org.nd4j.linalg.convolution.BaseConvolution Maven / Gradle / Ivy
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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.convolution;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.common.util.ArrayUtil;
/**
* Base convolution implementation
*
* @author Adam Gibson
*/
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));
}
}