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-rw-r--r--src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp121
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diff --git a/src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp b/src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp
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+++ b/src/runtime/NEON/functions/NEDeconvolutionLayerUpsample.cpp
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+/*
+ * 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();
+}