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Update release notes
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RELEASE.md

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# TensorFlow Model Optimization next release TBD
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# TensorFlow Model Optimization 0.7.0
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TFMOT 0.7.0 adds updates for Quantization Aware Training (QAT)
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and Pruning API. Adds support for structured (MxN) pruning.
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QAT now also has support for layers with swish activations and ability
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to disable per-axis quantization in the default8_bit scheme.
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Adds support for combining pruning, QAT and weight clustering.
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Keras Quantization API:
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Tested against TensorFlow 2.6.0, 2.5.1 and nightly with Python 3.
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* Added QuantizeWrapperV2 class which preserves order of weights is the default for quantize_apply.
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* Added a flag to disable per-axis quantizers in default8_bit scheme.
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* Added swish as supported activation.
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Keras pruning API:
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Tested against TensorFlow 2.6.0, 2.5.1 and nightly with Python 3.
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* Added structural pruning with MxN sparsity.
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Keras clustering API:

tensorflow_model_optimization/python/core/version.py

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# We follow Semantic Versioning (https://semver.org/)
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_MAJOR_VERSION = '0'
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_MINOR_VERSION = '6'
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_MINOR_VERSION = '7'
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_PATCH_VERSION = '0'
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# When building releases, we can update this value on the release branch to

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