| /* |
| * Copyright (c) 2017 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/GCGEMMMatrixAccumulateBiasesKernel.h" |
| |
| #include "arm_compute/core/AccessWindowStatic.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/Types.h" |
| #include "arm_compute/core/Utils.h" |
| #include "arm_compute/core/Validate.h" |
| |
| using namespace arm_compute; |
| |
| GCGEMMMatrixAccumulateBiasesKernel::GCGEMMMatrixAccumulateBiasesKernel() |
| : _accum(nullptr), _biases(nullptr) |
| { |
| } |
| |
| void GCGEMMMatrixAccumulateBiasesKernel::configure(IGCTensor *accum, const IGCTensor *biases) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(accum, 1, DataType::F16, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(biases, accum); |
| ARM_COMPUTE_ERROR_ON(biases->info()->num_dimensions() != 1); |
| |
| _biases = biases; |
| _accum = accum; |
| |
| std::set<std::string> build_opts; |
| 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)); |
| |
| // Create kernel |
| build_opts.emplace("#define GEMM_ACCUMULATE_BIASES"); |
| std::string dt_name = (accum->info()->data_type() == DataType::F32) ? "DATA_TYPE_FP32" : "DATA_TYPE_FP16"; |
| build_opts.emplace(("#define " + dt_name)); |
| _kernel = GCKernelLibrary::get().create_kernel("gemm_accumulate_biases", build_opts); |
| |
| // Configure kernel window |
| unsigned int num_elems_processed_per_iteration = 1; |
| |
| if(_accum->info()->data_type() == DataType::F32) |
| { |
| num_elems_processed_per_iteration = 16; |
| } |
| else if(_accum->info()->data_type() == DataType::F16) |
| { |
| num_elems_processed_per_iteration = 4; |
| } |
| |
| Window win = calculate_max_window(*_accum->info(), Steps(num_elems_processed_per_iteration)); |
| |
| AccessWindowStatic biases_access(biases->info(), 0, 0, ceil_to_multiple(biases->info()->dimension(0), num_elems_processed_per_iteration), biases->info()->dimension(1)); |
| AccessWindowHorizontal accum_access(_accum->info(), 0, num_elems_processed_per_iteration); |
| |
| update_window_and_padding(win, biases_access, accum_access); |
| |
| _kernel.clear_params(); |
| // set shader params binding point |
| _kernel.set_shader_params_binding_point(0); |
| |
| IGCKernel::configure(win); |
| } |
| |
| void GCGEMMMatrixAccumulateBiasesKernel::run(const Window &window) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_WINDOWS(IGCKernel::window(), window); |
| |
| _kernel.use(); |
| |
| 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; |
| if(_accum->info()->data_type() == DataType::F32) |
| { |
| add_2D_tensor_argument(idx, _accum, 1, accum_slice); |
| add_1D_tensor_argument(idx, _biases, 2, biases_slice); |
| } |
| else if(_accum->info()->data_type() == DataType::F16) |
| { |
| add_2D_tensor_argument(idx, _accum, BufferParam(1, 3), accum_slice); |
| add_1D_tensor_argument(idx, _biases, BufferParam(2, 3), biases_slice); |
| } |
| |
| _kernel.update_shader_params(); |
| |
| enqueue(*this, accum_slice); |
| } |
| while(window.slide_window_slice_2D(accum_slice)); |
| } |