/* * Copyright (c) 2019 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/core/NEON/kernels/NESpaceToDepthLayerKernel.h" #include "arm_compute/core/Helpers.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/NEON/wrapper/wrapper.h" #include "arm_compute/core/Types.h" #include "arm_compute/core/Validate.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" #include #include using namespace arm_compute::misc::shape_calculator; namespace arm_compute { namespace { Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, int32_t block_shape) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4); ARM_COMPUTE_RETURN_ERROR_ON(block_shape < 1); // Validate output if initialized if(output->total_size() != 0) { const DataLayout data_layout = input->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); const int idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); const int idx_batch = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES); ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_width] % block_shape != 0); ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_height] % block_shape != 0); ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_batch] != output->tensor_shape()[idx_batch]); ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_channel] % (block_shape * block_shape) != 0); ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape().total_size() != output->tensor_shape().total_size()); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); } return Status{}; } } // namespace NESpaceToDepthLayerKernel::NESpaceToDepthLayerKernel() : _input(nullptr), _output(nullptr), _block_shape() { } void NESpaceToDepthLayerKernel::configure(const ITensor *input, ITensor *output, int32_t block_shape) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); TensorShape output_shape = misc::shape_calculator::compute_space_to_depth_shape(input->info(), block_shape); auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type()); ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), block_shape)); _input = input; _block_shape = block_shape; _output = output; // Configure kernel window Window win = calculate_max_window(*output->info(), Steps()); INEKernel::configure(win); } Status NESpaceToDepthLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, int32_t block_shape) { ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, block_shape)); return Status{}; } void NESpaceToDepthLayerKernel::run(const Window &window, const ThreadInfo &info) { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICPPKernel::window(), window); const DataLayout data_layout = _input->info()->data_layout(); const int channel_idx = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); const int element_size = _input->info()->element_size(); const size_t channel_size = _input->info()->dimension(channel_idx); Window slice_out = window.first_slice_window_3D(); int batch_id = 0; // Main loop for NCHW and NHWC if(_output->info()->data_layout() == DataLayout::NCHW) { do { Iterator out(_output, slice_out); execute_window_loop(slice_out, [&](const Coordinates & id) { const size_t channel_id = id.z(); const size_t in_x = id.x() * _block_shape + (channel_id / channel_size) % _block_shape; const size_t in_y = id.y() * _block_shape + (channel_id / channel_size) / _block_shape; const int z = channel_id % channel_size; Coordinates input_coords{ in_x, in_y, z, batch_id }; memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size); }, out); ++batch_id; } while(window.slide_window_slice_3D(slice_out)); } else { do { Iterator out(_output, slice_out); execute_window_loop(slice_out, [&](const Coordinates & id) { const size_t channel_id = id.x(); const size_t in_x = id.y() * _block_shape + (channel_id / channel_size) % _block_shape; const size_t in_y = id.z() * _block_shape + (channel_id / channel_size) / _block_shape; const int z = channel_id % channel_size; Coordinates input_coords{ z, in_x, in_y, batch_id }; memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size); }, out); ++batch_id; } while(window.slide_window_slice_3D(slice_out)); } } } // namespace arm_compute