Clean up Embedding op side effect handling

- now we have two Embedding side effects, read and write
- now dependencies between EnqueueTPUEmbedding ops with same device ordinal are
  properly modeled
- we now finally don't have any Embedding-specific code left in side effect
  analysis
- introduced new `TF_MustExecute` trait that avoids pruning of an op; this is
  useful for side-effecting ops that don't produce any output and don't have
  dependencies to/from other ops
- for ops that just used `TF_TPUEmbeddingSideEffect` to avoid pruning, use new
  `TF_MustExecute` trait instead
- in contrast to the old `TF_TPUEmbeddingSideEffect`, `TF_MustExecute` avoids
  pruning independent of reachability (see new graph pruning test)

PiperOrigin-RevId: 413175982
Change-Id: I7b65c7a0e8a17b8a1683a0e01d1fd0614f7ac95a
12 files changed
tree: 4de94bd588a5177e6148b46c32be589fd235d970
  1. .github/
  2. tensorflow/
  3. third_party/
  4. tools/
  5. .bazelrc
  6. .bazelversion
  7. .gitignore
  8. .zenodo.json
  9. arm_compiler.BUILD
  10. AUTHORS
  11. BUILD
  12. CITATION.cff
  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

Python PyPI DOI

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

You can find more community-supported platforms and configurations in the TensorFlow SIG Build community builds table.

Official Builds

Build TypeStatusArtifacts
Linux CPUStatusPyPI
Linux GPUStatusPyPI
Linux XLAStatusTBA
macOSStatusPyPI
Windows CPUStatusPyPI
Windows GPUStatusPyPI
AndroidStatusDownload
Raspberry Pi 0 and 1StatusPy3
Raspberry Pi 2 and 3StatusPy3
Libtensorflow MacOS CPUStatus Temporarily UnavailableNightly Binary Official GCS
Libtensorflow Linux CPUStatus Temporarily UnavailableNightly Binary Official GCS
Libtensorflow Linux GPUStatus Temporarily UnavailableNightly Binary Official GCS
Libtensorflow Windows CPUStatus Temporarily UnavailableNightly Binary Official GCS
Libtensorflow Windows GPUStatus Temporarily UnavailableNightly Binary Official GCS

Resources

Learn more about the TensorFlow community and how to contribute.

License

Apache License 2.0