| /* |
| * Copyright (c) 2018-2020 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 "src/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/TensorInfo.h" |
| #include "arm_compute/core/Validate.h" |
| #include "src/core/NEON/NEAsymm.h" |
| #include "src/core/NEON/wrapper/wrapper.h" |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| #include "arm_compute/core/Utils.h" |
| |
| namespace arm_compute |
| { |
| namespace |
| { |
| template <typename T> |
| void range_function(ITensor *output, float start, float step, const Window &window) |
| { |
| /** NEON vector tag type. */ |
| using ExactTagType = typename wrapper::traits::neon_bitvector<T, wrapper::traits::BitWidth::W128>::tag_type; |
| |
| const auto step_vec = wrapper::vdup_n(static_cast<T>(step), ExactTagType{}); |
| const auto start_vec = wrapper::vdup_n(static_cast<T>(start), ExactTagType{}); |
| auto id_vec = wrapper::vdup_n(static_cast<T>(0.f), ExactTagType{}); |
| |
| const auto window_start_x = static_cast<int>(window.x().start()); |
| const auto window_end_x = static_cast<int>(window.x().end()); |
| const int window_step_x = 16 / sizeof(T); |
| |
| Window win{ window }; |
| win.set(Window::DimX, Window::Dimension(0, 1, 1)); |
| Iterator output_it(output, win); |
| |
| execute_window_loop(win, [&](const Coordinates &) |
| { |
| int x = window_start_x; |
| const auto out_ptr = reinterpret_cast<T *>(output_it.ptr()); |
| for(; x <= (window_end_x - window_step_x); x += window_step_x) |
| { |
| for(int count = 0; count < window_step_x; ++count) |
| { |
| id_vec = wrapper::vsetlane(static_cast<T>(x + count), id_vec, count); |
| } |
| |
| // start + step * id |
| const auto res_vec = wrapper::vmla(start_vec, id_vec, step_vec); |
| wrapper::vstore(out_ptr + x, res_vec); |
| } |
| |
| // Compute left-over elements |
| for(; x < window_end_x; ++x) |
| { |
| const auto res = start + x * step; |
| *(out_ptr + x) = res; |
| } |
| |
| }, |
| 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{}; |
| } |
| } // 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)); |
| |
| // Auto initialize output if not initialized |
| auto_init_if_empty(*output->info(), TensorShape(num_of_elements_in_range(start, end, step)), 1, output->info()->data_type(), output->info()->quantization_info()); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*output->info(), Steps()); |
| Coordinates coord; |
| coord.set_num_dimensions(output->info()->num_dimensions()); |
| output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape())); |
| |
| _start = start; |
| _end = end; |
| _step = step; |
| _output = output; |
| switch(_output->info()->data_type()) |
| { |
| case DataType::U8: |
| _func = &range_function<uint8_t>; |
| break; |
| case DataType::U16: |
| _func = &range_function<uint16_t>; |
| break; |
| case DataType::U32: |
| _func = &range_function<uint32_t>; |
| break; |
| case DataType::S8: |
| _func = &range_function<int8_t>; |
| break; |
| case DataType::S16: |
| _func = &range_function<int16_t>; |
| break; |
| case DataType::S32: |
| _func = &range_function<int32_t>; |
| break; |
| case DataType::F32: |
| _func = &range_function<float>; |
| break; |
| #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| case DataType::F16: |
| _func = &range_function<float16_t>; |
| break; |
| #endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC |
| default: |
| ARM_COMPUTE_ERROR("Unsupported data type."); |
| break; |
| } |
| |
| INEKernel::configure(win); |
| } |
| |
| 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)); |
| |
| 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 |