| /* |
| * 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/CLReverse.h" |
| #include "arm_compute/runtime/CL/functions/CLTranspose.h" |
| |
| #include "arm_compute/runtime/CL/CLTensor.h" |
| #include "arm_compute/runtime/IFunction.h" |
| #include "arm_compute/runtime/IMemoryManager.h" |
| #include "arm_compute/runtime/MemoryGroup.h" |
| |
| #include <memory> |
| |
| 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 CLReverse |
| * |
| */ |
| class CLDirectDeconvolutionLayer : public IFunction |
| { |
| public: |
| /** Constructor */ |
| CLDirectDeconvolutionLayer(std::shared_ptr<IMemoryManager> 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: |
| MemoryGroup _memory_group; |
| CLDeconvolutionLayerUpsample _scale_f; |
| CLConvolutionLayer _conv_f; |
| CLReverse _flip_weights; |
| |
| CLTensor _scaled_output; |
| ICLTensor *_original_weights; |
| CLTensor _weights_flipped; |
| CLTensor _flip_axis; |
| |
| bool _is_prepared; |
| }; |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_CLDECONVOLUTIONLAYER_H */ |