All Downloads are FREE. Search and download functionalities are using the official Maven repository.

org.nd4j.linalg.convolution.BaseConvolution Maven / Gradle / Ivy

There is a newer version: 1.0.0-M2.1
Show newest version
/*
 *
 *  * Copyright 2015 Skymind,Inc.
 *  *
 *  *    Licensed under the Apache License, Version 2.0 (the "License");
 *  *    you may not use this file except in compliance with the License.
 *  *    You may obtain a copy of the License at
 *  *
 *  *        http://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.
 *
 *
 */

package org.nd4j.linalg.convolution;

import org.nd4j.linalg.api.complex.IComplexNDArray;
import org.nd4j.linalg.api.ndarray.INDArray;
import org.nd4j.linalg.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);
    }

    @Override
    public INDArray conv2d(IComplexNDArray input, IComplexNDArray 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 type 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));
    }

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



}




© 2015 - 2024 Weber Informatics LLC | Privacy Policy