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/*******************************************************************************
 * 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;

import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;

import java.util.Arrays;
import java.util.Collections;
import java.util.List;
import java.util.UUID;

/**
 * Identity function
 *
 * @author Adam Gibson
 */
public class Identity extends BaseDynamicTransformOp {

    public Identity(SameDiff sd, SDVariable input){
        super(sd, new SDVariable[]{input}, false);
    }

    public Identity(){ }

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

    @Override
    public String onnxName() {
        return "Constant";
    }

    @Override
    public String tensorflowName() {
        return "Identity";
    }

    @Override
    public String[] tensorflowNames() {
        return new String[]{"Identity", "NoOp"};
    }

    @Override
    public List doDiff(List i_v) {
        //TODO can we skip the identity here?
        return Collections.singletonList(sameDiff.identity(i_v.get(0)));
    }

}