| /* |
| * Copyright (c) 2017-2021 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 "src/core/gpu/cl/kernels/ClGemmLowpReductionKernel.h" |
| |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "arm_compute/core/KernelDescriptors.h" |
| |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| #include "support/Cast.h" |
| #include "support/StringSupport.h" |
| |
| namespace arm_compute |
| { |
| namespace opencl |
| { |
| namespace kernels |
| { |
| namespace |
| { |
| Status validate_arguments_matrix_a_reduction(const ITensorInfo *src, const ITensorInfo *dst) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM8); |
| |
| if(dst->total_size() > 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, 1, DataType::S32); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->dimension(0) != src->dimension(1), "Output vector must have length equal to the number of rows of the input matrix"); |
| } |
| return Status{}; |
| } |
| |
| Status validate_arguments_matrix_b_reduction(const ITensorInfo *src, const ITensorInfo *dst) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QSYMM8, DataType::QSYMM8_PER_CHANNEL); |
| |
| if(dst->total_size() > 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(dst, 1, DataType::S32); |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->dimension(0) != src->dimension(0), "Output vector must have length equal to the number of columns of the input matrix"); |
| } |
| return Status{}; |
| } |
| } // namespace |
| |
| IClGemmLowpReductionKernel::IClGemmLowpReductionKernel() |
| { |
| _type = CLKernelType::ELEMENTWISE; |
| } |
| |
| void ClGemmLowpMatrixAReductionKernel::configure(const CLCompileContext &compile_context, const ITensorInfo *mtx_a, ITensorInfo *vector_sum_row, const GEMMLowpReductionKernelInfo &info) |
| { |
| // Perform validate step |
| ARM_COMPUTE_ERROR_ON_NULLPTR(mtx_a, vector_sum_row); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_matrix_a_reduction(mtx_a, vector_sum_row)); |
| |
| // Output auto initialization if not yet initialized |
| auto_init_if_empty(*vector_sum_row, TensorShape(mtx_a->dimension(1)), 1, DataType::S32); |
| |
| auto padding_info = get_padding_info({ mtx_a, vector_sum_row }); |
| |
| // Set the arguments to pass at compile time |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DCOLS_A=" + support::cpp11::to_string(mtx_a->dimension(0))); |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(mtx_a->data_type())); |
| build_opts.add_option("-DACC_DATA_TYPE=" + get_cl_dot8_acc_type_from_data_type(mtx_a->data_type())); |
| build_opts.add_option_if(info.mul_by_scalar, "-DSCALAR=" + support::cpp11::to_string(info.scalar)); |
| |
| const bool is_dot8_supported = dot8_supported(CLKernelLibrary::get().get_device()); |
| |
| std::string kernel_name = "gemmlowp_matrix_a_reduction" + std::string(is_dot8_supported ? "_dot8" : ""); |
| |
| // Create kernel |
| _kernel = create_kernel(compile_context, kernel_name, build_opts.options()); |
| |
| // Configure kernel window |
| // This kernel does not need padding |
| Window win = calculate_max_window(*vector_sum_row, Steps()); |
| ICLKernel::configure_internal(win); |
| |
| _config_id = kernel_name; |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(mtx_a->dimension(0)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(mtx_a->dimension(1)); |
| _config_id += "_"; |
| _config_id += support::cpp11::to_string(mtx_a->dimension(2)); |
| |
| ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); |
| } |
| |
| Status ClGemmLowpMatrixAReductionKernel::validate(const ITensorInfo *mtx_a, const ITensorInfo *vector_sum_row, const GEMMLowpReductionKernelInfo &info) |
| { |
| ARM_COMPUTE_UNUSED(info); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_matrix_a_reduction(mtx_a, vector_sum_row)); |
| |
| return Status{}; |
| } |
| |
| void ClGemmLowpMatrixAReductionKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| |
| const auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC)); |
| auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); |
| |
| Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimY); |
| Window slice_in = collapsed.first_slice_window_2D(); |
| Window slice_out = collapsed.first_slice_window_2D(); |
| |
| // Setup input slice. Its dimensions are increased in the cl kernel. |
| slice_in.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| slice_in.set(Window::DimY, Window::Dimension(0, 0, 0)); |
| slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0)); |
| |
| do |
| { |
| unsigned int idx = 0; |
| add_3D_tensor_argument(idx, src, slice_in); |
| add_2D_tensor_argument(idx, dst, slice_out); |
| enqueue(queue, *this, slice_out, lws_hint()); |
| } |
| while(collapsed.slide_window_slice_2D(slice_out)); |
| } |
| |
| void ClGemmLowpMatrixBReductionKernel::configure(const CLCompileContext &compile_context, const ITensorInfo *mtx_b, ITensorInfo *vector_sum_col, const GEMMLowpReductionKernelInfo &info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(mtx_b, vector_sum_col); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_matrix_b_reduction(mtx_b, vector_sum_col)); |
| |
| // Output auto initialization if not yet initialized |
| auto_init_if_empty(*vector_sum_col, TensorShape(mtx_b->dimension(0)), 1, DataType::S32); |
| |
| auto padding_info = get_padding_info({ mtx_b, vector_sum_col }); |
| |
| const unsigned int num_elems_processed_per_iteration = adjust_vec_size(16, mtx_b->dimension(0)); |
| |
| // Set the arguments to pass at compile time |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(num_elems_processed_per_iteration)); |
| build_opts.add_option("-DVEC_SIZE_LEFTOVER=" + support::cpp11::to_string(mtx_b->dimension(0) % num_elems_processed_per_iteration)); |
| build_opts.add_option("-DCOLS_B=" + support::cpp11::to_string(mtx_b->dimension(0))); |
| build_opts.add_option("-DROWS_B=" + support::cpp11::to_string(mtx_b->dimension(1))); |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(mtx_b->data_type())); |
| build_opts.add_option("-DACC_DATA_TYPE=" + get_cl_dot8_acc_type_from_data_type(mtx_b->data_type())); |
| build_opts.add_option_if(info.mul_by_scalar, "-DSCALAR=" + support::cpp11::to_string(info.scalar)); |
| |
| // Create kernel |
| _kernel = create_kernel(compile_context, "gemmlowp_matrix_b_reduction", build_opts.options()); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*vector_sum_col, Steps(num_elems_processed_per_iteration)); |
| IClKernel::configure_internal(win); |
| |
| ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); |
| } |
| |
| Status ClGemmLowpMatrixBReductionKernel::validate(const ITensorInfo *mtx_b, const ITensorInfo *vector_sum_col, const GEMMLowpReductionKernelInfo &info) |
| { |
| ARM_COMPUTE_UNUSED(info); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_matrix_b_reduction(mtx_b, vector_sum_col)); |
| |
| return Status{}; |
| } |
| |
| void ClGemmLowpMatrixBReductionKernel::run_op(ITensorPack &tensors, const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| |
| const auto src = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_SRC)); |
| auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); |
| |
| Window collapsed = window.collapse_if_possible(IKernel::window(), Window::DimY); |
| |
| Window slice_out = collapsed.first_slice_window_2D(); |
| Window slice_in = slice_out; |
| |
| slice_in.set(Window::DimY, Window::Dimension(0, 0, 0)); |
| slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0)); |
| |
| do |
| { |
| unsigned int idx = 0; |
| add_3D_tensor_argument(idx, src, slice_in); |
| add_2D_tensor_argument(idx, dst, slice_out); |
| enqueue(queue, *this, slice_out, lws_hint()); |
| } |
| while(collapsed.slide_window_slice_2D(slice_out)); |
| } |
| } // namespace kernels |
| } // namespace opencl |
| } // namespace arm_compute |