org.tensorflow.op.nn.MaxPool3dGradGrad Maven / Gradle / Ivy
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/* Copyright 2018 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.
=======================================================================*/
// This class has been generated, DO NOT EDIT!
package org.tensorflow.op.nn;
import java.util.List;
import org.tensorflow.Operand;
import org.tensorflow.Operation;
import org.tensorflow.OperationBuilder;
import org.tensorflow.Output;
import org.tensorflow.op.PrimitiveOp;
import org.tensorflow.op.Scope;
import org.tensorflow.op.annotation.Operator;
/**
* Computes second-order gradients of the maxpooling function.
*
* @param data type for {@code output()} output
*/
@Operator(group = "nn")
public final class MaxPool3dGradGrad extends PrimitiveOp implements Operand {
/**
* Optional attributes for {@link org.tensorflow.op.nn.MaxPool3dGradGrad}
*/
public static class Options {
/**
* @param dataFormat The data format of the input and output data. With the
* default format "NDHWC", the data is stored in the order of:
* [batch, in_depth, in_height, in_width, in_channels].
* Alternatively, the format could be "NCDHW", the data storage order is:
* [batch, in_channels, in_depth, in_height, in_width].
*/
public Options dataFormat(String dataFormat) {
this.dataFormat = dataFormat;
return this;
}
private String dataFormat;
private Options() {
}
}
/**
* Factory method to create a class wrapping a new MaxPool3dGradGrad operation.
*
* @param scope current scope
* @param origInput The original input tensor.
* @param origOutput The original output tensor.
* @param grad Output backprop of shape `[batch, depth, rows, cols, channels]`.
* @param ksize 1-D tensor of length 5. The size of the window for each dimension of
* the input tensor. Must have `ksize[0] = ksize[4] = 1`.
* @param strides 1-D tensor of length 5. The stride of the sliding window for each
* dimension of `input`. Must have `strides[0] = strides[4] = 1`.
* @param padding The type of padding algorithm to use.
* @param options carries optional attributes values
* @return a new instance of MaxPool3dGradGrad
*/
public static MaxPool3dGradGrad create(Scope scope, Operand origInput, Operand origOutput, Operand grad, List ksize, List strides, String padding, Options... options) {
OperationBuilder opBuilder = scope.env().opBuilder("MaxPool3DGradGrad", scope.makeOpName("MaxPool3dGradGrad"));
opBuilder.addInput(origInput.asOutput());
opBuilder.addInput(origOutput.asOutput());
opBuilder.addInput(grad.asOutput());
opBuilder = scope.applyControlDependencies(opBuilder);
long[] ksizeArray = new long[ksize.size()];
for (int i = 0; i < ksizeArray.length; ++i) {
ksizeArray[i] = ksize.get(i);
}
opBuilder.setAttr("ksize", ksizeArray);
long[] stridesArray = new long[strides.size()];
for (int i = 0; i < stridesArray.length; ++i) {
stridesArray[i] = strides.get(i);
}
opBuilder.setAttr("strides", stridesArray);
opBuilder.setAttr("padding", padding);
if (options != null) {
for (Options opts : options) {
if (opts.dataFormat != null) {
opBuilder.setAttr("data_format", opts.dataFormat);
}
}
}
return new MaxPool3dGradGrad(opBuilder.build());
}
/**
* @param dataFormat The data format of the input and output data. With the
* default format "NDHWC", the data is stored in the order of:
* [batch, in_depth, in_height, in_width, in_channels].
* Alternatively, the format could be "NCDHW", the data storage order is:
* [batch, in_channels, in_depth, in_height, in_width].
*/
public static Options dataFormat(String dataFormat) {
return new Options().dataFormat(dataFormat);
}
/**
* Gradients of gradients w.r.t. the input to `max_pool`.
*/
public Output output() {
return output;
}
@Override
public Output asOutput() {
return output;
}
private Output output;
private MaxPool3dGradGrad(Operation operation) {
super(operation);
int outputIdx = 0;
output = operation.output(outputIdx++);
}
}