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CONTRIBUTING.md
`comp:` etc. At this stage we check if the PR is valid and meets certain quality requirements. For example, we check if the CLA is signed, PR has sufficient description, if applicable unit tests are added, if it is a reasonable contribution (meaning it is not a single liner cosmetic PR). **2. Valid?** - If the PR passes all the quality checks then we go ahead and assign a reviewer.
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RELEASE.md
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 * Added 'UpdateEmbeddingCallback`
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configure.py
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