cavis/cavis-dnn/cavis-dnn-api/src/main/java/org/nd4j/linalg/lossfunctions/LossUtil.java

/*
 *  ******************************************************************************
 *  *
 *  *
 *  * 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.lossfunctions;

import org.nd4j.linalg.api.ndarray.INDArray;

import java.util.Arrays;

public class LossUtil {

    /**
     *
     * @param to
     * @param mask
     * @return
     */
    public static boolean isPerOutputMasking(INDArray to, INDArray mask) {
        return !mask.isColumnVector() || Arrays.equals(to.shape(), mask.shape());
    }

    /**
     *
     * @param to
     * @param mask
     */
    public static void applyMask(INDArray to, INDArray mask) {
        //Two possibilities exist: it's *per example* masking, or it's *per output* masking
        //These cases have different mask shapes. Per example: column vector. Per output: same shape as score array
        if (mask.isColumnVectorOrScalar()) {
            to.muliColumnVector(mask.castTo(to.dataType()));
        } else if (Arrays.equals(to.shape(), mask.shape())) {
            to.muli(mask.castTo(to.dataType()));
        } else {
            throw new IllegalStateException("Invalid mask array: per-example masking should be a column vector, "
                            + "per output masking arrays should be the same shape as the labels array. Mask shape: "
                            + Arrays.toString(mask.shape()) + ", output shape: " + Arrays.toString(to.shape()));
        }
    }
}