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 --- arm_compute/runtime/NEON/NEFunctions.h | 1 + .../runtime/NEON/functions/NEConvolutionLayer.h | 132 ++++----------- .../NEON/functions/NEGEMMConvolutionLayer.h | 184 +++++++++++++++++++++ .../runtime/NEON/functions/NEWinogradLayer.h | 16 ++ 4 files changed, 231 insertions(+), 102 deletions(-) create mode 100644 arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h (limited to 'arm_compute') diff --git a/arm_compute/runtime/NEON/NEFunctions.h b/arm_compute/runtime/NEON/NEFunctions.h index 077cf577e7..1531377e2e 100644 --- a/arm_compute/runtime/NEON/NEFunctions.h +++ b/arm_compute/runtime/NEON/NEFunctions.h @@ -60,6 +60,7 @@ #include "arm_compute/runtime/NEON/functions/NEFloor.h" #include "arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h" #include "arm_compute/runtime/NEON/functions/NEGEMM.h" +#include "arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h" #include "arm_compute/runtime/NEON/functions/NEGEMMInterleave4x4.h" #include "arm_compute/runtime/NEON/functions/NEGEMMLowpAssemblyMatrixMultiplyCore.h" #include "arm_compute/runtime/NEON/functions/NEGEMMLowpMatrixMultiplyCore.h" diff --git a/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h b/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h index f80f67d944..6ab1350b25 100644 --- a/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h +++ b/arm_compute/runtime/NEON/functions/NEConvolutionLayer.h @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2018 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -26,79 +26,27 @@ #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 "arm_compute/runtime/NEON/functions/NEDirectConvolutionLayer.h" +#include "arm_compute/runtime/NEON/functions/NEGEMMConvolutionLayer.h" +#include "arm_compute/runtime/NEON/functions/NEWinogradLayer.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 +/** Basic function to simulate a convolution layer. This function calls one of the following NEON functions: + * -# @ref NEGEMMConvolutionLayer (executed only in case GEMM is required for the operation) + * -# @ref NEWinogradLayer (executed only in case Winograd is required for the operation) + * -# @ref NEDirectConvolutionLayer (executed only in case Direct Convolution is required for the operation) */ class NEConvolutionLayer : public IFunction { public: /** Constructor */ - NEConvolutionLayer(const std::shared_ptr &memory_manager = nullptr); + NEConvolutionLayer(std::shared_ptr memory_manager = nullptr); /** Set the input and output tensors. * @@ -114,7 +62,7 @@ public: * @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()); + void configure(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 NEConvolutionLayer * * @param[in] input Source tensor. 3 lower dimensions represent a single input [width, height, IFM], @@ -133,51 +81,31 @@ public: */ 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 + /** Static function to check if given info will return the convolution called by @ref NEConvolutionLayer * - * @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] 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. * - * @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 + * @return the Convolution Method Hint */ - void configure_asm_mm(const struct CPUInfo &ci, int M, int N, int K); + static ConvolutionMethod get_convolution_method(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info, + const WeightsInfo &weights_info = WeightsInfo()); -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; + // Inherited methods overridden: + void run() override; - bool _append_bias; - bool _is_fully_connected_convolution; - bool _are_weights_reshaped; - bool _is_quantized; - bool _is_interleaved_transposed; +private: + std::shared_ptr _memory_manager; + std::unique_ptr _function; /**< Function to run */ }; } #endif /* __ARM_COMPUTE_NECONVOLUTIONLAYER_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__ */ diff --git a/arm_compute/runtime/NEON/functions/NEWinogradLayer.h b/arm_compute/runtime/NEON/functions/NEWinogradLayer.h index f57be697b5..a939f82854 100644 --- a/arm_compute/runtime/NEON/functions/NEWinogradLayer.h +++ b/arm_compute/runtime/NEON/functions/NEWinogradLayer.h @@ -67,6 +67,22 @@ public: // Inherited methods overridden: void run() override; + /** 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: 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. + * Currently only 3x3 kernels are supported. + * @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. 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. Currently only unit strides are supported. + * + * @return a status + */ + static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info); + /** Prevent instances of this class from being copied (As this class contains pointers) */ NEWinogradLayer(const NEWinogradLayer &) = delete; /** Prevent instances of this class from being copied (As this class contains pointers) */ -- cgit v1.2.1