| /* |
| * 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/runtime/NEON/functions/NEDeconvolutionLayerUpsample.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/NEON/kernels/NEDeconvolutionLayerUpsampleKernel.h" |
| #include "arm_compute/core/PixelValue.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Window.h" |
| #include "arm_compute/runtime/NEON/NEScheduler.h" |
| #include "arm_compute/runtime/TensorAllocator.h" |
| #include "support/ToolchainSupport.h" |
| |
| #include <cmath> |
| #include <cstddef> |
| #include <utility> |
| |
| using namespace arm_compute; |
| |
| namespace |
| { |
| inline void precompute_offsets(ITensor *offsets, float wr, size_t input_element_size, const std::pair<unsigned int, unsigned int> &a, |
| const std::pair<unsigned int, unsigned int> &iz, const PadStrideInfo &info) |
| { |
| ARM_COMPUTE_ERROR_ON(nullptr == offsets); |
| Window win; |
| const int padx = info.pad().first; |
| const int pady = info.pad().second; |
| const int ax = a.first; |
| const int ay = a.second; |
| const int offset_width = offsets->info()->dimension(0); |
| const int offset_height = offsets->info()->dimension(1); |
| // The values of ax and ay denote the number of ZEROS to be added on the top and right inner border of the image. |
| // Step value along the XY axis will depend on the number of zeros to be inserted between samples (number of zeros + 1). |
| // Pre-compute the X offset, Y's stride is unknown at this point so we can't precompute Y's offsets |
| for(int yi = ay; yi < (offset_height - pady); yi += (1 + iz.second)) |
| { |
| for(int xi = padx; xi < (offset_width - ax); xi += (1 + iz.first)) |
| { |
| int *ptr = reinterpret_cast<int *>(offsets->ptr_to_element(Coordinates(xi, yi))); |
| const size_t in_xi = (xi + 0.5f) * wr; |
| *reinterpret_cast<int32_t *>(ptr) = in_xi * input_element_size; |
| } |
| } |
| } |
| } // namespace |
| |
| NEDeconvolutionLayerUpsample::NEDeconvolutionLayerUpsample(std::shared_ptr<IMemoryManager> memory_manager) // NOLINT |
| : _memory_group(std::move(memory_manager)), |
| _offsets(), |
| _border_handler(), |
| _upsample() |
| { |
| } |
| |
| void NEDeconvolutionLayerUpsample::configure(ITensor *input, ITensor *output, const std::pair<unsigned int, unsigned int> &a, |
| const std::pair<unsigned int, unsigned int> &iz, const PadStrideInfo &info) |
| { |
| ARM_COMPUTE_ERROR_ON(nullptr == input); |
| ARM_COMPUTE_ERROR_ON(nullptr == output); |
| |
| for(size_t i = 2; i < Coordinates::num_max_dimensions; ++i) |
| { |
| ARM_COMPUTE_ERROR_ON(input->info()->dimension(i) != output->info()->dimension(i)); |
| } |
| |
| // Get the tensor shape |
| const TensorShape shape(output->info()->dimension(0), output->info()->dimension(1)); |
| |
| // Compute the ratio between source width/height and destination width/height |
| const auto wr = static_cast<float>(input->info()->dimension(0)) / static_cast<float>(output->info()->dimension(0)); |
| const auto hr = static_cast<float>(input->info()->dimension(1)) / static_cast<float>(output->info()->dimension(1)); |
| ARM_COMPUTE_UNUSED(hr); |
| // Get the element size of the input image |
| const size_t input_element_size = input->info()->element_size(); |
| |
| TensorInfo tensor_info_offsets(shape, Format::S32); |
| _offsets.allocator()->init(tensor_info_offsets); |
| |
| _upsample.configure(input, &_offsets, output); |
| |
| // Allocate once the configure methods have been called |
| _offsets.allocator()->allocate(); |
| // Pre-compute offsets for nearest interpolation |
| std::fill_n(reinterpret_cast<int32_t *>(_offsets.buffer()), _offsets.info()->total_size() / sizeof(int32_t), -1 * input_element_size); |
| precompute_offsets(&_offsets, wr, input_element_size, a, iz, info); |
| |
| _border_handler.configure(input, _upsample.border_size(), BorderMode::CONSTANT, PixelValue(0)); |
| } |
| |
| void NEDeconvolutionLayerUpsample::run() |
| { |
| NEScheduler::get().schedule(&_border_handler, Window::DimZ); |
| _memory_group.acquire(); |
| NEScheduler::get().schedule(&_upsample, Window::DimY); |
| _memory_group.release(); |
| } |