
deepboof.backward.DSpatialPadding2D Maven / Gradle / Ivy
/*
* Copyright (c) 2016, Peter Abeles. All Rights Reserved.
*
* This file is part of DeepBoof
*
* 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 deepboof.backward;
import deepboof.Tensor;
import deepboof.forward.SpatialPadding2D;
/**
* Interface for computing the gradient of a padded spatial tensor. Spatial tensors have the shape of (N, C, H, W)
* where N is the number of mini-batches, C channels, H height and W width.
*
* @author Peter Abeles
*/
public interface DSpatialPadding2D> extends SpatialPadding2D
{
/**
* Compute the gradient of the input image from the gradient of the padded image for a specific mini-batch and
* channel of the input tensor.
*
* @param gradientPadded (Input) Gradient of padded image at specific mini-batch and channel. (H, W)
* @param batch (Input) mini-batch.
* @param channel (Input) Channel.
* @param gradientInput (Output) Output 4D spatial tensor. Only elements used to compute the channel are modified.
* (N, C, H, W)
*/
void backwardsChannel(T gradientPadded, int batch, int channel, T gradientInput);
/**
* Compute the gradient of the input image from the gradient of the padded image for a specific mini-batch and
* channel of the input tensor.
*
* @param gradientPadded (Input) Gradient of padded image at specific mini-batch. (C, H, W)
* @param batch (Input) mini-batch.
* @param gradientInput (Output) Output 4D spatial tensor. Only elements used to compute the image are modified.
* (N, C, H, W)
*/
void backwardsImage(T gradientPadded, int batch, T gradientInput);
}
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