| /* |
| * 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/CLGEMMMatrixAccumulateBiasesKernel.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 "arm_compute/core/Utils.h" |
| #include "support/StringSupport.h" |
| |
| using namespace arm_compute; |
| |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *accum, const ITensorInfo *biases) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(accum); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::F16, DataType::F32); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(biases, accum); |
| ARM_COMPUTE_RETURN_ERROR_ON(biases->num_dimensions() != 1); |
| |
| return Status{}; |
| } |
| |
| std::pair<Status, Window> validate_and_configure_window(ITensorInfo *accum, ITensorInfo *biases, GPUTarget gpu_target, |
| unsigned int &num_elems_processed_per_iteration) |
| { |
| // Select the vector size to use (8 for Bifrost; 16 for Midgard). |
| bool is_gpu_bifrost = gpu_target_is_in(gpu_target, |
| GPUTarget::G71, GPUTarget::G72, GPUTarget::G76, |
| GPUTarget::G51, GPUTarget::G51BIG, GPUTarget::G51LIT, |
| GPUTarget::G52, GPUTarget::G52LIT); |
| num_elems_processed_per_iteration = is_gpu_bifrost ? 8 : 16; |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*accum, Steps(num_elems_processed_per_iteration)); |
| |
| AccessWindowStatic biases_access(biases, 0, 0, ceil_to_multiple(biases->dimension(0), num_elems_processed_per_iteration), biases->dimension(1)); |
| AccessWindowHorizontal accum_access(accum, 0, num_elems_processed_per_iteration); |
| |
| bool window_changed = update_window_and_padding(win, biases_access, accum_access); |
| |
| Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; |
| return std::make_pair(err, win); |
| } |
| } // namespace |
| |
| CLGEMMMatrixAccumulateBiasesKernel::CLGEMMMatrixAccumulateBiasesKernel() |
| : _accum(nullptr), _biases(nullptr) |
| { |
| } |
| |
| void CLGEMMMatrixAccumulateBiasesKernel::configure(ICLTensor *accum, const ICLTensor *biases) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), accum, biases); |
| } |
| |
| void CLGEMMMatrixAccumulateBiasesKernel::configure(const CLCompileContext &compile_context, ICLTensor *accum, const ICLTensor *biases) |
| { |
| // Perform validate step |
| ARM_COMPUTE_ERROR_ON_NULLPTR(accum, biases); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(accum->info(), biases->info())); |
| |
| _biases = biases; |
| _accum = accum; |
| |
| // Get the target gpu |
| GPUTarget gpu_target = get_target(); |
| unsigned int vector_size = 0; |
| |
| // Configure kernel window |
| auto win_config = validate_and_configure_window(accum->info(), biases->info(), gpu_target, vector_size); |
| ARM_COMPUTE_ERROR_THROW_ON(win_config.first); |
| ICLKernel::configure_internal(win_config.second); |
| |
| // Add build options |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(accum->info()->data_type())); |
| build_opts.add_option("-DVECTOR_SIZE=" + support::cpp11::to_string(vector_size)); |
| |
| // Create kernel |
| _kernel = create_kernel(compile_context, "gemm_accumulate_biases", build_opts.options()); |
| } |
| |
| Status CLGEMMMatrixAccumulateBiasesKernel::validate(const ITensorInfo *accum, const ITensorInfo *biases, GPUTarget gpu_target) |
| { |
| unsigned int num_elems_processed_per_iteration = 0; |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(accum, biases)); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(accum->clone().get(), biases->clone().get(), gpu_target, num_elems_processed_per_iteration).first); |
| |
| return Status{}; |
| } |
| |
| void CLGEMMMatrixAccumulateBiasesKernel::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(ICLKernel::window(), window); |
| |
| Window accum_slice = window.first_slice_window_2D(); |
| |
| Window biases_slice(accum_slice); |
| biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1)); |
| |
| // Run kernel |
| do |
| { |
| // Set arguments |
| unsigned int idx = 0; |
| add_2D_tensor_argument(idx, _accum, accum_slice); |
| add_1D_tensor_argument(idx, _biases, biases_slice); |
| |
| enqueue(queue, *this, accum_slice, lws_hint()); |
| } |
| while(window.slide_window_slice_2D(accum_slice)); |
| } |