/* * Copyright (c) 2016-2021 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/NEScale.h" #include "arm_compute/core/Validate.h" #include "arm_compute/runtime/Tensor.h" #include "src/core/utils/ScaleUtils.h" #include "src/runtime/cpu/operators/CpuScale.h" #include "support/Rounding.h" namespace arm_compute { struct NEScale::Impl { const ITensor *src{ nullptr }; ITensor *dst{ nullptr }; Tensor dx{ nullptr }; /**< Element's distance between the X real coordinate and the smallest X following integer */ Tensor dy{ nullptr }; /**< Element's distance between the Y real coordinate and the smallest Y following integer */ Tensor offsets{ nullptr }; /**< Offset to access the element with NEAREST interpolation or the top-left element with BILINEAR interpolation in the input tensor */ std::unique_ptr op{ nullptr }; }; NEScale::NEScale() : _impl(std::make_unique()) { } NEScale::~NEScale() = default; void NEScale::configure(ITensor *input, ITensor *output, const ScaleKernelInfo &info) { _impl->src = input; _impl->dst = output; _impl->op = std::make_unique(); _impl->op->configure(input->info(), output->info(), info); // Configure for size of allocation of internal tensors // Get data layout and width/height indices const DataLayout data_layout = info.data_layout == DataLayout::UNKNOWN ? input->info()->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(input->info()->dimension(idx_width), output->info()->dimension(idx_width), is_align_corners_used); const auto hr = arm_compute::scale_utils::calculate_resize_ratio(input->info()->dimension(idx_height), output->info()->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 TensorShape shape(output->info()->dimension(idx_width)); shape.set(1, output->info()->dimension(idx_height), false); const TensorInfo tensor_info_dxdy(shape, Format::F32); const TensorInfo tensor_info_offsets(shape, Format::S32); _impl->dx.allocator()->init(tensor_info_dxdy); _impl->dy.allocator()->init(tensor_info_dxdy); _impl->offsets.allocator()->init(tensor_info_offsets); switch(policy_to_use) { case InterpolationPolicy::NEAREST_NEIGHBOR: { // Allocate once the configure methods have been called _impl->offsets.allocator()->allocate(); break; } case InterpolationPolicy::BILINEAR: { // Allocate once the configure methods have been called _impl->dx.allocator()->allocate(); _impl->dy.allocator()->allocate(); _impl->offsets.allocator()->allocate(); break; } case InterpolationPolicy::AREA: { break; } default: ARM_COMPUTE_ERROR("Unsupported interpolation mode"); } } Status NEScale::validate(const ITensorInfo *input, const ITensorInfo *output, const ScaleKernelInfo &info) { return cpu::CpuScale::validate(input, output, info); } void NEScale::run() { ITensorPack pack; pack.add_tensor(TensorType::ACL_SRC, _impl->src); pack.add_tensor(TensorType::ACL_DST, _impl->dst); pack.add_tensor(TensorType::ACL_INT_0, &_impl->dx); pack.add_tensor(TensorType::ACL_INT_1, &_impl->dy); pack.add_tensor(TensorType::ACL_INT_2, &_impl->offsets); _impl->op->run(pack); } } // namespace arm_compute