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    README.md

    Python PyPI

    Documentation
    Documentation

    TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.

    TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization to conduct machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well.

    TensorFlow provides stable Python and C++ APIs, as well as non-guaranteed backward compatible API for other languages.

    Keep up-to-date with release announcements and security updates by subscribing to announce@tensorflow.org. See all the mailing lists.

    Install

    See the TensorFlow install guide for the pip package, to enable GPU support, use a Docker container, and build from source.

    To install the current release, which includes support for CUDA-enabled GPU cards (Ubuntu and Windows):

    $ pip install tensorflow
    

    A smaller CPU-only package is also available:

    $ pip install tensorflow-cpu
    

    To update TensorFlow to the latest version, add --upgrade flag to the above commands.

    Nightly binaries are available for testing using the tf-nightly and tf-nightly-cpu packages on PyPi.

    Try your first TensorFlow program

    $ python
    >>> import tensorflow as tf
    >>> tf.add(1, 2).numpy()
    3
    >>> hello = tf.constant('Hello, TensorFlow!')
    >>> hello.numpy()
    b'Hello, TensorFlow!'

    For more examples, see the TensorFlow tutorials.

    Contribution guidelines

    If you want to contribute to TensorFlow, be sure to review the contribution guidelines. This project adheres to TensorFlow's code of conduct. By participating, you are expected to uphold this code.

    We use GitHub issues for tracking requests and bugs, please see TensorFlow Discuss for general questions and discussion, and please direct specific questions to Stack Overflow.

    The TensorFlow project strives to abide by generally accepted best practices in open-source software development:

    Fuzzing Status CII Best Practices Contributor Covenant

    Continuous build status

    Official Builds

    Build Type Status Artifacts
    Linux CPU Status PyPI
    Linux GPU Status PyPI
    Linux XLA Status TBA
    macOS Status PyPI
    Windows CPU Status PyPI
    Windows GPU Status PyPI
    Android Status Download
    Raspberry Pi 0 and 1 Status Py3
    Raspberry Pi 2 and 3 Status Py3
    Libtensorflow MacOS CPU Status Temporarily Unavailable Nightly Binary Official GCS
    Libtensorflow Linux CPU Status Temporarily Unavailable Nightly Binary Official GCS
    Libtensorflow Linux GPU Status Temporarily Unavailable Nightly Binary Official GCS
    Libtensorflow Windows CPU Status Temporarily Unavailable Nightly Binary Official GCS
    Libtensorflow Windows GPU Status Temporarily Unavailable Nightly Binary Official GCS

    Community Supported Builds

    Build Type Status Artifacts
    Linux AMD ROCm GPU Nightly Build Status Nightly
    Linux AMD ROCm GPU Stable Release Build Status Release 1.15 / 2.x
    Linux s390x Nightly Build Status Nightly
    Linux s390x CPU Stable Release Build Status Release
    Linux ppc64le CPU Nightly Build Status Nightly
    Linux ppc64le CPU Stable Release Build Status Release 1.15 / 2.x
    Linux ppc64le GPU Nightly Build Status Nightly
    Linux ppc64le GPU Stable Release Build Status Release 1.15 / 2.x
    Linux aarch64 CPU Nightly (Linaro) Build Status Nightly
    Linux aarch64 CPU Stable Release (Linaro) Build Status Release 1.x & 2.x
    Linux aarch64 CPU Nightly (OpenLab)
    Python 3.6
    Build Status Nightly
    Linux aarch64 CPU Stable Release (OpenLab) Build Status Release 1.15 / 2.x
    Linux CPU with Intel oneAPI Deep Neural Network Library (oneDNN) Nightly Build Status Nightly
    Linux CPU with Intel oneAPI Deep Neural Network Library (oneDNN) Stable Release Build Status Release 1.15 / 2.x
    Red Hat? Enterprise Linux? 7.6 CPU & GPU
    Python 2.7, 3.6
    Build Status 1.13.1 PyPI

    Community Supported Containers

    Container Type Status Artifacts
    TensorFlow aarch64 Neoverse-N1 CPU Stable (Linaro)
    Debian
    Static Release 2.3

    Resources

    Learn more about the TensorFlow community and how to contribute.

    License

    Apache License 2.0

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