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RELEASE.md
* `tf.lite` * Add experimental supports conversion of models that may be larger than 2GB before buffer deduplication ### Bug Fixes and Other Changes * `tf.py_function` and `tf.numpy_function` can now be used as function decorators for clearer code: ``` @tf.py_function(Tout=tf.float32) def my_fun(x): print("This always executes eagerly.") return x+1
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