/*
 *  ******************************************************************************
 *  *
 *  *
 *  * 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.deeplearning4j.nn.adapters;

import lombok.extern.slf4j.Slf4j;
import lombok.val;
import org.nd4j.adapters.OutputAdapter;
import org.nd4j.common.base.Preconditions;
import org.nd4j.linalg.api.ndarray.INDArray;

@Slf4j
public class Regression2dAdapter implements OutputAdapter<double[][]> {
    @Override
    public double[][] apply(INDArray... outputs) {
        Preconditions.checkArgument(outputs.length == 1, "Argmax adapter can have only 1 output");
        val array = outputs[0];
        Preconditions.checkArgument(array.rank() < 3, "Argmax adapter requires 2D or 1D output");

        if (array.rank() == 2 && !array.isVector()) {
            return array.toDoubleMatrix();
        } else {
            val result = new double[1][(int) array.length()];

            for (int e = 0; e< array.length(); e++)
                result[0][e] = array.getDouble(e);

            return result;
        }
    }
}
