tensorflow::ops::FusedBatchNormGradV3
#include <nn_ops.h>
Gradient for batch normalization.
Summary
Note that the size of 4D Tensors are defined by either "NHWC" or "NCHW". The size of 1D Tensors matches the dimension C of the 4D Tensors.
Arguments:
- scope: A Scope object
- y_backprop: A 4D Tensor for the gradient with respect to y.
- x: A 4D Tensor for input data.
- scale: A 1D Tensor for scaling factor, to scale the normalized x.
- reserve_space_1: When is_training is True, a 1D Tensor for the computed batch mean to be reused in gradient computation. When is_training is False, a 1D Tensor for the population mean to be reused in both 1st and 2nd order gradient computation.
- reserve_space_2: When is_training is True, a 1D Tensor for the computed batch variance (inverted variance in the cuDNN case) to be reused in gradient computation. When is_training is False, a 1D Tensor for the population variance to be reused in both 1st and 2nd order gradient computation.
- reserve_space_3: When is_training is True, a 1D Tensor for some intermediate results to be reused in gradient computation. When is_training is False, a dummy empty Tensor will be created.
Optional attributes (see Attrs
):
- epsilon: A small float number added to the variance of x.
- data_format: The data format for y_backprop, x, x_backprop. Either "NHWC" (default) or "NCHW".
- is_training: A bool value to indicate the operation is for training (default) or inference.
Returns:
-
Output
x_backprop: A 4D Tensor for the gradient with respect to x. -
Output
scale_backprop: A 1D Tensor for the gradient with respect to scale. -
Output
offset_backprop: A 1D Tensor for the gradient with respect to offset. -
Output
reserve_space_4: Unused placeholder to match the mean input in FusedBatchNorm. -
Output
reserve_space_5: Unused placeholder to match the variance input in FusedBatchNorm.
Constructors and Destructors | |
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FusedBatchNormGradV3(const ::tensorflow::Scope & scope, ::tensorflow::Input y_backprop, ::tensorflow::Input x, ::tensorflow::Input scale, ::tensorflow::Input reserve_space_1, ::tensorflow::Input reserve_space_2, ::tensorflow::Input reserve_space_3) | |
FusedBatchNormGradV3(const ::tensorflow::Scope & scope, ::tensorflow::Input y_backprop, ::tensorflow::Input x, ::tensorflow::Input scale, ::tensorflow::Input reserve_space_1, ::tensorflow::Input reserve_space_2, ::tensorflow::Input reserve_space_3, const FusedBatchNormGradV3::Attrs & attrs) |
Public attributes | |
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offset_backprop | |
operation | |
reserve_space_4 | |
reserve_space_5 | |
scale_backprop | |
x_backprop |
Public static functions | |
---|---|
DataFormat(StringPiece x) | |
Epsilon(float x) | |
IsTraining(bool x) |
Structs | |
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tensorflow::ops::FusedBatchNormGradV3::Attrs | Optional attribute setters for FusedBatchNormGradV3. |
Public attributes
offset_backprop
::tensorflow::Output offset_backprop
operation
Operation operation
reserve_space_4
::tensorflow::Output reserve_space_4
reserve_space_5
::tensorflow::Output reserve_space_5
scale_backprop
::tensorflow::Output scale_backprop
x_backprop
::tensorflow::Output x_backprop
Public functions
FusedBatchNormGradV3
FusedBatchNormGradV3( const ::tensorflow::Scope & scope, ::tensorflow::Input y_backprop, ::tensorflow::Input x, ::tensorflow::Input scale, ::tensorflow::Input reserve_space_1, ::tensorflow::Input reserve_space_2, ::tensorflow::Input reserve_space_3 )
FusedBatchNormGradV3
FusedBatchNormGradV3( const ::tensorflow::Scope & scope, ::tensorflow::Input y_backprop, ::tensorflow::Input x, ::tensorflow::Input scale, ::tensorflow::Input reserve_space_1, ::tensorflow::Input reserve_space_2, ::tensorflow::Input reserve_space_3, const FusedBatchNormGradV3::Attrs & attrs )
Public static functions
DataFormat
Attrs DataFormat( StringPiece x )
Epsilon
Attrs Epsilon( float x )
IsTraining
Attrs IsTraining( bool x )
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 4.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/cc/class/tensorflow/ops/fused-batch-norm-grad-v3