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1# Copyright 2017 The TensorFlow Authors. All Rights Reserved. 

2# 

3# Licensed under the Apache License, Version 2.0 (the "License"); 

4# you may not use this file except in compliance with the License. 

5# You may obtain a copy of the License at 

6# 

7# http://www.apache.org/licenses/LICENSE-2.0 

8# 

9# Unless required by applicable law or agreed to in writing, software 

10# distributed under the License is distributed on an "AS IS" BASIS, 

11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 

12# See the License for the specific language governing permissions and 

13# limitations under the License. 

14# ============================================================================== 

15 

16"""Utilities for calculating gradients.""" 

17import enum 

18 

19from tensorflow.python.util.tf_export import tf_export 

20 

21 

22@tf_export("UnconnectedGradients") 

23class UnconnectedGradients(enum.Enum): 

24 """Controls how gradient computation behaves when y does not depend on x. 

25 

26 The gradient of y with respect to x can be zero in two different ways: there 

27 could be no differentiable path in the graph connecting x to y (and so we can 

28 statically prove that the gradient is zero) or it could be that runtime values 

29 of tensors in a particular execution lead to a gradient of zero (say, if a 

30 relu unit happens to not be activated). To allow you to distinguish between 

31 these two cases you can choose what value gets returned for the gradient when 

32 there is no path in the graph from x to y: 

33 

34 * `NONE`: Indicates that [None] will be returned if there is no path from x 

35 to y 

36 * `ZERO`: Indicates that a zero tensor will be returned in the shape of x. 

37 """ 

38 NONE = "none" 

39 ZERO = "zero"