Python tensorflow.python.ops.gen_image_ops._resize_nearest_neighbor_grad() Examples
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Example #1
| Source File: image_grad.py From lambda-packs with MIT License | 6 votes |
|
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.
"""
image = op.inputs[0]
if image.get_shape()[1:3].is_fully_defined():
image_shape = image.get_shape()[1:3]
else:
image_shape = array_ops.shape(image)[1:3]
# pylint: disable=protected-access
grads = gen_image_ops._resize_nearest_neighbor_grad(
grad,
image_shape,
align_corners=op.get_attr("align_corners"))
# pylint: enable=protected-access
return [grads, None]
Example #2
| Source File: image_grad.py From auto-alt-text-lambda-api with MIT License | 6 votes |
|
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.
"""
image = op.inputs[0]
if image.get_shape()[1:3].is_fully_defined():
image_shape = image.get_shape()[1:3]
else:
image_shape = array_ops.shape(image)[1:3]
# pylint: disable=protected-access
grads = gen_image_ops._resize_nearest_neighbor_grad(
grad,
image_shape,
align_corners=op.get_attr("align_corners"))
# pylint: enable=protected-access
return [grads, None]
Example #3
| Source File: image_grad.py From deep_image_model with Apache License 2.0 | 6 votes |
|
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.
"""
image = op.inputs[0]
if image.get_shape()[1:3].is_fully_defined():
image_shape = image.get_shape()[1:3]
else:
image_shape = array_ops.shape(image)[1:3]
# pylint: disable=protected-access
grads = gen_image_ops._resize_nearest_neighbor_grad(
grad,
image_shape,
align_corners=op.get_attr("align_corners"))
# pylint: enable=protected-access
return [grads, None]
Example #4
| Source File: image_grad.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 6 votes |
|
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.
"""
image = op.inputs[0]
if image.get_shape()[1:3].is_fully_defined():
image_shape = image.get_shape()[1:3]
else:
image_shape = array_ops.shape(image)[1:3]
# pylint: disable=protected-access
grads = gen_image_ops._resize_nearest_neighbor_grad(
grad,
image_shape,
align_corners=op.get_attr("align_corners"))
# pylint: enable=protected-access
return [grads, None]
Example #5
| Source File: image_grad.py From keras-lambda with MIT License | 6 votes |
|
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.
"""
image = op.inputs[0]
if image.get_shape()[1:3].is_fully_defined():
image_shape = image.get_shape()[1:3]
else:
image_shape = array_ops.shape(image)[1:3]
# pylint: disable=protected-access
grads = gen_image_ops._resize_nearest_neighbor_grad(
grad,
image_shape,
align_corners=op.get_attr("align_corners"))
# pylint: enable=protected-access
return [grads, None]
