| /* |
| * 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::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<Status, Window> 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(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<int>(idx++, -iq0_info.offset); |
| _kernel.setArg<int>(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 |