org.nd4j.linalg.api.ops.impl.transforms.custom.MatrixDiagPart 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.
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* * 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
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* * SPDX-License-Identifier: Apache-2.0
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package org.nd4j.linalg.api.ops.impl.transforms.custom;
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.ops.DynamicCustomOp;
import java.util.Collections;
import java.util.List;
public class MatrixDiagPart extends DynamicCustomOp {
public MatrixDiagPart() {
//
}
public MatrixDiagPart(SameDiff sameDiff, SDVariable in, boolean inPlace) {
super(null, sameDiff, new SDVariable[]{in}, inPlace);
}
@Override
public String opName() {
return "matrix_diag_part";
}
@Override
public String[] tensorflowNames() {
return new String[]{"MatrixDiagPart"};
}
@Override
public List doDiff(List i_v) {
throw new UnsupportedOperationException("Not implemented yet");
}
@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));
}
}