org.nd4j.linalg.api.ops.impl.broadcast.BiasAddGrad Maven / Gradle / Ivy
/*******************************************************************************
* 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.broadcast;
import lombok.NonNull;
import org.nd4j.autodiff.functions.DifferentialFunction;
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.BaseBroadcastOp;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import java.util.Arrays;
import java.util.Collections;
import java.util.List;
public class BiasAddGrad extends DynamicCustomOp {
protected boolean nchw = true;
public BiasAddGrad(SameDiff sameDiff, SDVariable input, SDVariable bias, SDVariable gradient, boolean nchw) {
super(null, sameDiff, new SDVariable[]{input, bias, gradient});
this.nchw = nchw;
addBArgument(nchw);
}
public BiasAddGrad(@NonNull INDArray input, @NonNull INDArray bias, @NonNull INDArray gradient, INDArray output){
super(new INDArray[]{input, bias, gradient}, wrapOrNull(output));
}
public BiasAddGrad() {}
@Override
public int opNum() {
return 0;
}
@Override
public String opName() {
return "biasadd_bp";
}
@Override
public List doDiff(List f1) {
throw new UnsupportedOperationException("Differentiation not supported for op " + getClass().getSimpleName());
}
@Override
public String onnxName() {
return "BiasAddGrad";
}
@Override
public List calculateOutputDataTypes(List inputDataTypes){
Preconditions.checkState(inputDataTypes != null && inputDataTypes.size() == 3, "Expected 3 input data types for %s, got %s", getClass(), inputDataTypes);
return Arrays.asList(inputDataTypes.get(0), inputDataTypes.get(1));
}
}