From 4a8ec803747780c97a444ca3df4bdeaa8c10190b Mon Sep 17 00:00:00 2001 From: giuros01 Date: Mon, 18 Mar 2019 13:25:05 +0000 Subject: Optimize CL DeconvolutionLayer-Part II: Add CLDirectDeconvolution function to be used by CLDeconvolution. This is only a code refactoring (no optimizations have been added) Change-Id: I78488f4aecfe1cce93c31dba31489dcee4c85c67 Signed-off-by: giuros01 Reviewed-on: https://review.mlplatform.org/c/895 Tested-by: Arm Jenkins Comments-Addressed: Arm Jenkins Reviewed-by: Gian Marco Iodice --- .../CL/functions/CLDirectDeconvolutionLayer.h | 131 +++++++++++++++++++++ 1 file changed, 131 insertions(+) create mode 100644 arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h (limited to 'arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h') diff --git a/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h b/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h new file mode 100644 index 0000000000..936263d635 --- /dev/null +++ b/arm_compute/runtime/CL/functions/CLDirectDeconvolutionLayer.h @@ -0,0 +1,131 @@ +/* + * Copyright (c) 2019 ARM Limited. + * + * SPDX-License-Identifier: MIT + * + * Permission is hereby granted, free of charge, to any person obtaining a copy + * of this software and associated documentation files (the "Software"), to + * deal in the Software without restriction, including without limitation the + * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or + * sell copies of the Software, and to permit persons to whom the Software is + * furnished to do so, subject to the following conditions: + * + * The above copyright notice and this permission notice shall be included in all + * copies or substantial portions of the Software. + * + * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR + * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, + * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE + * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER + * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, + * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE + * SOFTWARE. + */ +#ifndef __ARM_COMPUTE_CLDIRECTDECONVOLUTIONLAYER_H__ +#define __ARM_COMPUTE_CLDIRECTDECONVOLUTIONLAYER_H__ + +#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h" +#include "arm_compute/runtime/CL/functions/CLDeconvolutionLayerUpsample.h" +#include "arm_compute/runtime/CL/functions/CLTranspose.h" + +#include "arm_compute/core/CPP/kernels/CPPFlipWeightsKernel.h" + +#include "arm_compute/runtime/CL/CLMemoryGroup.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/IFunction.h" +#include "arm_compute/runtime/IMemoryManager.h" + +#include + +namespace arm_compute +{ +class ICLTensor; +/** Function to run the deconvolution layer. + * + * Deconvolution Layer is the backward pass of Convolution Layer. First we transform the input depending on the stride and pad info and then perform a 1x1 + * convolution pass. Input stride defines how many zeroes we should put between each element of the input and pad is the amount of padding. + * + * The relation between input to output is as follows: + * \f[ + * width\_output = (width\_input - 1) \cdot stride\_x - 2 \cdot padding\_x + kernel\_x + * \f] + * \f[ + * height\_output = (height\_input - 1) \cdot stride\_y - 2 \cdot padding\_y + kernel\_y + * \f] + * + * where: + * width_input is the size of the first input dimension. + * height_input is the size of the second input dimension. + * width_output is the size of the first output dimension. + * height_output is the size of the second output dimension. + * kernel_x and kernel_y are the convolution sizes in x and y. + * stride_x and stride_y is the input stride of the first and second dimension. + * + * The weights used by Deconvolution are supposed to be the same as the ones used for Convolution. Therefore, it will be necessary to use the weights in the + * reverse order to perform an actual convolution. This is achieved by using the @ref CPPFlipWeightsKernel. + * + * This function calls the following OpenCL kernels/functions: + * + * -# @ref CLDeconvolutionLayerUpsample + * -# @ref CLConvolutionLayer + * + * And the following CPP kernels: + * -# @ref CPPFlipWeightsKernel + * + */ +class CLDirectDeconvolutionLayer : public IFunction +{ +public: + /** Constructor */ + CLDirectDeconvolutionLayer(std::shared_ptr memory_manager = nullptr); + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDirectDeconvolutionLayer(const CLDirectDeconvolutionLayer &) = delete; + /** Default move constructor */ + CLDirectDeconvolutionLayer(CLDirectDeconvolutionLayer &&) = default; + /** Prevent instances of this class from being copied (As this class contains pointers) */ + CLDirectDeconvolutionLayer &operator=(const CLDirectDeconvolutionLayer &) = delete; + /** Default move assignment operator */ + CLDirectDeconvolutionLayer &operator=(CLDirectDeconvolutionLayer &&) = default; + /** Set the input, weights, biases and output tensors. + * + * @param[in,out] input Input tensor. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: QASYMM8/F16/F32. + * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input. + * @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as @p input. + * @param[out] output Output tensor. The output has the same number of dimensions as the @p input. + * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. + * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref CLWeightsReshapeKernel. + * + */ + void configure(ICLTensor *input, ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &info, const WeightsInfo &weights_info = WeightsInfo()); + /** Static function to check if given info will lead to a valid configuration of @ref CLDirectDeconvolutionLayer + * + * @param[in] input Input tensor info. 3 lower dimensions represent a single input, and an optional 4th dimension for batch of inputs. Data types supported: QASYMM8/F16/F32. + * @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input. + * @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as @p input. + * @param[in] output Output tensor info. The output has the same number of dimensions as the @p input. + * @param[in] info Contains padding and policies to be used in the deconvolution, this is decribed in @ref PadStrideInfo. + * @param[in] weights_info (Optional) Weights information needed for @ref CLConvolutionLayer, specifies if the weights tensor has been reshaped with @ref CLWeightsReshapeKernel. + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, ITensorInfo *output, const PadStrideInfo &info, + const WeightsInfo &weights_info = WeightsInfo()); + + // Inherited methods overridden: + void run() override; + void prepare() override; + +private: + CLMemoryGroup _memory_group; + CLDeconvolutionLayerUpsample _scale_f; + CLConvolutionLayer _conv_f; + CPPFlipWeightsKernel _flip_weights; + + CLTensor _scaled_output; + ICLTensor *_original_weights; + CLTensor _weights_flipped; + + bool _is_prepared; +}; +} // namespace arm_compute +#endif /* __ARM_COMPUTE_CLDECONVOLUTIONLAYER_H__ */ -- cgit v1.2.1