| /* |
| * Copyright (c) 2016, 2017 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/NEMeanStdDevKernel.h" |
| |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/IAccessWindow.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/Validate.h" |
| |
| #include <arm_neon.h> |
| #include <cmath> |
| #include <tuple> |
| #include <utility> |
| |
| using namespace arm_compute; |
| |
| namespace arm_compute |
| { |
| class Coordinates; |
| } // namespace arm_compute |
| |
| namespace |
| { |
| template <bool calc_sum_squared> |
| std::pair<uint64x1_t, uint64x1_t> accumulate(const Window &window, Iterator &iterator) |
| { |
| uint64x1_t sum = vdup_n_u64(0); |
| uint64x1_t sum_squared = vdup_n_u64(0); |
| |
| // Calculate sum |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| const uint8x16_t in_data = vld1q_u8(iterator.ptr()); |
| |
| // Sum of the low and high elements of data |
| const uint16x8_t tmp0 = vaddl_u8(vget_low_u8(in_data), vget_high_u8(in_data)); |
| const uint32x4_t tmp1 = vaddl_u16(vget_low_u16(tmp0), vget_high_u16(tmp0)); |
| const uint32x2_t tmp2 = vadd_u32(vget_low_u32(tmp1), vget_high_u32(tmp1)); |
| |
| // Update sum |
| sum = vpadal_u32(sum, tmp2); |
| |
| if(calc_sum_squared) |
| { |
| const uint16x8_t square_data_low = vmull_u8(vget_low_u8(in_data), vget_low_u8(in_data)); |
| const uint16x8_t square_data_high = vmull_u8(vget_high_u8(in_data), vget_high_u8(in_data)); |
| |
| // Sum of the low and high elements of data |
| const uint32x4_t tmp0_low = vaddl_u16(vget_low_u16(square_data_low), vget_high_u16(square_data_low)); |
| const uint32x4_t tmp0_high = vaddl_u16(vget_low_u16(square_data_high), vget_high_u16(square_data_high)); |
| const uint32x4_t tmp1 = vaddq_u32(tmp0_low, tmp0_high); |
| const uint32x2_t tmp2 = vadd_u32(vget_low_u32(tmp1), vget_high_u32(tmp1)); |
| |
| // Update sum |
| sum_squared = vpadal_u32(sum_squared, tmp2); |
| } |
| }, |
| iterator); |
| |
| return std::make_pair(sum, sum_squared); |
| } |
| } // namespace |
| |
| NEMeanStdDevKernel::NEMeanStdDevKernel() |
| : _input(nullptr), _mean(nullptr), _stddev(nullptr), _global_sum(nullptr), _global_sum_squared(nullptr), _mtx() |
| { |
| } |
| |
| void NEMeanStdDevKernel::configure(const IImage *input, float *mean, uint64_t *global_sum, float *stddev, uint64_t *global_sum_squared) |
| { |
| ARM_COMPUTE_ERROR_ON_TENSOR_NOT_2D(input); |
| ARM_COMPUTE_ERROR_ON(nullptr == mean); |
| ARM_COMPUTE_ERROR_ON(nullptr == global_sum); |
| ARM_COMPUTE_ERROR_ON(stddev && nullptr == global_sum_squared); |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::U8); |
| |
| _input = input; |
| _mean = mean; |
| _stddev = stddev; |
| _global_sum = global_sum; |
| _global_sum_squared = global_sum_squared; |
| |
| constexpr unsigned int num_elems_processed_per_iteration = 16; |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); |
| |
| update_window_and_padding(win, AccessWindowHorizontal(input->info(), 0, num_elems_processed_per_iteration)); |
| |
| INEKernel::configure(win); |
| } |
| |
| void NEMeanStdDevKernel::run(const Window &window) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); |
| Iterator input(_input, window); |
| |
| uint64x1_t local_sum = vdup_n_u64(0); |
| uint64x1_t local_sum_squared = vdup_n_u64(0); |
| |
| if(_stddev != nullptr) |
| { |
| std::tie(local_sum, local_sum_squared) = accumulate<true>(window, input); |
| } |
| else |
| { |
| std::tie(local_sum, local_sum_squared) = accumulate<false>(window, input); |
| } |
| |
| const float num_pixels = _input->info()->dimension(0) * _input->info()->dimension(1); |
| |
| // Merge sum and calculate mean and stddev |
| std::unique_lock<std::mutex> lock(_mtx); |
| |
| *_global_sum += vget_lane_u64(local_sum, 0); |
| |
| const float mean = *_global_sum / num_pixels; |
| *_mean = mean; |
| |
| if(_stddev != nullptr) |
| { |
| const uint64_t tmp_sum_squared = vget_lane_u64(local_sum_squared, 0); |
| *_global_sum_squared += tmp_sum_squared; |
| *_stddev = std::sqrt((*_global_sum_squared / num_pixels) - (mean * mean)); |
| } |
| |
| lock.unlock(); |
| } |