org.nd4j.linalg.api.ops.impl.layers.convolution.Conv2DDerivative 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
******************************************************************************/
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.imports.NoOpNameFoundException;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.impl.layers.convolution.config.Conv2DConfig;
import java.util.List;
/**
* Conv2DDerivative operation
*/
@Slf4j
public class Conv2DDerivative extends Conv2D {
@Builder(builderMethodName = "derivativeBuilder")
public Conv2DDerivative(SameDiff sameDiff, SDVariable[] inputFunctions, INDArray[] inputArrays, INDArray[] outputs, Conv2DConfig config) {
super(sameDiff, inputFunctions, inputArrays, outputs, config);
}
public Conv2DDerivative() {}
@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 String[] tensorflowNames() {
throw new NoOpNameFoundException("No op name found for backwards");
}
@Override
public String opName() {
return "conv2d_bp";
}
@Override
public List doDiff(List f1) {
throw new UnsupportedOperationException("Unable to take derivative of derivative.");
}
@Override
public int getNumOutputs(){
if(args().length == 4){
return 3; //Includes bias
} else {
return 2; //No bias - only input + weight grads
}
}
}