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.github/ISSUE_TEMPLATE/tflite-converter-issue.md
### 3. Failure after conversion If the conversion is successful, but the generated model is wrong, then state what is wrong: - Model produces wrong results and/or has lesser accuracy. - Model produces correct results, but it is slower than expected. ### 4. (optional) RNN conversion support If converting TF RNN to TFLite fused RNN ops, please prefix [RNN] in the title. ### 5. (optional) Any other info / logs
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CONTRIBUTING.md
#### General guidelines and philosophy for contribution * Include unit tests when you contribute new features, as they help to a) prove that your code works correctly, and b) guard against future breaking changes to lower the maintenance cost. * Bug fixes also generally require unit tests, because the presence of bugs usually indicates insufficient test coverage. * Keep API compatibility in mind when you change code in core TensorFlow,
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LICENSE
other entities that control, are controlled by, or are under common control with that entity. For the purposes of this definition, "control" means (i) the power, direct or indirect, to cause the direction or management of such entity, whether by contract or otherwise, or (ii) ownership of fifty percent (50%) or more of the
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RELEASE.md
* `tf.data` * `tf.data` now has an `autotune_options.initial_parallelism` option to control the initial parallelism setting used by autotune before the data pipeline has started running. The default is 16. A lower value reduces initial memory usage, while a higher value improves startup time. ## Keras * `keras.layers.experimental.DynamicEmbedding` * Added `DynamicEmbedding` Keras layer
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