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/*
* Copyright (c) 2019-2020 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_CLGEMMLOWPMATRIXMULTIPLYRESHAPEDONLYRHSKERNEL_H
#define ARM_COMPUTE_CLGEMMLOWPMATRIXMULTIPLYRESHAPEDONLYRHSKERNEL_H
#include "arm_compute/core/CL/ICLKernel.h"
#include "arm_compute/core/KernelDescriptors.h"
namespace arm_compute
{
class ICLTensor;
/** OpenCL kernel to multiply matrices with QASYMM8 data type when only the input matrix RHS (input1) has been reshaped
*
* @note The input matrix input1 must be reshaped through @ref CLGEMMReshapeRHSMatrixKernel
* @note For fused output stage, only GEMMLowpOutputStageType::QUANTIZE_DOWN_FIXEDPOINT type is supported
*/
class CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel : public ICLKernel
{
public:
/** Default Constructor */
CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel();
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel(const CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel &) = delete;
/** Prevent instances of this class from being copied (As this class contains pointers) */
CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel &operator=(const CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel &) = delete;
/** Allow instances of this class to be moved */
CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel(CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel &&) = default;
/** Allow instances of this class to be moved */
CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel &operator=(CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel &&) = default;
/** Initialise the kernel's input and output.
*
* @param[in] input0 Input tensor containing the LHS matrix. Data type supported: QASYMM8/QASYMM8_SIGNED
* @param[in] input1 Input tensor containing the RHS reshaped matrix. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL
* @param[out] output Output tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/S32.
* @param[in] gemm_info GEMM information used to retrieve the original dimensions of the input matrices, output stage information and RHS/LHS info.
* Only the following values are supported for LHS info:
* lhs_info.m0: 2,3,4,5,6,7,8
* lhs_info.k0: 2,3,4,8,16
* Only the following values are supported for RHS info:
* rhs_info.n0: 2,3,4,8,16
* rhs_info.k0: same as lhs_info.k0
* rhs_info.transpose: true
* @param[in] vector_sum_col (Optional) 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: S32
* @param[in] vector_sum_row (Optional) 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: S32
* @param[in] bias (Optional) 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: S32.
* @param[in] output_multipliers (Optional) Output multipliers tensor. In case of per-channel quantization, the number of multipliers must be equal to the number of filters (OFM).
* Supported data types: S32.
* @param[in] output_shifts (Optional) Output shifts tensor. In case of per-channel quantization, the number of multipliers must be equal to the number of filters (OFM).
* Supported data types: S32.
*/
void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMKernelInfo &gemm_info, const ICLTensor *vector_sum_col = nullptr,
const ICLTensor *vector_sum_row = nullptr, const ICLTensor *bias = nullptr, const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr);
/** Initialise the kernel's input and output.
*
* @param[in] compile_context The compile context to be used.
* @param[in] input0 Input tensor containing the LHS matrix. Data type supported: QASYMM8/QASYMM8_SIGNED
* @param[in] input1 Input tensor containing the RHS reshaped matrix. Data type supported: same as @p input0
* @param[out] output Output tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/S32.
* @param[in] gemm_info GEMM information used to retrieve the original dimensions of the input matrices, output stage information and RHS/LHS info.
* Only the following values are supported for LHS info:
* lhs_info.m0: 2,3,4,5,6,7,8
* lhs_info.k0: 2,3,4,8,16
* Only the following values are supported for RHS info:
* rhs_info.n0: 2,3,4,8,16
* rhs_info.k0: same as lhs_info.k0
* rhs_info.transpose: true
* @param[in] vector_sum_col (Optional) 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: S32
* @param[in] vector_sum_row (Optional) 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: S32
* @param[in] bias (Optional) 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: S32.
* @param[in] output_multipliers (Optional) Output multipliers tensor. In case of per-channel quantization, the number of multipliers must be equal to the number of filters (OFM).
* Supported data types: S32.
* @param[in] output_shifts (Optional) Output shifts tensor. In case of per-channel quantization, the number of multipliers must be equal to the number of filters (OFM).
* Supported data types: S32.
*/
void configure(const CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, const GEMMKernelInfo &gemm_info, const ICLTensor *vector_sum_col = nullptr,
const ICLTensor *vector_sum_row = nullptr, const ICLTensor *bias = nullptr, const ICLTensor *output_multipliers = nullptr, const ICLTensor *output_shifts = nullptr);
/** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixMultiplyReshapedOnlyRHSKernel
*
* @param[in] input0 Input tensor info for the LHS matrix. Data type supported: QASYMM8/QASYMM8_SIGNED
* @param[in] input1 Input tensor info for the RHS reshaped matrix. Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM8/QSYMM8_PER_CHANNEL
* @param[in] output Output tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/S32.
* @param[in] gemm_info GEMM information used to retrieve the original dimensions of the input matrices, output stage information and RHS/LHS info.
* Only the following values are supported for LHS info:
* lhs_info.m0: 2,3,4,5,6,7,8
* lhs_info.k0: 2,3,4,8,16
* Only the following values are supported for RHS info:
* rhs_info.n0: 2,3,4,8,16
* rhs_info.k0: same as lhs_info.k0
* rhs_info.transpose: true
* @param[in] vector_sum_col (Optional) Input row-vector 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: S32
* @param[in] vector_sum_row (Optional) Input row-vector info 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: S32
* @param[in] bias (Optional) 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: S32.
* @param[in] output_multipliers (Optional) Output multipliers tensor info. In case of per-channel quantization, the number of multipliers must be equal to the number of filters (OFM).
* Supported data types: S32.
* @param[in] output_shifts (Optional) Output shifts tensor info. In case of per-channel quantization, the number of multipliers must be equal to the number of filters (OFM).
* Supported data types: S32.
*
* @return a status
*/
static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, const GEMMKernelInfo &gemm_info, const ITensorInfo *vector_sum_col = nullptr,
const ITensorInfo *vector_sum_row = nullptr, const ITensorInfo *bias = nullptr, const ITensorInfo *output_multipliers = nullptr,
const ITensorInfo *output_shifts = nullptr);
// Inherited methods overridden:
void run(const Window &window, cl::CommandQueue &queue) override;
private:
const ICLTensor *_input0;
const ICLTensor *_input1;
ICLTensor *_output;
const ICLTensor *_vector_sum_col;
const ICLTensor *_vector_sum_row;
const ICLTensor *_bias;
const ICLTensor *_output_multipliers;
const ICLTensor *_output_shifts;
bool _slide_matrix_b;
bool _reinterpret_input_as_3d;
bool _reinterpret_output_as_3d;
bool _use_dummy_work_items;
bool _is_quantized_per_channel;
bool _fuse_output_stage;
};
} // namespace arm_compute
#endif /* ARM_COMPUTE_CLGEMMLOWPMATRIXMULTIPLYRESHAPEDONLYRHSKERNEL_H */
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