diff options
author | George Wort <george.wort@arm.com> | 2019-02-22 16:37:41 +0000 |
---|---|---|
committer | Giuseppe Rossini <giuseppe.rossini@arm.com> | 2019-03-15 13:34:00 +0000 |
commit | 2d7e683e79c8ad328d4930c1f82a46827313faf4 (patch) | |
tree | eb81f928ecd2543ef80af87f65d1bdef5a78ea2a /arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.h | |
parent | 3814b30623d6a9e570d850fe5ae275fe2117f3f5 (diff) | |
download | ComputeLibrary-2d7e683e79c8ad328d4930c1f82a46827313faf4.tar.gz |
COMPMID-1694: Fuse offset contribution with the output stage when we use NEGEMMLowpMatrixMultiplyCore
Change-Id: Ic1a681e4cc03e1eba3bf8485d9cdb17b3e926047
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/c/561
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Diffstat (limited to 'arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.h')
-rw-r--r-- | arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.h | 136 |
1 files changed, 136 insertions, 0 deletions
diff --git a/arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.h b/arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.h new file mode 100644 index 0000000000..c284ca5c5f --- /dev/null +++ b/arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionOutputStageKernel.h @@ -0,0 +1,136 @@ +/* + * 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_NEGEMMLOWPOFFSETCONTRIBUTIONOUTPUTSTAGEKERNEL_H__ +#define __ARM_COMPUTE_NEGEMMLOWPOFFSETCONTRIBUTIONOUTPUTSTAGEKERNEL_H__ + +#include "arm_compute/core/NEON/INEKernel.h" + +namespace arm_compute +{ +class ITensor; + +/** NEON kernel used to add the offset contribution and perform the output stage after @ref NEGEMMLowpMatrixMultiplyKernel. + * + * The computation is performed in-place + * + * This kernel takes a final int32 accumulator value (the output of @ref NEGEMMLowpMatrixMultiplyKernel), + * and adds to it the offset contribution of matrix A and matrix B in-place. + * + * The output stage can perform either QuantizeDownInt32ToUint8Scale or QuantizeDownInt32ToUint8ScaleByFixedPoint. + * + * For QuantizeDownInt32ToUint8Scale the final result is: + * + * ((mm_result'[i][k] + result_offset) * result_mult_int) >> result_shift + * + * For QuantizeDownInt32ToUint8ScaleByFixedPoint the final result is: + * + * (FixedPointMul(mm_result'[i][k], result_fixedpoint_multiplier) >> result_shift) + result_offset_after_shift + * + * where FixedPointMul(x, y) is the nearest integer to the following + * mathematical expression, evaluated without overflow or intermediate rounding: + * + * (x * y) / 2^31 + * + * and mm_result'[i][k] = mm_result[i][k] + + * (vector_sum_col[k] * a_offset) + + * (vector_sum_row[i] * b_offset) + + * (a_offset * b_offset * k) + */ + +class NEGEMMLowpOffsetContributionOutputStageKernel : public INEKernel +{ +public: + const char *name() const override + { + return "NEGEMMLowpOffsetContributionOutputStageKernel"; + } + /** Constructor */ + NEGEMMLowpOffsetContributionOutputStageKernel(); + /** Prevent instances of this class from being copied (As this class contains pointers)*/ + NEGEMMLowpOffsetContributionOutputStageKernel(const NEGEMMLowpOffsetContributionOutputStageKernel &) = delete; + /** Prevent instances of this class from being copied (As this class contains pointers)*/ + NEGEMMLowpOffsetContributionOutputStageKernel &operator=(const NEGEMMLowpOffsetContributionOutputStageKernel &) = delete; + /** Allow instances of this class to be moved */ + NEGEMMLowpOffsetContributionOutputStageKernel(NEGEMMLowpOffsetContributionOutputStageKernel &&) = default; + /** Allow instances of this class to be moved */ + NEGEMMLowpOffsetContributionOutputStageKernel &operator=(NEGEMMLowpOffsetContributionOutputStageKernel &&) = default; + /** Initialise the kernel's input and output. + * + * @param[in] mm_result Input tensor containing the result of @ref NEGEMMLowpMatrixMultiplyKernel. Data type supported: S32 + * @param[in] vector_sum_col Input row-vector of sums of all the entries in each column of matrix B. + * Note: vector_sum_col can be a nullptr in case a_offset = 0. Data type supported: same as @p mm_result + * @param[in] vector_sum_row Input row-vector of sums of all the entries in each row of matrix A. + * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the addition of biases is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p mm_result. + * @param[out] output Output tensor containing the final quantized result. Data type supported: QASYMM8 + * @param[in] k Number of matrix A columns or Matrix B rows + * @param[in] a_offset Offset to be added to each element of the matrix A. + * @param[in] b_offset Offset to be added to each element of the matrix B. + * @param[in] output_stage GEMMLowp output stage info, providing the type of quantization and the necessary parameters. + */ + void configure(const ITensor *mm_result, const ITensor *vector_sum_col, const ITensor *vector_sum_row, const ITensor *bias, ITensor *output, int32_t k, int32_t a_offset, int32_t b_offset, + GEMMLowpOutputStageInfo output_stage); + /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpOffsetContributionOutputStageKernel + * + * @param[in] mm_result Input tensor info containing the result of @ref NEGEMMLowpMatrixMultiplyKernel. Data type supported: S32 + * @param[in] vector_sum_col Tensor info for the input row-vector of sums of all the entries in each column of matrix B. + * Note: vector_sum_col can be a nullptr in case a_offset = 0. Data type supported: same as @p mm_result + * @param[in] vector_sum_row Tensor info for the input row-vector of sums of all the entries in each row of matrix A. + * Note: vector_sum_row can be a nullptr in case b_offset = 0. Data type supported: same as @p mm_result + * @param[in] bias Biases tensor info. Only shared biases supported and it can be a nullptr if the addition of biases is not required. + * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p mm_result. + * @param[in] output Output tensor info containing the final quantized result. Data type supported: QASYMM8 + * @param[in] a_offset Offset to be added to each element of the matrix A. + * @param[in] b_offset Offset to be added to each element of the matrix B. + * @param[in] output_stage GEMMLowp output stage info, providing the type of quantization and the necessary parameters. + * + * @return a status + */ + static Status validate(const ITensorInfo *mm_result, const ITensorInfo *vector_sum_col, const ITensorInfo *vector_sum_row, const ITensorInfo *bias, const ITensorInfo *output, int32_t a_offset, + int32_t b_offset, + GEMMLowpOutputStageInfo output_stage); + + // Inherited methods overridden: + void run(const Window &window, const ThreadInfo &info) override; + + using NEGEMMLowpOffsetContributionOutputStageFunction = std::function<void(const Window, const ITensor *, const ITensor *, const ITensor *, const ITensor *, + ITensor *, int32_t, int32_t, int32_t, bool, GEMMLowpOutputStageInfo)>; + +private: + /** Function to use for the particular tensors passed to configure() */ + NEGEMMLowpOffsetContributionOutputStageFunction _function; + const ITensor *_vector_sum_col; + const ITensor *_vector_sum_row; + const ITensor *_bias; + const ITensor *_mm_result; + ITensor *_output; + int32_t _a_offset; + int32_t _b_offset; + int32_t _k_offset; + bool _slide_vector_sum_col; + GEMMLowpOutputStageInfo _output_stage; +}; +} // namespace arm_compute + +#endif /* __ARM_COMPUTE_NEGEMMLOWPOFFSETCONTRIBUTIONOUTPUTSTAGEKERNEL_H__ */ |