Merge pull request #12 from tensorflow/master

Merge changes from tensorflow:master

.bazelversion

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

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

@@ -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/60-tflite-converter-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/80-performance-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/bot_config.yml

@@ -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/stale.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

.gitignore

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

CODE_OF_CONDUCT.md

@@ -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
 

CONTRIBUTING.md

@@ -88,6 +88,9 @@ TensorFlow coding style.
     submitting PRs to fix one typo, one warning,etc. We recommend fixing the
     same issue at the file level at least (e.g.: fix all typos in a file, fix
     all compiler warning in a file, etc.)
+*   Tests should follow the
+    [testing best practices](https://www.tensorflow.org/community/contribute/tests)
+    guide.
 
 #### License
 

ISSUE_TEMPLATE.md

@@ -4,26 +4,31 @@ https://stackoverflow.com/questions/tagged/tensorflow
 
 If you open a GitHub issue, here is our policy:
 
-1. It must be a bug, a feature request, or a significant problem with documentation (for small docs fixes please send a PR instead).
-2. The form below must be filled out.
-3. It shouldn't be a TensorBoard issue. Those go [here](https://github.com/tensorflow/tensorboard/issues).
+1.  It must be a bug, a feature request, or a significant problem with the
+    documentation (for small docs fixes please send a PR instead).
+2.  The form below must be filled out.
+3.  It shouldn't be a TensorBoard issue. Those go
+    [here](https://github.com/tensorflow/tensorboard/issues).
 
 **Here's why we have that policy**: TensorFlow developers respond to issues. We want to focus on work that benefits the whole community, e.g., fixing bugs and adding features. Support only helps individuals. GitHub also notifies thousands of people when issues are filed. We want them to see you communicating an interesting problem, rather than being redirected to Stack Overflow.
 
 ------------------------
 
 ### 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**:
-- **Exact command to reproduce**:
+
+-   **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 a 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**:
+-   **Exact command to reproduce**:
 
 You can collect some of this information using our environment capture script: