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Diffstat (limited to 'src/cpu/kernels/CpuGemmMatrixMultiplyKernel.cpp')
| -rw-r--r-- | src/cpu/kernels/CpuGemmMatrixMultiplyKernel.cpp | 213 |
1 files changed, 213 insertions, 0 deletions
diff --git a/src/cpu/kernels/CpuGemmMatrixMultiplyKernel.cpp b/src/cpu/kernels/CpuGemmMatrixMultiplyKernel.cpp new file mode 100644 index 0000000000..beccd94844 --- /dev/null +++ b/src/cpu/kernels/CpuGemmMatrixMultiplyKernel.cpp @@ -0,0 +1,213 @@ +/* + * Copyright (c) 2017-2022 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. + */ +#include "src/cpu/kernels/CpuGemmMatrixMultiplyKernel.h" + +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" +#include "arm_compute/core/Validate.h" + +#include "src/core/common/Registrars.h" +#include "src/core/CPP/Validate.h" +#include "src/core/helpers/AutoConfiguration.h" +#include "src/core/helpers/WindowHelpers.h" +#include "src/cpu/kernels/gemm_matrix_mul/list.h" + +namespace arm_compute +{ +namespace cpu +{ +namespace kernels +{ +namespace +{ +static const std::vector<CpuGemmMatrixMultiplyKernel::GemmMatrixMulKernel> available_kernels = { + {"neon_fp32_gemm_matrix_mul", [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F32); }, + REGISTER_FP32_NEON(neon_fp32_gemm_matrix_mul)}, + {"neon_fp16_gemm_matrix_mul", + [](const DataTypeISASelectorData &data) { return (data.dt == DataType::F16) && data.isa.fp16; }, + REGISTER_FP16_NEON(neon_fp16_gemm_matrix_mul)}, +}; + +inline Status validate_arguments(const ITensorInfo *lhs, + const ITensorInfo *rhs, + const ITensorInfo *dst, + float alpha, + bool is_interleaved, + const GEMMReshapeInfo &reshape_info) +{ + ARM_COMPUTE_UNUSED(alpha); + + ARM_COMPUTE_RETURN_ERROR_ON_CPU_F16_UNSUPPORTED(lhs); + ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(lhs, 1, DataType::F16, DataType::F32); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, rhs, dst); + + if (!is_interleaved) + { + ARM_COMPUTE_RETURN_ERROR_ON(lhs->dimension(0) != rhs->dimension(1)); + + if (dst->total_size() != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON(rhs->dimension(0) != dst->dimension(0)); + ARM_COMPUTE_RETURN_ERROR_ON(lhs->dimension(1) != dst->dimension(1)); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst); + } + } + else + { + const int m = reshape_info.m(); + const int n = reshape_info.n(); + const int k = reshape_info.k(); + const int mult_transpose1xW_width = reshape_info.mult_transpose1xW_width(); + const int mult_interleave4x4_height = reshape_info.mult_interleave4x4_height(); + + /* Interleave */ + TensorShape tensor_shape0{lhs->tensor_shape()}; + tensor_shape0.set(0, k); + tensor_shape0.set(1, m); + + const TensorInfo tensor_info0 = lhs->clone()->set_tensor_shape(tensor_shape0); + const TensorInfo tensor_info_reshaped0 = lhs->clone()->set_tensor_shape( + misc::shape_calculator::compute_interleaved_shape(tensor_info0, mult_interleave4x4_height)); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(lhs, &tensor_info_reshaped0); + + if (n != 0) /* Transpose */ + { + TensorShape tensor_shape1{rhs->tensor_shape()}; + tensor_shape1.set(0, n); + tensor_shape1.set(1, k); + + const TensorInfo tensor_info1 = rhs->clone()->set_tensor_shape(tensor_shape1); + const TensorInfo tensor_info_reshaped1 = + rhs->clone()->set_tensor_shape(misc::shape_calculator::compute_transpose1xW_with_element_size_shape( + tensor_info1, mult_transpose1xW_width)); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(rhs, &tensor_info_reshaped1); + } + + if (dst->total_size() != 0) + { + if (n != 0) + { + ARM_COMPUTE_RETURN_ERROR_ON(dst->dimension(0) != static_cast<size_t>(n)); + } + ARM_COMPUTE_RETURN_ERROR_ON(dst->dimension(1) != static_cast<size_t>(m)); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(lhs, dst); + } + } + + return Status{}; +} + +} // namespace + +void CpuGemmMatrixMultiplyKernel::configure(const ITensorInfo *lhs, + const ITensorInfo *rhs, + ITensorInfo *dst, + float alpha, + bool is_interleaved, + const GEMMReshapeInfo &reshape_info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(lhs, rhs, dst); + + // dst tensor auto inizialitation if not yet initialized + TensorShape tensor_shape{lhs->tensor_shape()}; + tensor_shape.set(0, is_interleaved ? reshape_info.n() : rhs->dimension(0)); + tensor_shape.set(1, is_interleaved ? reshape_info.m() : lhs->dimension(1)); + + auto_init_if_empty(*dst, lhs->clone()->set_tensor_shape(tensor_shape)); + + // Perform validate step + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(lhs, rhs, dst, alpha, is_interleaved, reshape_info)); + + _alpha = alpha; + + // Configure kernel window + Window win{}; + + // Check if the dst tensor is a vector. If so,the kernel runs the vector-matrix multiplication + const bool is_dst_vector = (dst->dimension(1) == 1); + if (is_dst_vector) + { + const unsigned int num_elems_processed_per_iteration_x = (lhs->data_type() == DataType::F32) ? 16 : 32; + + win = calculate_max_window(*dst, Steps(num_elems_processed_per_iteration_x)); + } + else + { + constexpr unsigned int num_elems_processed_per_iteration_x = 8; + constexpr unsigned int num_elems_processed_per_iteration_y = 4; + + win = + calculate_max_window(*dst, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); + } + + const auto uk = CpuGemmMatrixMultiplyKernel::get_implementation( + DataTypeISASelectorData{lhs->data_type(), CPUInfo::get().get_isa()}); + ARM_COMPUTE_ERROR_ON_NULLPTR(uk); + _func = uk->ukernel; + + ICPPKernel::configure(win); +} + +Status CpuGemmMatrixMultiplyKernel::validate(const ITensorInfo *lhs, + const ITensorInfo *rhs, + const ITensorInfo *dst, + float alpha, + bool is_interleaved, + const GEMMReshapeInfo &reshape_info) +{ + ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(lhs, rhs, dst, alpha, is_interleaved, reshape_info)); + + return Status{}; +} + +void CpuGemmMatrixMultiplyKernel::run_op(ITensorPack &tensors, const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window); + ARM_COMPUTE_ERROR_ON(tensors.empty()); + ARM_COMPUTE_ERROR_ON(_func == nullptr); + + const ITensor *lhs = tensors.get_const_tensor(TensorType::ACL_SRC_0); + const ITensor *rhs = tensors.get_const_tensor(TensorType::ACL_SRC_1); + ITensor *dst = tensors.get_tensor(TensorType::ACL_DST); + + const bool is_dst_vector = (dst->info()->dimension(1) == 1); + (*_func)(lhs, rhs, dst, window, info, _alpha, is_dst_vector); +} + +const char *CpuGemmMatrixMultiplyKernel::name() const +{ + return "CpuGemmMatrixMultiplyKernel"; +} + +const std::vector<CpuGemmMatrixMultiplyKernel::GemmMatrixMulKernel> & +CpuGemmMatrixMultiplyKernel::get_available_kernels() +{ + return available_kernels; +} +} // namespace kernels +} // namespace cpu +} // namespace arm_compute |