| /* |
| * Copyright (c) 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/NEL2NormalizeLayerKernel.h" |
| |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/NEON/NEMath.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_neon.h> |
| #include <cmath> |
| |
| using namespace arm_compute; |
| |
| namespace |
| { |
| void l2_normalize_X(const ITensor *in, const ITensor *sum, ITensor *out, float epsilon, const Window &window) |
| { |
| Window window_sum(window); |
| window_sum.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| |
| Window in_slice = window.first_slice_window_1D(); |
| Window sum_slice = window_sum.first_slice_window_1D(); |
| |
| do |
| { |
| Iterator input_it(in, in_slice); |
| Iterator sum_it(sum, sum_slice); |
| Iterator output_it(out, in_slice); |
| |
| const float sum_value = *reinterpret_cast<const float *>(sum_it.ptr()); |
| const float32x4_t vec_normalize_value = vdupq_n_f32(1.f / std::sqrt(std::max(sum_value, epsilon))); |
| |
| execute_window_loop(in_slice, [&](const Coordinates & id) |
| { |
| const auto in_ptr = reinterpret_cast<const float *>(input_it.ptr()); |
| const auto out_ptr = reinterpret_cast<float *>(output_it.ptr()); |
| |
| vst1q_f32(out_ptr, vmulq_f32(vld1q_f32(in_ptr), vec_normalize_value)); |
| }, |
| input_it, output_it); |
| } |
| while(window.slide_window_slice_1D(in_slice) && window.slide_window_slice_1D(sum_slice)); |
| } |
| } // namespace |
| |
| NEL2NormalizeLayerKernel::NEL2NormalizeLayerKernel() |
| : _input(nullptr), _sum(nullptr), _output(nullptr), _axis(0), _epsilon(1e-12) |
| { |
| } |
| |
| void NEL2NormalizeLayerKernel::configure(const ITensor *input, const ITensor *sum, ITensor *output, unsigned int axis, float epsilon) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, sum, output); |
| ARM_COMPUTE_ERROR_ON_MSG(axis >= TensorShape::num_max_dimensions, "Normalization axis greater than max number of dimensions"); |
| ARM_COMPUTE_ERROR_ON_MSG(axis > 0, "Unsupported normalization axis, Supported axis is 0"); |
| |
| // Output auto initialization if not yet initialized |
| auto_init_if_empty(*output->info(), input->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position()); |
| |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(input, output, sum); |
| ARM_COMPUTE_ERROR_ON_MISMATCHING_SHAPES(input, output); |
| |
| unsigned int num_elems_processed_per_iteration = 16 / data_size_from_type(input->info()->data_type()); |
| unsigned int num_elems_processed_per_iteration_sum = (axis == 0) ? 1 : num_elems_processed_per_iteration; |
| |
| _input = input; |
| _sum = sum; |
| _output = output; |
| _axis = axis; |
| _epsilon = epsilon; |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*input->info(), Steps(num_elems_processed_per_iteration)); |
| AccessWindowHorizontal input_access(input->info(), 0, num_elems_processed_per_iteration); |
| AccessWindowHorizontal sum_access(sum->info(), 0, num_elems_processed_per_iteration_sum); |
| AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); |
| |
| update_window_and_padding(win, input_access, sum_access, output_access); |
| |
| output_access.set_valid_region(win, input->info()->valid_region()); |
| |
| INEKernel::configure(win); |
| } |
| |
| void NEL2NormalizeLayerKernel::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); |
| |
| switch(_axis) |
| { |
| case 0: |
| l2_normalize_X(_input, _sum, _output, _epsilon, window); |
| break; |
| default: |
| ARM_COMPUTE_ERROR("Unsupported normalization axis"); |
| } |
| } |