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Diffstat (limited to 'src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp')
-rw-r--r-- | src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp | 121 |
1 files changed, 121 insertions, 0 deletions
diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp new file mode 100644 index 0000000000..63f17bcb5a --- /dev/null +++ b/src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp @@ -0,0 +1,121 @@ +/* + * 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(); +} |