/* * Copyright (c) 2016-2020 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/NEON/kernels/NEThresholdKernel.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/NEON/wrapper/wrapper.h" namespace arm_compute { namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const ThresholdKernelInfo &info) { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::U8); // Checks performed when output is configured if((output != nullptr) && (output->total_size() != 0)) { ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); } return Status{}; } std::pair validate_and_configure_window(ITensorInfo *input, ITensorInfo *output) { // Configure kernel window Window win = calculate_max_window(*input, Steps()); // Output auto inizialitation if not yet initialized auto_init_if_empty(*output, *input->clone()); // NEThresholdKernel doesn't need padding so update_window_and_padding() can be skipped 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 NEThresholdKernel::NEThresholdKernel() : _func(nullptr), _input(nullptr), _output(nullptr), _info() { } void NEThresholdKernel::configure(const ITensor *input, ITensor *output, const ThresholdKernelInfo &info) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_ERROR_THROW_ON(validate(input->info(), output->info(), info)); _input = input; _output = output; _info = info; switch(_info.type) { case ThresholdType::BINARY: _func = &NEThresholdKernel::run_binary; break; case ThresholdType::RANGE: _func = &NEThresholdKernel::run_range; break; default: ARM_COMPUTE_ERROR("Thresholding type not recognized"); break; } // Configure kernel window auto win_config = validate_and_configure_window(input->info(), output->info()); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); ICPPKernel::configure(win_config.second); } Status NEThresholdKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const ThresholdKernelInfo &info) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, info)); ARM_COMPUTE_RETURN_ON_ERROR(validate_and_configure_window(input->clone().get(), output->clone().get()).first); return Status{}; } inline void NEThresholdKernel::run_binary(const Window &window) { /** NEON vector tag type. */ using Type = uint8_t; using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t; const int window_step_x = 16 / sizeof(Type); const auto window_start_x = static_cast(window.x().start()); const auto window_end_x = static_cast(window.x().end()); Window win_collapsed = window.collapse_if_possible(window, Window::DimZ); win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1)); const uint8_t threshold = _info.threshold; const uint8_t true_value = _info.true_value; const uint8_t false_value = _info.false_value; const auto vthreshold = wrapper::vdup_n(threshold, ExactTagType{}); const auto vtrue_value = wrapper::vdup_n(true_value, ExactTagType{}); const auto vfalse_value = wrapper::vdup_n(false_value, ExactTagType{}); Iterator input(_input, win_collapsed); Iterator output(_output, win_collapsed); execute_window_loop(win_collapsed, [&](const Coordinates &) { const auto input_ptr = reinterpret_cast(input.ptr()); const auto output_ptr = reinterpret_cast(output.ptr()); int x = window_start_x; for(; x <= (window_end_x - window_step_x); x += window_step_x) { const auto vdata = wrapper::vloadq(input_ptr + x); const auto vmask = wrapper::vcgt(vdata, vthreshold); wrapper::vstore(output_ptr + x, wrapper::vbsl(vmask, vtrue_value, vfalse_value)); } for(; x < window_end_x; ++x) { const Type data = *(reinterpret_cast(input_ptr + x)); *(output_ptr + x) = (data > threshold) ? true_value : false_value; } }, input, output); } inline void NEThresholdKernel::run_range(const Window &window) { /** NEON vector tag type. */ using Type = uint8_t; using ExactTagType = typename wrapper::traits::neon_bitvector_tag_t; const int window_step_x = 16 / sizeof(Type); const auto window_start_x = static_cast(window.x().start()); const auto window_end_x = static_cast(window.x().end()); Window win_collapsed = window.collapse_if_possible(window, Window::DimZ); win_collapsed.set(Window::DimX, Window::Dimension(0, 1, 1)); const uint8_t lower_threshold = _info.threshold; const uint8_t upper_threshold = _info.upper; const uint8_t true_value = _info.true_value; const uint8_t false_value = _info.false_value; const auto vlower_threshold = wrapper::vdup_n(lower_threshold, ExactTagType{}); const auto vupper_threshold = wrapper::vdup_n(upper_threshold, ExactTagType{}); const auto vtrue_value = wrapper::vdup_n(true_value, ExactTagType{}); const auto vfalse_value = wrapper::vdup_n(false_value, ExactTagType{}); Iterator input(_input, win_collapsed); Iterator output(_output, win_collapsed); execute_window_loop(win_collapsed, [&](const Coordinates &) { const auto input_ptr = reinterpret_cast(input.ptr()); const auto output_ptr = reinterpret_cast(output.ptr()); int x = window_start_x; for(; x <= (window_end_x - window_step_x); x += window_step_x) { const auto vdata = wrapper::vloadq(input_ptr + x); auto vmask = wrapper::vcle(vdata, vupper_threshold); vmask = wrapper::vand(wrapper::vcge(vdata, vlower_threshold), vmask); wrapper::vstore(output_ptr + x, wrapper::vbsl(vmask, vtrue_value, vfalse_value)); } for(; x < window_end_x; ++x) { const Type data = *(reinterpret_cast(input_ptr + x)); *(output_ptr + x) = (data <= upper_threshold && data >= lower_threshold) ? true_value : false_value; } }, input, output); } void NEThresholdKernel::run(const Window &window, const ThreadInfo &info) { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); ARM_COMPUTE_ERROR_ON(_func == nullptr); (this->*_func)(window); } } // namespace arm_compute