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Diffstat (limited to 'src/core/NEON/kernels/convolution/depthwise/impl_dilated.hpp')
| -rw-r--r-- | src/core/NEON/kernels/convolution/depthwise/impl_dilated.hpp | 295 |
1 files changed, 0 insertions, 295 deletions
diff --git a/src/core/NEON/kernels/convolution/depthwise/impl_dilated.hpp b/src/core/NEON/kernels/convolution/depthwise/impl_dilated.hpp deleted file mode 100644 index 4130188187..0000000000 --- a/src/core/NEON/kernels/convolution/depthwise/impl_dilated.hpp +++ /dev/null @@ -1,295 +0,0 @@ -/* - * 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 "depthwise_dilated.hpp" -#include "utils.hpp" - -#define MEMBERFN(TOUT) \ - template <unsigned int OutputTileRows, unsigned int OutputTileColumns, \ - unsigned int KernelRows, unsigned int KernelColumns, \ - unsigned int StrideRows, unsigned int StrideColumns, typename TIn, \ - typename TBias, typename TOut> \ - TOUT DilatedDepthwiseConvolution<OutputTileRows, OutputTileColumns, \ - KernelRows, KernelColumns, StrideRows, \ - StrideColumns, TIn, TBias, TOut> - -namespace depthwise { - -MEMBERFN() -::DilatedDepthwiseConvolution(const int n_batches, const int n_input_rows, - const int n_input_cols, const int n_channels, - const int dilation_factor, - nck::ActivationFunction activation, - const unsigned int padding_top, - const unsigned int padding_left, - const unsigned int padding_bottom, - const unsigned int padding_right) - : DilatedDepthwiseConvolution( - n_batches, n_input_rows, n_input_cols, n_channels, dilation_factor, - DilatedDepthwiseConvolution::get_output_size( - n_input_rows, padding_top, padding_bottom, dilation_factor), - DilatedDepthwiseConvolution::get_output_size( - n_input_cols, padding_left, padding_right, dilation_factor), - activation, padding_top, padding_left, padding_bottom, - padding_right) {} - -MEMBERFN() -::DilatedDepthwiseConvolution(const int n_batches, const int n_input_rows, - const int n_input_cols, const int n_channels, - const int dilation_factor, - const int n_output_rows, const int n_output_cols, - nck::ActivationFunction activation, - const unsigned int padding_top, - const unsigned int padding_left, - const unsigned int, // padding_bottom - const unsigned int // padding_right - ) - : DilatedDepthwiseConvolution( - n_batches, n_input_rows, n_input_cols, n_channels, dilation_factor, - n_output_rows, n_output_cols, activation, padding_top, padding_left, - 0, 0, - // Function which creates a new (standard) depthwise convolution - [](const int n_batches, const int n_input_rows, - const int n_input_cols, const int n_channels, - const int n_output_rows, const int n_output_cols, - const nck::ActivationFunction activation, - const unsigned int padding_top, const unsigned int padding_left, - const unsigned int padding_bottom, - const unsigned int padding_right) -> IDepthwiseConvolution * { - return new DepthwiseConvolution< - OutputTileRows, OutputTileColumns, KernelRows, KernelColumns, - StrideRows, StrideColumns, TIn, TBias, TOut>( - n_batches, n_input_rows, n_input_cols, n_channels, - n_output_rows, n_output_cols, activation, padding_top, - padding_left, padding_bottom, padding_right); - }) {} - -MEMBERFN() -::DilatedDepthwiseConvolution( - const int n_batches, const int n_input_rows, const int n_input_cols, - const int n_channels, const int dilation_factor, const int n_output_rows, - const int n_output_cols, nck::ActivationFunction activation, - const unsigned int padding_top, const unsigned int padding_left, - const unsigned int, // padding_bottom - const unsigned int, // padding_right - std::function<IDepthwiseConvolution *( - int, int, int, int, int, int, nck::ActivationFunction, unsigned int, - unsigned int, unsigned int, unsigned int)> - subconvfn // Function to create a new convolution - ) - : _dilation_factor(dilation_factor), _n_input_rows(n_input_rows), - _n_input_cols(n_input_cols), _n_channels(n_channels), - _padding_top(static_cast<int>(padding_top)), - _padding_left(static_cast<int>(padding_left)), - _n_output_rows(n_output_rows), _n_output_cols(n_output_cols), - _convs(_dilation_factor) { - // Instantiate the base convolutions - for (uint32_t i = 0; i < static_cast<uint32_t>(_dilation_factor); i++) { - // Compute properties of this row of base convolutions - const int row_top = - i * StrideRows - _padding_top; // -ve values are in the padding - const int row_pad_top = - row_top < 0 ? iceildiv(-row_top, dilation_factor) : 0; - - const int _n_input_rows = iceildiv(n_input_rows - i, dilation_factor); - const int _n_output_rows = iceildiv(n_output_rows - i, dilation_factor); - - for (uint32_t j = 0; j < static_cast<uint32_t>(_dilation_factor); j++) { - // Compute properties of the base convolution - const int col_left = - j * StrideColumns - padding_left; // -ve values are in the padding - const int col_pad_left = - col_left < 0 ? iceildiv(-col_left, dilation_factor) : 0; - - const int _n_input_cols = iceildiv(n_input_cols - j, dilation_factor); - const int _n_output_cols = iceildiv(n_output_cols - j, dilation_factor); - - // Create new depthwise convolution engine and include it in the vector - // of engines. The new depthwise convolution engine is created by calling - // the delegate function we received as an argument. - _convs[i].emplace_back(subconvfn( - n_batches, _n_input_rows, _n_input_cols, n_channels, _n_output_rows, - _n_output_cols, activation, - // Note: since we have computed the output tensor size we don't need - // to explicitly provide bottom and right padding values to the - // depthwise convolution. - row_pad_top, col_pad_left, 0, 0)); - } - } -} - -MEMBERFN(void)::set_input(const void *const inptr) { - set_input(inptr, _n_channels); -} - -MEMBERFN(void)::set_input(const void *const inptr, const int ldcol) { - set_input(inptr, _n_input_cols * ldcol, ldcol); -} - -MEMBERFN(void) -::set_input(const void *const inptr, const int ldrow, const int ldcol) { - set_input(inptr, _n_input_rows * ldrow, ldrow, ldcol); -} - -MEMBERFN(void) -::set_input(const void *const inptr, const int ldbatch, const int ldrow, - const int ldcol) { - // Compute dilated strides - const int ldrow_dilated = ldrow * _dilation_factor; - const int ldcol_dilated = ldcol * _dilation_factor; - - // Pass input parameters on to base convolutions - for (uint32_t i = 0; i < static_cast<uint32_t>(_dilation_factor); i++) { - const int top_pos = - i * StrideRows - _padding_top + - ((static_cast<int>(i * StrideRows) < _padding_top) - ? iceildiv(_padding_top - i * StrideRows, _dilation_factor) * - _dilation_factor - : 0); - const TIn *const inptr_i = - static_cast<const TIn *>(inptr) + top_pos * ldrow; - - for (uint32_t j = 0; j < static_cast<uint32_t>(_dilation_factor); j++) { - int left_pos = j * StrideColumns - _padding_left; - while (left_pos < 0) - left_pos += _dilation_factor; - - // Modify the pointer to point to the first element of the dilated input - // tensor, then set the input for this convolution engine. - const void *const inptr_ij = inptr_i + left_pos * ldcol; - _convs[i][j]->set_input(inptr_ij, ldbatch, ldrow_dilated, ldcol_dilated); - } - } -} - -MEMBERFN(void)::set_output(void *const outptr) { - set_output(outptr, _n_channels); -} - -MEMBERFN(void)::set_output(void *const outptr, const int ldcol) { - set_output(outptr, _n_output_cols * ldcol, ldcol); -} - -MEMBERFN(void) -::set_output(void *const outptr, const int ldrow, const int ldcol) { - set_output(outptr, _n_output_rows * ldrow, ldrow, ldcol); -} - -MEMBERFN(void) -::set_output(void *const outptr, const int ldbatch, const int ldrow, - const int ldcol) { - // Compute dilated strides - const int ldrow_dilated = ldrow * _dilation_factor; - const int ldcol_dilated = ldcol * _dilation_factor; - - // Pass input parameters on to base convolutions - for (uint32_t i = 0; i < static_cast<uint32_t>(_dilation_factor); i++) { - for (uint32_t j = 0; j < static_cast<uint32_t>(_dilation_factor); j++) { - // Modify the pointer to point to the first element of the dilated input - // tensor, then set the input for this convolution engine. - void *const outptr_ij = - static_cast<TOut *>(outptr) + i * ldrow + j * ldcol; - _convs[i][j]->set_output(outptr_ij, ldbatch, ldrow_dilated, - ldcol_dilated); - } - } -} - -MEMBERFN(int) -::get_output_size(const int dim_size, const unsigned int padding_before, - const unsigned int padding_after, const int dilation_factor) { - const int input_size = - dim_size + static_cast<int>(padding_before + padding_after); - const int window_size = (KernelRows - 1) * dilation_factor + 1; - return iceildiv(input_size - window_size + 1, StrideRows); -} - -MEMBERFN(int) -::output_size(const int dim_size, const unsigned int padding_before, - const unsigned int padding_after) const { - return get_output_size(dim_size, padding_before, padding_after, - _dilation_factor); -} - -MEMBERFN(size_t)::get_packed_params_size(void) const { - return _convs[0][0]->get_packed_params_size(); -} - -MEMBERFN(void)::set_packed_params_buffer(void *buffer) { - // Set the buffer for all convolution engines - for (auto &&row : _convs) { - for (auto &&conv : row) { - conv->set_packed_params_buffer(buffer); - } - } -} - -MEMBERFN(void) -::pack_params(const void *const weights, const void *const biases) const { - _convs[0][0]->pack_params(weights, biases); -} - -MEMBERFN(void) -::pack_params(void *const buffer, const void *const weights, - const void *const biases) const { - _convs[0][0]->pack_params(buffer, weights, biases); -} - -MEMBERFN(void) -::pack_params(void *const buffer, const void *const weights, - const unsigned int ldrow, const unsigned int ldcol, - const void *const biases) const { - _convs[0][0]->pack_params(buffer, weights, ldrow, ldcol, biases); -} - -MEMBERFN(size_t)::get_working_space_size(unsigned int nthreads) const { - return _convs[0][0]->get_working_space_size(nthreads); -} - -MEMBERFN(void)::set_working_space(void *const ws) { - // Use the same working space set for all contained depthwise engines. - for (auto &&row : _convs) { - for (auto &&conv : row) { - conv->set_working_space(ws); - } - } -} - -MEMBERFN(unsigned int)::get_window(void) const { - return _convs[0][0]->get_window(); -} - -MEMBERFN(void) -::run(const unsigned int start, const unsigned int stop, - const unsigned int threadid) { - // Run each contained convolution in turn - for (auto &&row : _convs) { - for (auto &&conv : row) { - conv->run(start, stop, threadid); - } - } -} - -} // namespace depthwise |