| /* |
| * 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_CLGEMMDECONVOLUTIONLAYER_H |
| #define ARM_COMPUTE_CLGEMMDECONVOLUTIONLAYER_H |
| |
| #include "arm_compute/core/CL/kernels/CLDeconvolutionReshapeOutputKernel.h" |
| #include "arm_compute/runtime/CL/CLTensor.h" |
| #include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h" |
| #include "arm_compute/runtime/CL/functions/CLGEMMLowpOutputStage.h" |
| #include "arm_compute/runtime/CL/functions/CLPermute.h" |
| #include "arm_compute/runtime/CL/functions/CLReshapeLayer.h" |
| #include "arm_compute/runtime/CL/functions/CLSlice.h" |
| #include "arm_compute/runtime/CL/functions/CLTranspose.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 through a call to GEMM. |
| * |
| * 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, pad is the amount of padding and finally a is a user |
| * specified value where a < stride - 1, that increases the padding top and right of the input image. |
| * |
| * 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. |
| * |
| * This function calls the following OpenCL kernels/functions: |
| * |
| * -# @ref CLGEMMLowpMatrixMultiplyCore |
| * -# @ref CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint |
| * -# @ref CLPermute |
| * -# @ref CLPermute |
| * -# @ref CLReshapeLayer |
| * -# @ref CLTranspose |
| * -# @ref CLDeconvolutionReshapeOutputKernel |
| * -# @ref CLSlice |
| */ |
| class CLGEMMDeconvolutionLayer : public IFunction |
| { |
| public: |
| /** Constructor */ |
| CLGEMMDeconvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr); |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| CLGEMMDeconvolutionLayer(const CLGEMMDeconvolutionLayer &) = delete; |
| /** Default move constructor */ |
| CLGEMMDeconvolutionLayer(CLGEMMDeconvolutionLayer &&) = default; |
| /** Prevent instances of this class from being copied (As this class contains pointers) */ |
| CLGEMMDeconvolutionLayer &operator=(const CLGEMMDeconvolutionLayer &) = delete; |
| /** Default move assignment operator */ |
| CLGEMMDeconvolutionLayer &operator=(CLGEMMDeconvolutionLayer &&) = 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: F16/F32. Data layout supported: NHWC |
| * @param[in] weights The 4d weights with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input. Data layout supported: same as @p input. |
| * @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as @p input. Data layout supported: same as @p input. |
| * @param[out] output Output tensor. The output has the same number of dimensions as the @p input. Data layout supported: same as @p input. |
| * @param[in] deconv_info Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo. This function supports only stride_x = weights.width && stride_y = weights.height. Moreover, padding is not supported. |
| */ |
| void configure(const ICLTensor *input, const ICLTensor *weights, const ICLTensor *bias, ICLTensor *output, const PadStrideInfo &deconv_info); |
| /** Static function to check if given info will lead to a valid configuration of @ref CLDeconvolutionLayer |
| * |
| * @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: F16/F32. Data layout supported: NHWC |
| * @param[in] weights The 4d weights info with dimensions [width, height, IFM, OFM]. Data type supported: Same as @p input. Data layout supported: same as @p input. |
| * @param[in] bias (Optional) The biases have one dimension. Data type supported: Same as @p input. Data layout supported: same as @p input. |
| * @param[in] output Output tensor info. The output has the same number of dimensions as the @p input. Data layout supported: same as @p input. |
| * @param[in] deconv_info Contains padding and policies to be used in the deconvolution, this is described in @ref PadStrideInfo. |
| * |
| * @return a status |
| */ |
| static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *bias, const ITensorInfo *output, const PadStrideInfo &deconv_info); |
| |
| // Inherited methods overridden: |
| void run() override; |
| void prepare() override; |
| |
| private: |
| MemoryGroup _memory_group; |
| |
| CLGEMM _mm_gemm; |
| CLGEMMLowpMatrixMultiplyCore _mm_gemmlowp; |
| CLGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage; |
| CLPermute _permute_input_to_nhwc; |
| CLPermute _permute_weights_to_nhwc; |
| CLReshapeLayer _reshape_weights; |
| CLTranspose _transpose_weights; |
| CLDeconvolutionReshapeOutputKernel _deconv_reshape; |
| CLSlice _slice_gemm; |
| |
| CLTensor _gemmlowp_final; |
| CLTensor _reshaped_weights; |
| CLTensor _reshaped_weights_t; |
| CLTensor _permuted_input; |
| CLTensor _permuted_weights; |
| CLTensor _gemm_output; |
| CLTensor _slice_gemm_input; |
| |
| const ICLTensor *_original_weights; |
| bool _is_prepared; |
| bool _padded_input; |
| bool _is_nchw; |
| bool _is_quantized; |
| }; |
| } // namespace arm_compute |
| #endif /* ARM_COMPUTE_CLGEMMDECONVOLUTIONLAYER_H */ |