you.
+# Comment to post when removing the stale label. Set to `false` to disable
+unmarkComment: false
+closeComment: >
+  Closing as stale. Please reopen if you'd like to work on this further.
+limitPerRun: 30
+# Limit to only `issues` or `pulls`
+only: issues

.github/stale.yml

@@ -38,6 +38,7 @@ gradleBuild
 *.pbxproj
 *.xcworkspace
 /*.podspec
+/tensorflow/lite/**/coreml/**/BUILD
 /tensorflow/lite/**/ios/BUILD
 /tensorflow/lite/**/objc/BUILD
 /tensorflow/lite/**/swift/BUILD

.gitignore

@@ -1,7 +1,11 @@
 # TensorFlow Code of Conduct
 
-In the interest of fostering an open and welcoming environment, we as contributors and maintainers pledge to making participation in our project and our community a harassment-free experience for everyone, regardless of age, body size, disability, ethnicity, gender identity and expression, level of experience, nationality, personal appearance, race, religion, or sexual identity and orientation.
-
+In the interest of fostering an open and welcoming environment, we as
+contributors and maintainers pledge to make participation in our project and our
+community a harassment-free experience for everyone, regardless of age, body
+size, disability, ethnicity, gender identity and expression, level of
+experience, nationality, personal appearance, race, religion, or sexual identity
+and orientation.
 
 ## Our Standards