base on Models and examples built with TensorFlow <div align="center"> <img src="https://storage.googleapis.com/tf_model_garden/tf_model_garden_logo.png"> </div> [](https://badge.fury.io/py/tensorflow) [](https://badge.fury.io/py/tf-models-official) # Welcome to the Model Garden for TensorFlow The TensorFlow Model Garden is a repository with a number of different implementations of state-of-the-art (SOTA) models and modeling solutions for TensorFlow users. We aim to demonstrate the best practices for modeling so that TensorFlow users can take full advantage of TensorFlow for their research and product development. To improve the transparency and reproducibility of our models, training logs on [TensorBoard.dev](https://tensorboard.dev) are also provided for models to the extent possible though not all models are suitable. | Directory | Description | |-----------|-------------| | [official](official) | • A collection of example implementations for SOTA models using the latest TensorFlow 2's high-level APIs<br />• Officially maintained, supported, and kept up to date with the latest TensorFlow 2 APIs by TensorFlow<br />• Reasonably optimized for fast performance while still being easy to read<br /> For more details on the capabilities, check the guide on the [Model-garden](https://www.tensorflow.org/tfmodels)| | [research](research) | • A collection of research model implementations in TensorFlow 1 or 2 by researchers<br />• Maintained and supported by researchers | | [community](community) | • A curated list of the GitHub repositories with machine learning models and implementations powered by TensorFlow 2 | | [orbit](orbit) | • A flexible and lightweight library that users can easily use or fork when writing customized training loop code in TensorFlow 2.x. It seamlessly integrates with `tf.distribute` and supports running on different device types (CPU, GPU, and TPU). | ## Installation To install the current release of tensorflow-models, please follow any one of the methods described below. #### Method 1: Install the TensorFlow Model Garden pip package <details> **tf-models-official** is the stable Model Garden package. Please check out the [releases](https://github.com/tensorflow/models/releases) to see what are available modules. pip3 will install all models and dependencies automatically. ```shell pip3 install tf-models-official ``` Please check out our examples: - [basic library import](https://github.com/tensorflow/models/blob/master/tensorflow_models/tensorflow_models_pypi.ipynb) - [nlp model building](https://github.com/tensorflow/models/blob/master/docs/nlp/index.ipynb) to learn how to use a PIP package. Note that **tf-models-official** may not include the latest changes in the master branch of this github repo. To include latest changes, you may install **tf-models-nightly**, which is the nightly Model Garden package created daily automatically. ```shell pip3 install tf-models-nightly ``` </details> #### Method 2: Clone the source <details> 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 in a Windows environment, you may need to use the following command with PowerShell: ```shell $env: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 models/official/requirements.txt ``` Finally, if you are using nlp packages, please also install **tensorflow-text-nightly**: ```shell pip3 install tensorflow-text-nightly ``` </details> ## Announcements Please check [this page](https://github.com/tensorflow/models/wiki/Announcements) for recent announcements. ## Contributions [](https://github.com/tensorflow/models/labels/help%20wanted%3Apaper%20implementation) If you want to contribute, please review the [contribution guidelines](https://github.com/tensorflow/models/wiki/How-to-contribute). ## License [Apache License 2.0](LICENSE) ## Citing TensorFlow Model Garden If you use TensorFlow Model Garden in your research, please cite this repository. ``` @misc{tensorflowmodelgarden2020, author = {Hongkun Yu and Chen Chen and Xianzhi Du and Yeqing Li and Abdullah Rashwan and Le Hou and Pengchong Jin and Fan Yang and Frederick Liu and Jaeyoun Kim and Jing Li}, title = {{TensorFlow Model Garden}}, howpublished = {\url{https://github.com/tensorflow/models}}, year = {2020} } ``` ", Assign "at most 3 tags" to the expected json: {"id":"10876","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"