Update code to v2.8.0

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

+---
+name: "[Official Model] Bug Report"
+about: Use this template for reporting a bug for the “official” directory
+labels: type:bug,models:official
+
+---
+
+# Prerequisites
+
+Please answer the following questions for yourself before submitting an issue.
+
+- [ ] I am using the latest TensorFlow Model Garden release and TensorFlow 2.
+- [ ] I am reporting the issue to the correct repository. (Model Garden official or research directory)
+- [ ] I checked to make sure that this issue has not been filed already.
+
+## 1. The entire URL of the file you are using
+
+https://github.com/tensorflow/models/tree/master/official/...
+
+## 2. Describe the bug
+
+A clear and concise description of what the bug is.
+
+## 3. Steps to reproduce
+
+Steps to reproduce the behavior.
+
+## 4. Expected behavior
+
+A clear and concise description of what you expected to happen.
+
+## 5. Additional context
+
+Include any logs that would be helpful to diagnose the problem.
+
+## 6. System information
+
+- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
+- Mobile device name 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:
+
+<!-- 
+Collect system 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. TensorFlow 1.0
+`python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"`
+
+2. TensorFlow 2.0
+`python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`
+-->

.github/ISSUE_TEMPLATE/10-official-documentation-issue.md

+---
+name: "[Official Model] Documentation Issue"
+about: Use this template for reporting a documentation issue for the “official” directory
+labels: type:docs,models:official
+
+---
+
+# Prerequisites
+
+Please answer the following question for yourself before submitting an issue.
+
+- [ ] I checked to make sure that this issue has not been filed already.
+
+## 1. The entire URL of the documentation with the issue
+
+https://github.com/tensorflow/models/tree/master/official/...
+
+## 2. Describe the issue
+
+A clear and concise description of what needs to be changed.

.github/ISSUE_TEMPLATE/20-official-feature-request-issue.md

+---
+name: "[Official Model] Feature request"
+about: Use this template for raising a feature request for the “official” directory
+labels: type:feature,models:official
+
+---
+
+# Prerequisites
+
+Please answer the following question for yourself before submitting an issue.
+
+- [ ] I checked to make sure that this feature has not been requested already.
+
+## 1. The entire URL of the file you are using
+
+https://github.com/tensorflow/models/tree/master/official/...
+
+## 2. Describe the feature you request
+
+A clear and concise description of what you want to happen.
+
+## 3. Additional context
+
+Add any other context about the feature request here.
+
+## 4. Are you willing to contribute it? (Yes or No)

.github/ISSUE_TEMPLATE/30-research-bug-report-issue.md

+---
+name: "[Research Model] Bug Report"
+about: Use this template for reporting a bug for the “research” directory
+labels: type:bug,models:research
+
+---
+# Prerequisites
+
+Please answer the following questions for yourself before submitting an issue.
+
+- [ ] I am using the latest TensorFlow Model Garden release and TensorFlow 2.
+- [ ] I am reporting the issue to the correct repository. (Model Garden official or research directory)
+- [ ] I checked to make sure that this issue has not already been filed.
+
+## 1. The entire URL of the file you are using
+
+https://github.com/tensorflow/models/tree/master/research/...
+
+## 2. Describe the bug
+
+A clear and concise description of what the bug is.
+
+## 3. Steps to reproduce
+
+Steps to reproduce the behavior.
+
+## 4. Expected behavior
+
+A clear and concise description of what you expected to happen.
+
+## 5. Additional context
+
+Include any logs that would be helpful to diagnose the problem.
+
+## 6. System information
+
+- OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
+- Mobile device name 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:
+
+<!-- 
+Collect system 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. TensorFlow 1.0
+`python -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"`
+
+2. TensorFlow 2.0
+`python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"`
+-->

.github/ISSUE_TEMPLATE/40-research-documentation-issue.md

+---
+name: "[Research Model] Documentation Issue"
+about: Use this template for reporting a documentation issue for the “research” directory
+labels: type:docs,models:research
+
+---
+
+# Prerequisites
+
+Please answer the following question for yourself before submitting an issue.
+
+- [ ] I checked to make sure that this issue has not been filed already.
+
+## 1. The entire URL of the documentation with the issue
+
+https://github.com/tensorflow/models/tree/master/research/...
+
+## 2. Describe the issue
+
+A clear and concise description of what needs to be changed.

.github/ISSUE_TEMPLATE/50-research-feature-request-issue.md

+---
+name: "[Research Model] Feature Request"
+about: Use this template for raising a feature request for the “research” directory
+labels: type:feature,models:research
+
+---
+
+# Prerequisites
+
+Please answer the following question for yourself before submitting an issue.
+
+- [ ] I checked to make sure that this feature has not been requested already.
+
+## 1. The entire URL of the file you are using
+
+https://github.com/tensorflow/models/tree/master/research/...
+
+## 2. Describe the feature you request
+
+A clear and concise description of what you want to happen.
+
+## 3. Additional context
+
+Add any other context about the feature request here.
+
+## 4. Are you willing to contribute it? (Yes or No)

.github/ISSUE_TEMPLATE/60-questions-help-issue.md

+---
+name: Questions and Help
+about: Use this template for Questions and Help.
+labels: type:support
+
+---
+<!--
+As per our GitHub Policy (https://github.com/tensorflow/models/blob/master/ISSUES.md), we only address code bugs, documentation issues, and feature requests on GitHub.
+
+We will automatically close questions and help related issues.
+
+Please go to Stack Overflow (http://stackoverflow.com/questions/tagged/tensorflow-model-garden) for questions and help.
+
+-->

.github/ISSUE_TEMPLATE/config.yml

+blank_issues_enabled: false

.github/PULL_REQUEST_TEMPLATE.md

+# Description
+
+> :memo: Please include a summary of the change. 
+>  
+> * Please also include relevant motivation and context.  
+> * List any dependencies that are required for this change.  
+
+## Type of change
+
+For a new feature or function, please create an issue first to discuss it
+with us before submitting a pull request.
+
+Note: Please delete options that are not relevant.
+
+- [ ] Bug fix (non-breaking change which fixes an issue)
+- [ ] Documentation update
+- [ ] TensorFlow 2 migration
+- [ ] New feature (non-breaking change which adds functionality)
+- [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
+- [ ] A new research paper code implementation
+- [ ] Other (Specify)
+
+## Tests
+
+> :memo: Please describe the tests that you ran to verify your changes.
+>  
+> * Provide instructions so we can reproduce.  
+> * Please also list any relevant details for your test configuration.  
+
+**Test Configuration**:
+
+## Checklist
+
+- [ ] I have signed the [Contributor License Agreement](https://github.com/tensorflow/models/wiki/Contributor-License-Agreements).
+- [ ] I have read [guidelines for pull request](https://github.com/tensorflow/models/wiki/Submitting-a-pull-request).
+- [ ] My code follows the [coding guidelines](https://github.com/tensorflow/models/wiki/Coding-guidelines).
+- [ ] I have performed a self [code review](https://github.com/tensorflow/models/wiki/Code-review) of my own code.
+- [ ] I have commented my code, particularly in hard-to-understand areas.
+- [ ] I have made corresponding changes to the documentation.
+- [ ] My changes generate no new warnings.
+- [ ] I have added tests that prove my fix is effective or that my feature works.

.github/README_TEMPLATE.md

+> :memo: A README.md template for releasing a paper code implementation to a GitHub repository.  
+>  
+> * Template version: 1.0.2020.170  
+> * Please modify sections depending on needs.  
+
+# Model name, Paper title, or Project Name
+
+> :memo: Add a badge for the ArXiv identifier of your paper (arXiv:YYMM.NNNNN)
+
+[![Paper](http://img.shields.io/badge/Paper-arXiv.YYMM.NNNNN-B3181B?logo=arXiv)](https://arxiv.org/abs/...)
+
+This repository is the official or unofficial implementation of the following paper.
+
+* Paper title: [Paper Title](https://arxiv.org/abs/YYMM.NNNNN)
+
+## Description
+
+> :memo: Provide description of the model.  
+>  
+> * Provide brief information of the algorithms used.  
+> * Provide links for demos, blog posts, etc.  
+
+## History
+
+> :memo: Provide a changelog.
+
+## Authors or Maintainers
+
+> :memo: Provide maintainer information.  
+
+* Full name ([@GitHub username](https://github.com/username))
+* Full name ([@GitHub username](https://github.com/username))
+
+## Table of Contents
+
+> :memo: Provide a table of contents to help readers navigate a lengthy README document.
+
+## Requirements
+
+[![TensorFlow 2.1](https://img.shields.io/badge/TensorFlow-2.1-FF6F00?logo=tensorflow)](https://github.com/tensorflow/tensorflow/releases/tag/v2.1.0)
+[![Python 3.6](https://img.shields.io/badge/Python-3.6-3776AB)](https://www.python.org/downloads/release/python-360/)
+
+> :memo: Provide details of the software required.  
+>  
+> * Add a `requirements.txt` file to the root directory for installing the necessary dependencies.  
+>   * Describe how to install requirements using pip.  
+> * Alternatively, create INSTALL.md.  
+
+To install requirements:
+
+```setup
+pip install -r requirements.txt
+```
+
+## Results
+
+> :memo: Provide a table with results. (e.g., accuracy, latency)  
+>  
+> * Provide links to the pre-trained models (checkpoint, SavedModel files).  
+>   * Publish TensorFlow SavedModel files on TensorFlow Hub (tfhub.dev) if possible.  
+> * Add links to [TensorBoard.dev](https://tensorboard.dev/) for visualizing metrics.  
+>  
+> An example table for image classification results  
+>  
+> ### Image Classification  
+>  
+> | Model name | Download | Top 1 Accuracy | Top 5 Accuracy |  
+> |------------|----------|----------------|----------------|  
+> | Model name | [Checkpoint](https://drive.google.com/...), [SavedModel](https://tfhub.dev/...) | xx% | xx% |  
+
+## Dataset
+
+> :memo: Provide information of the dataset used.  
+
+## Training
+
+> :memo: Provide training information.  
+>  
+> * Provide details for preprocessing, hyperparameters, random seeds, and environment.  
+> * Provide a command line example for training.  
+
+Please run this command line for training.
+
+```shell
+python3 ...
+```
+
+## Evaluation
+
+> :memo: Provide an evaluation script with details of how to reproduce results.  
+>  
+> * Describe data preprocessing / postprocessing steps.  
+> * Provide a command line example for evaluation.  
+
+Please run this command line for evaluation.
+
+```shell
+python3 ...
+```
+
+## References
+
+> :memo: Provide links to references.  
+
+## License
+
+[![License](https://img.shields.io/badge/License-Apache%202.0-blue.svg)](https://opensource.org/licenses/Apache-2.0)
+
+> :memo: Place your license text in a file named LICENSE in the root of the repository.  
+>  
+> * Include information about your license.  
+> * Reference: [Adding a license to a repository](https://help.github.com/en/github/building-a-strong-community/adding-a-license-to-a-repository)  
+
+This project is licensed under the terms of the **Apache License 2.0**.
+
+## Citation
+
+> :memo: Make your repository citable.  
+>  
+> * Reference: [Making Your Code Citable](https://guides.github.com/activities/citable-code/)  
+
+If you want to cite this repository in your research paper, please use the following information.

.gitignore

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

AUTHORS

+# This is the official list of authors for copyright purposes.
+# This file is distinct from the CONTRIBUTORS files.
+# See the latter for an explanation.
+
+# Names should be added to this file as:
+# Name or Organization <email address>
+# The email address is not required for organizations.
+
+Google Inc.
+David Dao <daviddao@broad.mit.edu>

CODEOWNERS

+* @tensorflow/tf-garden-team @tensorflow/tf-model-garden-team
+/official/ @rachellj218 @saberkun @jaeyounkim
+/official/nlp/ @saberkun @chenGitHuber @lehougoogle @rachellj218
+/official/vision/ @pengchongjin @xianzhidu @yeqingli @arashwan @saberkun @rachellj218
+/research/adv_imagenet_models/ @alexeykurakin
+/research/adversarial_crypto/ @dave-andersen
+/research/adversarial_logit_pairing/ @alexeykurakin
+/research/adversarial_text/ @rsepassi @a-dai
+/research/attention_ocr/ @xavigibert
+/research/audioset/ @plakal @dpwe
+/research/autoaugment/* @barretzoph
+/research/autoencoders/ @snurkabill
+/research/brain_coder/ @danabo
+/research/cognitive_mapping_and_planning/ @s-gupta
+/research/compression/ @nmjohn
+/research/cvt_text/ @clarkkev @lmthang
+/research/deep_contextual_bandits/ @rikel
+/research/deep_speech/ @yhliang2018
+/research/deeplab/ @aquariusjay @yknzhu @gpapan
+/research/delf/ @andrefaraujo
+/research/domain_adaptation/ @bousmalis @dmrd
+/research/efficient-hrl/ @ofirnachum
+/research/feelvos/ @pvoigtlaender @yuningchai @aquariusjay
+/research/fivo/ @dieterichlawson
+/research/global_objectives/ @mackeya-google
+/research/im2txt/ @cshallue
+/research/inception/ @shlens @vincentvanhoucke
+/research/keypointnet/ @mnorouzi
+/research/learned_optimizer/ @olganw @nirum
+/research/learning_to_remember_rare_events/ @lukaszkaiser @ofirnachum
+/research/learning_unsupervised_learning/ @lukemetz @nirum
+/research/lexnet_nc/ @vered1986 @waterson
+/research/lfads/ @jazcollins @sussillo
+/research/lm_1b/ @oriolvinyals @panyx0718
+/research/lm_commonsense/ @thtrieu
+/research/lstm_object_detection/ @yinxiaoli @yongzhe2160
+/research/marco/ @vincentvanhoucke
+/research/maskgan/ @liamb315 @a-dai
+/research/namignizer/ @knathanieltucker
+/research/neural_gpu/ @lukaszkaiser
+/research/neural_programmer/ @arvind2505
+/research/next_frame_prediction/ @panyx0718
+/research/object_detection/ @jch1 @tombstone @pkulzc
+/research/pcl_rl/ @ofirnachum
+/research/ptn/ @xcyan @arkanath @hellojas @honglaklee
+/research/qa_kg/ @yuyuz
+/research/real_nvp/ @laurent-dinh
+/research/rebar/ @gjtucker
+/research/sentiment_analysis/ @sculd
+/research/seq2species/ @apbusia @depristo
+/research/skip_thoughts/ @cshallue
+/research/slim/ @sguada @marksandler2
+/research/steve/ @buckman-google
+/research/street/ @theraysmith
+/research/struct2depth/ @aneliaangelova
+/research/swivel/ @waterson
+/research/tcn/ @coreylynch @sermanet
+/research/textsum/ @panyx0718 @peterjliu
+/research/transformer/ @daviddao
+/research/vid2depth/ @rezama
+/research/video_prediction/ @cbfinn

CONTRIBUTING.md

+# How to contribute
+
+![Contributors](https://img.shields.io/github/contributors/tensorflow/models)
+
+We encourage you to contribute to the TensorFlow Model Garden.
+
+Please read our [guidelines](../../wiki/How-to-contribute) for details.
+
+**NOTE**: Only [code owners](./CODEOWNERS) are allowed to merge a pull request.
+Please contact the code owners of each model to merge your pull request.

ISSUES.md

+# If you open a GitHub issue, here is our policy.
+
+* It must be a **bug**, a **feature request**, or a significant problem
+with **documentation**.
+  * Please send a pull request instead for small documentation fixes.
+* The required form must be filled out.
+* The issue should be related to the repository it is created in.
+
+General help and support should be sought on [Stack Overflow](https://stackoverflow.com/questions/tagged/tensorflow-model-garden) or other non-GitHub channels.
+
+[![](https://img.shields.io/stackexchange/stackoverflow/t/tensorflow-model-garden)](https://stackoverflow.com/questions/tagged/tensorflow-model-garden)
+
+TensorFlow developers respond to issues.
+We want to focus on work that benefits the whole community such as fixing bugs
+and adding new features.
+It helps us to address bugs and feature requests in a timely manner.
+
+--- 
+
+Please understand that research models in the [research directory](https://github.com/tensorflow/models/tree/master/research)
+included in this repository are experimental and research-style code.
+They are not officially supported by the TensorFlow team.
+
+

LICENSE

+Copyright 2016 The TensorFlow Authors.  All rights reserved.
+
+                                 Apache License
+                           Version 2.0, January 2004
+                        http://www.apache.org/licenses/
+
+   TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
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+
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+Copyright 2015 The TensorFlow Authors.  All rights reserved.
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official/README-TPU.md

+# Offically Supported TensorFlow 2.1+ Models on Cloud TPU
+
+## Natural Language Processing
+
+*   [bert](nlp/bert): A powerful pre-trained language representation model:
+    BERT, which stands for Bidirectional Encoder Representations from
+    Transformers.
+    [BERT FineTuning with Cloud TPU](https://cloud.google.com/tpu/docs/tutorials/bert-2.x) provides step by step instructions on Cloud TPU training. You can look [Bert MNLI Tensorboard.dev metrics](https://tensorboard.dev/experiment/LijZ1IrERxKALQfr76gndA) for MNLI fine tuning task.
+*   [transformer](nlp/transformer): A transformer model to translate the WMT
+    English to German dataset.
+        [Training transformer on Cloud TPU](https://cloud.google.com/tpu/docs/tutorials/transformer-2.x) for step by step instructions on Cloud TPU training.
+
+## Computer Vision
+
+*   [efficientnet](vision/image_classification): A family of convolutional
+    neural networks that scale by balancing network depth, width, and
+    resolution and can be used to classify ImageNet's dataset of 1000 classes.
+    See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/KnaWjrq5TXGfv0NW5m7rpg/#scalars).
+*   [mnist](vision/image_classification): A basic model to classify digits
+    from the MNIST dataset. See [Running MNIST on Cloud TPU](https://cloud.google.com/tpu/docs/tutorials/mnist-2.x) tutorial and [Tensorboard.dev metrics](https://tensorboard.dev/experiment/mIah5lppTASvrHqWrdr6NA).
+*   [mask-rcnn](vision/detection): An object detection and instance segmentation model. See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/LH7k0fMsRwqUAcE09o9kPA).
+*   [resnet](vision/image_classification): A deep residual network that can
+    be used to classify ImageNet's dataset of 1000 classes.
+    See [Training ResNet on Cloud TPU](https://cloud.google.com/tpu/docs/tutorials/resnet-2.x) tutorial and [Tensorboard.dev metrics](https://tensorboard.dev/experiment/CxlDK8YMRrSpYEGtBRpOhg).
+*   [retinanet](vision/detection): A fast and powerful object detector. See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/b8NRnWU3TqG6Rw0UxueU6Q).
+*   [shapemask](vision/detection): An object detection and instance segmentation model using shape priors. See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/ZbXgVoc6Rf6mBRlPj0JpLA).
+
+## Recommendation
+*   [dlrm](recommendation/ranking): [Deep Learning Recommendation Model for
+Personalization and Recommendation Systems](https://arxiv.org/abs/1906.00091).
+*   [dcn v2](recommendation/ranking): [Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems](https://arxiv.org/abs/2008.13535).
+*   [ncf](recommendation): Neural Collaborative Filtering. See [Tensorboard.dev training metrics](https://tensorboard.dev/experiment/0k3gKjZlR1ewkVTRyLB6IQ).

official/README.md

+![Logo](https://storage.googleapis.com/model_garden_artifacts/TF_Model_Garden.png)
+
+# TensorFlow Official Models
+
+The TensorFlow official models are a collection of models
+that use TensorFlow’s high-level APIs.
+They are intended to be well-maintained, tested, and kept up to date
+with the latest TensorFlow API.
+
+They should also be reasonably optimized for fast performance while still
+being easy to read.
+These models are used as end-to-end tests, ensuring that the models run
+with the same or improved speed and performance with each new TensorFlow build.
+
+## More models to come!
+
+The team is actively developing new models.
+In the near future, we will add:
+
+* State-of-the-art language understanding models.
+* State-of-the-art image classification models.
+* State-of-the-art object detection and instance segmentation models.
+
+## Table of Contents
+
+- [Models and Implementations](#models-and-implementations)
+  * [Computer Vision](#computer-vision)
+    + [Image Classification](#image-classification)
+    + [Object Detection and Segmentation](#object-detection-and-segmentation)
+  * [Natural Language Processing](#natural-language-processing)
+  * [Recommendation](#recommendation)
+- [How to get started with the official models](#how-to-get-started-with-the-official-models)
+
+## Models and Implementations
+
+### Computer Vision
+
+#### Image Classification
+
+| Model | Reference (Paper) |
+|-------|-------------------|
+| [MNIST](vision/image_classification) | A basic model to classify digits from the [MNIST dataset](http://yann.lecun.com/exdb/mnist/) |
+| [ResNet](vision/beta/MODEL_GARDEN.md) | [Deep Residual Learning for Image Recognition](https://arxiv.org/abs/1512.03385) |
+| [ResNet-RS](vision/beta/MODEL_GARDEN.md) | [Revisiting ResNets: Improved Training and Scaling Strategies](https://arxiv.org/abs/2103.07579) |
+| [EfficientNet](vision/image_classification) | [EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks](https://arxiv.org/abs/1905.11946) |
+
+#### Object Detection and Segmentation
+
+| Model | Reference (Paper) |
+|-------|-------------------|
+| [RetinaNet](vision/beta/MODEL_GARDEN.md) | [Focal Loss for Dense Object Detection](https://arxiv.org/abs/1708.02002) |
+| [Mask R-CNN](vision/beta/MODEL_GARDEN.md) | [Mask R-CNN](https://arxiv.org/abs/1703.06870) |
+| [ShapeMask](vision/detection) | [ShapeMask: Learning to Segment Novel Objects by Refining Shape Priors](https://arxiv.org/abs/1904.03239) |
+| [SpineNet](vision/beta/MODEL_GARDEN.md) | [SpineNet: Learning Scale-Permuted Backbone for Recognition and Localization](https://arxiv.org/abs/1912.05027) |
+| [Cascade RCNN-RS and RetinaNet-RS](vision/beta/MODEL_GARDEN.md) | [Simple Training Strategies and Model Scaling for Object Detection](https://arxiv.org/abs/2107.00057)|
+
+### Natural Language Processing
+
+| Model | Reference (Paper) |
+|-------|-------------------|
+| [ALBERT (A Lite BERT)](nlp/MODEL_GARDEN.md#available-model-configs) | [ALBERT: A Lite BERT for Self-supervised Learning of Language Representations](https://arxiv.org/abs/1909.11942) |
+| [BERT (Bidirectional Encoder Representations from Transformers)](nlp/MODEL_GARDEN.md#available-model-configs) | [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://arxiv.org/abs/1810.04805) |
+| [NHNet (News Headline generation model)](projects/nhnet) | [Generating Representative Headlines for News Stories](https://arxiv.org/abs/2001.09386) |
+| [Transformer](nlp/transformer) | [Attention Is All You Need](https://arxiv.org/abs/1706.03762) |
+| [XLNet](nlp/xlnet) | [XLNet: Generalized Autoregressive Pretraining for Language Understanding](https://arxiv.org/abs/1906.08237) |
+| [MobileBERT](projects/mobilebert) | [MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices](https://arxiv.org/abs/2004.02984) |
+
+### Recommendation
+
+Model                            | Reference (Paper)
+-------------------------------- | -----------------
+[DLRM](recommendation/ranking)   | [Deep Learning Recommendation Model for Personalization and Recommendation Systems](https://arxiv.org/abs/1906.00091)
+[DCN v2](recommendation/ranking) | [Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems](https://arxiv.org/abs/2008.13535)
+[NCF](recommendation)            | [Neural Collaborative Filtering](https://arxiv.org/abs/1708.05031)
+
+## How to get started with the official models
+
+* The models in the master branch are developed using TensorFlow 2,
+and they target the TensorFlow [nightly binaries](https://github.com/tensorflow/tensorflow#installation)
+built from the
+[master branch of TensorFlow](https://github.com/tensorflow/tensorflow/tree/master).
+* The stable versions targeting releases of TensorFlow are available
+as tagged branches or [downloadable releases](https://github.com/tensorflow/models/releases).
+* Model repository version numbers match the target TensorFlow release,
+such that
+[release v2.5.0](https://github.com/tensorflow/models/releases/tag/v2.5.0)
+are compatible with
+[TensorFlow v2.5.0](https://github.com/tensorflow/tensorflow/releases/tag/v2.5.0).
+
+Please follow the below steps before running models in this repository.
+
+### Requirements
+
+* The latest TensorFlow Model Garden release and TensorFlow 2
+  * If you are on a version of TensorFlow earlier than 2.2, please
+upgrade your TensorFlow to [the latest TensorFlow 2](https://www.tensorflow.org/install/).
+
+```shell
+pip3 install tf-nightly
+```
+
+* Python 3.7+
+
+Our integration tests run with Python 3.7. Although Python 3.6 should work, we
+don't recommend earlier versions.
+
+### Installation
+
+#### Method 1: Install the TensorFlow Model Garden pip package
+
+**tf-models-official** is the stable Model Garden package.
+pip will install all models and dependencies automatically.
+
+```shell
+pip install tf-models-official
+```
+
+If you are using nlp packages, please also install **tensorflow-text**:
+
+```shell
+pip install tensorflow-text
+```
+
+Please check out our [example](colab/fine_tuning_bert.ipynb)
+to learn how to use a PIP package.
+
+Note that **tf-models-official** may not include the latest changes in this
+github repo. To include latest changes, you may install **tf-models-nightly**,
+which is the nightly Model Garden package created daily automatically.
+
+```shell
+pip install tf-models-nightly
+```
+
+#### Method 2: Clone the source
+
+1. Clone the GitHub repository:
+
+```shell
+git clone https://github.com/tensorflow/models.git
+```
+
+2. Add the top-level ***/models*** folder to the Python path.
+
+```shell
+export PYTHONPATH=$PYTHONPATH:/path/to/models
+```
+
+If you are using a Colab notebook, please set the Python path with os.environ.
+
+```python
+import os
+os.environ['PYTHONPATH'] += ":/path/to/models"
+```
+
+3. Install other dependencies
+
+```shell
+pip3 install --user -r official/requirements.txt
+```
+
+Finally, if you are using nlp packages, please also install
+**tensorflow-text-nightly**:
+
+```shell
+pip3 install tensorflow-text-nightly
+```
+
+## Contributions
+
+If you want to contribute, please review the [contribution guidelines](https://github.com/tensorflow/models/wiki/How-to-contribute).