diff options
Diffstat (limited to 'src/core/GLES_COMPUTE/kernels/GCGEMMMatrixMultiplyKernel.cpp')
| -rw-r--r-- | src/core/GLES_COMPUTE/kernels/GCGEMMMatrixMultiplyKernel.cpp | 336 |
1 files changed, 0 insertions, 336 deletions
diff --git a/src/core/GLES_COMPUTE/kernels/GCGEMMMatrixMultiplyKernel.cpp b/src/core/GLES_COMPUTE/kernels/GCGEMMMatrixMultiplyKernel.cpp deleted file mode 100644 index 2a85e0d77d..0000000000 --- a/src/core/GLES_COMPUTE/kernels/GCGEMMMatrixMultiplyKernel.cpp +++ /dev/null @@ -1,336 +0,0 @@ -/* - * Copyright (c) 2017-2020 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. - */ -#include "arm_compute/core/GLES_COMPUTE/kernels/GCGEMMMatrixMultiplyKernel.h" - -#include "arm_compute/core/AccessWindowStatic.h" -#include "arm_compute/core/AccessWindowTranspose.h" -#include "arm_compute/core/Error.h" -#include "arm_compute/core/GLES_COMPUTE/GCHelpers.h" -#include "arm_compute/core/GLES_COMPUTE/GCKernelLibrary.h" -#include "arm_compute/core/GLES_COMPUTE/IGCTensor.h" -#include "arm_compute/core/GLES_COMPUTE/OpenGLES.h" -#include "arm_compute/core/Helpers.h" -#include "arm_compute/core/TensorInfo.h" -#include "arm_compute/core/Types.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/Validate.h" -#include "arm_compute/core/Window.h" -#include "arm_compute/core/utils/misc/ShapeCalculator.h" -#include "support/StringSupport.h" - -#include <set> -#include <string> - -using namespace arm_compute; -using namespace arm_compute::misc::shape_calculator; - -namespace -{ -using ElementsProcessed = Steps; - -inline Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info) -{ - ARM_COMPUTE_UNUSED(reshape_info); - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input0, input1, output); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::F16, DataType::F32); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1); - ARM_COMPUTE_RETURN_ERROR_ON_MSG(input1->num_dimensions() > 3, "The number of dimensions for the matrix B must be <= 3"); - - if(!is_interleaved_transposed) - { - ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(0) != input1->dimension(1)); - - if(output->total_size() != 0) - { - ARM_COMPUTE_RETURN_ERROR_ON(input1->dimension(0) != output->dimension(0)); - ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(1) != output->dimension(1)); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output); - } - } - 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(); - - TensorShape tensor_shape0{ input0->tensor_shape() }; - tensor_shape0.set(0, k); - tensor_shape0.set(1, m); - - TensorShape tensor_shape1{ input1->tensor_shape() }; - tensor_shape1.set(0, n); - tensor_shape1.set(1, k); - - const TensorInfo tensor_info0 = input0->clone()->set_tensor_shape(tensor_shape0); - const TensorInfo tensor_info1 = input1->clone()->set_tensor_shape(tensor_shape1); - - const TensorInfo tensor_info_reshaped0 = input0->clone()->set_tensor_shape(compute_interleaved_shape(tensor_info0, mult_interleave4x4_height)); - const TensorInfo tensor_info_reshaped1 = input1->clone()->set_tensor_shape(compute_transpose1xW_with_element_size_shape(tensor_info1, mult_transpose1xW_width)); - - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input0, &tensor_info_reshaped0); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input1, &tensor_info_reshaped1); - - if(output->total_size() != 0) - { - ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(0) != static_cast<size_t>(n)); - ARM_COMPUTE_RETURN_ERROR_ON(output->dimension(1) != static_cast<size_t>(m)); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, output); - } - } - - return Status{}; -} - -inline std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *output, - bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info, - GPUTarget gpu_target, ElementsProcessed &num_elements_processed) -{ - ARM_COMPUTE_UNUSED(gpu_target); - - // Output tensor auto inizialitation if not yet initialized - TensorShape tensor_shape{ input0->tensor_shape() }; - tensor_shape.set(0, is_interleaved_transposed ? reshape_info.n() : input1->dimension(0)); - tensor_shape.set(1, is_interleaved_transposed ? reshape_info.m() : input0->dimension(1)); - - auto_init_if_empty(*output, input0->clone()->set_tensor_shape(tensor_shape)); - - bool window_changed = false; - Window win{}; - - const DataType data_type = input0->data_type(); - unsigned int &num_elems_processed_per_iteration_x = num_elements_processed[0]; - unsigned int &num_elems_processed_per_iteration_y = num_elements_processed[1]; - - if(is_interleaved_transposed) - { - // Configure window kernel - num_elems_processed_per_iteration_x = max_gc_vector_width / data_size_from_type(data_type); - num_elems_processed_per_iteration_y = 4; - - win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); - - AccessWindowRectangle input0_access(input0, 0, 0, num_elems_processed_per_iteration_y, 1, 1.f, 0.25f); - AccessWindowTranspose input1_access(input1, 0, 0, num_elems_processed_per_iteration_x, 1, 0.f, 0.25f); - AccessWindowRectangle output_access(output, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y); - - update_window_and_padding(win, input0_access, input1_access, output_access); - - output_access.set_valid_region(win, ValidRegion(Coordinates(), output->tensor_shape())); - } - else // The input tensors have not been reshaped - { - // Special case for 1xN, 2xN, 3xN and 4xN input0 tensor. - num_elems_processed_per_iteration_y = std::min(static_cast<int>(output->dimension(1)), 4); - - switch(data_type) - { - case DataType::F16: - num_elems_processed_per_iteration_x = 4; - break; - - case DataType::F32: - num_elems_processed_per_iteration_x = max_gc_vector_width / data_size_from_type(data_type); - break; - - default: - ARM_COMPUTE_ERROR("Current data type is not supported"); - break; - } - - win = calculate_max_window(*output, Steps(num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y)); - - AccessWindowStatic input0_access(input0, 0, 0, ceil_to_multiple(input0->dimension(0), 8), ceil_to_multiple(input0->dimension(1), num_elems_processed_per_iteration_y)); - AccessWindowStatic input1_access(input1, 0, 0, ceil_to_multiple(input1->dimension(0), num_elems_processed_per_iteration_x), input1->dimension(1)); - AccessWindowRectangle output_access(output, 0, 0, num_elems_processed_per_iteration_x, num_elems_processed_per_iteration_y); - - update_window_and_padding(win, input0_access, input1_access, output_access); - - Coordinates coord; - coord.set_num_dimensions(output->num_dimensions()); - output_access.set_valid_region(win, ValidRegion(coord, output->tensor_shape())); - } - - Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; - return std::make_pair(err, win); -} -} // namespace - -GCGEMMMatrixMultiplyKernel::GCGEMMMatrixMultiplyKernel() - : _input0(nullptr), _input1(nullptr), _output(nullptr) -{ -} - -void GCGEMMMatrixMultiplyKernel::configure(const IGCTensor *input0, const IGCTensor *input1, IGCTensor *output, float alpha, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output); - - // Perform validate step - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info(), is_interleaved_transposed, reshape_info)); - - _input0 = input0; - _input1 = input1; - _output = output; - - // Get target architecture - GPUTarget gpu_target = get_target(); - - ElementsProcessed num_elements_processed{}; - - // Configure kernel window - auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info(), is_interleaved_transposed, reshape_info, gpu_target, num_elements_processed); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - IGCKernel::configure(win_config.second); - - // Create build options - std::set<std::string> build_opts; - std::string kernel_name; - - build_opts.emplace("#define LOCAL_SIZE_X " + support::cpp11::to_string(1)); - build_opts.emplace("#define LOCAL_SIZE_Y " + support::cpp11::to_string(1)); - build_opts.emplace("#define LOCAL_SIZE_Z " + support::cpp11::to_string(1)); - build_opts.emplace("#define COLS_A " + support::cpp11::to_string(input0->info()->dimension(0))); - build_opts.emplace("#define COLS_B " + support::cpp11::to_string(input1->info()->dimension(0))); - build_opts.emplace("#define ALPHA " + float_to_string_with_full_precision(alpha)); - - // Check if the output tensor is a vector. If so,the kernel runs the vector-matrix multiplication - if(is_interleaved_transposed) - { - const int mult_transpose1xW_width = reshape_info.mult_transpose1xW_width(); - const int mult_interleave4x4_height = reshape_info.mult_interleave4x4_height(); - - build_opts.emplace("#define MULT_TRANSPOSE1XW_WIDTH " + support::cpp11::to_string(mult_transpose1xW_width)); - build_opts.emplace("#define MULT_INTERLEAVE4X4_HEIGHT " + support::cpp11::to_string(mult_interleave4x4_height)); - - switch(input0->info()->data_type()) - { - case DataType::F16: - build_opts.emplace("#define DATA_TYPE_FP16"); - break; - - case DataType::F32: - build_opts.emplace("#define DATA_TYPE_FP32"); - break; - - default: - ARM_COMPUTE_ERROR("Current data type is not supported"); - break; - } - - build_opts.emplace("#define GEMM_MM_INTERLEAVED_TRANSPOSED"); - - kernel_name = "gemm_mm_interleaved_transposed"; - } - else - { - // Special case for 1xN, 2xN, 3xN and 4xN input0 tensor - - GPUTarget arch_target = get_arch_from_target(gpu_target); - switch(input0->info()->data_type()) - { - case DataType::F16: - build_opts.emplace("#define DATA_TYPE_FP16"); - build_opts.emplace("#define MM_PROCESS_4X_OPTIMIZED"); - build_opts.emplace("#define GEMM_MM_FLOATING_POINT"); - break; - - case DataType::F32: - build_opts.emplace("#define DATA_TYPE_FP32"); - - if(arch_target == GPUTarget::BIFROST && input0->info()->num_dimensions() != 1) - { - build_opts.emplace("#define GEMM_MM_FLOATING_POINT_BIFROST"); - } - else - { - build_opts.emplace("#define GEMM_MM_FLOATING_POINT"); - } - break; - - default: - ARM_COMPUTE_ERROR("Current data type is not supported"); - break; - } - - build_opts.emplace("#define NUM_ELEMS_PROCESSED_PER_THREAD_X " + support::cpp11::to_string(num_elements_processed.x())); - build_opts.emplace("#define NUM_ELEMS_PROCESSED_PER_THREAD_Y " + support::cpp11::to_string(num_elements_processed.y())); - - kernel_name = "gemm_mm_floating_point"; - } - - // Create kernel - _kernel = GCKernelLibrary::get().create_kernel(kernel_name, build_opts); -} - -Status GCGEMMMatrixMultiplyKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, bool is_interleaved_transposed, - const GEMMReshapeInfo &reshape_info, GPUTarget gpu_target) -{ - ARM_COMPUTE_UNUSED(alpha); - ElementsProcessed num_elements_processed{}; - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output, is_interleaved_transposed, reshape_info)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(), - input1->clone().get(), - output->clone().get(), - is_interleaved_transposed, - reshape_info, - gpu_target, - num_elements_processed) - .first); - return Status{}; -} - -void GCGEMMMatrixMultiplyKernel::run(const Window &window) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IGCKernel::window(), window); - - _kernel.use(); - - Window slice = window.first_slice_window_2D(); - Window slice_matrix_b = slice; - - slice_matrix_b.set(Window::DimX, Window::Dimension(0, 1, 1)); - slice_matrix_b.set(Window::DimY, Window::Dimension(0, 1, 1)); - - do - { - Window slice_b = slice; - // Don't slice matrix B along the z dimension if matrix B has just 2 dimensions and matrix A more than 2 - // This scenario can happen when the the matrix multiplication is used to perform a convolution operation - if(_input1->info()->num_dimensions() < 3) - { - slice_b = slice_matrix_b; - } - - unsigned int idx = 0; - - add_2D_tensor_argument(idx, _input0, 1, slice); - add_2D_tensor_argument(idx, _input1, 2, slice_b); - add_2D_tensor_argument(idx, _output, 3, slice); - _kernel.update_shader_params(); - enqueue(*this, slice); - } - while(window.slide_window_slice_2D(slice)); -} |