org.nd4j.linalg.api.ops.custom.TriangularSolve Maven / Gradle / Ivy
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* *
* * 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.
* *
* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
* * 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
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package org.nd4j.linalg.api.ops.custom;
import lombok.NoArgsConstructor;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.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.tensorflow.framework.AttrValue;
import org.tensorflow.framework.GraphDef;
import org.tensorflow.framework.NodeDef;
import java.util.Collections;
import java.util.List;
import java.util.Map;
@NoArgsConstructor
public class TriangularSolve extends DynamicCustomOp {
public TriangularSolve(INDArray matrix, INDArray rhs, boolean lower, boolean adjoint) {
addInputArgument(matrix, rhs);
addBArgument(lower, adjoint);
}
public TriangularSolve(SameDiff sameDiff, SDVariable matrix, SDVariable rhs,
SDVariable lower, SDVariable adjoint) {
super(sameDiff, new SDVariable[] {matrix, rhs, lower, adjoint});
}
public TriangularSolve(SameDiff sameDiff, SDVariable matrix, SDVariable rhs,
boolean lower, boolean adjoint) {
super(sameDiff, new SDVariable[] {matrix, rhs});
addBArgument(lower, adjoint);
}
@Override
public void initFromTensorFlow(NodeDef nodeDef, SameDiff initWith, Map attributesForNode, GraphDef graph) {
if(attributesForNode.containsKey("lower")){
addBArgument(attributesForNode.get("lower").getB());
}
if(attributesForNode.containsKey("adjoint")){
addBArgument(attributesForNode.get("adjoint").getB());
}
}
@Override
public String opName() {
return "triangular_solve";
}
@Override
public String tensorflowName() {
return "MatrixTriangularSolve";
}
@Override
public List calculateOutputDataTypes(List dataTypes) {
int n = args().length;
Preconditions.checkState(dataTypes != null && dataTypes.size() == n, "Expected %s input data types for %s, got %s", n, getClass(), dataTypes);
return Collections.singletonList(dataTypes.get(0));
}
}