| /* | |
| * Copyright (c) 2021-2022 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/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 |