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author | Sang-Hoon Park <sang-hoon.park@arm.com> | 2020-10-19 16:00:11 +0100 |
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committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2020-10-20 10:27:40 +0000 |
commit | 68dd25fbe6e4d3c3513fa5993863419769aa08fc (patch) | |
tree | b918be923f9e4550c306d7f44d168ab938a71fc8 /src/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp | |
parent | f0a4e609d98f111b6a7d4a2b578d1b7cba64b805 (diff) | |
download | ComputeLibrary-68dd25fbe6e4d3c3513fa5993863419769aa08fc.tar.gz |
COMPMID-3637: Move utility headers from arm_compute to src
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Change-Id: If9d6fa8c900b68c4b6fd373f2fc1f9abb83ea917
Signed-off-by: Michalis Spyrou <michalis.spyrou@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4145
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'src/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp')
-rw-r--r-- | src/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp | 291 |
1 files changed, 291 insertions, 0 deletions
diff --git a/src/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp b/src/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp new file mode 100644 index 0000000000..4343f6ad45 --- /dev/null +++ b/src/core/NEON/kernels/convolution/depthwise/depthwise_quantized.hpp @@ -0,0 +1,291 @@ +/* + * Copyright (c) 2018-2019 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. + */ + +#pragma once +#include "depthwise.hpp" +#include "qasymm8.hpp" +#include "qsymm8.hpp" +#pragma once + +using namespace neon_convolution_kernels; +using namespace qasymm8; + +inline int32x4_t saturating_doubling_high_mul(const int32x4_t& a, const int32x4_t& b) +{ + return vqrdmulhq_s32(a, b); +} + +inline int32x4_t saturating_doubling_high_mul(const int32x4_t& a, const int32_t& b) +{ + return vqrdmulhq_n_s32(a, b); +} + +inline int32_t saturating_doubling_high_mul(const int32_t& a, const int32_t& b) +{ + return vget_lane_s32(vqrdmulh_n_s32(vdup_n_s32(a), b), 0); +} + +inline int32x4_t rounding_divide_by_exp2(const int32x4_t& x, const int32x4_t shift) +{ + const int32x4_t fixup = vshrq_n_s32(vandq_s32(x, shift), 31); + const int32x4_t fixed = vqaddq_s32(x, fixup); + return vrshlq_s32(fixed, shift); +} + +inline int32x4_t rounding_divide_by_exp2(const int32x4_t& x, const int exponent) +{ + const int32x4_t shift = vdupq_n_s32(-exponent); + const int32x4_t fixup = vshrq_n_s32(vandq_s32(x, shift), 31); + const int32x4_t fixed = vqaddq_s32(x, fixup); + return vrshlq_s32(fixed, shift); +} + +inline int32x2_t rounding_divide_by_exp2(const int32x2_t& x, const int exponent) +{ + const int32x2_t shift = vdup_n_s32(-exponent); + const int32x2_t fixup = vshr_n_s32(vand_s32(x, shift), 31); + const int32x2_t fixed = vqadd_s32(x, fixup); + return vrshl_s32(fixed, shift); +} + +inline int32_t rounding_divide_by_exp2(const int32_t& x, const int exponent) +{ + const int32x2_t xs = vdup_n_s32(x); + return vget_lane_s32(rounding_divide_by_exp2(xs, exponent), 0); +} + +namespace depthwise +{ + +namespace nck = neon_convolution_kernels; + +template < + unsigned int OutputTileRows, unsigned int OutputTileCols, + unsigned int KernelRows, unsigned int KernelCols, + unsigned int StrideRows, unsigned int StrideCols +> +class QAsymm8DepthwiseConvolution : public DepthwiseConvolutionBase< + OutputTileRows, OutputTileCols, + KernelRows, KernelCols, + StrideRows, StrideCols, + uint8_t, int32_t, uint8_t, + QAsymm8DepthwiseConvolution<OutputTileRows, OutputTileCols, KernelRows, KernelCols, StrideRows, StrideCols> +> +{ + using Base = DepthwiseConvolutionBase< + OutputTileRows, OutputTileCols, + KernelRows, KernelCols, + StrideRows, StrideCols, + uint8_t, int32_t, uint8_t, + QAsymm8DepthwiseConvolution<OutputTileRows, OutputTileCols, KernelRows, KernelCols, StrideRows, StrideCols> + >; + friend Base; + using InputType = typename Base::InputType; + using OutputType = typename Base::OutputType; + + public: + QAsymm8DepthwiseConvolution( + int n_batches, int n_input_rows, int n_input_cols, int n_channels, + nck::ActivationFunction activation, + const qasymm8::QAsymm8Params& weight_quantisation, + const qasymm8::QAsymm8Params& input_quantisation, + const qasymm8::QAsymm8Params& output_quantisation, + unsigned int padding_top, + unsigned int padding_left, + unsigned int padding_bottom, + unsigned int padding_right + ); + + QAsymm8DepthwiseConvolution( + int n_batches, int n_input_rows, int n_input_cols, int n_channels, + int n_output_rows, int n_output_cols, + nck::ActivationFunction activation, + const qasymm8::QAsymm8Params& weight_quantisation, + const qasymm8::QAsymm8Params& input_quantisation, + const qasymm8::QAsymm8Params& output_quantisation, + unsigned int padding_top, + unsigned int padding_left, + unsigned int padding_bottom, + unsigned int padding_right + ); + + QAsymm8DepthwiseConvolution( + int n_batches, int n_input_rows, int n_input_cols, int n_channels, + nck::ActivationFunction activation, + const qasymm8::QAsymm8Params& weight_quantisation, + const qasymm8::QAsymm8Params& input_quantisation, + const qasymm8::QAsymm8Params& output_quantisation, + const qasymm8::QAsymm8RescaleParams& rescale_parameters, + unsigned int padding_top, + unsigned int padding_left, + unsigned int padding_bottom, + unsigned int padding_right + ); + + QAsymm8DepthwiseConvolution( + int n_batches, int n_input_rows, int n_input_cols, int n_channels, + int n_output_rows, int n_output_cols, + nck::ActivationFunction activation, + const qasymm8::QAsymm8Params& weight_quantisation, + const qasymm8::QAsymm8Params& input_quantisation, + const qasymm8::QAsymm8Params& output_quantisation, + const qasymm8::QAsymm8RescaleParams& rescale_parameters, + unsigned int padding_top, + unsigned int padding_left, + unsigned int padding_bottom, + unsigned int padding_right + ); + + protected: + uint8_t _input_padding_value(void) const; + + void _pack_params( + void *buffer, + const void *weights, + unsigned int weight_row_stride, + unsigned int weight_col_stride, + const void *biases=nullptr + ) const; + + template <nck::ActivationFunction Activation> + void execute_tile( + int n_channels, + const void* packed_params, + const uint8_t* inptr, + unsigned int in_row_stride, + unsigned int in_col_stride, + uint8_t* outptr, + unsigned int out_row_stride, + unsigned int out_col_stride + ); + + template <nck::ActivationFunction Activation> + void execute_tile( + int n_channels, + const void* packed_params, + const uint8_t* inptrs[Base::inner_tile_rows][Base::inner_tile_cols], + uint8_t* outptrs[Base::output_tile_rows][Base::output_tile_cols] + ); + + private: + // Quantization parameters + const qasymm8::QAsymm8Params _weights_quant, _inputs_quant, _output_quant; + const qasymm8::QAsymm8RescaleParams rescale_parameters; +}; + +template < + unsigned int OutputTileRows, unsigned int OutputTileCols, + unsigned int KernelRows, unsigned int KernelCols, + unsigned int StrideRows, unsigned int StrideCols +> +class QSymm8HybridPerChannelDepthwiseConvolution : public DepthwiseConvolutionBase< + OutputTileRows, OutputTileCols, + KernelRows, KernelCols, + StrideRows, StrideCols, + uint8_t, int32_t, uint8_t, + QSymm8HybridPerChannelDepthwiseConvolution<OutputTileRows, OutputTileCols, KernelRows, KernelCols, StrideRows, StrideCols> +> +{ + using Base = DepthwiseConvolutionBase< + OutputTileRows, OutputTileCols, + KernelRows, KernelCols, + StrideRows, StrideCols, + uint8_t, int32_t, uint8_t, + QSymm8HybridPerChannelDepthwiseConvolution<OutputTileRows, OutputTileCols, KernelRows, KernelCols, StrideRows, StrideCols> + >; + friend Base; + using InputType = typename Base::InputType; + using OutputType = typename Base::OutputType; + + public: + QSymm8HybridPerChannelDepthwiseConvolution( + int n_batches, int n_input_rows, int n_input_cols, int n_channels, + nck::ActivationFunction activation, + const qsymm8::QSymm8PerChannelParams& weight_quantisation, + const qasymm8::QAsymm8Params& input_quantisation, + const qasymm8::QAsymm8Params& output_quantisation, + unsigned int padding_top, + unsigned int padding_left, + unsigned int padding_bottom, + unsigned int padding_right + ); + + QSymm8HybridPerChannelDepthwiseConvolution( + int n_batches, int n_input_rows, int n_input_cols, int n_channels, + nck::ActivationFunction activation, + const qsymm8::QSymm8PerChannelParams& weight_quantisation, + const qasymm8::QAsymm8Params& input_quantisation, + const qasymm8::QAsymm8Params& output_quantisation, + const qsymm8::QSymm8PerChannelRescaleParams& rescale_parameters, + unsigned int padding_top, + unsigned int padding_left, + unsigned int padding_bottom, + unsigned int padding_right + ); + + size_t get_packed_params_size(void) const override + { + return this->n_channels() * (sizeof(int8_t)*KernelRows*KernelCols + 3*sizeof(int32_t)); + + } + + protected: + uint8_t _input_padding_value(void) const; + + void _pack_params( + void *buffer, + const void *weights, + unsigned int weight_row_stride, + unsigned int weight_col_stride, + const void *biases=nullptr + ) const; + + template <nck::ActivationFunction Activation> + void execute_tile( + int n_channels, + const void* packed_params, + const uint8_t* inptr, + unsigned int in_row_stride, + unsigned int in_col_stride, + uint8_t* outptr, + unsigned int out_row_stride, + unsigned int out_col_stride + ); + + template <nck::ActivationFunction Activation> + void execute_tile( + int n_channels, + const void* packed_params, + const uint8_t* inptrs[Base::inner_tile_rows][Base::inner_tile_cols], + uint8_t* outptrs[Base::output_tile_rows][Base::output_tile_cols] + ); + + private: + // Quantization parameters + const qsymm8::QSymm8PerChannelParams _weights_quant; + const qasymm8::QAsymm8Params _input_quant, _output_quant; + const qsymm8::QSymm8PerChannelRescaleParams _rescale_parameters; +}; + +} // namespace depthwise |