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Diffstat (limited to 'arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h')
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diff --git a/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h b/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h new file mode 100644 index 0000000000..b28fa0f3f5 --- /dev/null +++ b/arm_compute/runtime/CL/functions/CLGEMMDeconvolutionLayer.h @@ -0,0 +1,144 @@ +/* + * 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/CLMemoryGroup.h" +#include "arm_compute/runtime/CL/CLTensor.h" +#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.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 <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: + CLMemoryGroup _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__ */ |