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-/*
- * Copyright (c) 2019-2021 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_CPU_GEMMLOWP_OFFSETCONTRIBUTION_OUTPUTSTAGE_KERNEL_H
-#define ARM_COMPUTE_CPU_GEMMLOWP_OFFSETCONTRIBUTION_OUTPUTSTAGE_KERNEL_H
-
-#include "arm_compute/core/KernelDescriptors.h"
-#include "src/core/common/Macros.h"
-#include "src/core/cpu/ICpuKernel.h"
-
-namespace arm_compute
-{
-namespace cpu
-{
-namespace kernels
-{
-/** Kernel used to add the offset contribution and perform the output stage after @ref CpuGemmLowpMatrixMultiplyKernel.
- *
- * The computation is performed in-place
- *
- * This kernel takes a final int32 accumulator value (the output of @ref CpuGemmLowpMatrixMultiplyKernel),
- * 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 Uint8.
- * The output stage can perform either QuantizeDownInt32ToInt8Scale or QuantizeDownInt32ToInt8ScaleByFixedPoint for Int8.
- *
- * For QuantizeDownInt32ToUint8Scale/QuantizeDownInt32ToInt8Scale the final result is:
- *
- * ((mm_result'[i][k] + result_offset) * result_mult_int) >> result_shift
- *
- * For QuantizeDownInt32ToUint8ScaleByFixedPoint/QuantizeDownInt32ToInt8ScaleByFixedPoint 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 CpuGemmLowpOffsetContributionOutputStageKernel : public ICpuKernel
-{
-public:
- /** Default constructor */
- CpuGemmLowpOffsetContributionOutputStageKernel() = default;
- ARM_COMPUTE_DISALLOW_COPY_ALLOW_MOVE(CpuGemmLowpOffsetContributionOutputStageKernel);
- /** Initialise the kernel inputs and output.
- *
- * @param[in] mm_result Input tensor info containing the result of @ref CpuGemmLowpMatrixMultiplyKernel. Data type supported: S32
- * @param[in] vector_sum_col Input row-vector tensor info 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 tensor info of sums of all the entries in each row of matrix A.
- * @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[out] dst Output tensor info containing the final quantized result. Data type supported: QASYMM8/QASYMM8_SIGNED
- * @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 ITensorInfo *mm_result, const ITensorInfo *vector_sum_col, const ITensorInfo *vector_sum_row, const ITensorInfo *bias, ITensorInfo *dst, 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
- *
- * Similar to CpuGemmLowpOffsetContributionOutputStageKernel::configure()
- *
- * @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 *dst, int32_t a_offset,
- int32_t b_offset,
- GEMMLowpOutputStageInfo output_stage);
-
- // Inherited methods overridden:
- void run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) override;
- const char *name() const override;
-
-private:
- /** Function to use for the particular tensors passed to configure() */
- int32_t _a_offset{ 0 };
- int32_t _b_offset{ 0 };
- int32_t _k_offset{ 0 };
- bool _slide_vector_sum_col{ true };
- GEMMLowpOutputStageInfo _output_stage{ GEMMLowpOutputStageInfo() };
-};
-} // namespace kernels
-} // namespace cpu
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_CPU_GEMMLOWP_OFFSETCONTRIBUTION_OUTPUTSTAGE_KERNEL_H */