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Diffstat (limited to 'src/cpu/operators/CpuScale.cpp')
| -rw-r--r-- | src/cpu/operators/CpuScale.cpp | 289 |
1 files changed, 289 insertions, 0 deletions
diff --git a/src/cpu/operators/CpuScale.cpp b/src/cpu/operators/CpuScale.cpp new file mode 100644 index 0000000000..7df9296931 --- /dev/null +++ b/src/cpu/operators/CpuScale.cpp @@ -0,0 +1,289 @@ +/* + * Copyright (c) 2021-2023 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 "src/cpu/operators/CpuScale.h" + +#include "arm_compute/core/Helpers.h" +#include "arm_compute/core/TensorInfo.h" +#include "arm_compute/runtime/NEON/NEScheduler.h" + +#include "src/common/utils/Log.h" +#include "src/core/utils/ScaleUtils.h" +#include "src/cpu/kernels/CpuScaleKernel.h" +#include "support/Rounding.h" + +namespace arm_compute +{ +namespace cpu +{ +namespace +{ +void precompute_dx_dy_offsets( + ITensor *dx, ITensor *dy, ITensor *offsets, float wr, float hr, SamplingPolicy sampling_policy, bool align_corners) +{ + ARM_COMPUTE_ERROR_ON(offsets == nullptr); + float sampling_offset = 0.0f; + if (sampling_policy == SamplingPolicy::CENTER) + { + sampling_offset = 0.5f; + } + + Window win; + win.set(Window::DimX, Window::Dimension(0, offsets->info()->dimension(0), 1)); + win.set(Window::DimY, Window::Dimension(0, offsets->info()->dimension(1), 1)); + + if (dx != nullptr && dy != nullptr) + { + // Pre-compute the offset and pixel's distance for BILINEAR interpolation + Iterator offsets_it(offsets, win); + Iterator dx_it(dx, win); + Iterator dy_it(dy, win); + + execute_window_loop( + win, + [&](const Coordinates &id) + { + const float in_x = (id.x() + sampling_offset) * wr - sampling_offset; + const float in_y = (id.y() + sampling_offset) * hr - sampling_offset; + const int in_xi = std::floor(in_x); + const int in_yi = std::floor(in_y); + + *reinterpret_cast<int32_t *>(offsets_it.ptr()) = in_xi; + *reinterpret_cast<float *>(dx_it.ptr()) = in_x - in_xi; + *reinterpret_cast<float *>(dy_it.ptr()) = in_y - in_yi; + }, + offsets_it, dx_it, dy_it); + } + else + { + // Pre-compute the offset for NEAREST interpolation + Iterator offsets_it(offsets, win); + + execute_window_loop( + win, + [&](const Coordinates &id) + { + const float float_in_xi = (id.x() + sampling_offset) * wr; + const auto in_xi = static_cast<size_t>( + align_corners ? arm_compute::utils::rounding::round_half_away_from_zero(float_in_xi) + : std::floor(float_in_xi)); + *reinterpret_cast<int32_t *>(offsets_it.ptr()) = in_xi; + }, + offsets_it); + } +} +} // namespace + +void CpuScale::configure(ITensorInfo *src, ITensorInfo *dst, const ScaleKernelInfo &info) +{ + ARM_COMPUTE_ERROR_ON_NULLPTR(src, dst); + ARM_COMPUTE_ERROR_THROW_ON(CpuScale::validate(src, dst, info)); + ARM_COMPUTE_LOG_PARAMS(src, dst, info); + + _scale_info = info; + _is_prepared = false; + + // Get data layout and width/height indices + _data_layout = _scale_info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : _scale_info.data_layout; + const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); + const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); + + // Compute the ratio between source width/height and destination width/height + const bool is_align_corners_used = + _scale_info.align_corners && + arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(_scale_info.sampling_policy); + const auto wr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_width), + dst->dimension(idx_width), is_align_corners_used); + const auto hr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_height), + dst->dimension(idx_height), is_align_corners_used); + + // Area interpolation behaves as Nearest Neighbour in case of up-sampling + InterpolationPolicy policy_to_use = + (_scale_info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) + ? InterpolationPolicy::NEAREST_NEIGHBOR + : _scale_info.interpolation_policy; + + // Get the tensor shape + TensorShape shape(dst->dimension(idx_width)); + shape.set(1, dst->dimension(idx_height), false); + + TensorInfo tensor_info_offsets(shape, Format::S32); + TensorInfo tensor_info_dxdy(shape, Format::F32); + + auto dx = std::make_unique<TensorInfo>(tensor_info_dxdy); + auto dy = std::make_unique<TensorInfo>(tensor_info_dxdy); + auto offsets = std::make_unique<TensorInfo>(tensor_info_offsets); + auto scale_kernel = std::make_unique<kernels::CpuScaleKernel>(); + switch (policy_to_use) + { + case InterpolationPolicy::NEAREST_NEIGHBOR: + { + scale_kernel->configure(src, nullptr, nullptr, offsets.get(), dst, info); + break; + } + case InterpolationPolicy::BILINEAR: + { + scale_kernel->configure(src, dx.get(), dy.get(), offsets.get(), dst, info); + break; + } + case InterpolationPolicy::AREA: + { + scale_kernel->configure(src, nullptr, nullptr, nullptr, dst, info); + break; + } + default: + ARM_COMPUTE_ERROR("Unsupported interpolation mode"); + } + _kernel = std::move(scale_kernel); +} + +Status CpuScale::validate(const ITensorInfo *src, const ITensorInfo *dst, const ScaleKernelInfo &info) +{ + ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(src, dst); + ARM_COMPUTE_RETURN_ERROR_ON(info.sampling_policy != SamplingPolicy::CENTER && + info.sampling_policy != SamplingPolicy::TOP_LEFT); + + ITensorInfo *offsets = nullptr; + ITensorInfo *dx = nullptr; + ITensorInfo *dy = nullptr; + + // Get data layout and width/height indices + const DataLayout data_layout = info.data_layout == DataLayout::UNKNOWN ? src->data_layout() : info.data_layout; + const int idx_width = get_data_layout_dimension_index(data_layout, DataLayoutDimension::WIDTH); + const int idx_height = get_data_layout_dimension_index(data_layout, DataLayoutDimension::HEIGHT); + + // Compute the ratio between source width/height and destination width/height + const bool is_align_corners_used = + info.align_corners && arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(info.sampling_policy); + const auto wr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_width), + dst->dimension(idx_width), is_align_corners_used); + const auto hr = arm_compute::scale_utils::calculate_resize_ratio(src->dimension(idx_height), + dst->dimension(idx_height), is_align_corners_used); + + // Area interpolation behaves as Nearest Neighbour in case of up-sampling + InterpolationPolicy policy_to_use = + (info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) + ? InterpolationPolicy::NEAREST_NEIGHBOR + : info.interpolation_policy; + + // Get the tensor shape of auxilary buffers + const TensorShape shape(dst->dimension(idx_width), dst->dimension(idx_height)); + TensorInfo tensor_info_offsets(shape, Format::S32); + TensorInfo tensor_info_dx(shape, Format::F32); + TensorInfo tensor_info_dy(shape, Format::F32); + switch (policy_to_use) + { + case InterpolationPolicy::NEAREST_NEIGHBOR: + offsets = &tensor_info_offsets; + break; + case InterpolationPolicy::BILINEAR: + offsets = &tensor_info_offsets; + dx = &tensor_info_dx; + dy = &tensor_info_dy; + break; + default: + break; + } + + ARM_COMPUTE_RETURN_ON_ERROR( + kernels::CpuScaleKernel::validate(src->clone().get(), dx, dy, offsets, dst->clone().get(), info)); + return Status{}; +} + +void CpuScale::prepare(ITensorPack &tensors) +{ + if (!_is_prepared) + { + _is_prepared = true; + const auto src = tensors.get_const_tensor(TensorType::ACL_SRC); + auto dst = tensors.get_tensor(TensorType::ACL_DST); + auto dx = tensors.get_tensor(TensorType::ACL_INT_0); + auto dy = tensors.get_tensor(TensorType::ACL_INT_1); + auto offsets = tensors.get_tensor(TensorType::ACL_INT_2); + + // Get data layout and width/height indices + const int idx_width = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::WIDTH); + const int idx_height = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); + + // Compute the ratio between source width/height and destination width/height + const bool is_align_corners_used = + _scale_info.align_corners && + arm_compute::scale_utils::is_align_corners_allowed_sampling_policy(_scale_info.sampling_policy); + const auto wr = arm_compute::scale_utils::calculate_resize_ratio( + src->info()->dimension(idx_width), dst->info()->dimension(idx_width), is_align_corners_used); + const auto hr = arm_compute::scale_utils::calculate_resize_ratio( + src->info()->dimension(idx_height), dst->info()->dimension(idx_height), is_align_corners_used); + + // Area interpolation behaves as Nearest Neighbour in case of up-sampling + InterpolationPolicy policy_to_use = + (_scale_info.interpolation_policy == InterpolationPolicy::AREA && wr <= 1.f && hr <= 1.f) + ? InterpolationPolicy::NEAREST_NEIGHBOR + : _scale_info.interpolation_policy; + const SamplingPolicy sampling_policy = _scale_info.sampling_policy; + + bool precompute_indices_weights = arm_compute::scale_utils::is_precomputation_required( + _data_layout, src->info()->data_type(), policy_to_use, _scale_info.border_mode); + + if (precompute_indices_weights) + { + switch (policy_to_use) + { + case InterpolationPolicy::NEAREST_NEIGHBOR: + { + // Pre-compute offsets for nearest interpolation + precompute_dx_dy_offsets(nullptr, nullptr, offsets, wr, hr, sampling_policy, is_align_corners_used); + break; + } + case InterpolationPolicy::BILINEAR: + { + // Pre-compute dx, dy and offsets for bilinear interpolation + precompute_dx_dy_offsets(dx, dy, offsets, wr, hr, sampling_policy, is_align_corners_used); + break; + } + case InterpolationPolicy::AREA: + { + break; + } + default: + ARM_COMPUTE_ERROR("Unsupported interpolation mode"); + } + } + else + { + if (policy_to_use != InterpolationPolicy::NEAREST_NEIGHBOR && + policy_to_use != InterpolationPolicy::BILINEAR && policy_to_use != InterpolationPolicy::AREA) + { + ARM_COMPUTE_ERROR("Unsupported interpolation mode"); + } + } + } +} + +void CpuScale::run(ITensorPack &tensors) +{ + ARM_COMPUTE_ERROR_ON_MSG(tensors.empty(), "No inputs provided"); + prepare(tensors); + NEScheduler::get().schedule_op(_kernel.get(), Window::DimY, _kernel->window(), tensors); +} +} // namespace cpu +} // namespace arm_compute |