diff options
Diffstat (limited to 'src/core/NEON/kernels/NEPadLayerKernel.cpp')
| -rw-r--r-- | src/core/NEON/kernels/NEPadLayerKernel.cpp | 115 |
1 files changed, 72 insertions, 43 deletions
diff --git a/src/core/NEON/kernels/NEPadLayerKernel.cpp b/src/core/NEON/kernels/NEPadLayerKernel.cpp index 3e2c57a18c..c9bcbc9127 100644 --- a/src/core/NEON/kernels/NEPadLayerKernel.cpp +++ b/src/core/NEON/kernels/NEPadLayerKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2019-2021 Arm Limited. + * Copyright (c) 2019-2022 Arm Limited. * * SPDX-License-Identifier: MIT * @@ -28,26 +28,31 @@ #include "arm_compute/core/ITensor.h" #include "arm_compute/core/TensorInfo.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" namespace arm_compute { namespace { -Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const PaddingList &paddings, const PaddingMode mode) +Status validate_arguments(const ITensorInfo *input, + const ITensorInfo *output, + const PaddingList &paddings, + const PaddingMode mode) { ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input); ARM_COMPUTE_RETURN_ERROR_ON(input->data_type() == DataType::UNKNOWN); ARM_COMPUTE_RETURN_ERROR_ON_MSG(mode != PaddingMode::CONSTANT, "Only constant padding mode is supported"); ARM_COMPUTE_RETURN_ERROR_ON_MSG(paddings.size() > 4, "Padding list bigger than 4 dimensions"); - if(output->total_size() != 0) + if (output->total_size() != 0) { - const TensorShape expected_output_shape = arm_compute::misc::shape_calculator::compute_padded_shape(input->tensor_shape(), paddings); - const TensorInfo expected_output_info = input->clone()->set_tensor_shape(expected_output_shape); + const TensorShape expected_output_shape = + arm_compute::misc::shape_calculator::compute_padded_shape(input->tensor_shape(), paddings); + const TensorInfo expected_output_info = input->clone()->set_tensor_shape(expected_output_shape); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(output, &expected_output_info); ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input, output); } @@ -58,30 +63,34 @@ Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, c template <typename T> void NEPadLayerKernel::run_pad_constant(const Window &window) { - Window output_window{ window }; + Window output_window{window}; output_window.set(Window::DimX, Window::Dimension(0, 1, 1)); const size_t element_size = _input->info()->element_size(); Iterator output_it(_output, output_window); - execute_window_loop(output_window, [&](const Coordinates & id) - { - Coordinates idin{ id }; - for(size_t dim = _padding.size() - 1; dim > 0; --dim) + execute_window_loop( + output_window, + [&](const Coordinates &id) { - idin[dim] -= _padding[dim].first; - if(idin[dim] < 0 || static_cast<int>(_input->info()->dimension(dim)) - 1 < idin[dim]) + Coordinates idin{id}; + for (size_t dim = _padding.size() - 1; dim > 0; --dim) { - std::fill_n(reinterpret_cast<T *>(output_it.ptr()), _output->info()->dimension(0), _constant_value.get<T>()); - return; + idin[dim] -= _padding[dim].first; + if (idin[dim] < 0 || static_cast<int>(_input->info()->dimension(dim)) - 1 < idin[dim]) + { + std::fill_n(reinterpret_cast<T *>(output_it.ptr()), _output->info()->dimension(0), + _constant_value.get<T>()); + return; + } } - } - T *input_it_ptr = reinterpret_cast<T *>(_input->ptr_to_element(idin)); - T *output_it_ptr = reinterpret_cast<T *>(output_it.ptr()); - std::fill_n(output_it_ptr, _padding[0].first, _constant_value.get<T>()); - memcpy(output_it_ptr + _padding[0].first, input_it_ptr, _input->info()->dimension(0) * element_size); - std::fill_n(output_it_ptr + _padding[0].first + _input->info()->dimension(0), _padding[0].second, _constant_value.get<T>()); - }, - output_it); + T *input_it_ptr = reinterpret_cast<T *>(_input->ptr_to_element(idin)); + T *output_it_ptr = reinterpret_cast<T *>(output_it.ptr()); + std::fill_n(output_it_ptr, _padding[0].first, _constant_value.get<T>()); + memcpy(output_it_ptr + _padding[0].first, input_it_ptr, _input->info()->dimension(0) * element_size); + std::fill_n(output_it_ptr + _padding[0].first + _input->info()->dimension(0), _padding[0].second, + _constant_value.get<T>()); + }, + output_it); } void NEPadLayerKernel::run_pad_constant_uint8_3Dinput_3Dpad(const Window &window) @@ -92,7 +101,7 @@ void NEPadLayerKernel::run_pad_constant_uint8_3Dinput_3Dpad(const Window &window const size_t end_plane = window.z().end(); size_t start_plane_input = start_plane; - if(_padding.size() > 2) + if (_padding.size() > 2) { start_plane_input = (start_plane < _padding[2].first) ? 0 : start_plane - _padding[2].first; } @@ -105,18 +114,20 @@ void NEPadLayerKernel::run_pad_constant_uint8_3Dinput_3Dpad(const Window &window const size_t jump_to_next_row_input = _input->info()->dimension(0); const size_t jump_to_next_row_output = _padding[0].first + _padding[0].second; - uint8_t *output_row_ptr = _output->buffer() + _output->info()->offset_first_element_in_bytes() + start_plane * output_plane_size; - const uint8_t *input_it_ptr = _input->buffer() + _input->info()->offset_first_element_in_bytes() + start_plane_input * input_plane_size; - const auto pad_value = _constant_value.get<uint8_t>(); + uint8_t *output_row_ptr = + _output->buffer() + _output->info()->offset_first_element_in_bytes() + start_plane * output_plane_size; + const uint8_t *input_it_ptr = + _input->buffer() + _input->info()->offset_first_element_in_bytes() + start_plane_input * input_plane_size; + const auto pad_value = _constant_value.get<uint8_t>(); - for(size_t z_i = start_plane; z_i < end_plane; ++z_i) + for (size_t z_i = start_plane; z_i < end_plane; ++z_i) { - if(_padding.size() > 2 && z_i < _padding[2].first) + if (_padding.size() > 2 && z_i < _padding[2].first) { memset(output_row_ptr, pad_value, output_plane_size); output_row_ptr += output_plane_size; } - else if(_padding.size() > 2 && z_i > (_input->info()->dimension(2) + _padding[2].first - 1)) + else if (_padding.size() > 2 && z_i > (_input->info()->dimension(2) + _padding[2].first - 1)) { memset(output_row_ptr, pad_value, output_plane_size); output_row_ptr += output_plane_size; @@ -127,7 +138,7 @@ void NEPadLayerKernel::run_pad_constant_uint8_3Dinput_3Dpad(const Window &window output_row_ptr += pad_y_elems_top; size_t y_i = _input->info()->dimension(1); // Basic loop unrolling - for(; y_i > 3; y_i -= 4) + for (; y_i > 3; y_i -= 4) { memset(output_row_ptr, pad_value, _padding[0].first); output_row_ptr += _padding[0].first; @@ -160,7 +171,7 @@ void NEPadLayerKernel::run_pad_constant_uint8_3Dinput_3Dpad(const Window &window memset(output_row_ptr, pad_value, _padding[0].second); output_row_ptr += _padding[0].second; } - for(; y_i > 0; --y_i) + for (; y_i > 0; --y_i) { memset(output_row_ptr, pad_value, _padding[0].first); output_row_ptr += _padding[0].first; @@ -183,12 +194,17 @@ NEPadLayerKernel::NEPadLayerKernel() { } -void NEPadLayerKernel::configure(ITensor *input, ITensor *output, const PaddingList &padding, const PixelValue constant_value, const PaddingMode mode) +void NEPadLayerKernel::configure(ITensor *input, + ITensor *output, + const PaddingList &padding, + const PixelValue constant_value, + const PaddingMode mode) { ARM_COMPUTE_ERROR_ON_NULLPTR(input, output); // Auto-init - const TensorShape expected_output_shape = arm_compute::misc::shape_calculator::compute_padded_shape(input->info()->tensor_shape(), padding); - const TensorInfo expected_output_info = input->info()->clone()->set_tensor_shape(expected_output_shape); + const TensorShape expected_output_shape = + arm_compute::misc::shape_calculator::compute_padded_shape(input->info()->tensor_shape(), padding); + const TensorInfo expected_output_info = input->info()->clone()->set_tensor_shape(expected_output_shape); auto_init_if_empty(*output->info(), expected_output_info); // Perform validation step @@ -200,14 +216,14 @@ void NEPadLayerKernel::configure(ITensor *input, ITensor *output, const PaddingL _constant_value = constant_value; _mode = mode; - if(_mode == PaddingMode::CONSTANT) + if (_mode == PaddingMode::CONSTANT) { - switch(_input->info()->element_size()) + switch (_input->info()->element_size()) { case 1: - if(_input->info()->num_dimensions() == 3 && // Is 3D - padding.size() <= 3 && // Has 3D padding - !_input->info()->has_padding() && !_output->info()->has_padding()) // Input & Output have no padding + if (_input->info()->num_dimensions() == 3 && // Is 3D + padding.size() <= 3 && // Has 3D padding + !_input->info()->has_padding() && !_output->info()->has_padding()) // Input & Output have no padding { _func = &NEPadLayerKernel::run_pad_constant_uint8_3Dinput_3Dpad; } @@ -240,7 +256,11 @@ void NEPadLayerKernel::configure(ITensor *input, ITensor *output, const PaddingL ICPPKernel::configure(win); } -Status NEPadLayerKernel::validate(const ITensorInfo *input, const ITensorInfo *output, const PaddingList &padding, const PixelValue constant_value, const PaddingMode mode) +Status NEPadLayerKernel::validate(const ITensorInfo *input, + const ITensorInfo *output, + const PaddingList &padding, + const PixelValue constant_value, + const PaddingMode mode) { ARM_COMPUTE_UNUSED(constant_value); ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(input, output, padding, mode)); @@ -253,9 +273,18 @@ void NEPadLayerKernel::run(const Window &window, const ThreadInfo &info) ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); - if(_func != nullptr) + if (_func != nullptr) { (this->*_func)(window); } } + +size_t NEPadLayerKernel::get_mws(const CPUInfo &platform, size_t thread_count) const +{ + ARM_COMPUTE_UNUSED(thread_count); + ARM_COMPUTE_UNUSED(platform); + + return ICPPKernel::default_mws; +} + } // namespace arm_compute |