/* * 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/CL/kernels/CLGEMMMatrixVectorMultiplyKernel.h" #include "arm_compute/core/AccessWindowStatic.h" #include "arm_compute/core/CL/CLHelpers.h" #include "arm_compute/core/CL/CLKernelLibrary.h" #include "arm_compute/core/CL/CLValidate.h" #include "arm_compute/core/CL/ICLTensor.h" #include "arm_compute/core/CL/OpenCL.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/Types.h" #include "support/StringSupport.h" namespace arm_compute { namespace { constexpr unsigned int num_elems_read_per_iteration = 4; constexpr unsigned int num_rows_read_per_iteration = 4; Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output) { ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input0); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1); ARM_COMPUTE_RETURN_ERROR_ON(is_data_type_quantized_asymmetric(input0->data_type()) && (output->data_type() != DataType::S32)); ARM_COMPUTE_RETURN_ERROR_ON(input0->dimension(2) != input1->dimension(1)); return Status{}; } std::pair validate_and_configure_window(ITensorInfo *input0, ITensorInfo *input1, ITensorInfo *output) { const unsigned int border_x = ceil_to_multiple(input0->dimension(0), num_elems_read_per_iteration) - input0->dimension(0); const unsigned int border_y = ceil_to_multiple(input0->dimension(1), num_rows_read_per_iteration) - input0->dimension(1); Window win = calculate_max_window(*input0, Steps(num_elems_read_per_iteration)); AccessWindowRectangle input0_access(input0, 0, 0, num_elems_read_per_iteration, num_rows_read_per_iteration); AccessWindowHorizontal input1_access(input1, 0, num_elems_read_per_iteration); AccessWindowStatic output_access(output, 0, 0, output->dimension(0) + border_x, output->dimension(1) + border_y); bool window_changed = update_window_and_padding(win, input0_access, input1_access, output_access); output->set_valid_region(ValidRegion(Coordinates(), output->tensor_shape())); Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_pair(err, win); } } // namespace CLGEMMMatrixVectorMultiplyKernel::CLGEMMMatrixVectorMultiplyKernel() : _input0(nullptr), _input1(nullptr), _output(nullptr), _num_rows_read_per_iteration(0), _border_size(0) { } BorderSize CLGEMMMatrixVectorMultiplyKernel::border_size() const { return _border_size; } void CLGEMMMatrixVectorMultiplyKernel::configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output) { configure(CLKernelLibrary::get().get_compile_context(), input0, input1, output); } void CLGEMMMatrixVectorMultiplyKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output) { ARM_COMPUTE_ERROR_ON_NULLPTR(input0, input1, output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input0->info(), input1->info(), output->info())); _input0 = input0; _input1 = input1; _output = output; // Check if is a quantized operation const bool is_quantized = is_data_type_quantized_asymmetric(_input0->info()->data_type()); // Create kernel CLBuildOptions build_opts; build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(input0->info()->data_type())); build_opts.add_option("-DSRC_WIDTH=" + support::cpp11::to_string(input0->info()->dimension(0))); build_opts.add_option("-DSRC_HEIGHT=" + support::cpp11::to_string(input0->info()->dimension(1))); std::string kernel_name = is_quantized ? std::string("gemm_mv_quantized") : std::string("gemm_mv"); _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); // Add static arguments if(is_quantized) { const UniformQuantizationInfo iq0_info = _input0->info()->quantization_info().uniform(); const UniformQuantizationInfo iq1_info = _input1->info()->quantization_info().uniform(); unsigned int idx = num_arguments_per_3D_tensor() + num_arguments_per_2D_tensor() + num_arguments_per_1D_tensor(); _kernel.setArg(idx++, -iq0_info.offset); _kernel.setArg(idx++, -iq1_info.offset); } // Configure kernel window _num_rows_read_per_iteration = num_rows_read_per_iteration; const unsigned int border_x = ceil_to_multiple(input0->info()->dimension(0), num_elems_read_per_iteration) - input0->info()->dimension(0); const unsigned int border_y = ceil_to_multiple(input0->info()->dimension(1), _num_rows_read_per_iteration) - input0->info()->dimension(1); _border_size = BorderSize(border_y, border_x); auto win_config = validate_and_configure_window(input0->info(), input1->info(), output->info()); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICLKernel::configure_internal(win_config.second); } Status CLGEMMMatrixVectorMultiplyKernel::validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input0, input1, output)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input0->clone().get(), input1->clone().get(), output->clone().get()).first); return Status{}; } void CLGEMMMatrixVectorMultiplyKernel::run(const Window &window, cl::CommandQueue &queue) { ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window); Window slice_in = window.first_slice_window_3D(); Window slice_in2 = window.first_slice_window_3D(); Window slice_out = window.first_slice_window_3D(); // Setup input0 slice slice_in.set(Window::DimX, Window::Dimension(0, _input0->info()->dimension(0), _input0->info()->dimension(0))); slice_in.set(Window::DimY, Window::Dimension(0, _input0->info()->dimension(1) + border_size().bottom, _num_rows_read_per_iteration)); slice_in.set(Window::DimZ, Window::Dimension(0, _input0->info()->dimension(2), 1)); // Setup input1 and output slice. Their dimensions are increased in the cl kernel. slice_in2.set(Window::DimX, Window::Dimension(0, 0, 0)); slice_in2.set(Window::DimY, Window::Dimension(0, 0, 0)); slice_in2.set(Window::DimZ, Window::Dimension(0, 0, 0)); slice_out.set(Window::DimX, Window::Dimension(0, 0, 0)); slice_out.set(Window::DimY, Window::Dimension(0, 0, 0)); slice_out.set(Window::DimZ, Window::Dimension(0, 0, 0)); unsigned int idx_1 = num_arguments_per_3D_tensor(); add_2D_tensor_argument(idx_1, _input1, slice_in2); do { unsigned int idx_0 = 0; unsigned int idx_2 = num_arguments_per_3D_tensor() + num_arguments_per_2D_tensor(); add_3D_tensor_argument(idx_0, _input0, slice_in); add_1D_tensor_argument(idx_2, _output, slice_out); enqueue(queue, *this, slice_in, lws_hint()); } while(window.slide_window_slice_3D(slice_in) && window.slide_window_slice_3D(slice_out)); } } // namespace arm_compute