/* * Copyright (c) 2018-2019 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/NERangeKernel.h" #include "arm_compute/core/Error.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/IAccessWindow.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/NEON/NEAsymm.h" #include "arm_compute/core/NEON/wrapper/wrapper.h" #include "arm_compute/core/TensorInfo.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/Utils.h" namespace arm_compute { namespace { template void range_function(ITensor *output, float start, float step, const Window &window) { const unsigned int num_elems_processed_per_iteration = 16 / sizeof(T); /** NEON vector tag type. */ using ExactTagType = typename wrapper::traits::neon_bitvector::tag_type; const auto step_vec = wrapper::vdup_n(static_cast(step), ExactTagType{}); const auto start_vec = wrapper::vdup_n(static_cast(start), ExactTagType{}); auto id_vec = wrapper::vdup_n(static_cast(0.f), ExactTagType{}); Iterator output_it(output, window); execute_window_loop(window, [&](const Coordinates & id) { for(unsigned int count = 0; count < num_elems_processed_per_iteration; ++count) { id_vec = wrapper::vsetlane(static_cast(id.x() + count), id_vec, count); } // start + step * id const auto res_vec = wrapper::vmla(start_vec, id_vec, step_vec); const auto out_ptr = reinterpret_cast(output_it.ptr()); wrapper::vstore(out_ptr, res_vec); }, output_it); } Status validate_arguments(const ITensorInfo &output, const float start, const float end, const float step) { ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(&output, 1, DataType::U8, DataType::S8, DataType::U16, DataType::S16, DataType::U32, DataType::S32, DataType::F16, DataType::F32); ARM_COMPUTE_RETURN_ERROR_ON_MSG((start == end), "start of the requested sequence must not be equal to the end"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(((start < end) && (step <= 0)), "step must be greater than 0 when start < end"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(((start > end) && (step >= 0)), "step must be less than 0 when start > end"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(!check_value_range(start, output.data_type(), output.quantization_info()), "start value is outside the range of the data type"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(!check_value_range(end, output.data_type(), output.quantization_info()), "end value is outside the range of the data type"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(!check_value_range(step, output.data_type(), output.quantization_info()), "step value is outside the range of the data type"); ARM_COMPUTE_RETURN_ERROR_ON_MSG((start == end), "start of the requested sequence must not be equal to the end"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(output.num_dimensions() != 1, "Output has to be a 1-D tensor"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(output.tensor_shape().total_size() < num_of_elements_in_range(start, end, step), "Output tensor size is incorrect"); return Status{}; } std::pair validate_and_configure_window(ITensorInfo &output, const float start, const float end, const float step) { const unsigned int num_elems_processed_per_iteration = 16 / output.element_size(); // Auto initialize output if not initialized auto_init_if_empty(output, TensorShape(num_of_elements_in_range(start, end, step)), 1, output.data_type(), output.quantization_info()); // Configure kernel window Window win = calculate_max_window(output, Steps(num_elems_processed_per_iteration)); AccessWindowHorizontal output_access(&output, 0, num_elems_processed_per_iteration); bool window_changed = update_window_and_padding(win, output_access); output_access.set_valid_region(win, ValidRegion(Coordinates(), TensorShape(num_of_elements_in_range(start, end, step)))); Status err = (window_changed) ? ARM_COMPUTE_CREATE_ERROR(ErrorCode::RUNTIME_ERROR, "Insufficient Padding!") : Status{}; return std::make_pair(err, win); } } // namespace NERangeKernel::NERangeKernel() : _func(nullptr), _start(0), _end(1), _step(1), _output(nullptr) { } void NERangeKernel::configure(ITensor *output, float start, float end, float step) { ARM_COMPUTE_ERROR_ON_NULLPTR(output); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(*(output->info()), start, end, step)); // Configure kernel window auto win_config = validate_and_configure_window(*(output->info()), start, end, step); ARM_COMPUTE_ERROR_THROW_ON(win_config.first); _start = start; _end = end; _step = step; _output = output; switch(_output->info()->data_type()) { case DataType::U8: _func = &range_function; break; case DataType::U16: _func = &range_function; break; case DataType::U32: _func = &range_function; break; case DataType::S8: _func = &range_function; break; case DataType::S16: _func = &range_function; break; case DataType::S32: _func = &range_function; break; case DataType::F32: _func = &range_function; break; #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC case DataType::F16: _func = &range_function; break; #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC default: ARM_COMPUTE_ERROR("Unsupported data type."); break; } INEKernel::configure(win_config.second); } Status NERangeKernel::validate(const ITensorInfo *output, float start, float end, float step) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output); ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(*output, start, end, step)); ARM_COMPUTE_RETURN_ON_ERROR((validate_and_configure_window(*(output->clone()), start, end, step)).first); return Status{}; } void NERangeKernel::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); (*_func)(_output, _start, _step, window); } } // namespace arm_compute