org.nd4j.linalg.api.ops.impl.transforms.custom.IsNumericTensor 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
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* * WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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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.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import java.util.Collections;
import java.util.List;
public class IsNumericTensor extends DynamicCustomOp {
public IsNumericTensor() {}
public IsNumericTensor( SameDiff sameDiff, SDVariable args) {
this(sameDiff, new SDVariable[]{args}, false);
}
public IsNumericTensor( SameDiff sameDiff, SDVariable[] args, boolean inPlace) {
super(null, sameDiff, args, inPlace);
}
public IsNumericTensor( INDArray[] inputs, INDArray[] outputs) {
super(null, inputs, outputs);
}
public IsNumericTensor(INDArray inputs) {
super( new INDArray[] {inputs}, null);
}
@Override
public String opName() {
return "is_numeric_tensor";
}
@Override
public List doDiff(List f1) {
throw new UnsupportedOperationException("");
}
@Override
public List calculateOutputDataTypes(List dataTypes){
Preconditions.checkState(dataTypes != null && dataTypes.size() == 1, "Expected exactly 1 input datatypes for %s, got %s", getClass(), dataTypes);
return Collections.singletonList(DataType.BOOL);
}
}