| /* |
| * 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/NEBatchToSpaceLayerKernel.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 <arm_neon.h> |
| #include <cstdint> |
| |
| 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, const int block_shape_x, const int block_shape_y, const ITensorInfo *output) |
| { |
| 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) |
| { |
| 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); |
| ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_width] != (block_shape_x * input->tensor_shape()[idx_width])); |
| ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_height] != (block_shape_y * input->tensor_shape()[idx_height])); |
| ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_channel] != input->tensor_shape()[idx_channel]); |
| ARM_COMPUTE_RETURN_ERROR_ON(output->num_dimensions() > 4); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| } |
| |
| return Status{}; |
| } |
| } // namespace |
| |
| NEBatchToSpaceLayerKernel::NEBatchToSpaceLayerKernel() |
| : _input(nullptr), _block_shape(nullptr), _output(nullptr), _block_shape_x(), _block_shape_y() |
| { |
| } |
| |
| 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; |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*input->info(), Steps()); |
| ICPPKernel::configure(win); |
| } |
| |
| void NEBatchToSpaceLayerKernel::configure(const ITensor *input, const int32_t block_shape_x, const int32_t block_shape_y, ITensor *output) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| TensorShape output_shape = compute_batch_to_space_shape(input->info(), block_shape_x, block_shape_y); |
| // Output auto inizialitation 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())); |
| |
| _input = input; |
| _output = output; |
| _block_shape_x = block_shape_x; |
| _block_shape_y = block_shape_y; |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*input->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, const int32_t block_shape_x, const int32_t block_shape_y, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, output)); |
| 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 = _input->info()->dimension(3); |
| const int r = (batch_size / (_block_shape_x * _block_shape_y)); |
| const int element_size = _input->info()->element_size(); |
| |
| Window slice_in = window.first_slice_window_3D(); |
| Window slice_out = window.first_slice_window_4D(); |
| |
| // The slice_out slice does not move |
| slice_out.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| slice_out.set(Window::DimY, Window::Dimension(0, 0, 0)); |
| slice_out.set(Window::DimZ, Window::Dimension(0, 0, 0)); |
| slice_out.set(3, Window::Dimension(0, 0, 0)); |
| |
| int batch_id = 0; |
| // Main loop for NCHW and NHWC |
| if(_input->info()->data_layout() == DataLayout::NCHW) |
| { |
| do |
| { |
| Iterator in(_input, slice_in); |
| execute_window_loop(slice_in, [&](const Coordinates & id) |
| { |
| |
| const int x = id.x(); |
| const int y = id.y(); |
| const int z = id.z(); |
| |
| const int w = batch_id % r; |
| const int out_x = x * _block_shape_x + (batch_id / r) % _block_shape_x; |
| const int out_y = y * _block_shape_y + (batch_id / r) / _block_shape_x; |
| Coordinates output_coords{ out_x, out_y, z, w }; |
| memcpy(_output->ptr_to_element(output_coords), in.ptr(), element_size); |
| }, |
| in); |
| ++batch_id; |
| } |
| while(window.slide_window_slice_3D(slice_in)); |
| } |
| else |
| { |
| do |
| { |
| Iterator in(_input, slice_in); |
| execute_window_loop(slice_in, [&](const Coordinates & id) |
| { |
| |
| const int z = id.x(); |
| const int x = id.y(); |
| const int y = id.z(); |
| |
| const int w = batch_id % r; |
| const int out_x = x * _block_shape_x + (batch_id / r) % _block_shape_x; |
| const int out_y = y * _block_shape_y + (batch_id / r) / _block_shape_x; |
| Coordinates output_coords{ z, out_x, out_y, w }; |
| memcpy(_output->ptr_to_element(output_coords), in.ptr(), element_size); |
| }, |
| in); |
| ++batch_id; |
| } |
| while(window.slide_window_slice_3D(slice_in)); |
| } |
| } |
| } // namespace arm_compute |