| /* |
| * Copyright (c) 2020-2021 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/ClGemmLowpQuantizeDownInt32ScaleKernel.h" |
| |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/utils/quantization/AsymmHelpers.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(const ITensorInfo *src, const ITensorInfo *bias, const ITensorInfo *dst, const GEMMLowpOutputStageInfo *output_stage) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(src, 1, DataType::S32); |
| ARM_COMPUTE_RETURN_ERROR_ON((output_stage->output_data_type != DataType::QASYMM8) && (output_stage->output_data_type != DataType::QASYMM8_SIGNED)); |
| ARM_COMPUTE_RETURN_ERROR_ON(output_stage->gemmlowp_max_bound > std::get<1>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type))); |
| ARM_COMPUTE_RETURN_ERROR_ON(output_stage->gemmlowp_min_bound < std::get<0>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type)) |
| || output_stage->gemmlowp_min_bound > output_stage->gemmlowp_max_bound); |
| |
| // Check biases if exist |
| if(bias != nullptr) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(src, bias); |
| ARM_COMPUTE_RETURN_ERROR_ON(bias->num_dimensions() > 1); |
| ARM_COMPUTE_RETURN_ERROR_ON(src->dimension(0) != bias->dimension(0)); |
| } |
| |
| if(dst->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_MSG(dst->data_type() != output_stage->output_data_type, "Mismatching output data type"); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(src, dst); |
| } |
| |
| return Status{}; |
| } |
| } //namespace |
| |
| ClGemmLowpQuantizeDownInt32ScaleKernel::ClGemmLowpQuantizeDownInt32ScaleKernel() |
| { |
| _type = CLKernelType::ELEMENTWISE; |
| } |
| |
| Status ClGemmLowpQuantizeDownInt32ScaleKernel::validate(const ITensorInfo *src, const ITensorInfo *bias, const ITensorInfo *dst, const GEMMLowpOutputStageInfo *output_stage) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(src, bias, dst, output_stage)); |
| |
| return Status{}; |
| } |
| |
| void ClGemmLowpQuantizeDownInt32ScaleKernel::configure(const CLCompileContext &compile_context, const ITensorInfo *src, const ITensorInfo *bias, ITensorInfo *dst, |
| const GEMMLowpOutputStageInfo *output_stage) |
| { |
| // Perform validate step |
| ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(src, bias, dst, output_stage)); |
| |
| auto padding_info = get_padding_info({ src, bias, dst }); |
| |
| // Output auto inizialitation if not yet initialized |
| auto_init_if_empty(*dst, src->clone()->set_data_type(output_stage->output_data_type)); |
| |
| const unsigned int num_elems_processed_per_iteration = adjust_vec_size(4, src->dimension(0)); |
| |
| // Set the arguments to pass at compile time |
| auto min = output_stage->gemmlowp_min_bound; |
| auto max = output_stage->gemmlowp_max_bound; |
| 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(src->dimension(0) % num_elems_processed_per_iteration)); |
| build_opts.add_option("-DRESULT_OFFSET=" + support::cpp11::to_string(output_stage->gemmlowp_offset)); |
| build_opts.add_option("-DRESULT_MULT_INT=" + support::cpp11::to_string(output_stage->gemmlowp_multiplier)); |
| build_opts.add_option("-DRESULT_SHIFT=" + support::cpp11::to_string(output_stage->gemmlowp_shift)); |
| build_opts.add_option_if((min > std::get<0>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type))) && (min != max), |
| "-DMIN_BOUND=" + support::cpp11::to_string(min)); |
| build_opts.add_option_if((max < std::get<1>(quantization::get_min_max_values_from_quantized_data_type(output_stage->output_data_type))) && (min != max), |
| "-DMAX_BOUND=" + support::cpp11::to_string(max)); |
| build_opts.add_option("-DOUTPUT_DATA_TYPE=" + get_cl_type_from_data_type(dst->data_type())); |
| build_opts.add_option_if(bias != nullptr, "-DADD_BIAS"); |
| |
| // Create kernel |
| _kernel = create_kernel(compile_context, "gemmlowp_output_stage_quantize_down", build_opts.options()); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*src, Steps(num_elems_processed_per_iteration)); |
| ICLKernel::configure_internal(win); |
| |
| ARM_COMPUTE_ERROR_ON(has_padding_changed(padding_info)); |
| } |
| |
| void ClGemmLowpQuantizeDownInt32ScaleKernel::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)); |
| const auto bias = utils::cast::polymorphic_downcast<const ICLTensor *>(tensors.get_const_tensor(TensorType::ACL_BIAS)); |
| auto dst = utils::cast::polymorphic_downcast<ICLTensor *>(tensors.get_tensor(TensorType::ACL_DST)); |
| |
| Window collapsed = window.collapse_if_possible(ICLKernel::window(), Window::DimZ); |
| Window slice = collapsed.first_slice_window_3D(); |
| |
| unsigned int idx1 = num_arguments_per_3D_tensor(); |
| if(bias != nullptr) |
| { |
| Window biases_slice(slice); |
| biases_slice.set(Window::DimY, Window::Dimension(0, 1, 1)); |
| biases_slice.set(Window::DimZ, Window::Dimension(0, 1, 1)); |
| add_1D_tensor_argument(idx1, bias, biases_slice); |
| } |
| |
| do |
| { |
| unsigned int idx = 0; |
| add_3D_tensor_argument(idx, src, slice); |
| add_3D_tensor_argument(idx1, dst, slice); |
| enqueue(queue, *this, slice, lws_hint()); |
| } |
| while(collapsed.slide_window_slice_3D(slice)); |
| } |
| } // namespace kernels |
| } // namespace opencl |
| } // namespace arm_compute |