This directory is dedicated to tests that require a built TensorFlow wheel
file for testing, such as:

* Ensuring the entire API is importable
* Testing downstream projects against the wheel

Ensure you have Bazel installed and accessible from your command line.

These tests use hermetic Python. They also require a built TensorFlow wheel file
and a requirements_lock file. The requirements_lock file is generated by the

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Follow either of the two links above to access the appropriate CLA and instructions for how to sign and return it. Once we receive it, we'll be able to accept your pull requests.

#
#   Note: if you interrupt a bazel command on docker (ctrl-c), you
#   will need to run `docker exec tf pkill bazel` to quit bazel.
#
#   Note: new files created from the container are owned by "root".
#   You can run e.g. `docker exec tf chown -R $(id -u):$(id -g) build_output`
#   to transfer ownership to your user.
#
# Docker is enabled by default on Linux. You may disable it if you prefer:

```
(You can paste links or attach files by dragging & dropping them below)
- Provide links to your updated versions of the above two colab notebooks.
- Provide links to your TensorFlow model and (optionally) TensorFlow Lite Model.
```

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TensorFlow process effectively executes arbitrary code.

The risk of loading untrusted checkpoints depends on the code or graph that you
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variables from your model are also going to be untrusted. That means that if
your code interacts with the filesystem, network, etc. and uses checkpointed

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## Our Standards

Examples of behavior that contributes to creating a positive environment include:

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