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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.
 *  *
 *  * 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.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);
    }
}