| /* |
| * Copyright (c) 2019-2020, 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/core/NEON/kernels/NEBatchToSpaceLayerKernel.h" |
| |
| #include "arm_compute/core/Helpers.h" |
| #include "arm_compute/core/ITensor.h" |
| #include "arm_compute/core/TensorInfo.h" |
| #include "arm_compute/core/Types.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "arm_compute/core/Validate.h" |
| |
| #include "src/core/helpers/AutoConfiguration.h" |
| #include "src/core/helpers/WindowHelpers.h" |
| |
| using namespace arm_compute::misc::shape_calculator; |
| |
| namespace arm_compute |
| { |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_info, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(block_info, 1, DataType::S32); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN); |
| |
| // Validate output if initialized |
| if (output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| } |
| |
| return Status{}; |
| } |
| Status validate_arguments_static(const ITensorInfo *input, |
| int block_shape_x, |
| int block_shape_y, |
| const ITensorInfo *output, |
| const CropInfo &crop_info) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4); |
| ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x <= 0); |
| ARM_COMPUTE_RETURN_ERROR_ON(block_shape_y <= 0); |
| |
| const DataLayout data_layout = input->data_layout(); |
| const int idx_batch = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_batch] % (block_shape_x * block_shape_y) != 0); |
| // Validate output if initialized |
| if (output->total_size() != 0) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| |
| const TensorShape expected_output_shape = compute_batch_to_space_shape( |
| input->data_layout(), input->tensor_shape(), block_shape_x, block_shape_y, crop_info); |
| const TensorInfo expected_output = output->clone()->set_tensor_shape(expected_output_shape); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &expected_output); |
| } |
| |
| return Status{}; |
| } |
| } // namespace |
| |
| NEBatchToSpaceLayerKernel::NEBatchToSpaceLayerKernel() |
| : _input(nullptr), |
| _block_shape(nullptr), |
| _output(nullptr), |
| _data_layout(DataLayout::UNKNOWN), |
| _block_shape_x(), |
| _block_shape_y(), |
| _crop_info() |
| { |
| } |
| |
| void NEBatchToSpaceLayerKernel::configure(const ITensor *input, const ITensor *block_shape, ITensor *output) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), output->info())); |
| |
| _input = input; |
| _block_shape = block_shape; |
| _output = output; |
| _data_layout = input->info()->data_layout(); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*output->info(), Steps()); |
| ICPPKernel::configure(win); |
| } |
| |
| void NEBatchToSpaceLayerKernel::configure( |
| const ITensor *input, int32_t block_shape_x, int32_t block_shape_y, ITensor *output, const CropInfo &crop_info) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| const TensorShape output_shape = compute_batch_to_space_shape( |
| input->info()->data_layout(), input->info()->tensor_shape(), block_shape_x, block_shape_y); |
| // Output auto initialization if not yet initialized |
| auto_init_if_empty(*output->info(), input->info()->clone()->set_tensor_shape(output_shape)); |
| |
| // Perform validation step |
| ARM_COMPUTE_ERROR_THROW_ON( |
| validate_arguments_static(input->info(), block_shape_x, block_shape_y, output->info(), crop_info)); |
| |
| _input = input; |
| _output = output; |
| _block_shape_x = block_shape_x; |
| _block_shape_y = block_shape_y; |
| _data_layout = input->info()->data_layout(); |
| _crop_info = crop_info; |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*output->info(), Steps()); |
| ICPPKernel::configure(win); |
| } |
| |
| Status |
| NEBatchToSpaceLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_shape, output); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, block_shape, output)); |
| return Status{}; |
| } |
| |
| Status NEBatchToSpaceLayerKernel::validate(const ITensorInfo *input, |
| int32_t block_shape_x, |
| int32_t block_shape_y, |
| const ITensorInfo *output, |
| const CropInfo &crop_info) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, output, crop_info)); |
| return Status{}; |
| } |
| |
| void NEBatchToSpaceLayerKernel::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); |
| |
| if (_block_shape != nullptr) |
| { |
| // Retrieve the block shapes dynamically |
| _block_shape_x = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(0))); |
| _block_shape_y = *(reinterpret_cast<const int *>(_block_shape->ptr_to_element(1))); |
| } |
| |
| const int batch_size = _output->info()->dimension(3); |
| const int element_size = _output->info()->element_size(); |
| |
| Window slice_out = window.first_slice_window_3D(); |
| |
| int batch_id = 0; |
| // Main loop for NCHW and NHWC |
| if (_data_layout == DataLayout::NCHW) |
| { |
| do |
| { |
| Iterator out(_output, slice_out); |
| execute_window_loop( |
| slice_out, |
| [&](const Coordinates &id) |
| { |
| const int x = id.x(); |
| const int y = id.y(); |
| const int z = id.z(); |
| // Translate x, y to uncropped version |
| const int x_c = x + _crop_info.left; |
| const int y_c = y + _crop_info.top; |
| |
| const int in_batch = |
| batch_id + ((x_c % _block_shape_x) + (y_c % _block_shape_y) * _block_shape_x) * batch_size; |
| const int in_x = x_c / _block_shape_x; |
| const int in_y = y_c / _block_shape_y; |
| Coordinates input_coords{in_x, in_y, z, in_batch}; |
| memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size); |
| }, |
| out); |
| ++batch_id; |
| } while (window.slide_window_slice_3D(slice_out)); |
| } |
| else |
| { |
| // For NHWC we can perform a block copy on the Channel (first) dimension. Thus we do not need to iterate over this dimension |
| slice_out.set(0U, Window::Dimension(0U, 1U, 1U)); |
| do |
| { |
| Iterator out(_output, slice_out); |
| execute_window_loop( |
| slice_out, |
| [&](const Coordinates &id) |
| { |
| const int x = id.y(); |
| const int y = id.z(); |
| |
| // Translate x, y to uncropped version |
| const int x_c = x + _crop_info.left; |
| const int y_c = y + _crop_info.top; |
| |
| const int in_batch = |
| batch_id + ((x_c % _block_shape_x) + (y_c % _block_shape_y) * _block_shape_x) * batch_size; |
| const int in_x = x_c / _block_shape_x; |
| const int in_y = y_c / _block_shape_y; |
| Coordinates input_coords{0, in_x, in_y, in_batch}; |
| memcpy(out.ptr(), _input->ptr_to_element(input_coords), |
| element_size * _input->info()->dimension(0)); |
| }, |
| out); |
| ++batch_id; |
| } while (window.slide_window_slice_3D(slice_out)); |
| } |
| } |
| } // namespace arm_compute |