Add release notes for Intel MKL integration.
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be replaced by calling `embedding_lookup` or `layers.dense` as pre- or post-
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processing of the rnn. For RNN decoding, this functionality has been replaced
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with an alternative API in `tf.contrib.seq2seq`.
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* Intel MKL Integration (https://software.intel.com/en-us/articles/tensorflow-optimizations-on-modern-intel-architecture). Intel developed a number of
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optimized deep learning primitives: In addition to matrix multiplication and
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convolution, these building blocks include:
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Direct batched convolution
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Pooling: maximum, minimum, average
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Normalization: LRN, batch normalization
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Activation: rectified linear unit (ReLU)
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Data manipulation: multi-dimensional transposition (conversion), split,
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concat, sum and scale.
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## Bug Fixes and Other Changes
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* In python, `Operation.get_attr` on type attributes returns the Python DType
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