| /* |
| * Copyright (c) 2018-2020 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/CL/kernels/CLSpaceToBatchLayerKernel.h" |
| |
| #include "arm_compute/core/CL/CLHelpers.h" |
| #include "arm_compute/core/CL/CLValidate.h" |
| #include "arm_compute/core/CL/ICLTensor.h" |
| #include "arm_compute/core/utils/misc/ShapeCalculator.h" |
| #include "support/StringSupport.h" |
| |
| using namespace arm_compute::misc::shape_calculator; |
| |
| namespace arm_compute |
| { |
| namespace |
| { |
| Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_info, const ITensorInfo *padddings, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, padddings, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(block_info, 1, DataType::S32); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4); |
| ARM_COMPUTE_RETURN_ERROR_ON(block_info->num_dimensions() > 1); |
| ARM_COMPUTE_RETURN_ERROR_ON(padddings->num_dimensions() > 2); |
| ARM_COMPUTE_RETURN_ERROR_ON(padddings->tensor_shape()[1] != block_info->tensor_shape()[0]); |
| |
| // Validate output if initialized |
| if(output->total_size() != 0) |
| { |
| const DataLayout data_layout = input->data_layout(); |
| const int idx_channel = get_data_layout_dimension_index(data_layout, DataLayoutDimension::CHANNEL); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] != output->tensor_shape()[idx_channel]); |
| 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 Size2D &padding_left, const Size2D &padding_right, |
| const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x < 1 || block_shape_y < 1); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->num_dimensions() > 4); |
| |
| // 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(output->tensor_shape()[idx_width] < padding_left.x() + padding_right.y()); |
| ARM_COMPUTE_RETURN_ERROR_ON((input->tensor_shape()[idx_width] + padding_left.x() + padding_right.x()) % block_shape_x != 0); |
| ARM_COMPUTE_RETURN_ERROR_ON((input->tensor_shape()[idx_height] + padding_left.y() + padding_right.y()) % block_shape_y != 0); |
| ARM_COMPUTE_RETURN_ERROR_ON(input->tensor_shape()[idx_channel] != output->tensor_shape()[idx_channel]); |
| ARM_COMPUTE_RETURN_ERROR_ON(output->tensor_shape()[idx_batch] % (block_shape_x * block_shape_y) != 0); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); |
| ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output); |
| } |
| |
| return Status{}; |
| } |
| } // namespace |
| |
| CLSpaceToBatchLayerKernel::CLSpaceToBatchLayerKernel() |
| : _input(nullptr), _block_shape(nullptr), _paddings(nullptr), _output(nullptr) |
| { |
| } |
| |
| void CLSpaceToBatchLayerKernel::configure(const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input, block_shape, paddings, output); |
| } |
| |
| void CLSpaceToBatchLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *block_shape, const ICLTensor *paddings, ICLTensor *output) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), paddings->info(), output->info())); |
| |
| _input = input; |
| _block_shape = block_shape; |
| _paddings = paddings; |
| _output = output; |
| |
| const DataLayout data_layout = input->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); |
| const int idx_batch = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES); |
| |
| // Create kernel |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(data_size_from_type(input->info()->data_type()))); |
| build_opts.add_option("-DWIDTH_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_width))); |
| build_opts.add_option("-DHEIGHT_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_height))); |
| build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(output->info()->dimension(idx_batch))); |
| build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width))); |
| build_opts.add_option("-DHEIGHT_IN=" + support::cpp11::to_string(input->info()->dimension(idx_height))); |
| build_opts.add_option("-DBATCH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_batch))); |
| _kernel = create_kernel(compile_context, "space_to_batch_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*output->info(), Steps()); |
| ICLKernel::configure_internal(win); |
| } |
| |
| void CLSpaceToBatchLayerKernel::configure(const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, |
| ICLTensor *output) |
| { |
| configure(CLKernelLibrary::get().get_compile_context(), input, block_shape_x, block_shape_y, padding_left, padding_right, output); |
| } |
| |
| void CLSpaceToBatchLayerKernel::configure(const CLCompileContext &compile_context, const ICLTensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, |
| const Size2D &padding_right, |
| ICLTensor *output) |
| { |
| ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); |
| |
| TensorShape output_shape = misc::shape_calculator::compute_space_to_batch_shape(input->info(), block_shape_x, block_shape_y, padding_left, padding_right); |
| auto_init_if_empty(*output->info(), output_shape, 1, input->info()->data_type(), input->info()->quantization_info()); |
| |
| ARM_COMPUTE_ERROR_THROW_ON(validate_arguments_static(input->info(), block_shape_x, block_shape_y, padding_left, padding_right, output->info())); |
| |
| _input = input; |
| _output = output; |
| |
| const DataLayout data_layout = input->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); |
| const int idx_batch = get_data_layout_dimension_index(data_layout, DataLayoutDimension::BATCHES); |
| |
| // Create kernel |
| CLBuildOptions build_opts; |
| build_opts.add_option("-DDATA_TYPE=" + get_cl_unsigned_type_from_element_size(data_size_from_type(input->info()->data_type()))); |
| build_opts.add_option("-DWIDTH_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_width))); |
| build_opts.add_option("-DHEIGHT_OUT=" + support::cpp11::to_string(output->info()->dimension(idx_height))); |
| build_opts.add_option("-DBATCH_SIZE=" + support::cpp11::to_string(output->info()->dimension(idx_batch))); |
| build_opts.add_option("-DWIDTH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_width))); |
| build_opts.add_option("-DHEIGHT_IN=" + support::cpp11::to_string(input->info()->dimension(idx_height))); |
| build_opts.add_option("-DBATCH_IN=" + support::cpp11::to_string(input->info()->dimension(idx_batch))); |
| build_opts.add_option("-DBLOCK_SHAPE_X=" + support::cpp11::to_string(block_shape_x)); |
| build_opts.add_option("-DBLOCK_SHAPE_Y=" + support::cpp11::to_string(block_shape_y)); |
| build_opts.add_option("-DPAD_LEFT_X=" + support::cpp11::to_string(padding_left.x())); |
| build_opts.add_option("-DPAD_RIGHT_X=" + support::cpp11::to_string(padding_right.x())); |
| build_opts.add_option("-DPAD_LEFT_Y=" + support::cpp11::to_string(padding_left.y())); |
| build_opts.add_option("-DPAD_RIGHT_Y=" + support::cpp11::to_string(padding_right.y())); |
| _kernel = create_kernel(compile_context, "space_to_batch_static_" + lower_string(string_from_data_layout(input->info()->data_layout())), build_opts.options()); |
| |
| // Configure kernel window |
| Window win = calculate_max_window(*output->info(), Steps()); |
| ICLKernel::configure_internal(win); |
| } |
| |
| Status CLSpaceToBatchLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *paddings, const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, block_shape, paddings, output)); |
| return Status{}; |
| } |
| Status CLSpaceToBatchLayerKernel::validate(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, |
| const ITensorInfo *output) |
| { |
| ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments_static(input, block_shape_x, block_shape_y, padding_left, padding_right, output)); |
| return Status{}; |
| } |
| |
| void CLSpaceToBatchLayerKernel::run(const Window &window, cl::CommandQueue &queue) |
| { |
| ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); |
| ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICLKernel::window(), window); |
| |
| Window slice_out = window.first_slice_window_3D(); |
| |
| Window slice_in = window.first_slice_window_4D(); |
| slice_in.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| slice_in.set(Window::DimY, Window::Dimension(0, 0, 0)); |
| slice_in.set(Window::DimZ, Window::Dimension(0, 0, 0)); |
| slice_in.set(3, Window::Dimension(0, 0, 0)); |
| |
| Window vector_slice = window.first_slice_window_1D(); |
| vector_slice.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| |
| Window padding_slice = window.first_slice_window_2D(); |
| padding_slice.set(Window::DimX, Window::Dimension(0, 0, 0)); |
| padding_slice.set(Window::DimY, Window::Dimension(0, 0, 0)); |
| |
| int batch_id = 0; |
| do |
| { |
| unsigned int idx = 0; |
| const bool cond = (_paddings != nullptr && _block_shape != nullptr); |
| add_4D_tensor_argument(idx, _input, slice_in); |
| add_2D_tensor_argument_if(cond, idx, _paddings, padding_slice); |
| add_1D_tensor_argument_if(cond, idx, _block_shape, vector_slice); |
| |
| add_argument(idx, batch_id); |
| add_3D_tensor_argument(idx, _output, slice_out); |
| enqueue(queue, *this, slice_out, lws_hint()); |
| ++batch_id; |
| } |
| while(window.slide_window_slice_3D(slice_out)); |
| } |
| } // namespace arm_compute |