From 9032ee32da54804806a3f26cbbf5a62b3c764f72 Mon Sep 17 00:00:00 2001 From: Manuel Bottini Date: Wed, 7 Aug 2019 17:04:11 +0100 Subject: MLCE-129: NEPad 30x slower than TensorFlow's implementation Change-Id: I44770e6a3134c70c4bd58f890d06cb43c9bd8bff Signed-off-by: Manuel Bottini Reviewed-on: https://review.mlplatform.org/c/1853 Reviewed-by: Giorgio Arena Comments-Addressed: Arm Jenkins Tested-by: Arm Jenkins --- src/core/NEON/kernels/NEPadLayerKernel.cpp | 259 +++++++++++++++++++++++++++++ 1 file changed, 259 insertions(+) create mode 100644 src/core/NEON/kernels/NEPadLayerKernel.cpp (limited to 'src/core/NEON/kernels') diff --git a/src/core/NEON/kernels/NEPadLayerKernel.cpp b/src/core/NEON/kernels/NEPadLayerKernel.cpp new file mode 100644 index 0000000000..88a1c2ec83 --- /dev/null +++ b/src/core/NEON/kernels/NEPadLayerKernel.cpp @@ -0,0 +1,259 @@ +/* + * 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/NEPadLayerKernel.h" + +#include "arm_compute/core/Error.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/TensorInfo.h" +#include "arm_compute/core/Types.h" +#include "arm_compute/core/Validate.h" +#include "arm_compute/core/utils/misc/ShapeCalculator.h" + +namespace arm_compute +{ +namespace +{ +Status validate_arguments(const ITensorInfo *input, const ITensorInfo *output, const PaddingList &paddings, const PaddingMode mode) +{ + 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) + { + 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); + } + return Status{}; +} +} // namespace + +template +void NEPadLayerKernel::run_pad_constant(const 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) + { + idin[dim] -= _padding[dim].first; + if(idin[dim] < 0 || static_cast(_input->info()->dimension(dim)) - 1 < idin[dim]) + { + std::fill_n(reinterpret_cast(output_it.ptr()), _output->info()->dimension(0), _constant_value.get()); + return; + } + } + T *input_it_ptr = reinterpret_cast(_input->ptr_to_element(idin)); + T *output_it_ptr = reinterpret_cast(output_it.ptr()); + std::fill_n(output_it_ptr, _padding[0].first, _constant_value.get()); + 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()); + }, + output_it); +} + +void NEPadLayerKernel::run_pad_constant_uint8_3Dinput_3Dpad(const Window &window) +{ + ARM_COMPUTE_UNUSED(window); + + const size_t start_plane = window.z().start(); + const size_t end_plane = window.z().end(); + + const size_t start_plane_input = start_plane - (_padding.size() > 2 && start_plane >= _padding[2].first ? _padding[2].first : 0); + + const int output_plane_size = _output->info()->dimension(0) * _output->info()->dimension(1); + const int input_plane_size = (_input->info()->dimension(0) + _input->info()->padding().right + _input->info()->padding().left) * (_input->info()->dimension( + 1) + + _input->info()->padding().top + _input->info()->padding().bottom); + + const int pad_y_elems_top = (_padding.size() > 1 ? _padding[1].first : 0) * _output->info()->dimension(0); + const int pad_y_elems_bot = (_padding.size() > 1 ? _padding[1].second : 0) * _output->info()->dimension(0); + + const size_t jump_to_next_row_input = _input->info()->dimension(0) + _input->info()->padding().right + _input->info()->padding().left; + const size_t jump_to_next_row_output = _padding[0].first + _padding[0].second; + const size_t jump_to_next_plane_input = _input->info()->padding().empty() ? 0 : _input->info()->dimension(0) * (_input->info()->padding().right + _input->info()->padding().top); + + uint8_t *output_row_ptr = _output->buffer() + 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(); + + for(size_t z_i = start_plane; z_i < end_plane; ++z_i) + { + 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) + { + memset(output_row_ptr, pad_value, output_plane_size); + output_row_ptr += output_plane_size; + } + else + { + memset(output_row_ptr, pad_value, pad_y_elems_top); + 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) + { + memset(output_row_ptr, pad_value, _padding[0].first); + output_row_ptr += _padding[0].first; + + memcpy(output_row_ptr, input_it_ptr, _input->info()->dimension(0)); + output_row_ptr += _input->info()->dimension(0); + input_it_ptr += jump_to_next_row_input; + + memset(output_row_ptr, pad_value, _padding[0].second + _padding[0].first); + output_row_ptr += jump_to_next_row_output; + + memcpy(output_row_ptr, input_it_ptr, _input->info()->dimension(0)); + output_row_ptr += _input->info()->dimension(0); + input_it_ptr += jump_to_next_row_input; + + memset(output_row_ptr, pad_value, _padding[0].second + _padding[0].first); + output_row_ptr += jump_to_next_row_output; + + memcpy(output_row_ptr, input_it_ptr, _input->info()->dimension(0)); + output_row_ptr += _input->info()->dimension(0); + input_it_ptr += jump_to_next_row_input; + + memset(output_row_ptr, pad_value, _padding[0].second + _padding[0].first); + output_row_ptr += jump_to_next_row_output; + + memcpy(output_row_ptr, input_it_ptr, _input->info()->dimension(0)); + output_row_ptr += _input->info()->dimension(0); + input_it_ptr += jump_to_next_row_input; + + memset(output_row_ptr, pad_value, _padding[0].second); + output_row_ptr += _padding[0].second; + } + for(; y_i > 0; --y_i) + { + memset(output_row_ptr, pad_value, _padding[0].first); + output_row_ptr += _padding[0].first; + + memcpy(output_row_ptr, input_it_ptr, _input->info()->dimension(0)); + output_row_ptr += _input->info()->dimension(0); + input_it_ptr += _input->info()->dimension(0); + + memset(output_row_ptr, pad_value, _padding[0].second); + output_row_ptr += _padding[0].second; + } + input_it_ptr += jump_to_next_plane_input; + memset(output_row_ptr, pad_value, pad_y_elems_bot); + output_row_ptr += pad_y_elems_bot; + } + } +} + +NEPadLayerKernel::NEPadLayerKernel() + : _func(), _input(nullptr), _output(nullptr), _padding(), _constant_value(), _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); + auto_init_if_empty(*output->info(), expected_output_info); + + // Perform validation step + ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(input->info(), output->info(), padding, mode)); + + _input = input; + _output = output; + _padding = padding; + _constant_value = constant_value; + _mode = mode; + + if(_mode == PaddingMode::CONSTANT) + { + switch(_input->info()->element_size()) + { + case 1: + if(_input->info()->num_dimensions() == 3 && padding.size() <= 3) + { + _func = &NEPadLayerKernel::run_pad_constant_uint8_3Dinput_3Dpad; + } + else + { + _func = &NEPadLayerKernel::run_pad_constant; + } + break; + case 2: + _func = &NEPadLayerKernel::run_pad_constant; + break; + case 4: + _func = &NEPadLayerKernel::run_pad_constant; + break; + default: + ARM_COMPUTE_ERROR("Element size not supported"); + break; + } + } + else + { + ARM_COMPUTE_ERROR("Padding mode not supported"); + } + + // Configure kernel window + Window win = calculate_max_window(*output->info(), Steps()); + + // The NEPad doesn't need padding so update_window_and_padding() can be skipped + Coordinates coord; + coord.set_num_dimensions(output->info()->num_dimensions()); + output->info()->set_valid_region(ValidRegion(coord, output->info()->tensor_shape())); + + ICPPKernel::configure(win); +} + +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)); + return Status{}; +} + +void NEPadLayerKernel::run(const Window &window, const ThreadInfo &info) +{ + ARM_COMPUTE_UNUSED(info); + ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(INEKernel::window(), window); + + if(_func != nullptr) + { + (this->*_func)(window); + } +} +} // namespace arm_compute -- cgit v1.2.1