/*
 *  ******************************************************************************
 *  *
 *  *
 *  * 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.reduce;

import lombok.NoArgsConstructor;
import lombok.NonNull;
import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.common.base.Preconditions;
import org.nd4j.imports.NoOpNameFoundException;
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;

@NoArgsConstructor
public class ZeroFraction extends DynamicCustomOp {

    public ZeroFraction(SameDiff sameDiff, SDVariable input) {
        super(null, sameDiff, new SDVariable[] {input}, false);
    }

    public ZeroFraction(@NonNull INDArray input){
        super(new INDArray[]{input}, null);
    }

    @Override
    public String opName() {
        return "zero_fraction";
    }


    @Override
    public String onnxName() {
        throw new NoOpNameFoundException("No onnx name found for shape " + opName());
    }

    @Override
    public String tensorflowName() {
        throw new NoOpNameFoundException("No tf name found for shape " + opName());
    }

    @Override
    public List<SDVariable> doDiff(List<SDVariable> grad){
        return Collections.singletonList(sameDiff.zerosLike(arg()));
    }

    @Override
    public List<DataType> calculateOutputDataTypes(List<DataType> dataTypes){
        Preconditions.checkState(dataTypes != null && dataTypes.size() == 1, "Expected 1 datatype for %s, got %s", getClass(), dataTypes);
        return Collections.singletonList(DataType.FLOAT);
    }
}
