org.nd4j.linalg.api.ops.impl.transforms.custom.IsNumericTensor 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 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 java.util.Arrays;
import java.util.Collections;
import java.util.List;
/**
* This op takes 1 n-dimensional array as input, and returns true if input is a numeric array.
*/
public class IsNumericTensor extends DynamicCustomOp {
public IsNumericTensor() {}
public IsNumericTensor( SameDiff sameDiff, SDVariable[] args, boolean inPlace) {
super(null, sameDiff, args, inPlace);
}
public IsNumericTensor( INDArray[] inputs, INDArray[] outputs) {
super(null, inputs, outputs);
}
@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);
}
}