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Diffstat (limited to 'src/core/CL/kernels/CLQuantizationLayerKernel.cpp')
| -rw-r--r-- | src/core/CL/kernels/CLQuantizationLayerKernel.cpp | 190 |
1 files changed, 0 insertions, 190 deletions
diff --git a/src/core/CL/kernels/CLQuantizationLayerKernel.cpp b/src/core/CL/kernels/CLQuantizationLayerKernel.cpp deleted file mode 100644 index b4b2217391..0000000000 --- a/src/core/CL/kernels/CLQuantizationLayerKernel.cpp +++ /dev/null @@ -1,190 +0,0 @@ -/* - * 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/CLQuantizationLayerKernel.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/TensorInfo.h" -#include "arm_compute/core/Utils.h" -#include "arm_compute/core/Validate.h" -#include "arm_compute/core/Window.h" -#include "arm_compute/core/utils/quantization/AsymmHelpers.h" -#include "support/StringSupport.h" - -namespace arm_compute -{ -namespace -{ -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output) -{ - ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::F32, DataType::F16); - ARM_COMPUTE_RETURN_ERROR_ON_F16_UNSUPPORTED(input); - - // Output must always be initialized - ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape().total_size() == 0); - ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::QASYMM8, DataType::QASYMM8_SIGNED, DataType::QASYMM16); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); - - return Status{}; -} - -std::pair<Status, Window> validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) -{ - // Configure kernel window - Window win = calculate_max_window(*input, Steps()); - - const int vec_size_x = 16 / input->element_size(); - const int input_width_x = input->tensor_shape().x(); - const bool multi_access_x = (input_width_x / vec_size_x > 0); - if(multi_access_x) - { - win.set(Window::DimX, Window::Dimension(win.x().start(), ceil_to_multiple(win.x().end(), vec_size_x), vec_size_x)); - } - - Coordinates coord; - coord.set_num_dimensions(output->num_dimensions()); - output->set_valid_region(ValidRegion(coord, output->tensor_shape())); - - return std::make_pair(Status{}, win); -} -} // namespace - -CLQuantizationLayerKernel::CLQuantizationLayerKernel() - : _input(nullptr), _output(nullptr) -{ -} - -void CLQuantizationLayerKernel::configure(const ICLTensor *input, ICLTensor *output) -{ - configure(CLKernelLibrary::get().get_compile_context(), input, output); -} - -void CLQuantizationLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output) -{ - ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info())); - - _input = input; - _output = output; - - const int vec_size_x = 16 / input->info()->element_size(); - const int input_width_x = input->info()->tensor_shape().x(); - const bool multi_access_x = (input_width_x / vec_size_x > 0); - - // Configure kernel window - auto win_config = validate_and_configure_window(input->info(), output->info()); - ARM_COMPUTE_ERROR_THROW_ON(win_config.first); - ICLKernel::configure_internal(win_config.second); - - const UniformQuantizationInfo qinfo = output->info()->quantization_info().uniform(); - const DataType output_data_type = output->info()->data_type(); - - float scale_to_apply = qinfo.scale; - int32_t offset_to_apply = qinfo.offset; - if(is_data_type_quantized_asymmetric(_input->info()->data_type())) - { - /* - * In case of requantization of a quantized input tensor to an output tensor with another quantization - * instead of of apply dequantization and then a quantization functions, we just compute new scale and - * offset to apply. - * - * Assuming: - * - q_i as input quantized value - * - q_o as output quantized value - * - z_i as input quantization offset value - * - z_o as output quantization offset value - * - s_i as input quantization scale value - * - s_o as output quantization scale value - * - z_n as new quantization offset value - * - s_n as new quantization scale value - * - * q_o = ( q_i - z_i ) * s_i / s_o + z_o - * - * We can rewrite the formula as: - * - * q_o = ( q_i * s_i / s_o ) - z_i * s_i / s_o + z_o - * - * q_o = q_i / s_n + z_n - * - * Where: - * - * s_n = s_o / s_i - * - * z_n = - z_i * s_i / s_o + z_o - * - */ - const UniformQuantizationInfo qinfo_in = _input->info()->quantization_info().uniform(); - scale_to_apply /= qinfo_in.scale; - // In order to minimize flooring we convert the offset to a float, - // then compute the new offset in the float domain, - // finally we convert it back as int32_t - offset_to_apply -= static_cast<int32_t>(static_cast<float>(qinfo_in.offset) * qinfo_in.scale / qinfo.scale); - } - - // Create kernel - CLBuildOptions build_opts; - build_opts.add_option_if(is_data_type_float(_input->info()->data_type()), "-DIS_FLOAT"); - build_opts.add_option("-DSCALE=" + float_to_string_with_full_precision(scale_to_apply)); - build_opts.add_option("-DOFFSET=" + support::cpp11::to_string(offset_to_apply)); - build_opts.add_option("-DVEC_SIZE=" + support::cpp11::to_string(vec_size_x)); - build_opts.add_option("-DDATA_TYPE_IN=" + get_cl_type_from_data_type(input->info()->data_type())); - build_opts.add_option("-DDATA_TYPE_OUT=" + get_cl_type_from_data_type(output_data_type)); - build_opts.add_option_if(multi_access_x, "-DLAST_ACCESSED_X=" + support::cpp11::to_string(std::max<int>(input_width_x - vec_size_x, 0))); - std::pair<int, int> min_max_quant_values = quantization::get_min_max_values_from_quantized_data_type(output_data_type); - build_opts.add_option("-DMIN_QUANT_VAL=" + support::cpp11::to_string(min_max_quant_values.first)); - build_opts.add_option("-DMAX_QUANT_VAL=" + support::cpp11::to_string(min_max_quant_values.second)); - - _kernel = create_kernel(compile_context, "quantization_layer", build_opts.options()); -} - -Status CLQuantizationLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output) -{ - ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output)); - ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first); - - return Status{}; -} - -void CLQuantizationLayerKernel::run(const Window &window, cl::CommandQueue &queue) -{ - ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); - - Window window_collapsed = window.collapse_if_possible(ICLKernel::window(), 3); - Window slice = window_collapsed.first_slice_window_3D(); - - do - { - unsigned int idx = 0; - add_3D_tensor_argument(idx, _input, slice); - add_3D_tensor_argument(idx, _output, slice); - enqueue(queue, *this, slice, lws_hint()); - } - while(window_collapsed.slide_window_slice_3D(slice)); -} -} // namespace arm_compute |