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<div align="center">
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<img src="https://www.tensorflow.org/images/tf_logo_horizontal.png">
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</div>
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[](https://badge.fury.io/py/tensorflow)
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[](https://badge.fury.io/py/tensorflow)
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[](https://doi.org/10.5281/zenodo.4724125)
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[](https://bestpractices.coreinfrastructure.org/projects/1486)
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[](https://securityscorecards.dev/viewer/?uri=github.com/tensorflow/tensorflow)
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[](https://bugs.chromium.org/p/oss-fuzz/issues/list?sort=-opened&can=1&q=proj:tensorflow)
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[](https://bugs.chromium.org/p/oss-fuzz/issues/list?sort=-opened&can=1&q=proj:tensorflow-py)
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[](https://ossrank.com/p/44)
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[](CODE_OF_CONDUCT.md)
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**`Documentation`** |
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------------------- |
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[](https://www.tensorflow.org/api_docs/) |
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[TensorFlow](https://www.tensorflow.org/) is an end-to-end open source platform
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for machine learning. It has a comprehensive, flexible ecosystem of
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[tools](https://www.tensorflow.org/resources/tools),
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[libraries](https://www.tensorflow.org/resources/libraries-extensions), and
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[community](https://www.tensorflow.org/community) resources that lets
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researchers push the state-of-the-art in ML and developers easily build and
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deploy ML-powered applications.
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TensorFlow was originally developed by researchers and engineers working within
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the Machine Intelligence team at Google Brain to conduct research in machine
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learning and neural networks. However, the framework is versatile enough to be
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used in other areas as well.
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TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)
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and [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as a
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non-guaranteed backward compatible API for
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[other languages](https://www.tensorflow.org/api_docs).
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Keep up-to-date with release announcements and security updates by subscribing
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to
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[announce@tensorflow.org](https://groups.google.com/a/tensorflow.org/forum/#!forum/announce).
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See all the [mailing lists](https://www.tensorflow.org/community/forums).
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## Install
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See the [TensorFlow install guide](https://www.tensorflow.org/install) for the
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[pip package](https://www.tensorflow.org/install/pip), to
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[enable GPU support](https://www.tensorflow.org/install/gpu), use a
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[Docker container](https://www.tensorflow.org/install/docker), and
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[build from source](https://www.tensorflow.org/install/source).
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To install the current release, which includes support for
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[CUDA-enabled GPU cards](https://www.tensorflow.org/install/gpu) *(Ubuntu and
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Windows)*:
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```
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pip install tensorflow
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```
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Other devices (DirectX and MacOS-metal) are supported using
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[Device Plugins](https://www.tensorflow.org/install/gpu_plugins#available_devices).
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A smaller CPU-only TensorFlow package is also available:
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```
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pip install tensorflow-cpu
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```
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To update TensorFlow to the latest version, add the `--upgrade` flag to the
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commands above.
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*Nightly binaries are available for testing using the
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[tf-nightly](https://pypi.python.org/pypi/tf-nightly) and
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[tf-nightly-cpu](https://pypi.python.org/pypi/tf-nightly-cpu) packages on PyPI.*
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#### *Try your first TensorFlow program*
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```shell
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$ python
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```
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```python
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>>> import tensorflow as tf
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>>> tf.add(1, 2).numpy()
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3
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>>> hello = tf.constant('Hello, TensorFlow!')
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>>> hello.numpy()
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b'Hello, TensorFlow!'
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```
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For more examples, see the
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[TensorFlow Tutorials](https://www.tensorflow.org/tutorials/).
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## Contribution guidelines
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**If you want to contribute to TensorFlow, be sure to review the
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[Contribution Guidelines](CONTRIBUTING.md). This project adheres to TensorFlow's
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[Code of Conduct](CODE_OF_CONDUCT.md). By participating, you are expected to
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uphold this code.**
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**We use [GitHub Issues](https://github.com/tensorflow/tensorflow/issues) for
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tracking requests and bugs, please see
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[TensorFlow Forum](https://discuss.tensorflow.org/) for general questions and
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discussion, and please direct specific questions to
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[Stack Overflow](https://stackoverflow.com/questions/tagged/tensorflow).**
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The TensorFlow project strives to abide by generally accepted best practices in
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open-source software development.
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## Patching guidelines
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Follow these steps to patch a specific version of TensorFlow, for example, to
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apply fixes to bugs or security vulnerabilities:
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* Clone the TensorFlow repository and switch to the appropriate branch for
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your desired version—for example, `r2.8` for version 2.8.
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* Apply the desired changes (i.e., cherry-pick them) and resolve any code
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conflicts.
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* Run TensorFlow tests and ensure they pass.
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* [Build](https://www.tensorflow.org/install/source) the TensorFlow pip
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package from source.
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## Continuous build status
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You can find more community-supported platforms and configurations in the
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[TensorFlow SIG Build Community Builds Table](https://github.com/tensorflow/build#community-supported-tensorflow-builds).
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### Official Builds
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Build Type | Status | Artifacts
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----------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ---------
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**Linux CPU** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-cc.html) | [PyPI](https://pypi.org/project/tf-nightly/)
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**Linux GPU** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-gpu-py3.html) | [PyPI](https://pypi.org/project/tf-nightly-gpu/)
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**Linux XLA** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-xla.html) | TBA
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**macOS** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/macos-py2-cc.html) | [PyPI](https://pypi.org/project/tf-nightly/)
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**Windows CPU** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/windows-cpu.html) | [PyPI](https://pypi.org/project/tf-nightly/)
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**Windows GPU** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/windows-gpu.html) | [PyPI](https://pypi.org/project/tf-nightly-gpu/)
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**Android** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/android.html) | [Download](https://bintray.com/google/tensorflow/tensorflow/_latestVersion)
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**Raspberry Pi 0 and 1** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi01-py3.html) | [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv6l.whl)
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**Raspberry Pi 2 and 3** | [](https://storage.googleapis.com/tensorflow-kokoro-build-badges/rpi23-py3.html) | [Py3](https://storage.googleapis.com/tensorflow-nightly/tensorflow-1.10.0-cp34-none-linux_armv7l.whl)
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## Resources
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* [TensorFlow.org](https://www.tensorflow.org)
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* [TensorFlow Tutorials](https://www.tensorflow.org/tutorials/)
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* [TensorFlow Official Models](https://github.com/tensorflow/models/tree/master/official)
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* [TensorFlow Examples](https://github.com/tensorflow/examples)
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* [TensorFlow Codelabs](https://codelabs.developers.google.com/?cat=TensorFlow)
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* [TensorFlow Blog](https://blog.tensorflow.org)
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* [Learn ML with TensorFlow](https://www.tensorflow.org/resources/learn-ml)
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* [TensorFlow Twitter](https://twitter.com/tensorflow)
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* [TensorFlow YouTube](https://www.youtube.com/channel/UC0rqucBdTuFTjJiefW5t-IQ)
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* [TensorFlow model optimization roadmap](https://www.tensorflow.org/model_optimization/guide/roadmap)
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* [TensorFlow White Papers](https://www.tensorflow.org/about/bib)
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* [TensorBoard Visualization Toolkit](https://github.com/tensorflow/tensorboard)
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* [TensorFlow Code Search](https://cs.opensource.google/tensorflow/tensorflow)
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Learn more about the
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[TensorFlow Community](https://www.tensorflow.org/community) and how to
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[Contribute](https://www.tensorflow.org/community/contribute).
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## Courses
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* [Coursera](https://www.coursera.org/search?query=TensorFlow)
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* [Udacity](https://www.udacity.com/courses/all?search=TensorFlow)
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* [Edx](https://www.edx.org/search?q=TensorFlow)
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## License
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[Apache License 2.0](LICENSE)
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