org.nd4j.linalg.api.ops.impl.layers.convolution.DeConv2DDerivative Maven / Gradle / Ivy
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* Copyright (c) 2015-2018 Skymind, Inc.
*
* This program and the accompanying materials are made available under the
* terms of the Apache License, Version 2.0 which is available at
* https://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.
*
* SPDX-License-Identifier: Apache-2.0
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package org.nd4j.linalg.api.ops.impl.layers.convolution;
import lombok.Builder;
import lombok.extern.slf4j.Slf4j;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.base.Preconditions;
import org.nd4j.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.impl.layers.convolution.config.DeConv2DConfig;
import java.util.ArrayList;
import java.util.Collections;
import java.util.List;
/**
* DeConv2DDerivative operation
*/
@Slf4j
public class DeConv2DDerivative extends DeConv2D {
public DeConv2DDerivative() {}
@Builder(builderMethodName = "derivativeBuilder")
public DeConv2DDerivative(SameDiff sameDiff, SDVariable[] inputs, DeConv2DConfig config) {
super(sameDiff, inputs, config);
}
@Override
public String opName() {
return "deconv2d_bp";
}
@Override
public String onnxName() {
throw new NoOpNameFoundException("No op name found for backwards.");
}
@Override
public String tensorflowName() {
throw new NoOpNameFoundException("No op name found for backwards");
}
@Override
public List doDiff(List f1) {
throw new UnsupportedOperationException("Unable to take derivative of derivative.");
}
@Override
public int getNumOutputs(){
//Inputs: in, weights, optional bias, gradOut 3 req, 1 optional
//Outputs: gradAtInput, gradW, optional gradB 2 req, 1 optional
SDVariable[] args = args();
return args.length - 1;
}
@Override
public List calculateOutputDataTypes(List inputDataTypes){
int n = args().length; //Original inputs + gradient at
Preconditions.checkState(inputDataTypes != null && inputDataTypes.size() == n, "Expected %s input data types for %s, got %s", n, getClass(), inputDataTypes);
List out = new ArrayList<>(n-1);
for( int i=0; i