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android / platform / external / tensorflow / b26e1efeced
commitb26e1efeceda14f2f0a72f607ab857c3a5be7978[log] [tgz]
authorEugene Brevdo <ebrevdo@google.com>Mon Jan 20 15:55:51 2020 -0800
committerTensorFlower Gardener <gardener@tensorflow.org>Mon Jan 20 15:58:44 2020 -0800
tree8af6324243076fdb5664a2d0786c04b0cf80e10e
parenta901c880618ca45b378afe87fefe6d50c5aec2df [diff]
[TF] Fixes and new features to saved_model_cli aot_compile_cpu, adds e2e test.

* Can now specify which variables can be fed/fetched.
* Bugfix when signature name contains slashes or starts with integers.
* Prune input config entries from tf2xla config when graph freeze removes
  unused input feed.
* Fixed a bug where third_party/tensorflow/ isn't properly renamed to tensorflow/
  in opensource HOST build (identified during the new genrule test).
  Solution: bring back the hardcoded #include in codegen.cc; it's always correct.

NOTE: The bugfix to the #include line in the compiler/ codebase is a partial rollback
of the initial tfcompile + saved_model_cli CL which moved from the hard-coded
include path to a parameterized value.  It turns out we don't need the complexity
of this approach and it's incorrect in the host opensource build.

TESTED:

Includes a bonafide genrule test which runs saved_model_cli to generate the
header and object files, and includes them in a c++ unit test and ensures
that they compile and the resulting object runs correctly.

PiperOrigin-RevId: 290655683
Change-Id: I4cfa2c595ebe56f8bdd47853f82371d97b92b081
14 files changed
tree: 8af6324243076fdb5664a2d0786c04b0cf80e10e
  1. .github/
  2. tensorflow/
  3. third_party/
  4. tools/
  5. .bazelrc
  6. .bazelversion
  7. .gitignore
  8. ACKNOWLEDGMENTS
  9. ADOPTERS.md
  10. arm_compiler.BUILD
  11. AUTHORS
  12. BUILD
  13. CODE_OF_CONDUCT.md
  14. CODEOWNERS
  15. configure
  16. configure.cmd
  17. configure.py
  18. CONTRIBUTING.md
  19. ISSUE_TEMPLATE.md
  20. ISSUES.md
  21. LICENSE
  22. models.BUILD
  23. README.md
  24. RELEASE.md
  25. SECURITY.md
  26. WORKSPACE
README.md
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()
'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:

CII Best Practices Contributor Covenant

Continuous build status

Official Builds

Build TypeStatusArtifacts
Linux CPUStatusPyPI
Linux GPUStatusPyPI
Linux XLAStatusTBA
macOSStatusPyPI
Windows CPUStatusPyPI
Windows GPUStatusPyPI
AndroidStatusDownload
Raspberry Pi 0 and 1Status StatusPy2 Py3
Raspberry Pi 2 and 3Status StatusPy2 Py3

Community Supported Builds

Build TypeStatusArtifacts
Linux AMD ROCm GPU NightlyBuild StatusNightly
Linux AMD ROCm GPU Stable ReleaseBuild StatusRelease 1.15 / 2.x
Linux s390x NightlyBuild StatusNightly
Linux s390x CPU Stable ReleaseBuild StatusRelease
Linux ppc64le CPU NightlyBuild StatusNightly
Linux ppc64le CPU Stable ReleaseBuild StatusRelease 1.15 / 2.x
Linux ppc64le GPU NightlyBuild StatusNightly
Linux ppc64le GPU Stable ReleaseBuild StatusRelease 1.15 / 2.x
Linux CPU with Intel® MKL-DNN NightlyBuild StatusNightly
Linux CPU with Intel® MKL-DNN Stable ReleaseBuild StatusRelease 1.15 / 2.x
Red Hat® Enterprise Linux® 7.6 CPU & GPU
Python 2.7, 3.6		Build Status1.13.1 PyPI

Resources

Learn more about the TensorFlow community and how to contribute.

License

Apache License 2.0