Updated the clarity of specifc comments 11212018
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@ -1,4 +1,4 @@
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# Copyright 2015 The TensorFlow Authors. All Rights Reserved.
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# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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@ -14,7 +14,7 @@
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# =============================================================================
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"""Python front-end supports for functions.
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NOTE: functions are currently experimental and subject to change!
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NOTE: At this time, functions are experimental and subject to change!. Proceed with caution.
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"""
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from __future__ import absolute_import
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@ -59,8 +59,8 @@ class Defun(object):
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def foo(x, y):
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...
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When you call the decorated function it will add `call` ops to the
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default graph and adds the definition of the function into the
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When you call the decorated function, it adds the `call` ops to the
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default graph. In addition, it adds the definition of the function into the
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default graph. Because the addition of the function into the graph
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is deferred, the decorator can be used anywhere in the program.
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@ -300,7 +300,7 @@ class _DefinedFunction(object):
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@property
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def grad_func_name(self):
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"""Its gradient function's name."""
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"""Returns the name of the gradient function."""
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return self._grad_func.name if self._grad_func else None
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@property
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