blob: 219a503fd7f8f15a3ad96912e084178ad4b0c1dd (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
|
# Copyright 2015 Google Inc. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
"""Gradients for operators defined in data_flow_ops.py."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from six.moves import xrange # pylint: disable=redefined-builtin
from tensorflow.python.framework import ops
from tensorflow.python.framework import types
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import constant_op
from tensorflow.python.ops import data_flow_ops
from tensorflow.python.ops import gen_data_flow_ops
from tensorflow.python.ops import math_ops
@ops.RegisterGradient("DynamicStitch")
def _DynamicStitchGrads(op, grad):
"""Gradients for DynamicStitch."""
num_values = len(op.inputs) // 2
indices_grad = [None] * num_values
def AsInt32(x):
return (x if op.inputs[0].dtype == types.int32 else
math_ops.cast(x, types.int32))
inputs = [AsInt32(op.inputs[i]) for i in xrange(num_values)]
if isinstance(grad, ops.IndexedSlices):
output_shape = array_ops.shape(op.outputs[0])
output_rows = output_shape[0]
grad = math_ops.unsorted_segment_sum(grad.values, grad.indices, output_rows)
values_grad = [array_ops.gather(grad, inp) for inp in inputs]
return indices_grad + values_grad
ops.NoGradient("Queue")
ops.NoGradient("QueueEnqueue")
ops.NoGradient("QueueEnqueueMany")
ops.NoGradient("QueueDequeue")
ops.NoGradient("QueueDequeueMany")
ops.NoGradient("QueueClose")
ops.NoGradient("QueueSize")
|
