org.tensorflow.op.nn.AvgPool Maven / Gradle / Ivy
/* 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;
/**
* Performs average pooling on the input.
*
* Each entry in `output` is the mean of the corresponding size `ksize`
* window in `value`.
*
* @param data type for {@code output()} output
*/
@Operator(group = "nn")
public final class AvgPool extends PrimitiveOp implements Operand {
/**
* Optional attributes for {@link org.tensorflow.op.nn.AvgPool}
*/
public static class Options {
/**
* @param dataFormat Specify the data format of the input and output data. With the
* default format "NHWC", the data is stored in the order of:
* [batch, in_height, in_width, in_channels].
* Alternatively, the format could be "NCHW", the data storage order of:
* [batch, in_channels, 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 AvgPool operation.
*
* @param scope current scope
* @param value 4-D with shape `[batch, height, width, channels]`.
* @param ksize The size of the sliding window for each dimension of `value`.
* @param strides The stride of the sliding window for each dimension of `value`.
* @param padding The type of padding algorithm to use.
* @param options carries optional attributes values
* @return a new instance of AvgPool
*/
public static AvgPool create(Scope scope, Operand value, List ksize, List strides, String padding, Options... options) {
OperationBuilder opBuilder = scope.env().opBuilder("AvgPool", scope.makeOpName("AvgPool"));
opBuilder.addInput(value.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 AvgPool(opBuilder.build());
}
/**
* @param dataFormat Specify the data format of the input and output data. With the
* default format "NHWC", the data is stored in the order of:
* [batch, in_height, in_width, in_channels].
* Alternatively, the format could be "NCHW", the data storage order of:
* [batch, in_channels, in_height, in_width].
*/
public static Options dataFormat(String dataFormat) {
return new Options().dataFormat(dataFormat);
}
/**
* The average pooled output tensor.
*/
public Output output() {
return output;
}
@Override
public Output asOutput() {
return output;
}
private Output output;
private AvgPool(Operation operation) {
super(operation);
int outputIdx = 0;
output = operation.output(outputIdx++);
}
}