From afd38f0c617d6f89b2b4532c6c44f116617e2b6f Mon Sep 17 00:00:00 2001 From: Felix Thomasmathibalan Date: Wed, 27 Sep 2023 17:46:17 +0100 Subject: Apply clang-format on repository Code is formatted as per a revised clang format configuration file(not part of this delivery). Version 14.0.6 is used. Exclusion List: - files with .cl extension - files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...) And the following directories - compute_kernel_writer/validation/ - tests/ - include/ - src/core/NEON/kernels/convolution/ - src/core/NEON/kernels/arm_gemm/ - src/core/NEON/kernels/arm_conv/ - data/ There will be a follow up for formatting of .cl files and the files under tests/ and compute_kernel_writer/validation/. Signed-off-by: Felix Thomasmathibalan Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391 Benchmark: Arm Jenkins Tested-by: Arm Jenkins Reviewed-by: Gunes Bayir --- .../NEON/kernels/NESpaceToBatchLayerKernel.cpp | 161 +++++++++++++-------- 1 file changed, 100 insertions(+), 61 deletions(-) (limited to 'src/core/NEON/kernels/NESpaceToBatchLayerKernel.cpp') diff --git a/src/core/NEON/kernels/NESpaceToBatchLayerKernel.cpp b/src/core/NEON/kernels/NESpaceToBatchLayerKernel.cpp index 673eace3c1..da023aeb96 100644 --- a/src/core/NEON/kernels/NESpaceToBatchLayerKernel.cpp +++ b/src/core/NEON/kernels/NESpaceToBatchLayerKernel.cpp @@ -26,11 +26,12 @@ #include "arm_compute/core/Helpers.h" #include "arm_compute/core/ITensor.h" #include "arm_compute/core/Types.h" -#include "arm_compute/core/Validate.h" #include "arm_compute/core/utils/misc/ShapeCalculator.h" -#include "src/core/NEON/wrapper/wrapper.h" +#include "arm_compute/core/Validate.h" + #include "src/core/helpers/AutoConfiguration.h" #include "src/core/helpers/WindowHelpers.h" +#include "src/core/NEON/wrapper/wrapper.h" #include #include @@ -41,19 +42,22 @@ namespace arm_compute { namespace { -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_info, const ITensorInfo *paddings, const ITensorInfo *output) +Status validate_arguments(const ITensorInfo *input, + const ITensorInfo *block_info, + const ITensorInfo *paddings, + const ITensorInfo *output) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, block_info, paddings, output); ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN); 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(block_info->num_dimensions() > 1); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(block_info->tensor_shape(), TensorShape{ 2 }); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(block_info->tensor_shape(), TensorShape{2}); ARM_COMPUTE_RETURN_ERROR_ON(paddings->num_dimensions() > 2); - ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(paddings->tensor_shape(), TensorShape{ 2, 2 }); + ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(paddings->tensor_shape(), TensorShape{2, 2}); // Validate output if initialized - if(output->total_size() != 0) + 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); @@ -64,7 +68,11 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *block_inf 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, +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); @@ -73,9 +81,10 @@ Status validate_arguments_static(const ITensorInfo *input, const int block_shape ARM_COMPUTE_RETURN_ERROR_ON(block_shape_x < 1 || block_shape_y < 1); // Validate output if initialized - if(output->total_size() != 0) + if (output->total_size() != 0) { - TensorShape expected_output_shape = misc::shape_calculator::compute_space_to_batch_shape(input, block_shape_x, block_shape_y, padding_left, padding_right); + TensorShape expected_output_shape = misc::shape_calculator::compute_space_to_batch_shape( + input, block_shape_x, block_shape_y, padding_left, padding_right); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DIMENSIONS(output->tensor_shape(), expected_output_shape); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_QUANTIZATION_INFO(input, output); @@ -86,14 +95,25 @@ Status validate_arguments_static(const ITensorInfo *input, const int block_shape } // namespace NESpaceToBatchLayerKernel::NESpaceToBatchLayerKernel() - : _input(nullptr), _block_shape(nullptr), _paddings(nullptr), _output(nullptr), _data_layout(DataLayout::UNKNOWN), _padding_left(), _block_shape_x(), _block_shape_y() + : _input(nullptr), + _block_shape(nullptr), + _paddings(nullptr), + _output(nullptr), + _data_layout(DataLayout::UNKNOWN), + _padding_left(), + _block_shape_x(), + _block_shape_y() { } -void NESpaceToBatchLayerKernel::configure(const ITensor *input, const ITensor *block_shape, const ITensor *paddings, ITensor *output) +void NESpaceToBatchLayerKernel::configure(const ITensor *input, + const ITensor *block_shape, + const ITensor *paddings, + ITensor *output) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, block_shape, paddings, output); - ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), block_shape->info(), paddings->info(), output->info())); + ARM_COMPUTE_ERROR_THROW_ON( + validate_arguments(input->info(), block_shape->info(), paddings->info(), output->info())); _input = input; _block_shape = block_shape; @@ -106,15 +126,22 @@ void NESpaceToBatchLayerKernel::configure(const ITensor *input, const ITensor *b ICPPKernel::configure(win); } -void NESpaceToBatchLayerKernel::configure(const ITensor *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, - ITensor *output) +void NESpaceToBatchLayerKernel::configure(const ITensor *input, + const int block_shape_x, + const int block_shape_y, + const Size2D &padding_left, + const Size2D &padding_right, + ITensor *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()); + 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())); + 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; @@ -128,15 +155,23 @@ void NESpaceToBatchLayerKernel::configure(const ITensor *input, const int block_ INEKernel::configure(win); } -Status NESpaceToBatchLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *block_shape, const ITensorInfo *paddings, const ITensorInfo *output) +Status NESpaceToBatchLayerKernel::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 NESpaceToBatchLayerKernel::validate(const ITensorInfo *input, const int block_shape_x, const int block_shape_y, const Size2D &padding_left, const Size2D &padding_right, +Status NESpaceToBatchLayerKernel::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)); + ARM_COMPUTE_RETURN_ON_ERROR( + validate_arguments_static(input, block_shape_x, block_shape_y, padding_left, padding_right, output)); return Status{}; } @@ -146,17 +181,17 @@ void NESpaceToBatchLayerKernel::run(const Window &window, const ThreadInfo &info ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(ICPPKernel::window(), window); - if(_block_shape != nullptr) + if (_block_shape != nullptr) { // Retrieve the block shapes dynamically _block_shape_x = *(reinterpret_cast(_block_shape->ptr_to_element(0))); _block_shape_y = *(reinterpret_cast(_block_shape->ptr_to_element(1))); } - if(_paddings != nullptr) + if (_paddings != nullptr) { - const size_t pad_left_x = *reinterpret_cast(_paddings->ptr_to_element({ 0, 0 })); - const size_t pad_left_y = *reinterpret_cast(_paddings->ptr_to_element({ 1, 0 })); + const size_t pad_left_x = *reinterpret_cast(_paddings->ptr_to_element({0, 0})); + const size_t pad_left_y = *reinterpret_cast(_paddings->ptr_to_element({1, 0})); _padding_left = Size2D(pad_left_x, pad_left_y); } const int height_idx = get_data_layout_dimension_index(_data_layout, DataLayoutDimension::HEIGHT); @@ -173,57 +208,61 @@ void NESpaceToBatchLayerKernel::run(const Window &window, const ThreadInfo &info int batch_id = 0; // Main loop for NCHW and NHWC - if(_data_layout == DataLayout::NCHW) + if (_data_layout == DataLayout::NCHW) { do { Iterator out(_output, slice_out); - execute_window_loop(slice_out, [&](const Coordinates & id) - { - const size_t out_x = id.x(); - const size_t out_y = id.y(); - const size_t z = id.z(); - const size_t pos_x = out_x * _block_shape_x + (batch_id / batch_size) % _block_shape_x; - const size_t pos_y = out_y * _block_shape_y + (batch_id / batch_size) / _block_shape_x; - if(pos_y >= _padding_left.y() && pos_y < _padding_left.y() + height && pos_x >= _padding_left.x() && pos_x < _padding_left.x() + width) + execute_window_loop( + slice_out, + [&](const Coordinates &id) { - const int w = batch_id % batch_size; - const int in_x = pos_x - _padding_left.x(); - const int in_y = pos_y - _padding_left.y(); - Coordinates input_coords{ in_x, in_y, z, w }; - memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size); - } - }, - out); + const size_t out_x = id.x(); + const size_t out_y = id.y(); + const size_t z = id.z(); + const size_t pos_x = out_x * _block_shape_x + (batch_id / batch_size) % _block_shape_x; + const size_t pos_y = out_y * _block_shape_y + (batch_id / batch_size) / _block_shape_x; + if (pos_y >= _padding_left.y() && pos_y < _padding_left.y() + height && + pos_x >= _padding_left.x() && pos_x < _padding_left.x() + width) + { + const int w = batch_id % batch_size; + const int in_x = pos_x - _padding_left.x(); + const int in_y = pos_y - _padding_left.y(); + Coordinates input_coords{in_x, in_y, z, w}; + memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size); + } + }, + out); ++batch_id; - } - while(window.slide_window_slice_3D(slice_out)); + } 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 out_x = id.y(); - const size_t out_y = id.z(); - const size_t z = id.x(); - const size_t pos_x = out_x * _block_shape_x + (batch_id / batch_size) % _block_shape_x; - const size_t pos_y = out_y * _block_shape_y + (batch_id / batch_size) / _block_shape_x; - if(pos_y >= _padding_left.y() && pos_y < _padding_left.y() + height && pos_x >= _padding_left.x() && pos_x < _padding_left.x() + width) + execute_window_loop( + slice_out, + [&](const Coordinates &id) { - const int w = batch_id % batch_size; - const int in_x = pos_x - _padding_left.x(); - const int in_y = pos_y - _padding_left.y(); - Coordinates input_coords{ z, in_x, in_y, w }; - memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size); - } - }, - out); + const size_t out_x = id.y(); + const size_t out_y = id.z(); + const size_t z = id.x(); + const size_t pos_x = out_x * _block_shape_x + (batch_id / batch_size) % _block_shape_x; + const size_t pos_y = out_y * _block_shape_y + (batch_id / batch_size) / _block_shape_x; + if (pos_y >= _padding_left.y() && pos_y < _padding_left.y() + height && + pos_x >= _padding_left.x() && pos_x < _padding_left.x() + width) + { + const int w = batch_id % batch_size; + const int in_x = pos_x - _padding_left.x(); + const int in_y = pos_y - _padding_left.y(); + Coordinates input_coords{z, in_x, in_y, w}; + memcpy(out.ptr(), _input->ptr_to_element(input_coords), element_size); + } + }, + out); ++batch_id; - } - while(window.slide_window_slice_3D(slice_out)); + } while (window.slide_window_slice_3D(slice_out)); } } } // namespace arm_compute -- cgit v1.2.1