rare occasion we may reject it.

**3. Review**

-   For a valid PR, reviewer (person familiar with the code/functionality)
    checks if the PR looks good or needs additional changes.
-   If all looks good, the reviewer will approve the PR.
-   If a change is needed, the contributor is requested to make the suggested
    change.
-   You make the change and submit it for the review again.

## Major Features And Improvements

*   [Eager execution](https://github.com/tensorflow/tensorflow/tree/r1.5/tensorflow/contrib/eager)
    preview version is now available.
*   [TensorFlow Lite](https://github.com/tensorflow/tensorflow/tree/r1.5/tensorflow/lite)
    dev preview is now available.
*   CUDA 9.0 and cuDNN 7 support.
*   Accelerated Linear Algebra (XLA):
    *   Add `complex64` support to XLA compiler.

};

/** For trusted parters like Intel, we want to auto-run tests
    This allows us to reduce the delay to external partners
    Add Labels - kokoro:force-run
    The PR is also assigned to specific teams to fast track review
    Additional reviewers can be added manually based on PR contents
  @param {!object}
    github enables querying for PR and also create issue using rest endpoint
    context has the commit message details in the payload

b'Hello, TensorFlow!'
```

For more examples, see the
[TensorFlow tutorials](https://www.tensorflow.org/tutorials/).

## Contribution guidelines

**If you want to contribute to TensorFlow, be sure to review the
[contribution guidelines](CONTRIBUTING.md). This project adheres to TensorFlow's
[code of conduct](CODE_OF_CONDUCT.md). By participating, you are expected to
uphold this code.**