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CONTRIBUTING.md
automatically on GitHub. If you want to contribute, start working through the TensorFlow codebase, navigate to the [GitHub "issues" tab](https://github.com/tensorflow/tensorflow/issues) and start looking through interesting issues. If you are not sure of where to start, then start by trying one of the smaller/easier issues here i.e.
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RELEASE.md
states. Specifically, it no longer ever drops the `c` (memory) state of an `LSTMStateTuple`. The new behavior leads to proper dropout behavior for LSTMs and stacked LSTMs. This bug fix follows recommendations from published literature, but is a behavioral change. State dropout behavior may be customized via the new `dropout_state_filter_visitor` argument.
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LICENSE
for any such Derivative Works as a whole, provided Your use, reproduction, and distribution of the Work otherwise complies with the conditions stated in this License. 5. Submission of Contributions. Unless You explicitly state otherwise, any Contribution intentionally submitted for inclusion in the Work by You to the Licensor shall be under the terms and conditions of
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SECURITY.md
executed. The security impact of skipping those checks should be low, since the attack scenario would require a malicious user to be able to control the model which as stated above is already equivalent to code execution. In any case, the recommendation is not to serve models using Eager mode since it also has performance limitations. ## Multi-Tenant environments
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