diff options
author | Pablo Tello <pablo.tello@arm.com> | 2019-03-27 09:28:32 +0000 |
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committer | Georgios Pinitas <georgios.pinitas@arm.com> | 2019-04-16 11:31:40 +0000 |
commit | 8f43d745b170aefca269a087fc045d8af3813c33 (patch) | |
tree | 08df4a26c3fab575eb9bdf061be89d2a71fb3581 /src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp | |
parent | 9e4824c909b14dbaf7106e9527b0ffa22ef09bdc (diff) | |
download | ComputeLibrary-8f43d745b170aefca269a087fc045d8af3813c33.tar.gz |
COMPMID-2063: New Winograd implementation
Refactoring of winograd code reducing the size of the binaries
about 8X.
Change-Id: If8845bda324573e1a5cf436f354ac8603e88a92e
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/959
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Anthony Barbier <Anthony.barbier@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp')
-rw-r--r-- | src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp | 142 |
1 files changed, 90 insertions, 52 deletions
diff --git a/src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp b/src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp index 3e76a080fd..263ded0b84 100644 --- a/src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp +++ b/src/core/NEON/kernels/NEWinogradConvolutionLayerKernel.cpp @@ -1,5 +1,5 @@ /* - * Copyright (c) 2017-2018 ARM Limited. + * Copyright (c) 2017-2019 ARM Limited. * * SPDX-License-Identifier: MIT * @@ -238,8 +238,7 @@ unsigned int NEWinogradLayerTransformWeightsKernel<T, OutputTileRows, OutputTile template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> NEWinogradLayerTransformWeightsKernel<T, OutputTileRows, OutputTileCols, KernelRows, KernelCols>::NEWinogradLayerTransformWeightsKernel() - : _weights_hwio(nullptr), _output(nullptr), _matrix_stride(0), _num_output_channels(0), _num_input_channels(0) - + : _transform(nullptr), _weights_hwio(nullptr), _output(nullptr), _matrix_stride(0), _num_output_channels(0), _num_input_channels(0) { } @@ -263,11 +262,10 @@ void NEWinogradLayerTransformWeightsKernel<T, OutputTileRows, OutputTileCols, Ke _matrix_stride = matrix_stride; _num_output_channels = num_output_channels; _num_input_channels = num_input_channels; + _transform = arm_compute::support::cpp14::make_unique<WeightsTransform>(num_output_channels, num_input_channels); - const int matrix_row_stride = roundup(num_output_channels, WinogradConv::N_BLOCK); - WeightsTransform transform(nullptr, nullptr, matrix_stride, matrix_row_stride, num_output_channels, num_input_channels); - Window win; - auto win_last = transform.get_window(); + Window win; + auto win_last = _transform->get_window(); win.set(Window::DimX, Window::Dimension(0, win_last, 1)); INEKernel::configure(win); } @@ -278,12 +276,14 @@ void NEWinogradLayerTransformWeightsKernel<T, OutputTileRows, OutputTileCols, Ke { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + const size_t fst = window.x().start(); + const size_t lst = window.x().end(); + _transform->set_weight_tensor(_weights_hwio->buffer()); + const int matrix_row_stride = roundup(_num_output_channels, WinogradConv::N_BLOCK); + _transform->set_output_matrices(_output->buffer(), _matrix_stride, matrix_row_stride); + _transform->set_working_space(_output->buffer()); - const int matrix_row_stride = roundup(_num_output_channels, WinogradConv::N_BLOCK); - WeightsTransform transform(reinterpret_cast<T *>(_weights_hwio->buffer()), reinterpret_cast<T *>(_output->buffer()), _matrix_stride, matrix_row_stride, _num_output_channels, _num_input_channels); - const size_t fst = window.x().start(); - const size_t lst = window.x().end(); - transform.run(fst, lst); + _transform->run(fst, lst); } template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> @@ -331,6 +331,12 @@ unsigned int NEWinogradLayerTransformInputKernel<T, OutputTileRows, OutputTileCo } template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> +unsigned int NEWinogradLayerTransformInputKernel<T, OutputTileRows, OutputTileCols, KernelRows, KernelCols>::get_working_space_size(unsigned int num_threads) const +{ + return _transform->get_working_space_size(num_threads) / sizeof(T); +} + +template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> int NEWinogradLayerTransformInputKernel<T, OutputTileRows, OutputTileCols, KernelRows, KernelCols>::get_matrix_stride( const KernelShape &kernel_shape, const Tensor4DShape &input_shape, const PaddingType padding_type) const { @@ -339,7 +345,8 @@ int NEWinogradLayerTransformInputKernel<T, OutputTileRows, OutputTileCols, Kerne template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> NEWinogradLayerTransformInputKernel<T, OutputTileRows, OutputTileCols, KernelRows, KernelCols>::NEWinogradLayerTransformInputKernel() - : _input_nhwc(), _num_batches(0), _num_rows(0), _num_cols(0), _num_channels(0), _padding(), _output(nullptr), _matrix_stride(0) + : _transform(nullptr), _input_nhwc(nullptr), _num_batches(0), _num_rows(0), _num_cols(0), _num_channels(0), _padding(), _output(nullptr), _matrix_stride(0), _padding_top(), _padding_left(), + _padding_right(), _padding_bottom(), _workspace(nullptr) { } @@ -352,7 +359,8 @@ void NEWinogradLayerTransformInputKernel<T, OutputTileRows, OutputTileCols, Kern const int num_channels, /* Number of channels in input tensor. */ const PaddingType padding, /* Padding type. */ ITensor *output, /* Base of output matrices. */ - const int matrix_stride) /* Stride between output matrices. */ + const int matrix_stride, /* Stride between output matrices. */ + ITensor *workspace) { _input_nhwc = input_nhwc; _num_batches = num_batches; @@ -362,9 +370,28 @@ void NEWinogradLayerTransformInputKernel<T, OutputTileRows, OutputTileCols, Kern _padding = padding; _output = output; _matrix_stride = matrix_stride; - InputTransform transform(nullptr, num_batches, num_rows, num_cols, num_channels, padding, nullptr, matrix_stride, num_channels); - Window win; - auto win_last = transform.get_window(); + _workspace = workspace; + + _padding_top = (padding == PADDING_SAME) ? (KernelRows - 1) / 2 : 0; + _padding_left = (padding == PADDING_SAME) ? (KernelCols - 1) / 2 : 0; + _padding_bottom = (padding == PADDING_SAME) ? iceildiv(KernelRows - 1, 2) : 0; + _padding_right = (padding == PADDING_SAME) ? iceildiv(KernelCols - 1, 2) : 0; + + _transform = arm_compute::support::cpp14::make_unique<InputTransform>( + KernelRows, + KernelCols, + num_batches, + num_rows, + num_cols, + num_channels, + _padding_top, /**< Padding to apply to the top of the image. */ + _padding_left, /**< Padding to apply to the left of the image. */ + _padding_bottom, /**< Padding to apply to the bottom of the image. */ + _padding_right /**< Padding to apply to the right of the image. */ + ); + + Window win; + auto win_last = _transform->get_window(); win.set(Window::DimX, Window::Dimension(0, win_last, 1)); INEKernel::configure(win); } @@ -374,22 +401,25 @@ void NEWinogradLayerTransformInputKernel<T, OutputTileRows, OutputTileCols, Kern { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); + ARM_COMPUTE_ERROR_ON_NULLPTR(_workspace); - const int element_size_in_bytes = _input_nhwc->info()->element_size(); - const int input_col_stride = _input_nhwc->info()->strides_in_bytes().y() / element_size_in_bytes; - const int input_row_stride = _input_nhwc->info()->strides_in_bytes().z() / element_size_in_bytes; - const int input_batch_stride = _input_nhwc->info()->strides_in_bytes()[3] / element_size_in_bytes; - const auto input_nhwc_ptr = reinterpret_cast<const T *>(_input_nhwc->buffer() + _input_nhwc->info()->offset_first_element_in_bytes()); - auto output_ptr = reinterpret_cast<T *>(_output->buffer() + _output->info()->offset_first_element_in_bytes()); - InputTransform input_transform(input_nhwc_ptr, - _num_batches, _num_rows, _num_cols, _num_channels, _padding, - output_ptr, - _matrix_stride, _num_channels, input_batch_stride, input_row_stride, input_col_stride); + const int element_size_in_bytes = _input_nhwc->info()->element_size(); + const int input_col_stride = _input_nhwc->info()->strides_in_bytes().y() / element_size_in_bytes; + const int input_row_stride = _input_nhwc->info()->strides_in_bytes().z() / element_size_in_bytes; + const int input_batch_stride = _input_nhwc->info()->strides_in_bytes()[3] / element_size_in_bytes; + const auto input_nhwc_ptr = reinterpret_cast<const T *>(_input_nhwc->buffer() + _input_nhwc->info()->offset_first_element_in_bytes()); + auto output_ptr = reinterpret_cast<T *>(_output->buffer() + _output->info()->offset_first_element_in_bytes()); + ARM_COMPUTE_ERROR_ON_NULLPTR(output_ptr); + + _transform->set_input_tensor(input_nhwc_ptr, input_batch_stride, input_row_stride, input_col_stride); + _transform->set_output_matrices(output_ptr, _matrix_stride, _num_channels); + + _transform->set_working_space(_workspace->buffer()); // The code below cannot be moved to configure because biases hasn't been allocated at that point const size_t fst = window.x().start(); const size_t lst = window.x().end(); - input_transform.run(fst, lst); + _transform->run(fst, lst, info.thread_id); } template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> @@ -435,11 +465,18 @@ unsigned int NEWinogradLayerTransformOutputKernel<T, OutputTileRows, OutputTileC template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> NEWinogradLayerTransformOutputKernel<T, OutputTileRows, OutputTileCols, KernelRows, KernelCols>::NEWinogradLayerTransformOutputKernel() - : _biases(nullptr), _output_workspace(nullptr), _matrix_stride(0), _matrix_row_stride(0), _output_nhwc(nullptr), _num_batches(0), _num_rows(0), _num_cols(0), _num_channels(0) + : _transform(nullptr), _biases(nullptr), _transformed_output(nullptr), _workspace(nullptr), _matrix_stride(0), _matrix_row_stride(0), _output_nhwc(nullptr), _num_batches(0), _num_rows(0), + _num_cols(0), _num_channels(0) { } template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> +unsigned int NEWinogradLayerTransformOutputKernel<T, OutputTileRows, OutputTileCols, KernelRows, KernelCols>::get_working_space_size(unsigned int num_threads) const +{ + return _transform->get_working_space_size(num_threads) / sizeof(T); +} + +template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> int NEWinogradLayerTransformOutputKernel<T, OutputTileRows, OutputTileCols, KernelRows, KernelCols>::get_matrix_stride( const KernelShape &kernel_shape, const Tensor4DShape &input_shape, const PaddingType padding_type) const { @@ -455,28 +492,29 @@ Tensor4DShape NEWinogradLayerTransformOutputKernel<T, OutputTileRows, OutputTile template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> void NEWinogradLayerTransformOutputKernel<T, OutputTileRows, OutputTileCols, KernelRows, KernelCols>::configure( const ITensor *biases, - const ITensor *output_workingspace, + const ITensor *transformed_output, const int matrix_stride, ITensor *output_nhwc, const int num_batches, const int num_rows, const int num_cols, - const int num_channels) -{ - _biases = biases; - _output_workspace = output_workingspace; - _matrix_stride = matrix_stride; - _matrix_row_stride = roundup(num_channels, WinogradConv::N_BLOCK); - _output_nhwc = output_nhwc; - _num_batches = num_batches; - _num_rows = num_rows; - _num_cols = num_cols; - _num_channels = num_channels; + const int num_channels, + ITensor *workspace) +{ + _biases = biases; + _workspace = workspace; + _transformed_output = transformed_output; + _matrix_stride = matrix_stride; + _matrix_row_stride = roundup(num_channels, WinogradConv::N_BLOCK); + _output_nhwc = output_nhwc; + _num_batches = num_batches; + _num_rows = num_rows; + _num_cols = num_cols; + _num_channels = num_channels; // We don't have the biases buffer at this stage as it hasn't been allocated, we pass in nullptr OutputTransform is only used here to compute the window - OutputTransform output_transform(nullptr, _matrix_stride, _matrix_row_stride, nullptr, nullptr, _num_batches, _num_rows, _num_cols, _num_channels); - + _transform = arm_compute::support::cpp14::make_unique<OutputTransform>(num_batches, num_rows, num_cols, num_channels); Window win; - auto win_last = output_transform.get_window(); + auto win_last = _transform->get_window(); win.set(Window::DimX, Window::Dimension(0, win_last, 1)); _output_nhwc->info()->set_valid_region(ValidRegion(Coordinates(), _output_nhwc->info()->tensor_shape())); @@ -488,22 +526,22 @@ void NEWinogradLayerTransformOutputKernel<T, OutputTileRows, OutputTileCols, Ker { ARM_COMPUTE_UNUSED(info); ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this); - ARM_COMPUTE_ERROR_ON_NULLPTR(_output_workspace); + ARM_COMPUTE_ERROR_ON_NULLPTR(_workspace); + ARM_COMPUTE_ERROR_ON_NULLPTR(_transformed_output); ARM_COMPUTE_ERROR_ON_NULLPTR(_output_nhwc); - const int out_batch_stride = 0; + const int out_batch_stride = _output_nhwc->info()->strides_in_bytes()[3] / sizeof(T); const int out_row_stride = _output_nhwc->info()->strides_in_bytes()[2] / sizeof(T); const int out_col_stride = _output_nhwc->info()->strides_in_bytes()[1] / sizeof(T); - OutputTransform output_transform(reinterpret_cast<T *>(_output_workspace->buffer()), _matrix_stride, _matrix_row_stride, - (_biases ? reinterpret_cast<T *>(_biases->buffer() + _biases->info()->offset_first_element_in_bytes()) : nullptr), - reinterpret_cast<T *>(_output_nhwc->buffer() + _output_nhwc->info()->offset_first_element_in_bytes()), - _num_batches, _num_rows, _num_cols, _num_channels, out_batch_stride, out_row_stride, out_col_stride); - + _transform->set_input_matrices(_transformed_output->buffer(), _matrix_stride, _matrix_row_stride); + _transform->set_bias((_biases ? reinterpret_cast<T *>(_biases->buffer() + _biases->info()->offset_first_element_in_bytes()) : nullptr)); + _transform->set_output_tensor(_output_nhwc->buffer() + _output_nhwc->info()->offset_first_element_in_bytes(), out_batch_stride, out_row_stride, out_col_stride); + _transform->set_working_space(_workspace->buffer()); // The code below cannot be moved to configure because biases hasn't been allocated at that point const size_t fst = window.x().start(); const size_t lst = window.x().end(); - output_transform.run(fst, lst); + _transform->run(fst, lst, info.thread_id); } template <typename T, int OutputTileRows, int OutputTileCols, int KernelRows, int KernelCols> |