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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.random.compat;

import org.nd4j.autodiff.samediff.SDVariable;
import org.nd4j.autodiff.samediff.SameDiff;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.api.ops.DynamicCustomOp;
import org.nd4j.linalg.factory.Nd4j;
import org.nd4j.linalg.util.ArrayUtil;

/**
 * This op is a wrapper for RandomNormal Op
 * @author [email protected]
 */
public class RandomStandardNormal extends DynamicCustomOp {

    public RandomStandardNormal() {
        // values are just hardcoded for this op
        addTArgument(0.0, 1.0);
    }

    public RandomStandardNormal(SameDiff sameDiff, SDVariable[] args) {
        super(null, sameDiff, args);

        // values are just hardcoded for this op
        addTArgument(0.0, 1.0);
    }

    public RandomStandardNormal(INDArray shape) {
        super(null, new INDArray[]{shape},new INDArray[0]);

        // values are just hardcoded for this op
        addTArgument(0.0, 1.0);
    }

    public RandomStandardNormal(INDArray shape, INDArray output) {
        super(null, new INDArray[]{shape},new INDArray[]{output});

        // values are just hardcoded for this op
        addTArgument(0.0, 1.0);
    }

    public RandomStandardNormal(long shape[]) {
        this(Nd4j.create(ArrayUtil.toDouble(shape)), Nd4j.create(shape));
    }

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

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

    @Override
    public Object[] getExtraArgs() {
        // FIXME: why the hell we need this?
        return new Object[] {new Double(0.0), new Double(1.0)};
    }
}




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