/*- * * * Copyright 2016 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.deeplearning4j.nn.layers.convolution.subsampling; import org.deeplearning4j.berkeley.Pair; import org.deeplearning4j.nn.conf.ConvolutionMode; import org.deeplearning4j.nn.conf.layers.PoolingType; import org.deeplearning4j.nn.gradient.Gradient; import org.nd4j.linalg.api.ndarray.INDArray; /** * Helper for the subsampling layer. * * @author saudet */ public interface SubsamplingHelper { boolean checkSupported(); Pair<Gradient, INDArray> backpropGradient(INDArray input, INDArray epsilon, int[] kernel, int[] strides, int[] pad, PoolingType poolingType, ConvolutionMode convolutionMode); INDArray activate(INDArray input, boolean training, int[] kernel, int[] strides, int[] pad, PoolingType poolingType, ConvolutionMode convolutionMode); }