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Merge branch 'master' of https://github.com/tensorflow/models
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.github/ISSUE_TEMPLATE.md

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.gitignore

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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env/
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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*.egg-info/
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.installed.cfg
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*.egg
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*,cover
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.hypothesis/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# IPython Notebook
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.ipynb_checkpoints
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# pyenv
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.python-version
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# celery beat schedule file
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celerybeat-schedule
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# dotenv
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.env
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# virtualenv
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venv/
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ENV/
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# Spyder project settings
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.spyderproject
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# Rope project settings
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.ropeproject
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# PyCharm
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.idea/

.gitmodules

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[submodule "tensorflow"]
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path = syntaxnet/tensorflow
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path = research/syntaxnet/tensorflow
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url = https://github.com/tensorflow/tensorflow.git

CODEOWNERS

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/official/ @nealwu @k-w-w @karmel
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/research/adversarial_crypto/ @dave-andersen
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/research/adversarial_text/ @rsepassi @a-dai
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/research/adv_imagenet_models/ @AlexeyKurakin
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/research/attention_ocr/ @alexgorban
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/research/audioset/ @plakal @dpwe
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/research/autoencoders/ @snurkabill
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/research/brain_coder/ @danabo
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/research/cognitive_mapping_and_planning/ @s-gupta
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/research/compression/ @nmjohn
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/research/deeplab/ @aquariusjay @yknzhu @gpapan
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/research/delf/ @andrefaraujo
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/research/differential_privacy/ @panyx0718
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/research/domain_adaptation/ @bousmalis @dmrd
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/research/gan/ @joel-shor
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/research/im2txt/ @cshallue
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/research/inception/ @shlens @vincentvanhoucke
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/research/learned_optimizer/ @olganw @nirum
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/research/learning_to_remember_rare_events/ @lukaszkaiser @ofirnachum
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/research/lfads/ @jazcollins @susillo
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/research/lm_1b/ @oriolvinyals @panyx0718
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/research/maskgan/ @a-dai
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/research/namignizer/ @knathanieltucker
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/research/neural_gpu/ @lukaszkaiser
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/research/neural_programmer/ @arvind2505
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/research/next_frame_prediction/ @panyx0718
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/research/object_detection/ @jch1 @tombstone @derekjchow @jesu9 @dreamdragon @pkulzc
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/research/pcl_rl/ @ofirnachum
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/research/ptn/ @xcyan @arkanath @hellojas @honglaklee
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/research/real_nvp/ @laurent-dinh
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/research/rebar/ @gjtucker
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/research/resnet/ @panyx0718
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/research/skip_thoughts/ @cshallue
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/research/slim/ @sguada @nathansilberman
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/research/street/ @theraysmith
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/research/swivel/ @waterson
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/research/syntaxnet/ @calberti @andorardo @bogatyy @markomernick
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/research/tcn/ @coreylynch @sermanet
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/research/textsum/ @panyx0718 @peterjliu
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/research/transformer/ @daviddao
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/research/video_prediction/ @cbfinn
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/research/fivo/ @dieterichlawson
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/samples/ @MarkDaoust
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/samples/languages/java/ @asimshankar
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/tutorials/embedding/ @zffchen78 @a-dai
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/tutorials/image/ @sherrym @shlens
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/tutorials/image/cifar10_estimator/ @tfboyd @protoget
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/tutorials/rnn/ @lukaszkaiser @ebrevdo

CONTRIBUTING.md

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# Contributing guidelines
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If you have created a model and would like to publish it here, please send us a
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pull request. For those just getting started with pull reuests, GitHub has a
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pull request. For those just getting started with pull requests, GitHub has a
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[howto](https://help.github.com/articles/using-pull-requests/).
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The code for any model in this repository is licensed under the Apache License

ISSUE_TEMPLATE.md

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Please go to Stack Overflow for help and support:
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http://stackoverflow.com/questions/tagged/tensorflow
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Also, please understand that many of the models included in this repository are experimental and research-style code. If you open a GitHub issue, here is our policy:
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1. It must be a bug, a feature request, or a significant problem with documentation (for small docs fixes please send a PR instead).
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2. The form below must be filled out.
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**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.
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------------------------
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### System information
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- **What is the top-level directory of the model you are using**:
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- **Have I written custom code (as opposed to using a stock example script provided in TensorFlow)**:
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- **OS Platform and Distribution (e.g., Linux Ubuntu 16.04)**:
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- **TensorFlow installed from (source or binary)**:
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- **TensorFlow version (use command below)**:
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- **Bazel version (if compiling from source)**:
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- **CUDA/cuDNN version**:
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- **GPU model and memory**:
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- **Exact command to reproduce**:
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You can collect some of this information using our environment capture script:
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https://github.com/tensorflow/tensorflow/tree/master/tools/tf_env_collect.sh
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You can obtain the TensorFlow version with
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python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"
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### Describe the problem
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Describe the problem clearly here. Be sure to convey here why it's a bug in TensorFlow or a feature request.
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### Source code / logs
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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. Try to provide a reproducible test case that is the bare minimum necessary to generate the problem.

README

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README.md

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# TensorFlow Models
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This repository contains machine learning models implemented in
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[TensorFlow](https://tensorflow.org). The models are maintained by their
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respective authors.
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This repository contains a number of different models implemented in [TensorFlow](https://www.tensorflow.org):
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To propose a model for inclusion please submit a pull request.
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The [official models](official) are a collection of example models that use TensorFlow's high-level APIs. They are intended to be well-maintained, tested, and kept up to date with the latest stable TensorFlow API. They should also be reasonably optimized for fast performance while still being easy to read. We especially recommend newer TensorFlow users to start here.
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The [research models](https://github.com/tensorflow/models/tree/master/research) are a large collection of models implemented in TensorFlow by researchers. They are not officially supported or available in release branches; it is up to the individual researchers to maintain the models and/or provide support on issues and pull requests.
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The [samples folder](samples) contains code snippets and smaller models that demonstrate features of TensorFlow, including code presented in various blog posts.
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The [tutorials folder](tutorials) is a collection of models described in the [TensorFlow tutorials](https://www.tensorflow.org/tutorials/).
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autoencoder/Utils.py

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