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# Copyright 2015 The TensorFlow Authors. 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.
# ==============================================================================
"""Contains Gradient functions for image ops."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
from tensorflow.python.framework import tensor_util
from tensorflow.python.ops import gen_image_ops
@ops.RegisterGradient("ResizeNearestNeighbor")
def _ResizeNearestNeighborGrad(op, grad):
"""The derivatives for nearest neighbor resizing.
Args:
op: The ResizeNearestNeighbor op.
grad: The tensor representing the gradient w.r.t. the output.
Returns:
The gradients w.r.t. the input and the output.
"""
# pylint: disable=protected-access
grads = gen_image_ops._resize_nearest_neighbor_grad(
grad,
op.inputs[0].get_shape()[1:3],
align_corners=op.get_attr("align_corners"))
# pylint: enable=protected-access
return [grads, None]
@ops.RegisterGradient("ResizeBilinear")
def _ResizeBilinearGrad(op, grad):
"""The derivatives for bilinear resizing.
Args:
op: The ResizeBilinear op.
grad: The tensor representing the gradient w.r.t. the output.
Returns:
The gradients w.r.t. the input.
"""
allowed_types = [dtypes.float32, dtypes.float64]
grad0 = None
if op.inputs[0].dtype in allowed_types:
# pylint: disable=protected-access
grad0 = gen_image_ops._resize_bilinear_grad(
grad,
op.inputs[0],
align_corners=op.get_attr("align_corners"))
# pylint: enable=protected-access
return [grad0, None]
@ops.RegisterShape("ResizeNearestNeighborGrad")
def _ResizeShape(op):
"""Shape function for the resize grad ops."""
input_shape = op.inputs[0].get_shape().with_rank(4)
size = tensor_util.constant_value(op.inputs[1])
if size is not None:
height = size[0]
width = size[1]
else:
height = None
width = None
return [
tensor_shape.TensorShape([input_shape[0], height, width, input_shape[3]])
]
@ops.RegisterShape("ResizeBilinearGrad")
def _ResizeBilinearGradShape(op):
"""Shape function for ResizeBilinearGrad."""
return [op.inputs[1].get_shape()]
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