From 6acc6add8412c6d3841a49684610fc5a6526312e Mon Sep 17 00:00:00 2001 From: Isabella Gottardi Date: Fri, 2 Feb 2018 17:19:18 +0000 Subject: COMPMID-846: Create a ConvolutionLayer for NEON Change-Id: I98bbef40bfac5b05134be4ef9fb54d14c0c9e8e8 Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/118806 Tested-by: Jenkins Reviewed-by: Anthony Barbier --- .../NEON/functions/NEGEMMConvolutionLayer.h | 184 +++++++++++++++++++++ 1 file changed, 184 insertions(+) create mode 100644 arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h (limited to 'arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h') diff --git a/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h new file mode 100644 index 0000000000..c3c7f825a9 --- /dev/null +++ b/arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h @@ -0,0 +1,184 @@ +/* + * Copyright (c) 2017-2018 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_NEGEMMCONVOLUTIONLAYER_H__ +#define __ARM_COMPUTE_NEGEMMCONVOLUTIONLAYER_H__ + +#include "arm_compute/runtime/IFunction.h" + +#include "arm_compute/core/NEON/kernels/NECol2ImKernel.h" +#include "arm_compute/core/NEON/kernels/NEFillBorderKernel.h" +#include "arm_compute/core/NEON/kernels/NEGEMMAssemblyBaseKernel.h" +#include "arm_compute/core/NEON/kernels/NEGEMMInterleave4x4Kernel.h" +#include "arm_compute/core/NEON/kernels/NEGEMMMatrixMultiplyKernel.h" +#include "arm_compute/core/NEON/kernels/NEGEMMTranspose1xWKernel.h" +#include "arm_compute/core/NEON/kernels/NEIm2ColKernel.h" +#include "arm_compute/core/NEON/kernels/NEWeightsReshapeKernel.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/runtime/MemoryGroup.h" +#include "arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h" +#include "arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h" +#include "arm_compute/runtime/Tensor.h" + +#include + +namespace arm_compute +{ +class ITensor; + +/** Function to reshape and perform 1xW transposition on the weights. This function calls the following kernels: + * -# @ref NEWeightsReshapeKernel + * -# @ref NEGEMMTranspose1xWKernel (executed in case GEMM is required for the operation) + */ +class NEConvolutionLayerReshapeWeights : public IFunction +{ +public: + /** Constructor */ + NEConvolutionLayerReshapeWeights(std::shared_ptr memory_manager = nullptr); + /** Set the input and output tensors. + * + * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QS8/QASYMM8/QS16/F32. + * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. + * @param[out] output Destination tensor. Data types supported: Same as @p weights. + * @param[in] transpose1xW True if the weights are to undergo a 1xW transposition after reshaping (in case of GEMM operation), false otherwise. + * Data types supported: Same as @p weights. + */ + void configure(const ITensor *weights, const ITensor *biases, ITensor *output, bool transpose1xW); + /** Static function to check if given info will lead to a valid configuration of @ref NEConvolutionLayerReshapeWeights + * + * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: QS8/QASYMM8/QS16/F16/F32. + * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p weights. + * @param[in] output Destination tensor. Data types supported: Same as @p weights. + * @param[in] transpose1xW True if the weights are to undergo a 1xW transposition after reshaping (in case of GEMM operation), false otherwise. + * Data types supported: Same as @p weights. + * + * @return an error status + */ + static Status validate(const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, bool transpose1xW); + + // Inherited methods overridden: + void run() override; + +private: + MemoryGroup _memory_group; + NEWeightsReshapeKernel _weights_reshape_kernel; + NEGEMMTranspose1xWKernel _weights_transposed_kernel; + Tensor _weights_reshaped; + bool _transpose1xW; +}; + +/** Basic function to simulate a convolution layer. This function calls the following NEON kernels: + * -# @ref NEWeightsReshapeKernel (executed only once for each configuration) + * -# @ref NEIm2ColKernel + * -# @ref NEGEMMInterleave4x4Kernel (executed only in case GEMM is required for the operation) + * -# @ref NEGEMMMatrixMultiplyKernel or @ref NEGEMMLowpMatrixMultiplyCore (if quantized asymmetric) + * -# @ref NEGEMMLowpQuantizeDownInt32ToUint8Scale (if quantized asymmetric) + * -# @ref NECol2ImKernel + */ +class NEGEMMConvolutionLayer : public IFunction +{ +public: + /** Constructor */ + NEGEMMConvolutionLayer(const std::shared_ptr &memory_manager = nullptr); + + /** Set the input and output tensors. + * + * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], + * while every optional dimension from 4 and above represent a batch of inputs. + * Data types supported: QS8/QASYMM8/QS16/F32. + * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported: Same as @p input. + * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. + * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. + * @param[out] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. + * Data types supported: Same as @p input. + * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. + * @param[in] weights_info Specifies if the weights tensor has been reshaped with NEWeightsReshapeKernel. If this is not part of the fully connected layer the weights + * tensor has also been transposed with NEGEMMTranspose1xWKernel. Data type supported: Same as @p input. + */ + void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info = WeightsInfo()); + /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMConvolutionLayer + * + * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], + * while every optional dimension from 4 and above represent a batch of inputs. + * Data types supported: QS8/QASYMM8/QS16/F16/F32. + * @param[in] weights Weights tensor. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM]. Data type supported:Same as @p input. + * @param[in] biases Biases tensor. Shared biases supported. Biases are 1D tensor with dimensions [OFM]. + * Data type supported: Should match @p input data type, except for input of QASYMM8 type where biases should be of S32 type. + * @param[in] output Destination tensor. 3 lower dimensions represent a single output [width, height, OFM], while the rest represent batch of outputs. + * Data types supported: Same as @p input. + * @param[in] conv_info Contains padding and stride information described in @ref PadStrideInfo. + * @param[in] weights_info Specifies if the weights tensor has been reshaped with NEWeightsReshapeKernel. If this is not part of the fully connected layer the weights + * tensor has also been transposed with NEGEMMTranspose1xWKernel. Data type supported: Same as @p input. + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, + const WeightsInfo &weights_info = WeightsInfo()); + + // Inherited methods overridden: + void run() override; + +private: + /** Configures the appropriate matrix multiply routine + * + * @param[in] input Input tensor. Data types supported: QS8/QASYMM8/QS16/F16/F32. + * @param[in] weights Weights tensor. Data type supported: Same as @p input. + * @param[out] output Output tensor. Data types supported: Same as @p input, + * except for input of QASYMM8 type where output should be of S32 type. + */ + void configure_mm(const ITensor *input, const ITensor *weights, ITensor *output); + /** Prepare the appropriate assembly optimized kernel + * + * @param[in] ci CPU information + * @param[in] M M parameter of matrix multiplication + * @param[in] N N parameter of matrix multiplication + * @param[in] K K parameter of matrix multiplication + */ + void configure_asm_mm(const struct CPUInfo &ci, int M, int N, int K); + +private: + MemoryGroup _memory_group; + NEIm2ColKernel _input_im2col_kernel; + NEGEMMInterleave4x4Kernel _input_interleave_kernel; + NEConvolutionLayerReshapeWeights _reshape_weights; + NEGEMMMatrixMultiplyKernel _mm_kernel; + std::unique_ptr _mm_optimised_kernel; + NEGEMMLowpMatrixMultiplyCore _mm_gemmlowp; + NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage; + NECol2ImKernel _output_col2im_kernel; + + Tensor _input_im2col_reshaped; + Tensor _input_interleaved_reshaped; + Tensor _weights_reshaped; + Tensor _gemm_output; + Tensor _tmp_output; + Tensor _workspace; + + bool _append_bias; + bool _is_fully_connected_convolution; + bool _are_weights_reshaped; + bool _is_quantized; + bool _is_interleaved_transposed; +}; +} +#endif /* __ARM_COMPUTE_NECONVOLUTIONGEMMLAYER_H__ */ -- cgit v1.2.1