org.nd4j.linalg.api.ops.impl.transforms.custom.Trace 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.transforms.custom;
import lombok.NonNull;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.base.Preconditions;
import org.nd4j.linalg.api.buffer.DataType;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.factory.Nd4j;
import java.util.Collections;
import java.util.List;
/**
* Matrix trace operation
*
* @author Alex Black
*/
public class Trace extends DynamicCustomOp {
public Trace(SameDiff sd, SDVariable in){
super(null, sd, new SDVariable[]{in});
}
public Trace(@NonNull INDArray in){
super(wrapOrNull(in), null);
}
public Trace(){ }
@Override
public String opName(){
return "trace";
}
@Override
public List doDiff(List gradAtOutput){
SDVariable rows = f().reshape(f().sizeAt(arg(), -2), new long[]{1});
SDVariable cols = f().reshape(f().sizeAt(arg(), -1), new long[]{1});
SDVariable eye = sameDiff.math().eye(f().shape(gradAtOutput.get(0)), rows, cols);
//Reshape gradient from [x,y,z] to [x,y,z,1,1]
SDVariable reshapedGrad = f().expandDims(gradAtOutput.get(0), -1);
reshapedGrad = f().expandDims(reshapedGrad, -1);
return Collections.singletonList(reshapedGrad.mul(eye));
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 1, "Expected exactly 1 input datatype for %s, got %s", getClass(), dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
}