| /* |
| * 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/NEDeconvolutionLayerUpsampleKernel.h" |
| |
| #include "arm_compute/core/AccessWindowStatic.h" |
| #include "arm_compute/core/Coordinates.h" |
| #include "arm_compute/core/Error.h" |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Validate.h" |
| #include "arm_compute/core/Window.h" |
| |
| #include <arm_neon.h> |
| #include <cstddef> |
| #include <cstdint> |
| |
| using namespace arm_compute; |
| |
| NEDeconvolutionLayerUpsampleKernel::NEDeconvolutionLayerUpsampleKernel() |
| : _offsets(nullptr), _input(nullptr), _output(nullptr) |
| { |
| } |
| |
| BorderSize NEDeconvolutionLayerUpsampleKernel::border_size() const |
| { |
| return BorderSize(1); |
| } |
| |
| void NEDeconvolutionLayerUpsampleKernel::configure(const ITensor *input, const ITensor *offsets, ITensor *output) |
| { |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::F32); |
| ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::F32); |
| ARM_COMPUTE_ERROR_ON(output->info()->dimension(0) == 0); |
| ARM_COMPUTE_ERROR_ON(output->info()->dimension(1) == 0); |
| |
| for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i) |
| { |
| ARM_COMPUTE_ERROR_ON(input->info()->dimension(i) != output->info()->dimension(i)); |
| } |
| |
| _input = input; |
| _output = output; |
| _offsets = offsets; |
| |
| constexpr unsigned int num_elems_processed_per_iteration = 16; |
| const int border_offset = border_size().left; |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*output->info(), Steps(num_elems_processed_per_iteration)); |
| |
| AccessWindowRectangle input_access(input->info(), -border_offset, -border_offset, input->info()->dimension(0) + border_offset, input->info()->dimension(1) + border_offset); |
| AccessWindowHorizontal offsets_access(offsets->info(), 0, num_elems_processed_per_iteration); |
| AccessWindowHorizontal output_access(output->info(), 0, num_elems_processed_per_iteration); |
| |
| update_window_and_padding(win, input_access, offsets_access, output_access); |
| |
| output_access.set_valid_region(win, ValidRegion(Coordinates(), output->info()->tensor_shape())); |
| |
| INEKernel::configure(win); |
| } |
| |
| void NEDeconvolutionLayerUpsampleKernel::scale_nearest(const Window &window) |
| { |
| const size_t input_stride = _input->info()->strides_in_bytes()[1]; |
| |
| // Compute the ratio between source height and destination height |
| const auto hr = static_cast<float>(_input->info()->dimension(1)) / static_cast<float>(_output->info()->dimension(1)); |
| |
| // Don't increment in X and Y direction for the input tensor |
| // A pointer to the start of this plane is needed as base for the precomputed offsets |
| Window win_in(window); |
| win_in.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| win_in.set(Window::DimY, Window::Dimension(0, 0, 0)); |
| |
| Window win_off; |
| win_off.set(Window::DimX, window[Window::DimX]); |
| win_off.set(Window::DimY, window[Window::DimY]); |
| |
| for(size_t d = Window::DimZ; d < _offsets->info()->num_dimensions(); ++d) |
| { |
| win_off.set(d, Window::Dimension(0, 0, 0)); |
| } |
| |
| Iterator in(_input, win_in); |
| Iterator out(_output, window); |
| Iterator offsets(_offsets, win_off); |
| |
| switch(_input->info()->data_type()) |
| { |
| case DataType::F32: |
| { |
| float32x4x4_t tmp = |
| { |
| { |
| vdupq_n_f32(0), |
| vdupq_n_f32(0) |
| } |
| }; |
| execute_window_loop(window, [&](const Coordinates & id) |
| { |
| const auto offsets_ptr = reinterpret_cast<const int32_t *>(offsets.ptr()); |
| |
| const size_t in_yi = (id.y() + 0.5f) * hr; |
| const size_t offset_row = in_yi * input_stride; |
| |
| tmp.val[0] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[0] + offset_row), tmp.val[0], 0); |
| tmp.val[0] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[4] + offset_row), tmp.val[0], 1); |
| tmp.val[0] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[8] + offset_row), tmp.val[0], 2); |
| tmp.val[0] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[12] + offset_row), tmp.val[0], 3); |
| |
| tmp.val[1] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[1] + offset_row), tmp.val[1], 0); |
| tmp.val[1] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[5] + offset_row), tmp.val[1], 1); |
| tmp.val[1] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[9] + offset_row), tmp.val[1], 2); |
| tmp.val[1] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[13] + offset_row), tmp.val[1], 3); |
| |
| tmp.val[2] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[2] + offset_row), tmp.val[2], 0); |
| tmp.val[2] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[6] + offset_row), tmp.val[2], 1); |
| tmp.val[2] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[10] + offset_row), tmp.val[2], 2); |
| tmp.val[2] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[14] + offset_row), tmp.val[2], 3); |
| |
| tmp.val[3] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[3] + offset_row), tmp.val[3], 0); |
| tmp.val[3] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[7] + offset_row), tmp.val[3], 1); |
| tmp.val[3] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[11] + offset_row), tmp.val[3], 2); |
| tmp.val[3] = vsetq_lane_f32(*reinterpret_cast<const float *>(in.ptr() + offsets_ptr[15] + offset_row), tmp.val[3], 3); |
| |
| vst4q_f32(reinterpret_cast<float *>(out.ptr()), tmp); |
| }, |
| in, offsets, out); |
| break; |
| } |
| default: |
| ARM_COMPUTE_ERROR("Not supported"); |
| break; |
| } |
| } |
| |
| void NEDeconvolutionLayerUpsampleKernel::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); |
| scale_nearest(window); |
| } |