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 *  * 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.
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 *  *  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
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package org.nd4j.linalg.convolution;

import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.common.util.ArrayUtil;


public abstract class BaseConvolution implements ConvolutionInstance {
    /**
     * 2d convolution (aka the last 2 dimensions
     *
     * @param input  the input to op
     * @param kernel the kernel to convolve with
     * @param type
     * @return
     */
    @Override
    public INDArray conv2d(INDArray input, INDArray kernel, Convolution.Type type) {
        int[] axes = input.shape().length < 2 ? ArrayUtil.range(0, 1)
                        : ArrayUtil.range(input.shape().length - 2, input.shape().length);
        return convn(input, kernel, type, axes);
    }


    /**
     * ND Convolution
     *
     * @param input  the input to transform
     * @param kernel the kernel to transform with
     * @param type   the opType of convolution
     * @return the convolution of the given input and kernel
     */
    @Override
    public INDArray convn(INDArray input, INDArray kernel, Convolution.Type type) {
        return convn(input, kernel, type, ArrayUtil.range(0, input.shape().length));
    }
}




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