org.nd4j.linalg.api.ops.impl.transforms.custom.MatrixInverse 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.
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* SPDX-License-Identifier: Apache-2.0
******************************************************************************/
package org.nd4j.linalg.api.ops.impl.transforms.custom;
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.ops.DynamicCustomOp;
import java.util.Collections;
import java.util.List;
/**
* Matrix Inverse Function
*
* @author Alex Black
*/
public class MatrixInverse extends DynamicCustomOp {
public MatrixInverse() {
//
}
public MatrixInverse(SameDiff sameDiff, SDVariable in, boolean inPlace) {
super(null, sameDiff, new SDVariable[]{in}, inPlace);
}
@Override
public String opName() {
return "matrix_inverse";
}
@Override
public String[] tensorflowNames() {
return new String[]{"MatrixInverse", "BatchMatrixInverse"};
}
@Override
public List doDiff(List i_v) {
//Derivative of matrix determinant
//From: Matrix Cookbook - Petersen & Pedersen
//if z = inverse(X)
//dz/dx = - z * dX/dx * z
//note that dX/dx is just identity matrix
//TODO non-matrix case
SDVariable dOutdIn = outputVariable().mmul(outputVariable()).neg();
return Collections.singletonList(i_v.get(0).mul(dOutdIn));
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 1, "Expected exactly 1 input datatype for %s, got %s", getClass(), dataTypes);
Preconditions.checkState(dataTypes.get(0).isFPType(), "Input datatype must be a floating point type, got %s", dataTypes.get(0));
return Collections.singletonList(dataTypes.get(0));
}
}