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/*
* Copyright (c) 2017-2019 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 <cstring>
#include "utils.hpp"
#include "winograd.hpp"
using namespace winograd;
using array2 = std::pair<unsigned int, unsigned int>;
#define MEMBERFN(RTYPE) \
template <int output_tile_rows, int output_tile_cols, int kernel_rows, \
int kernel_cols, WinogradRoots roots> \
template <typename TOut, typename TIn, typename TGEMMIn, typename TGEMMOut> \
RTYPE WinogradGEMM<output_tile_rows, output_tile_cols, kernel_rows, \
kernel_cols, \
roots>::Convolution<TOut, TIn, TGEMMIn, TGEMMOut>
/** Get the output shape of a convolution. */
MEMBERFN(array2)
::get_output_shape(const std::pair<unsigned int, unsigned int> input_shape,
const bool padding_same) {
const unsigned int n_rows =
padding_same ? input_shape.first : input_shape.first - (kernel_rows - 1);
const unsigned int n_cols = padding_same
? input_shape.second
: input_shape.second - (kernel_cols - 1);
return {n_rows, n_cols};
}
/** Get the memory required to store the kernel transformed into the
* Winograd domain.
*/
MEMBERFN(size_t)
::get_kernel_storage_size(const unsigned int n_input_channels,
const unsigned int n_output_channels) {
return N_GEMMS * get_kernel_matrix_size(n_input_channels, n_output_channels);
}
MEMBERFN(size_t)
::get_input_storage_size(const unsigned int n_batches,
const unsigned int n_rows, const unsigned int n_cols,
const unsigned int n_channels,
const bool same_padding) {
return N_GEMMS * get_input_matrix_size(n_batches, n_rows, n_cols, n_channels,
same_padding);
}
MEMBERFN(size_t)
::get_output_storage_size(const unsigned int n_batches,
const unsigned int n_rows, const unsigned int n_cols,
const unsigned int n_channels) {
return N_GEMMS *
get_output_matrix_size(n_batches, n_rows, n_cols, n_channels);
}
/** Get the memory required to apply a Winograd operator to some input.
*/
MEMBERFN(size_t)
::get_working_space_size(const unsigned int n_batches,
const unsigned int n_rows, const unsigned int n_cols,
const unsigned int n_input_channels,
const unsigned int n_output_channels,
const bool padding_same) {
const auto output_shape = get_output_shape({n_rows, n_cols}, padding_same);
// Get the memory required to store the matrices
const size_t matrix_sizes =
N_GEMMS *
(get_input_matrix_size(n_batches, n_rows, n_cols, n_input_channels,
padding_same) +
get_output_matrix_size(n_batches, output_shape.first,
output_shape.second, n_output_channels));
return matrix_sizes;
}
/* Get the memory required by a single "input" matrix.
*/
MEMBERFN(size_t)
::get_input_matrix_size(const unsigned int n_batches, const unsigned int n_rows,
const unsigned int n_cols,
const unsigned int n_channels,
const bool same_padding) {
return get_input_matrix_stride(n_batches, n_rows, n_cols, n_channels,
same_padding) *
sizeof(TGEMMIn);
}
MEMBERFN(int)
::get_input_matrix_stride(const unsigned int n_batches, const unsigned int n_rows,
const unsigned int n_cols,
const unsigned int n_channels,
const bool same_padding) {
const auto output_shape = get_output_shape({n_rows, n_cols}, same_padding);
const unsigned int tile_rows = iceildiv(output_shape.first, output_tile_rows);
const unsigned int tile_cols =
iceildiv(output_shape.second, output_tile_cols);
const unsigned int M =
roundup<unsigned int>(n_batches * tile_rows * tile_cols, M_BLOCK);
const unsigned int K = n_channels;
return M * K;
}
/* Get the memory required by a single "output" matrix.
*/
MEMBERFN(size_t)
::get_output_matrix_size(const unsigned int n_batches,
const unsigned int n_rows, const unsigned int n_cols,
const unsigned int n_channels) {
return get_output_matrix_stride(n_batches, n_rows, n_cols, n_channels) *
sizeof(TGEMMOut);
}
MEMBERFN(int)
::get_output_matrix_stride(const unsigned int n_batches,
const unsigned int n_rows, const unsigned int n_cols,
const unsigned int n_channels) {
// Compute shape for the GEMM
const int tile_rows = iceildiv(n_rows, output_tile_rows);
const int tile_cols = iceildiv(n_cols, output_tile_cols);
const int M = roundup<int>(tile_rows * tile_cols, M_BLOCK);
const int N = roundup<int>(n_channels, N_BLOCK);
return n_batches * M * N;
}
/* Get the memory required by a single "kernel" matrix.
*/
MEMBERFN(size_t)
::get_kernel_matrix_size(const unsigned int n_input_channels,
const unsigned int n_output_channels) {
return sizeof(TGEMMIn) *
get_kernel_matrix_stride(n_input_channels, n_output_channels);
}
MEMBERFN(int)
::get_kernel_matrix_stride(const unsigned int n_input_channels,
const unsigned int n_output_channels) {
return n_input_channels * roundup<int>(n_output_channels, N_BLOCK);
}
// Instantiate required implementations
template class WinogradGEMM<2, 2, 3, 3, WinogradRoots::Integers>::Convolution<float, float, float, float>;
template class WinogradGEMM<4, 4, 3, 3, WinogradRoots::Integers>::Convolution<float, float, float, float>;
template class WinogradGEMM<1, 6, 1, 3, WinogradRoots::Integers>::Convolution<float, float, float, float>;
template class WinogradGEMM<6, 1, 3, 1, WinogradRoots::Integers>::Convolution<float, float, float, float>;
template class WinogradGEMM<2, 2, 5, 5, WinogradRoots::Integers>::Convolution<float, float, float, float>;
template class WinogradGEMM<1, 4, 1, 5, WinogradRoots::Integers>::Convolution<float, float, float, float>;
template class WinogradGEMM<4, 1, 5, 1, WinogradRoots::Integers>::Convolution<float, float, float, float>;
template class WinogradGEMM<1, 2, 1, 7, WinogradRoots::Integers>::Convolution<float, float, float, float>;
template class WinogradGEMM<2, 1, 7, 1, WinogradRoots::Integers>::Convolution<float, float, float, float>;
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