diff options
Diffstat (limited to 'src/core/NEON/kernels/convolution/winograd/winograd_transforms')
22 files changed, 0 insertions, 5675 deletions
diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp deleted file mode 100644 index 8e4bebcd20..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input.hpp +++ /dev/null @@ -1,268 +0,0 @@ -/* - * 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. - */ - -#pragma once - -#include <algorithm> - -#include "padding.hpp" -#include "utils.hpp" -#include "winograd.hpp" - -#define MEMBERFN(RTYPE) template <\ - int InnerTileRows, int InnerTileCols,\ - typename TIn, typename TOut, WinogradRoots Roots\ -> RTYPE InputTransform<InnerTileRows, InnerTileCols, TIn, TOut, Roots> - - -#define Nx1MEMBERFN(RTYPE) template <\ - int InnerTileRows, typename TIn, typename TOut, WinogradRoots Roots\ -> RTYPE InputTransform<InnerTileRows, 1, TIn, TOut, Roots> - -namespace winograd -{ - -MEMBERFN()::InputTransform( - const int kernel_rows, - const int kernel_cols, - const int n_batches, - const int n_rows, - const int n_cols, - const int n_channels, - const int padding_top, - const int padding_left, - const int padding_bottom, - const int padding_right -) : _n_batches(n_batches), _n_rows(n_rows), _n_cols(n_cols), _n_channels(n_channels), - _inptr(nullptr), _outptr(nullptr), - _overlap_rows(kernel_rows - 1), _overlap_cols(kernel_cols - 1), - _padding_top(padding_top), _padding_left(padding_left), _padding_bottom(padding_bottom), _padding_right(padding_right), - _tiles_M(iceildiv(padding_top + n_rows + padding_bottom - kernel_rows + 1, InnerTileRows - kernel_rows + 1)), - _tiles_N(iceildiv(padding_left + n_cols + padding_right - kernel_cols + 1, InnerTileCols - kernel_cols + 1)), - _matrix_stride(0), _matrix_row_stride(0), _matrix_batch_stride(0), - _in_col_stride(0), _in_row_stride(0), _in_batch_stride(0), - _working_space_col_stride(n_channels), - _working_space_row_stride(InnerTileCols * _working_space_col_stride), - _working_space(nullptr) -{ -} - -MEMBERFN(void)::set_input_tensor(const void* const inptr) -{ - set_input_tensor(inptr, _n_channels); -} - -MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldcol) -{ - set_input_tensor(inptr, _n_cols * ldcol, ldcol); -} - -MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldrow, const int ldcol) -{ - set_input_tensor(inptr, _n_rows * ldrow, ldrow, ldcol); -} - -MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldbatch, const int ldrow, const int ldcol) -{ - _inptr = static_cast<const TIn *>(inptr); - _in_batch_stride = ldbatch; - _in_row_stride = ldrow; - _in_col_stride = ldcol; -} - -MEMBERFN(void)::set_output_matrices(void * const mptr, const int ldmatrix, const int ldrow) -{ - _outptr = static_cast<TOut *>(mptr); - _matrix_stride = ldmatrix; - _matrix_row_stride = ldrow; - _matrix_batch_stride = _tiles_M * _tiles_N * ldrow; -} - -Nx1MEMBERFN()::InputTransform( - const int kernel_rows, - const int kernel_cols, - const int n_batches, - const int n_rows, - const int n_cols, - const int n_channels, - const int padding_top, - const int padding_left, - const int padding_bottom, - const int padding_right -) : InputTransform<1, InnerTileRows, TIn, TOut, Roots>::InputTransform( - /* Transpose rows and columns */ - kernel_cols, kernel_rows, n_batches, n_cols, n_rows, n_channels, - padding_left, padding_top, padding_right, padding_bottom - ) -{ -} - -Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr) -{ - set_input_tensor(inptr, this->_n_channels); -} - -Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldcol) -{ - set_input_tensor(inptr, this->_n_cols * ldcol, ldcol); -} - -Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldrow, const int ldcol) -{ - set_input_tensor(inptr, this->_n_rows * ldrow, ldrow, ldcol); -} - -Nx1MEMBERFN(void)::set_input_tensor(const void* const inptr, const int ldbatch, const int ldrow, const int ldcol) -{ - // Transpose row and column strides - Base::set_input_tensor(inptr, ldbatch, ldcol, ldrow); -} - -MEMBERFN(size_t)::get_working_space_size(const unsigned int nthreads) const -{ - return sizeof(TIn) * InnerTileRows * _working_space_row_stride * nthreads; -} - -MEMBERFN(void)::set_working_space(void * const buffer) -{ - _working_space = static_cast<TIn *>(buffer); -} - -MEMBERFN(unsigned int)::get_window(void) const -{ - return iceildiv(_n_channels, WINDOW_BLOCK); -} - -MEMBERFN(void)::run( - const unsigned int start, - const unsigned int stop, - const unsigned int threadid -) -{ - // Determine the channels on which to work - if (start >= get_window()) - { - return; // No work to do beyond the end of the window - } - const unsigned int start_channel = start * WINDOW_BLOCK; - const unsigned int stop_channel = std::min<unsigned int>(_n_channels , stop * WINDOW_BLOCK); - const unsigned int n_channels = stop_channel - start_channel; - - // Loop over batches - for (int batch = 0; batch < _n_batches; batch++) - { - const TIn* const inptr_batch = _inptr + start_channel + batch*_in_batch_stride; - TOut* const outptr_batch = _outptr + start_channel + batch*_matrix_batch_stride; - - // Loop over rows of tiles - for (int tile_i = 0; tile_i < _tiles_M; tile_i++) - { - // Compute the starting and ending row of pixels within the row of tiles, - // hence compute the padding to apply to the top and bottom of each tile. - const int row_top = tile_i * (InnerTileRows - _overlap_rows) - _padding_top; - const int row_bottom = row_top + InnerTileRows; - const int row_pad_top = std::max(0, _padding_top - tile_i * (InnerTileRows - _overlap_rows)); - const int row_pad_bottom = std::max(0, row_bottom - _n_rows); - - // Get a pointer to the start of the row. - const int row_offset = std::min(0, row_pad_top - _padding_top); - const TIn* const inptr_row = inptr_batch + _in_row_stride*(row_offset + tile_i*(InnerTileRows - _overlap_rows)); - TOut* const outptr_row = outptr_batch + tile_i*_tiles_N*_matrix_row_stride; - - // Loop over tiles within the row - for (int tile_j = 0; tile_j < _tiles_N; tile_j++) - { - // Compute the starting and ending column of pixels within the tile, - // hence compute the padding to apply to the left and right of the - // tile. - const int tile_left = tile_j * (InnerTileCols - _overlap_cols) - _padding_left; - const int tile_right = tile_left + InnerTileCols; - const int tile_pad_left = std::max(0, _padding_left - tile_j * (InnerTileCols - _overlap_cols)); - const int tile_pad_right = std::max(0, tile_right - _n_cols); - - // Get a pointer to the start of the tile. - const int col_offset = std::min(0, tile_pad_left - _padding_left); - const TIn* const inptr_tile = inptr_row + _in_col_stride*(col_offset + tile_j*(InnerTileCols - _overlap_cols)); - TOut* const outptr_tile = outptr_row + tile_j * _matrix_row_stride; - - // Transform the tile, applying padding if necessary. - if (row_pad_top || tile_pad_left || row_pad_bottom || tile_pad_right) - { - transform_padded_tile( - threadid, n_channels, outptr_tile, inptr_tile, - row_pad_top, tile_pad_left, row_pad_bottom, tile_pad_right - ); - } - else - { - transform_unpadded_tile(threadid, n_channels, outptr_tile, inptr_tile); - } - } - } - } -} - -MEMBERFN(void)::transform_unpadded_tile( - const unsigned int /* threadid unused */, - const int n_channels, - TOut * const outptr, - const TIn * const inptr -) -{ - transform_tile( - n_channels, inptr, _in_row_stride, _in_col_stride, outptr, _matrix_stride - ); -} - -MEMBERFN(void)::transform_padded_tile( - const unsigned int threadid, - const int n_channels, - TOut * const outptr, - const TIn * const inptr, - const int padding_top, - const int padding_left, - const int padding_bottom, - const int padding_right -) -{ - padding::copy_and_pad_tile( - InnerTileRows, InnerTileCols, n_channels, - inptr, _in_row_stride, _in_col_stride, - static_cast<TIn *>(get_working_space(threadid)), _working_space_row_stride, _working_space_col_stride, - padding_top, padding_left, padding_bottom, padding_right - ); - - transform_tile( - n_channels, static_cast<const TIn *>(get_working_space(threadid)), - _working_space_row_stride, _working_space_col_stride, - outptr, _matrix_stride - ); -} - -MEMBERFN(void *)::get_working_space(const unsigned int threadid) const -{ - return _working_space + InnerTileRows * _working_space_row_stride * threadid; -} - -} // namespace winograd diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_1x8_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_1x8_fp32_fp32_integers.cpp deleted file mode 100644 index 5040ec1bd4..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_1x8_fp32_fp32_integers.cpp +++ /dev/null @@ -1,158 +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 "arm.hpp" -#include "input.hpp" - -namespace winograd -{ - -template <> -void InputTransform<1, 8, float, float, WinogradRoots::Integers>::transform_tile( - const int n_channels, - const float* const input_base, - const int, // We don't need to stride over rows - const int input_col_stride, - float* outptr, - const int matrix_stride -) -{ - constexpr int inner_tile_cols = 8; - - // Get pointers into the input tile - const float *x_ptrs[inner_tile_cols]; - for (int j = 0, xj = 0; j < inner_tile_cols; j++, xj++) - { - x_ptrs[j] = input_base + xj*input_col_stride; - } - - // Vectors used/computed in this kernel. - float x[inner_tile_cols]; - float U[inner_tile_cols]; - - for (int j = 0; j < inner_tile_cols; j++) - { - x[j] = 0.0f; - } - - // Perform the Winograd input transformation for each channel in the input - // tensor. - int channels_remaining = n_channels; -#ifdef _arm_any_ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - float32x4_t x[inner_tile_cols], U[inner_tile_cols]; - for (int j = 0; j < inner_tile_cols; j++) - { - x[j] = vdupq_n_f32(0.0f); - } - - // Load x - for (int j = 0; j < inner_tile_cols; j++) - { - x[j] = vld1q_f32(x_ptrs[j]); - x_ptrs[j] += 4; - } - - // Compute U = x . X - U[0] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[2], 49), x[4], -14), x[0], -36); - U[1] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[2], 36), x[3], 13), x[4], -13), x[1], -36), x[5], -1); - U[2] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[5], 1), x[2], 36), x[1], 36), x[4], -13), x[3], -13); - U[3] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[3], 20), x[2], 9), x[5], -2), x[4], -10), x[1], -18); - U[4] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[1], 18), x[2], 9), x[5], 2), x[4], -10), x[3], -20); - U[5] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[3], 15), x[2], 4), x[5], -3), x[4], -5), x[1], -12); - U[6] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[6], 1), x[1], 12), x[2], 4), x[5], 3), x[4], -5), x[3], -15); - U[7] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(x[7], 1), x[3], 49), x[5], -14), x[1], -36); - - // Store the transformed vector - for (int j = 0; j < inner_tile_cols; j++) - { - vst1q_f32(outptr + j*matrix_stride, U[j]); - } - outptr += 4; - } - for (; channels_remaining >= 2; channels_remaining -= 2) - { - float32x2_t x[inner_tile_cols], U[inner_tile_cols]; - for (int j = 0; j < inner_tile_cols; j++) - { - x[j] = vdup_n_f32(0.0f); - } - - // Load x - for (int j = 0; j < inner_tile_cols; j++) - { - x[j] = vld1_f32(x_ptrs[j]); - x_ptrs[j] += 2; - } - - // Compute U = x . X - U[0] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[2], 49), x[4], -14), x[0], -36); - U[1] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[2], 36), x[3], 13), x[4], -13), x[1], -36), x[5], -1); - U[2] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[5], 1), x[2], 36), x[1], 36), x[4], -13), x[3], -13); - U[3] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[3], 20), x[2], 9), x[5], -2), x[4], -10), x[1], -18); - U[4] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[1], 18), x[2], 9), x[5], 2), x[4], -10), x[3], -20); - U[5] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[3], 15), x[2], 4), x[5], -3), x[4], -5), x[1], -12); - U[6] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[6], 1), x[1], 12), x[2], 4), x[5], 3), x[4], -5), x[3], -15); - U[7] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(x[7], 1), x[3], 49), x[5], -14), x[1], -36); - - // Store the transformed vector - for (int j = 0; j < inner_tile_cols; j++) - { - vst1_f32(outptr + j*matrix_stride, U[j]); - } - outptr += 2; - } -#endif // _arm_any_ - for (; channels_remaining; channels_remaining--) - { - // Load x - for (int j = 0; j < inner_tile_cols; j++) - { - x[j] = *(x_ptrs[j]++); - } - - // Compute U = x . X - U[0] = x[0]*-36 + x[4]*-14 + x[2]*49 + x[6]*1; - U[1] = x[5]*-1 + x[1]*-36 + x[4]*-13 + x[3]*13 + x[2]*36 + x[6]*1; - U[2] = x[3]*-13 + x[4]*-13 + x[1]*36 + x[2]*36 + x[5]*1 + x[6]*1; - U[3] = x[1]*-18 + x[4]*-10 + x[5]*-2 + x[2]*9 + x[3]*20 + x[6]*1; - U[4] = x[3]*-20 + x[4]*-10 + x[5]*2 + x[2]*9 + x[1]*18 + x[6]*1; - U[5] = x[1]*-12 + x[4]*-5 + x[5]*-3 + x[2]*4 + x[3]*15 + x[6]*1; - U[6] = x[3]*-15 + x[4]*-5 + x[5]*3 + x[2]*4 + x[1]*12 + x[6]*1; - U[7] = x[1]*-36 + x[5]*-14 + x[3]*49 + x[7]*1; - - // Store the transformed vector - for (int j = 0; j < inner_tile_cols; j++) - { - *(outptr + j*matrix_stride) = U[j]; - } - outptr++; - } -} - -template class InputTransform<1, 8, float, float, WinogradRoots::Integers>; -template class InputTransform<8, 1, float, float, WinogradRoots::Integers>; - -} // namespace winograd diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_4x4_fp16_fp16_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_4x4_fp16_fp16_integers.cpp deleted file mode 100644 index 1ea68b5938..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_4x4_fp16_fp16_integers.cpp +++ /dev/null @@ -1,257 +0,0 @@ -/* - * Copyright (c) 2020 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. - */ -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC - -#include "input.hpp" -#include "arm.hpp" - -namespace winograd -{ - -template <> -void InputTransform<4, 4, __fp16, __fp16, WinogradRoots::Integers>::transform_tile( - const int n_channels, - const __fp16* const input_base, - const int input_row_stride, - const int input_col_stride, - __fp16* outptr, - const int matrix_stride -) -{ - constexpr int inner_tile_rows = 4, inner_tile_cols = 4; - - // Get pointers into the input tile - const __fp16 *x_ptrs[inner_tile_rows][inner_tile_cols]; - for (int i = 0, xi = 0; i < inner_tile_rows; i++, xi++) - { - // Get a pointer into the row - const __fp16* const row_ptr = input_base + xi*input_row_stride; - - for (int j = 0, xj = 0; j < inner_tile_cols; j++, xj++) - { - x_ptrs[i][j] = row_ptr + xj*input_col_stride; - } - } - - // Matrices used/computed in this kernel. - __fp16 x[inner_tile_rows][inner_tile_cols]; - __fp16 XTx[inner_tile_rows][inner_tile_cols]; - __fp16 U[inner_tile_rows][inner_tile_cols]; - - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = XTx[i][j] = 0.0f; - } - } - - // Perform the Winograd input transformation for each channel in the input - // tensor. - int channels_remaining = n_channels; -#ifdef __aarch64__ - for (; channels_remaining >= 8; channels_remaining -= 8) - { - // Matrices used/computed in this kernel. - float16x8_t x[inner_tile_rows][inner_tile_cols]; - float16x8_t XTx[inner_tile_rows][inner_tile_cols]; - float16x8_t U[inner_tile_rows][inner_tile_cols]; - - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vdupq_n_f16(0.0f); - XTx[i][j] = vdupq_n_f16(0.0f); - } - } - - // Load x - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vld1q_f16(x_ptrs[i][j]); - x_ptrs[i][j] += 8; - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - // XTx[0][j] = x[0][j] - x[2][j]; - XTx[0][j] = vsubq_f16(x[0][j], x[2][j]); - - // XTx[1][j] = x[1][j] + x[2][j]; - XTx[1][j] = vaddq_f16(x[1][j], x[2][j]); - - // XTx[2][j] = x[2][j] - x[1][j]; - XTx[2][j] = vsubq_f16(x[2][j], x[1][j]); - - // XTx[3][j] = x[1][j] - x[3][j]; - XTx[3][j] = vsubq_f16(x[1][j], x[3][j]); - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - // U[i][0] = XTx[i][0] - XTx[i][2]; - U[i][0] = vsubq_f16(XTx[i][0], XTx[i][2]); - - // U[i][1] = XTx[i][1] + XTx[i][2]; - U[i][1] = vaddq_f16(XTx[i][1], XTx[i][2]); - - // U[i][2] = XTx[i][2] - XTx[i][1]; - U[i][2] = vsubq_f16(XTx[i][2], XTx[i][1]); - - // U[i][3] = XTx[i][1] - XTx[i][3]; - U[i][3] = vsubq_f16(XTx[i][1], XTx[i][3]); - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - vst1q_f16(outptr + m*matrix_stride, U[i][j]); - } - } - outptr += 8; - } -#endif // __aarch64__ -#ifdef __arm_any__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used/computed in this kernel. - float16x4_t x[inner_tile_rows][inner_tile_cols]; - float16x4_t XTx[inner_tile_rows][inner_tile_cols]; - float16x4_t U[inner_tile_rows][inner_tile_cols]; - - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vdup_n_f16(0.0f); - XTx[i][j] = vdup_n_f16(0.0f); - } - } - - // Load x - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vld1_f16(x_ptrs[i][j]); - x_ptrs[i][j] += 4; - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - // XTx[0][j] = x[0][j] - x[2][j]; - XTx[0][j] = vsub_f16(x[0][j], x[2][j]); - - // XTx[1][j] = x[1][j] + x[2][j]; - XTx[1][j] = vadd_f16(x[1][j], x[2][j]); - - // XTx[2][j] = x[2][j] - x[1][j]; - XTx[2][j] = vsub_f16(x[2][j], x[1][j]); - - // XTx[3][j] = x[1][j] - x[3][j]; - XTx[3][j] = vsub_f16(x[1][j], x[3][j]); - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - // U[i][0] = XTx[i][0] - XTx[i][2]; - U[i][0] = vsub_f16(XTx[i][0], XTx[i][2]); - - // U[i][1] = XTx[i][1] + XTx[i][2]; - U[i][1] = vadd_f16(XTx[i][1], XTx[i][2]); - - // U[i][2] = XTx[i][2] - XTx[i][1]; - U[i][2] = vsub_f16(XTx[i][2], XTx[i][1]); - - // U[i][3] = XTx[i][1] - XTx[i][3]; - U[i][3] = vsub_f16(XTx[i][1], XTx[i][3]); - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - vst1_f16(outptr + m*matrix_stride, U[i][j]); - } - } - outptr += 4; - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Load x - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = *(x_ptrs[i][j]++); - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - XTx[0][j] = x[0][j] - x[2][j]; - XTx[1][j] = x[1][j] + x[2][j]; - XTx[2][j] = x[2][j] - x[1][j]; - XTx[3][j] = x[1][j] - x[3][j]; - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - U[i][0] = XTx[i][0] - XTx[i][2]; - U[i][1] = XTx[i][1] + XTx[i][2]; - U[i][2] = XTx[i][2] - XTx[i][1]; - U[i][3] = XTx[i][1] - XTx[i][3]; - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - *(outptr + m*matrix_stride) = U[i][j]; - } - } - outptr++; - } -} - -template class InputTransform<4, 4, __fp16, __fp16, WinogradRoots::Integers>; - -} // namespace -#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_4x4_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_4x4_fp32_fp32_integers.cpp deleted file mode 100644 index 9393785dfc..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_4x4_fp32_fp32_integers.cpp +++ /dev/null @@ -1,255 +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 "input.hpp" -#include "arm.hpp" - -namespace winograd -{ - -template <> -void InputTransform<4, 4, float, float, WinogradRoots::Integers>::transform_tile( - const int n_channels, - const float* const input_base, - const int input_row_stride, - const int input_col_stride, - float* outptr, - const int matrix_stride -) -{ - constexpr int inner_tile_rows = 4, inner_tile_cols = 4; - - // Get pointers into the input tile - const float *x_ptrs[inner_tile_rows][inner_tile_cols]; - for (int i = 0, xi = 0; i < inner_tile_rows; i++, xi++) - { - // Get a pointer into the row - const float* const row_ptr = input_base + xi*input_row_stride; - - for (int j = 0, xj = 0; j < inner_tile_cols; j++, xj++) - { - x_ptrs[i][j] = row_ptr + xj*input_col_stride; - } - } - - // Matrices used/computed in this kernel. - float x[inner_tile_rows][inner_tile_cols]; - float XTx[inner_tile_rows][inner_tile_cols]; - float U[inner_tile_rows][inner_tile_cols]; - - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = XTx[i][j] = 0.0f; - } - } - - // Perform the Winograd input transformation for each channel in the input - // tensor. - int channels_remaining = n_channels; -#ifdef __aarch64__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used/computed in this kernel. - float32x4_t x[inner_tile_rows][inner_tile_cols]; - float32x4_t XTx[inner_tile_rows][inner_tile_cols]; - float32x4_t U[inner_tile_rows][inner_tile_cols]; - - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vdupq_n_f32(0.0f); - XTx[i][j] = vdupq_n_f32(0.0f); - } - } - - // Load x - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vld1q_f32(x_ptrs[i][j]); - x_ptrs[i][j] += 4; - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - // XTx[0][j] = x[0][j] - x[2][j]; - XTx[0][j] = vsubq_f32(x[0][j], x[2][j]); - - // XTx[1][j] = x[1][j] + x[2][j]; - XTx[1][j] = vaddq_f32(x[1][j], x[2][j]); - - // XTx[2][j] = x[2][j] - x[1][j]; - XTx[2][j] = vsubq_f32(x[2][j], x[1][j]); - - // XTx[3][j] = x[1][j] - x[3][j]; - XTx[3][j] = vsubq_f32(x[1][j], x[3][j]); - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - // U[i][0] = XTx[i][0] - XTx[i][2]; - U[i][0] = vsubq_f32(XTx[i][0], XTx[i][2]); - - // U[i][1] = XTx[i][1] + XTx[i][2]; - U[i][1] = vaddq_f32(XTx[i][1], XTx[i][2]); - - // U[i][2] = XTx[i][2] - XTx[i][1]; - U[i][2] = vsubq_f32(XTx[i][2], XTx[i][1]); - - // U[i][3] = XTx[i][1] - XTx[i][3]; - U[i][3] = vsubq_f32(XTx[i][1], XTx[i][3]); - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - vst1q_f32(outptr + m*matrix_stride, U[i][j]); - } - } - outptr += 4; - } -#endif // __aarch64__ -#ifdef __arm_any__ - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used/computed in this kernel. - float32x2_t x[inner_tile_rows][inner_tile_cols]; - float32x2_t XTx[inner_tile_rows][inner_tile_cols]; - float32x2_t U[inner_tile_rows][inner_tile_cols]; - - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vdup_n_f32(0.0f); - XTx[i][j] = vdup_n_f32(0.0f); - } - } - - // Load x - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vld1_f32(x_ptrs[i][j]); - x_ptrs[i][j] += 2; - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - // XTx[0][j] = x[0][j] - x[2][j]; - XTx[0][j] = vsub_f32(x[0][j], x[2][j]); - - // XTx[1][j] = x[1][j] + x[2][j]; - XTx[1][j] = vadd_f32(x[1][j], x[2][j]); - - // XTx[2][j] = x[2][j] - x[1][j]; - XTx[2][j] = vsub_f32(x[2][j], x[1][j]); - - // XTx[3][j] = x[1][j] - x[3][j]; - XTx[3][j] = vsub_f32(x[1][j], x[3][j]); - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - // U[i][0] = XTx[i][0] - XTx[i][2]; - U[i][0] = vsub_f32(XTx[i][0], XTx[i][2]); - - // U[i][1] = XTx[i][1] + XTx[i][2]; - U[i][1] = vadd_f32(XTx[i][1], XTx[i][2]); - - // U[i][2] = XTx[i][2] - XTx[i][1]; - U[i][2] = vsub_f32(XTx[i][2], XTx[i][1]); - - // U[i][3] = XTx[i][1] - XTx[i][3]; - U[i][3] = vsub_f32(XTx[i][1], XTx[i][3]); - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - vst1_f32(outptr + m*matrix_stride, U[i][j]); - } - } - outptr += 2; - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Load x - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = *(x_ptrs[i][j]++); - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - XTx[0][j] = x[0][j] - x[2][j]; - XTx[1][j] = x[1][j] + x[2][j]; - XTx[2][j] = x[2][j] - x[1][j]; - XTx[3][j] = x[1][j] - x[3][j]; - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - U[i][0] = XTx[i][0] - XTx[i][2]; - U[i][1] = XTx[i][1] + XTx[i][2]; - U[i][2] = XTx[i][2] - XTx[i][1]; - U[i][3] = XTx[i][1] - XTx[i][3]; - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - *(outptr + m*matrix_stride) = U[i][j]; - } - } - outptr++; - } -} - -template class InputTransform<4, 4, float, float, WinogradRoots::Integers>; - -} // namespace diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_6x6_fp16_fp16_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_6x6_fp16_fp16_integers.cpp deleted file mode 100644 index 3eaf977826..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_6x6_fp16_fp16_integers.cpp +++ /dev/null @@ -1,277 +0,0 @@ -/* - * Copyright (c) 2020 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. - */ -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -#include "arm.hpp" -#include "input.hpp" - -namespace winograd -{ -template <> -void InputTransform<6, 6, __fp16, __fp16, WinogradRoots::Integers>::transform_tile( - const int n_channels, - const __fp16* const input_base, - const int input_row_stride, - const int input_col_stride, - __fp16* outptr, - const int matrix_stride -) -{ - constexpr int inner_tile_rows = 6; - constexpr int inner_tile_cols = 6; - - // Get pointers into the input tile - const __fp16 *x_ptrs[inner_tile_rows][inner_tile_cols]; - for (int i = 0, xi = 0; i < inner_tile_rows; i++, xi++) - { - // Get a pointer into the row - const __fp16* const row_ptr = input_base + xi*input_row_stride; - - for (int j = 0, xj = 0; j < inner_tile_cols; j++, xj++) - { - x_ptrs[i][j] = row_ptr + xj*input_col_stride; - } - } - - // Matrices used/computed in this kernel. - __fp16 x[inner_tile_rows][inner_tile_cols]; - __fp16 XTx[inner_tile_rows][inner_tile_cols]; - __fp16 U[inner_tile_rows][inner_tile_cols]; - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = XTx[i][j] = 0.0f; - } - } - - // Perform the Winograd input transformation for each channel in the input - // tensor. - int channels_remaining = n_channels; - for (; channels_remaining >= 8; channels_remaining -= 8) - { - // Matrices used/computed in this kernel - float16x8_t x[inner_tile_rows][inner_tile_cols]; - float16x8_t XTx[inner_tile_rows][inner_tile_cols]; - float16x8_t U[inner_tile_rows][inner_tile_cols]; - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vdupq_n_f16(0.0f); - XTx[i][j] = vdupq_n_f16(0.0f); - } - } - - // Read a 6x6 tile in the Winograd domain - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vld1q_f16(x_ptrs[i][j]); - x_ptrs[i][j] += 8; - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - // XTx[0][j] = 4*x[0][j] + -5*x[2][j] + 1*x[4][j]; - XTx[0][j] = vsubq_f16(vaddq_f16(x[4][j], vmulq_f16(x[0][j], vdupq_n_f16(4.0f))), vmulq_f16(x[2][j], vdupq_n_f16(5.0f))); - - // XTx[1][j] = -4*x[1][j] + -4*x[2][j] + 1*x[3][j] + 1*x[4][j]; - XTx[1][j] = vsubq_f16(vaddq_f16(x[3][j], x[4][j]), vmulq_f16(vaddq_f16(x[1][j], x[2][j]), vdupq_n_f16(4.0f))); - - // XTx[2][j] = 4*x[1][j] + -4*x[2][j] + -1*x[3][j] + 1*x[4][j]; - XTx[2][j] = vaddq_f16(vsubq_f16(x[4][j], x[3][j]), vmulq_f16(vsubq_f16(x[1][j], x[2][j]), vdupq_n_f16(4.0f))); - - // XTx[3][j] = -2*x[1][j] + -1*x[2][j] + 2*x[3][j] + 1*x[4][j]; - XTx[3][j] = vaddq_f16(vsubq_f16(x[4][j], x[2][j]), vmulq_f16(vsubq_f16(x[3][j], x[1][j]), vdupq_n_f16(2.0f))); - - // XTx[4][j] = 2*x[1][j] + -1*x[2][j] + -2*x[3][j] + 1*x[4][j]; - XTx[4][j] = vaddq_f16(vsubq_f16(x[4][j], x[2][j]), vmulq_f16(vsubq_f16(x[1][j], x[3][j]), vdupq_n_f16(2.0f))); - - // XTx[5][j] = 4*x[1][j] + -5*x[3][j] + 1*x[5][j]; - XTx[5][j] = vsubq_f16(vaddq_f16(x[5][j], vmulq_f16(x[1][j], vdupq_n_f16(4.0f))), vmulq_f16(x[3][j], vdupq_n_f16(5.0f))); - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - // U[i][0] = 4*XTx[i][0] + -5*XTx[i][2] + 1*XTx[i][4]; - U[i][0] = vsubq_f16(vaddq_f16(XTx[i][4], vmulq_f16(XTx[i][0], vdupq_n_f16(4.0f))), vmulq_f16(XTx[i][2], vdupq_n_f16(5.0f))); - - // U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] + 1*XTx[i][3] + 1*XTx[i][4]; - U[i][1] = vsubq_f16(vaddq_f16(XTx[i][3], XTx[i][4]), vmulq_f16(vaddq_f16(XTx[i][1], XTx[i][2]), vdupq_n_f16(4.0f))); - - // U[i][2] = 4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] + 1*XTx[i][4]; - U[i][2] = vaddq_f16(vsubq_f16(XTx[i][4], XTx[i][3]), vmulq_f16(vsubq_f16(XTx[i][1], XTx[i][2]), vdupq_n_f16(4.0f))); - - // U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] + 2*XTx[i][3] + 1*XTx[i][4]; - U[i][3] = vaddq_f16(vsubq_f16(XTx[i][4], XTx[i][2]), vmulq_f16(vsubq_f16(XTx[i][3], XTx[i][1]), vdupq_n_f16(2.0f))); - - // U[i][4] = 2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] + 1*XTx[i][4]; - U[i][4] = vaddq_f16(vsubq_f16(XTx[i][4], XTx[i][2]), vmulq_f16(vsubq_f16(XTx[i][1], XTx[i][3]), vdupq_n_f16(2.0f))); - - // U[i][5] = 4*XTx[i][1] + -5*XTx[i][3] + 1*XTx[i][5]; - U[i][5] = vsubq_f16(vaddq_f16(XTx[i][5], vmulq_f16(XTx[i][1], vdupq_n_f16(4.0f))), vmulq_f16(XTx[i][3], vdupq_n_f16(5.0f))); - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - vst1q_f16(outptr + m*matrix_stride, U[i][j]); - } - } - outptr += 8; - } - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used/computed in this kernel - float16x4_t x[inner_tile_rows][inner_tile_cols]; - float16x4_t XTx[inner_tile_rows][inner_tile_cols]; - float16x4_t U[inner_tile_rows][inner_tile_cols]; - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vdup_n_f16(0.0f); - XTx[i][j] = vdup_n_f16(0.0f); - } - } - - // Read a 6x6 tile in the Winograd domain - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vld1_f16(x_ptrs[i][j]); - x_ptrs[i][j] += 4; - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - // XTx[0][j] = 4*x[0][j] + -5*x[2][j] + 1*x[4][j]; - XTx[0][j] = vsub_f16(vadd_f16(x[4][j], vmul_f16(x[0][j], vdup_n_f16(4.0f))), vmul_f16(x[2][j], vdup_n_f16(5.0f))); - - // XTx[1][j] = -4*x[1][j] + -4*x[2][j] + 1*x[3][j] + 1*x[4][j]; - XTx[1][j] = vsub_f16(vadd_f16(x[3][j], x[4][j]), vmul_f16(vadd_f16(x[1][j], x[2][j]), vdup_n_f16(4.0f))); - - // XTx[2][j] = 4*x[1][j] + -4*x[2][j] + -1*x[3][j] + 1*x[4][j]; - XTx[2][j] = vadd_f16(vsub_f16(x[4][j], x[3][j]), vmul_f16(vsub_f16(x[1][j], x[2][j]), vdup_n_f16(4.0f))); - - // XTx[3][j] = -2*x[1][j] + -1*x[2][j] + 2*x[3][j] + 1*x[4][j]; - XTx[3][j] = vadd_f16(vsub_f16(x[4][j], x[2][j]), vmul_f16(vsub_f16(x[3][j], x[1][j]), vdup_n_f16(2.0f))); - - // XTx[4][j] = 2*x[1][j] + -1*x[2][j] + -2*x[3][j] + 1*x[4][j]; - XTx[4][j] = vadd_f16(vsub_f16(x[4][j], x[2][j]), vmul_f16(vsub_f16(x[1][j], x[3][j]), vdup_n_f16(2.0f))); - - // XTx[5][j] = 4*x[1][j] + -5*x[3][j] + 1*x[5][j]; - XTx[5][j] = vsub_f16(vadd_f16(x[5][j], vmul_f16(x[1][j], vdup_n_f16(4.0f))), vmul_f16(x[3][j], vdup_n_f16(5.0f))); - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - // U[i][0] = 4*XTx[i][0] + -5*XTx[i][2] + 1*XTx[i][4]; - U[i][0] = vsub_f16(vadd_f16(XTx[i][4], vmul_f16(XTx[i][0], vdup_n_f16(4.0f))), vmul_f16(XTx[i][2], vdup_n_f16(5.0f))); - - // U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] + 1*XTx[i][3] + 1*XTx[i][4]; - U[i][1] = vsub_f16(vadd_f16(XTx[i][3], XTx[i][4]), vmul_f16(vadd_f16(XTx[i][1], XTx[i][2]), vdup_n_f16(4.0f))); - - // U[i][2] = 4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] + 1*XTx[i][4]; - U[i][2] = vadd_f16(vsub_f16(XTx[i][4], XTx[i][3]), vmul_f16(vsub_f16(XTx[i][1], XTx[i][2]), vdup_n_f16(4.0f))); - - // U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] + 2*XTx[i][3] + 1*XTx[i][4]; - U[i][3] = vadd_f16(vsub_f16(XTx[i][4], XTx[i][2]), vmul_f16(vsub_f16(XTx[i][3], XTx[i][1]), vdup_n_f16(2.0f))); - - // U[i][4] = 2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] + 1*XTx[i][4]; - U[i][4] = vadd_f16(vsub_f16(XTx[i][4], XTx[i][2]), vmul_f16(vsub_f16(XTx[i][1], XTx[i][3]), vdup_n_f16(2.0f))); - - // U[i][5] = 4*XTx[i][1] + -5*XTx[i][3] + 1*XTx[i][5]; - U[i][5] = vsub_f16(vadd_f16(XTx[i][5], vmul_f16(XTx[i][1], vdup_n_f16(4.0f))), vmul_f16(XTx[i][3], vdup_n_f16(5.0f))); - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - vst1_f16(outptr + m*matrix_stride, U[i][j]); - } - } - outptr += 4; - } - for (; channels_remaining; channels_remaining--) - { - // Load x - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = *(x_ptrs[i][j]++); - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - XTx[0][j] = 4*x[0][j] + -5*x[2][j] + 1*x[4][j]; - XTx[1][j] = -4*x[1][j] + -4*x[2][j] + 1*x[3][j] + 1*x[4][j]; - XTx[2][j] = 4*x[1][j] + -4*x[2][j] + -1*x[3][j] + 1*x[4][j]; - XTx[3][j] = -2*x[1][j] + -1*x[2][j] + 2*x[3][j] + 1*x[4][j]; - XTx[4][j] = 2*x[1][j] + -1*x[2][j] + -2*x[3][j] + 1*x[4][j]; - XTx[5][j] = 4*x[1][j] + -5*x[3][j] + 1*x[5][j]; - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - U[i][0] = 4*XTx[i][0] + -5*XTx[i][2] + 1*XTx[i][4]; - U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] + 1*XTx[i][3] + 1*XTx[i][4]; - U[i][2] = 4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] + 1*XTx[i][4]; - U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] + 2*XTx[i][3] + 1*XTx[i][4]; - U[i][4] = 2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] + 1*XTx[i][4]; - U[i][5] = 4*XTx[i][1] + -5*XTx[i][3] + 1*XTx[i][5]; - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - *(outptr + m*matrix_stride) = U[i][j]; - } - } - outptr++; - } -} - -template class InputTransform<6, 6, __fp16, __fp16, WinogradRoots::Integers>; - -} // namespace winograd -#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
\ No newline at end of file diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_6x6_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_6x6_fp32_fp32_integers.cpp deleted file mode 100644 index e4aad76d97..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_6x6_fp32_fp32_integers.cpp +++ /dev/null @@ -1,1308 +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 "arm.hpp" -#include "input.hpp" - -namespace winograd -{ - -#ifdef __aarch64__ - -template <> -void InputTransform<6, 6, float, float, WinogradRoots::Integers>::transform_tile( - int n_channels, - const float* input_base, - const int input_row_stride, - const int input_col_stride, - float* matrix_base, - const int matrix_stride -) -{ - const float pcoeffs[4] = {1.0f, 2.0f, 4.0f, 5.0f}; - __asm__ __volatile__( - "ldr q0, [%[pcoeffs]]\n" - "add x25, %[inptr0], %[input_row_stride]\n" - "add x9, %[input_col_stride1], %[input_col_stride1]\n" - "add x16, x25, %[input_row_stride]\n" - "add x19, x9, %[input_col_stride1]\n" - "add x26, x16, %[input_row_stride]\n" - "add x20, x19, %[input_col_stride1]\n" - "add x17, x26, %[input_row_stride]\n" - "add x21, x20, %[input_col_stride1]\n" - "add x27, x17, %[input_row_stride]\n" - "add x28, %[outptr0], %[output_row_stride]\n" - "add x11, %[output_col_stride1], %[output_col_stride1]\n" - "add x22, x28, %[output_row_stride]\n" - "add x13, x11, %[output_col_stride1]\n" - "add x12, x22, %[output_row_stride]\n" - "add x23, x13, %[output_col_stride1]\n" - "add x14, x12, %[output_row_stride]\n" - "add x15, x23, %[output_col_stride1]\n" - "add x24, x14, %[output_row_stride]\n" - "cmp %w[n_channels], #4\n" - "blt 2f\n" - "1:\n" - "ldr q8, [%[inptr0], x20]\n" - "ldr q2, [%[inptr0], x9]\n" - "mov v14.16b, v8.16b\n" - "ldr q9, [%[inptr0]]\n" - "mov v10.16b, v8.16b\n" - "ldr q1, [%[inptr0], x21]\n" - "fmla v14.4s, v9.4s, v0.s[2]\n" - "ldr q4, [%[inptr0], x19]\n" - "mov v9.16b, v8.16b\n" - "ldr q12, [%[inptr0], %[input_col_stride1]]\n" - "fmls v10.4s, v12.4s, v0.s[2]\n" - "ldr q5, [x16, x20]\n" - "fmls v14.4s, v2.4s, v0.s[3]\n" - "ldr q20, [x16, x9]\n" - "fmla v9.4s, v12.4s, v0.s[2]\n" - "ldr q3, [x16]\n" - "fmls v10.4s, v2.4s, v0.s[2]\n" - "ldr q6, [x16, x21]\n" - "mov v7.16b, v8.16b\n" - "ldr q16, [x16, x19]\n" - "fmls v9.4s, v2.4s, v0.s[2]\n" - "ldr q22, [x16, %[input_col_stride1]]\n" - "fadd v10.4s, v10.4s, v4.4s\n" - "ldr q17, [x17, x20]\n" - "fmls v7.4s, v12.4s, v0.s[1]\n" - "ldr q15, [x17, x9]\n" - "fsub v9.4s, v9.4s, v4.4s\n" - "ldr q19, [x17]\n" - "mov v8.16b, v8.16b\n" - "ldr q18, [x17, x21]\n" - "fsub v7.4s, v7.4s, v2.4s\n" - "ldr q13, [x17, x19]\n" - "fmla v7.4s, v4.4s, v0.s[1]\n" - "ldr q21, [x17, %[input_col_stride1]]\n" - "fmla v8.4s, v12.4s, v0.s[1]\n" - "add %[inptr0], %[inptr0], #16\n" - "mov v11.16b, v1.16b\n" - "add x16, x16, #16\n" - "mov v1.16b, v5.16b\n" - "add x17, x17, #16\n" - "fsub v8.4s, v8.4s, v2.4s\n" - "fmla v11.4s, v12.4s, v0.s[2]\n" - "fmls v8.4s, v4.4s, v0.s[1]\n" - "fmla v1.4s, v3.4s, v0.s[2]\n" - "mov v2.16b, v5.16b\n" - "mov v3.16b, v5.16b\n" - "fmls v11.4s, v4.4s, v0.s[3]\n" - "mov v4.16b, v5.16b\n" - "fmls v1.4s, v20.4s, v0.s[3]\n" - "fmls v2.4s, v22.4s, v0.s[2]\n" - "fmla v3.4s, v22.4s, v0.s[2]\n" - "fmls v4.4s, v22.4s, v0.s[1]\n" - "mov v5.16b, v5.16b\n" - "mov v6.16b, v6.16b\n" - "fmls v2.4s, v20.4s, v0.s[2]\n" - "mov v12.16b, v17.16b\n" - "fmls v3.4s, v20.4s, v0.s[2]\n" - "fsub v4.4s, v4.4s, v20.4s\n" - "fmla v4.4s, v16.4s, v0.s[1]\n" - "fmla v5.4s, v22.4s, v0.s[1]\n" - "fadd v2.4s, v2.4s, v16.4s\n" - "fmla v6.4s, v22.4s, v0.s[2]\n" - "fsub v3.4s, v3.4s, v16.4s\n" - "fmla v12.4s, v19.4s, v0.s[2]\n" - "fsub v5.4s, v5.4s, v20.4s\n" - "mov v19.16b, v17.16b\n" - "fmls v5.4s, v16.4s, v0.s[1]\n" - "fmls v6.4s, v16.4s, v0.s[3]\n" - "fmls v12.4s, v15.4s, v0.s[3]\n" - "fmls v19.4s, v21.4s, v0.s[2]\n" - "mov v20.16b, v17.16b\n" - "mov v16.16b, v17.16b\n" - "mov v17.16b, v17.16b\n" - "mov v18.16b, v18.16b\n" - "fmls v19.4s, v15.4s, v0.s[2]\n" - "fmla v20.4s, v21.4s, v0.s[2]\n" - "fmls v16.4s, v21.4s, v0.s[1]\n" - "fmla v17.4s, v21.4s, v0.s[1]\n" - "fmla v18.4s, v21.4s, v0.s[2]\n" - "mov v23.16b, v12.16b\n" - "fadd v19.4s, v19.4s, v13.4s\n" - "fmls v20.4s, v15.4s, v0.s[2]\n" - "fsub v16.4s, v16.4s, v15.4s\n" - "fsub v17.4s, v17.4s, v15.4s\n" - "fmla v16.4s, v13.4s, v0.s[1]\n" - "fmls v17.4s, v13.4s, v0.s[1]\n" - "fsub v20.4s, v20.4s, v13.4s\n" - "fmls v18.4s, v13.4s, v0.s[3]\n" - "fmla v23.4s, v14.4s, v0.s[2]\n" - "mov v15.16b, v19.16b\n" - "mov v14.16b, v20.16b\n" - "mov v24.16b, v16.16b\n" - "fmla v15.4s, v10.4s, v0.s[2]\n" - "mov v10.16b, v17.16b\n" - "fmls v23.4s, v1.4s, v0.s[3]\n" - "fmla v14.4s, v9.4s, v0.s[2]\n" - "fmla v24.4s, v7.4s, v0.s[2]\n" - "fmla v10.4s, v8.4s, v0.s[2]\n" - "fmls v15.4s, v2.4s, v0.s[3]\n" - "mov v7.16b, v18.16b\n" - "str q23, [%[outptr0]]\n" - "fmls v14.4s, v3.4s, v0.s[3]\n" - "fmls v24.4s, v4.4s, v0.s[3]\n" - "fmls v10.4s, v5.4s, v0.s[3]\n" - "str q15, [%[outptr0], %[output_col_stride1]]\n" - "fmla v7.4s, v11.4s, v0.s[2]\n" - "str q14, [%[outptr0], x11]\n" - "str q24, [%[outptr0], x13]\n" - "str q10, [%[outptr0], x23]\n" - "fmls v7.4s, v6.4s, v0.s[3]\n" - "str q7, [%[outptr0], x15]\n" - "add %[outptr0], %[outptr0], #16\n" - "mov v26.16b, v12.16b\n" - "mov v25.16b, v19.16b\n" - "ldr q11, [x25, x20]\n" - "mov v10.16b, v11.16b\n" - "ldr q23, [x25, x9]\n" - "mov v9.16b, v11.16b\n" - "ldr q7, [x25]\n" - "fmla v10.4s, v7.4s, v0.s[2]\n" - "ldr q13, [x25, x21]\n" - "mov v7.16b, v11.16b\n" - "ldr q31, [x25, x19]\n" - "mov v8.16b, v11.16b\n" - "ldr q21, [x25, %[input_col_stride1]]\n" - "fmls v10.4s, v23.4s, v0.s[3]\n" - "ldr q30, [x26, x20]\n" - "fmls v9.4s, v21.4s, v0.s[2]\n" - "ldr q29, [x26, x9]\n" - "fmla v7.4s, v21.4s, v0.s[2]\n" - "ldr q22, [x26]\n" - "fmls v8.4s, v21.4s, v0.s[1]\n" - "ldr q24, [x26, x21]\n" - "fmls v9.4s, v23.4s, v0.s[2]\n" - "ldr q27, [x26, x19]\n" - "fmls v7.4s, v23.4s, v0.s[2]\n" - "ldr q28, [x26, %[input_col_stride1]]\n" - "fsub v8.4s, v8.4s, v23.4s\n" - "add x25, x25, #16\n" - "fadd v9.4s, v9.4s, v31.4s\n" - "add x26, x26, #16\n" - "fsub v7.4s, v7.4s, v31.4s\n" - "fmla v8.4s, v31.4s, v0.s[1]\n" - "mov v11.16b, v11.16b\n" - "mov v15.16b, v13.16b\n" - "mov v14.16b, v30.16b\n" - "mov v13.16b, v30.16b\n" - "fmla v11.4s, v21.4s, v0.s[1]\n" - "fmla v15.4s, v21.4s, v0.s[2]\n" - "fmla v14.4s, v22.4s, v0.s[2]\n" - "fmls v13.4s, v28.4s, v0.s[2]\n" - "mov v21.16b, v30.16b\n" - "mov v22.16b, v30.16b\n" - "fsub v11.4s, v11.4s, v23.4s\n" - "fmls v15.4s, v31.4s, v0.s[3]\n" - "fmls v11.4s, v31.4s, v0.s[1]\n" - "fmls v14.4s, v29.4s, v0.s[3]\n" - "fmls v13.4s, v29.4s, v0.s[2]\n" - "fmla v21.4s, v28.4s, v0.s[2]\n" - "fmls v22.4s, v28.4s, v0.s[1]\n" - "mov v23.16b, v30.16b\n" - "mov v24.16b, v24.16b\n" - "fmls v26.4s, v10.4s, v0.s[2]\n" - "fadd v13.4s, v13.4s, v27.4s\n" - "fmls v21.4s, v29.4s, v0.s[2]\n" - "fsub v22.4s, v22.4s, v29.4s\n" - "fmla v23.4s, v28.4s, v0.s[1]\n" - "fmla v22.4s, v27.4s, v0.s[1]\n" - "fmla v24.4s, v28.4s, v0.s[2]\n" - "fsub v21.4s, v21.4s, v27.4s\n" - "fmls v26.4s, v1.4s, v0.s[2]\n" - "fsub v23.4s, v23.4s, v29.4s\n" - "fmls v25.4s, v9.4s, v0.s[2]\n" - "fmls v23.4s, v27.4s, v0.s[1]\n" - "fmls v24.4s, v27.4s, v0.s[3]\n" - "fadd v26.4s, v26.4s, v14.4s\n" - "mov v27.16b, v20.16b\n" - "str q26, [x28]\n" - "fmls v25.4s, v2.4s, v0.s[2]\n" - "fmls v27.4s, v7.4s, v0.s[2]\n" - "mov v31.16b, v16.16b\n" - "mov v30.16b, v17.16b\n" - "mov v29.16b, v18.16b\n" - "fadd v25.4s, v25.4s, v13.4s\n" - "fmls v31.4s, v8.4s, v0.s[2]\n" - "str q25, [x28, %[output_col_stride1]]\n" - "fmls v27.4s, v3.4s, v0.s[2]\n" - "fmls v30.4s, v11.4s, v0.s[2]\n" - "fmls v29.4s, v15.4s, v0.s[2]\n" - "fmls v31.4s, v4.4s, v0.s[2]\n" - "mov v26.16b, v12.16b\n" - "fadd v27.4s, v27.4s, v21.4s\n" - "mov v25.16b, v19.16b\n" - "str q27, [x28, x11]\n" - "fmls v30.4s, v5.4s, v0.s[2]\n" - "fadd v31.4s, v31.4s, v22.4s\n" - "fmls v29.4s, v6.4s, v0.s[2]\n" - "str q31, [x28, x13]\n" - "fmla v26.4s, v10.4s, v0.s[2]\n" - "fadd v30.4s, v30.4s, v23.4s\n" - "fmla v25.4s, v9.4s, v0.s[2]\n" - "str q30, [x28, x23]\n" - "fadd v29.4s, v29.4s, v24.4s\n" - "str q29, [x28, x15]\n" - "fmls v26.4s, v1.4s, v0.s[2]\n" - "fmls v25.4s, v2.4s, v0.s[2]\n" - "add x28, x28, #16\n" - "mov v30.16b, v20.16b\n" - "mov v29.16b, v16.16b\n" - "fsub v26.4s, v26.4s, v14.4s\n" - "mov v28.16b, v17.16b\n" - "str q26, [x22]\n" - "fsub v25.4s, v25.4s, v13.4s\n" - "str q25, [x22, %[output_col_stride1]]\n" - "fmla v30.4s, v7.4s, v0.s[2]\n" - "fmla v29.4s, v8.4s, v0.s[2]\n" - "fmla v28.4s, v11.4s, v0.s[2]\n" - "mov v26.16b, v18.16b\n" - "mov v25.16b, v12.16b\n" - "fmls v30.4s, v3.4s, v0.s[2]\n" - "mov v31.16b, v19.16b\n" - "fmls v29.4s, v4.4s, v0.s[2]\n" - "fmls v28.4s, v5.4s, v0.s[2]\n" - "fmla v26.4s, v15.4s, v0.s[2]\n" - "fmls v25.4s, v10.4s, v0.s[1]\n" - "fsub v30.4s, v30.4s, v21.4s\n" - "fmls v31.4s, v9.4s, v0.s[1]\n" - "str q30, [x22, x11]\n" - "fsub v29.4s, v29.4s, v22.4s\n" - "str q29, [x22, x13]\n" - "fsub v28.4s, v28.4s, v23.4s\n" - "str q28, [x22, x23]\n" - "fmls v26.4s, v6.4s, v0.s[2]\n" - "fsub v25.4s, v25.4s, v1.4s\n" - "fsub v31.4s, v31.4s, v2.4s\n" - "fmla v25.4s, v14.4s, v0.s[1]\n" - "fmla v31.4s, v13.4s, v0.s[1]\n" - "fsub v26.4s, v26.4s, v24.4s\n" - "mov v27.16b, v20.16b\n" - "str q26, [x22, x15]\n" - "mov v26.16b, v16.16b\n" - "str q25, [x12]\n" - "fmls v27.4s, v7.4s, v0.s[1]\n" - "str q31, [x12, %[output_col_stride1]]\n" - "fmls v26.4s, v8.4s, v0.s[1]\n" - "mov v25.16b, v17.16b\n" - "add x22, x22, #16\n" - "fsub v27.4s, v27.4s, v3.4s\n" - "mov v28.16b, v18.16b\n" - "fmla v27.4s, v21.4s, v0.s[1]\n" - "fsub v26.4s, v26.4s, v4.4s\n" - "fmla v26.4s, v22.4s, v0.s[1]\n" - "fmls v25.4s, v11.4s, v0.s[1]\n" - "fmls v28.4s, v15.4s, v0.s[1]\n" - "mov v12.16b, v12.16b\n" - "str q27, [x12, x11]\n" - "mov v19.16b, v19.16b\n" - "str q26, [x12, x13]\n" - "fsub v25.4s, v25.4s, v5.4s\n" - "fmla v25.4s, v23.4s, v0.s[1]\n" - "fsub v28.4s, v28.4s, v6.4s\n" - "fmla v28.4s, v24.4s, v0.s[1]\n" - "fmla v12.4s, v10.4s, v0.s[1]\n" - "fmla v19.4s, v9.4s, v0.s[1]\n" - "mov v20.16b, v20.16b\n" - "str q25, [x12, x23]\n" - "mov v16.16b, v16.16b\n" - "str q28, [x12, x15]\n" - "fsub v12.4s, v12.4s, v1.4s\n" - "fmls v12.4s, v14.4s, v0.s[1]\n" - "add x12, x12, #16\n" - "fsub v19.4s, v19.4s, v2.4s\n" - "fmla v20.4s, v7.4s, v0.s[1]\n" - "fmls v19.4s, v13.4s, v0.s[1]\n" - "fmla v16.4s, v8.4s, v0.s[1]\n" - "str q12, [x14]\n" - "mov v1.16b, v17.16b\n" - "fsub v20.4s, v20.4s, v3.4s\n" - "mov v17.16b, v18.16b\n" - "str q19, [x14, %[output_col_stride1]]\n" - "fmls v20.4s, v21.4s, v0.s[1]\n" - "fsub v16.4s, v16.4s, v4.4s\n" - "fmla v1.4s, v11.4s, v0.s[1]\n" - "fmls v16.4s, v22.4s, v0.s[1]\n" - "fmla v17.4s, v15.4s, v0.s[1]\n" - "str q20, [x14, x11]\n" - "fsub v1.4s, v1.4s, v5.4s\n" - "str q16, [x14, x13]\n" - "fmls v1.4s, v23.4s, v0.s[1]\n" - "fsub v17.4s, v17.4s, v6.4s\n" - "fmls v17.4s, v24.4s, v0.s[1]\n" - "str q1, [x14, x23]\n" - "str q17, [x14, x15]\n" - "add x14, x14, #16\n" - "ldr q2, [x27, x20]\n" - "mov v4.16b, v2.16b\n" - "ldr q17, [x27, x9]\n" - "mov v12.16b, v2.16b\n" - "ldr q18, [x27]\n" - "fmla v4.4s, v18.4s, v0.s[2]\n" - "ldr q3, [x27, x21]\n" - "mov v6.16b, v2.16b\n" - "ldr q5, [x27, x19]\n" - "mov v1.16b, v2.16b\n" - "ldr q18, [x27, %[input_col_stride1]]\n" - "fmls v4.4s, v17.4s, v0.s[3]\n" - "add x27, x27, #16\n" - "fmls v12.4s, v18.4s, v0.s[2]\n" - "sub %w[n_channels], %w[n_channels], #4\n" - "fmla v6.4s, v18.4s, v0.s[2]\n" - "cmp %w[n_channels], #4\n" - "fmls v1.4s, v18.4s, v0.s[1]\n" - "mov v2.16b, v2.16b\n" - "fmls v12.4s, v17.4s, v0.s[2]\n" - "mov v3.16b, v3.16b\n" - "fmls v6.4s, v17.4s, v0.s[2]\n" - "fmla v2.4s, v18.4s, v0.s[1]\n" - "fsub v1.4s, v1.4s, v17.4s\n" - "fmla v3.4s, v18.4s, v0.s[2]\n" - "fadd v12.4s, v12.4s, v5.4s\n" - "fmla v1.4s, v5.4s, v0.s[1]\n" - "fsub v6.4s, v6.4s, v5.4s\n" - "fsub v2.4s, v2.4s, v17.4s\n" - "fmls v2.4s, v5.4s, v0.s[1]\n" - "fmls v3.4s, v5.4s, v0.s[3]\n" - "mov v4.16b, v4.16b\n" - "mov v16.16b, v12.16b\n" - "mov v5.16b, v6.16b\n" - "mov v6.16b, v1.16b\n" - "fmla v4.4s, v10.4s, v0.s[2]\n" - "fmla v16.4s, v9.4s, v0.s[2]\n" - "fmla v5.4s, v7.4s, v0.s[2]\n" - "fmla v6.4s, v8.4s, v0.s[2]\n" - "mov v9.16b, v2.16b\n" - "mov v10.16b, v3.16b\n" - "fmls v4.4s, v14.4s, v0.s[3]\n" - "fmls v16.4s, v13.4s, v0.s[3]\n" - "fmls v5.4s, v21.4s, v0.s[3]\n" - "fmls v6.4s, v22.4s, v0.s[3]\n" - "fmla v9.4s, v11.4s, v0.s[2]\n" - "fmla v10.4s, v15.4s, v0.s[2]\n" - "str q4, [x24]\n" - "str q16, [x24, %[output_col_stride1]]\n" - "str q5, [x24, x11]\n" - "str q6, [x24, x13]\n" - "fmls v9.4s, v23.4s, v0.s[3]\n" - "fmls v10.4s, v24.4s, v0.s[3]\n" - "str q9, [x24, x23]\n" - "str q10, [x24, x15]\n" - "add x24, x24, #16\n" - "bge 1b\n" - "2:\n" - "cmp %w[n_channels], #2\n" - "blt 3f\n" - "ldr d8, [%[inptr0], x20]\n" - "mov v14.16b, v8.16b\n" - "ldr d2, [%[inptr0], x9]\n" - "mov v10.16b, v8.16b\n" - "ldr d9, [%[inptr0]]\n" - "fmla v14.4s, v9.4s, v0.s[2]\n" - "ldr d1, [%[inptr0], x21]\n" - "mov v9.16b, v8.16b\n" - "ldr d4, [%[inptr0], x19]\n" - "mov v7.16b, v8.16b\n" - "ldr d12, [%[inptr0], %[input_col_stride1]]\n" - "fmls v14.4s, v2.4s, v0.s[3]\n" - "ldr d5, [x16, x20]\n" - "fmls v10.4s, v12.4s, v0.s[2]\n" - "ldr d20, [x16, x9]\n" - "fmla v9.4s, v12.4s, v0.s[2]\n" - "ldr d3, [x16]\n" - "fmls v7.4s, v12.4s, v0.s[1]\n" - "ldr d6, [x16, x21]\n" - "fmls v10.4s, v2.4s, v0.s[2]\n" - "ldr d16, [x16, x19]\n" - "fmls v9.4s, v2.4s, v0.s[2]\n" - "ldr d22, [x16, %[input_col_stride1]]\n" - "fsub v7.4s, v7.4s, v2.4s\n" - "ldr d17, [x17, x20]\n" - "fadd v10.4s, v10.4s, v4.4s\n" - "ldr d15, [x17, x9]\n" - "fsub v9.4s, v9.4s, v4.4s\n" - "ldr d19, [x17]\n" - "fmla v7.4s, v4.4s, v0.s[1]\n" - "ldr d18, [x17, x21]\n" - "mov v8.16b, v8.16b\n" - "ldr d13, [x17, x19]\n" - "mov v11.16b, v1.16b\n" - "ldr d21, [x17, %[input_col_stride1]]\n" - "fmla v8.4s, v12.4s, v0.s[1]\n" - "add %[inptr0], %[inptr0], #8\n" - "fmla v11.4s, v12.4s, v0.s[2]\n" - "add x16, x16, #8\n" - "mov v1.16b, v5.16b\n" - "add x17, x17, #8\n" - "fsub v8.4s, v8.4s, v2.4s\n" - "mov v2.16b, v5.16b\n" - "fmls v8.4s, v4.4s, v0.s[1]\n" - "fmls v11.4s, v4.4s, v0.s[3]\n" - "fmla v1.4s, v3.4s, v0.s[2]\n" - "fmls v2.4s, v22.4s, v0.s[2]\n" - "mov v3.16b, v5.16b\n" - "mov v4.16b, v5.16b\n" - "mov v5.16b, v5.16b\n" - "mov v6.16b, v6.16b\n" - "fmls v1.4s, v20.4s, v0.s[3]\n" - "fmls v2.4s, v20.4s, v0.s[2]\n" - "fmla v3.4s, v22.4s, v0.s[2]\n" - "fmls v4.4s, v22.4s, v0.s[1]\n" - "fmla v5.4s, v22.4s, v0.s[1]\n" - "fmla v6.4s, v22.4s, v0.s[2]\n" - "fadd v2.4s, v2.4s, v16.4s\n" - "mov v12.16b, v17.16b\n" - "fmls v3.4s, v20.4s, v0.s[2]\n" - "fsub v4.4s, v4.4s, v20.4s\n" - "fmla v4.4s, v16.4s, v0.s[1]\n" - "fsub v5.4s, v5.4s, v20.4s\n" - "fmls v5.4s, v16.4s, v0.s[1]\n" - "fmls v6.4s, v16.4s, v0.s[3]\n" - "fsub v3.4s, v3.4s, v16.4s\n" - "fmla v12.4s, v19.4s, v0.s[2]\n" - "mov v19.16b, v17.16b\n" - "mov v20.16b, v17.16b\n" - "mov v16.16b, v17.16b\n" - "mov v17.16b, v17.16b\n" - "fmls v12.4s, v15.4s, v0.s[3]\n" - "fmls v19.4s, v21.4s, v0.s[2]\n" - "fmla v20.4s, v21.4s, v0.s[2]\n" - "fmls v16.4s, v21.4s, v0.s[1]\n" - "fmla v17.4s, v21.4s, v0.s[1]\n" - "mov v18.16b, v18.16b\n" - "fmls v19.4s, v15.4s, v0.s[2]\n" - "mov v23.16b, v12.16b\n" - "fmls v20.4s, v15.4s, v0.s[2]\n" - "fsub v16.4s, v16.4s, v15.4s\n" - "fmla v16.4s, v13.4s, v0.s[1]\n" - "fsub v17.4s, v17.4s, v15.4s\n" - "fadd v19.4s, v19.4s, v13.4s\n" - "fmls v17.4s, v13.4s, v0.s[1]\n" - "fsub v20.4s, v20.4s, v13.4s\n" - "fmla v18.4s, v21.4s, v0.s[2]\n" - "fmla v23.4s, v14.4s, v0.s[2]\n" - "mov v15.16b, v19.16b\n" - "mov v14.16b, v20.16b\n" - "mov v24.16b, v16.16b\n" - "fmls v18.4s, v13.4s, v0.s[3]\n" - "fmla v15.4s, v10.4s, v0.s[2]\n" - "fmls v23.4s, v1.4s, v0.s[3]\n" - "fmla v14.4s, v9.4s, v0.s[2]\n" - "fmla v24.4s, v7.4s, v0.s[2]\n" - "mov v10.16b, v17.16b\n" - "fmls v15.4s, v2.4s, v0.s[3]\n" - "mov v7.16b, v18.16b\n" - "str d23, [%[outptr0]]\n" - "fmls v14.4s, v3.4s, v0.s[3]\n" - "fmls v24.4s, v4.4s, v0.s[3]\n" - "fmla v10.4s, v8.4s, v0.s[2]\n" - "str d15, [%[outptr0], %[output_col_stride1]]\n" - "fmla v7.4s, v11.4s, v0.s[2]\n" - "str d14, [%[outptr0], x11]\n" - "fmls v10.4s, v5.4s, v0.s[3]\n" - "str d24, [%[outptr0], x13]\n" - "fmls v7.4s, v6.4s, v0.s[3]\n" - "str d10, [%[outptr0], x23]\n" - "str d7, [%[outptr0], x15]\n" - "add %[outptr0], %[outptr0], #8\n" - "mov v26.16b, v12.16b\n" - "mov v25.16b, v19.16b\n" - "ldr d11, [x25, x20]\n" - "mov v10.16b, v11.16b\n" - "ldr d23, [x25, x9]\n" - "mov v9.16b, v11.16b\n" - "ldr d7, [x25]\n" - "fmla v10.4s, v7.4s, v0.s[2]\n" - "ldr d13, [x25, x21]\n" - "mov v7.16b, v11.16b\n" - "ldr d31, [x25, x19]\n" - "mov v8.16b, v11.16b\n" - "ldr d21, [x25, %[input_col_stride1]]\n" - "fmls v10.4s, v23.4s, v0.s[3]\n" - "ldr d30, [x26, x20]\n" - "fmls v9.4s, v21.4s, v0.s[2]\n" - "ldr d29, [x26, x9]\n" - "fmla v7.4s, v21.4s, v0.s[2]\n" - "ldr d22, [x26]\n" - "fmls v8.4s, v21.4s, v0.s[1]\n" - "ldr d24, [x26, x21]\n" - "fmls v9.4s, v23.4s, v0.s[2]\n" - "ldr d27, [x26, x19]\n" - "fmls v7.4s, v23.4s, v0.s[2]\n" - "ldr d28, [x26, %[input_col_stride1]]\n" - "fsub v8.4s, v8.4s, v23.4s\n" - "add x25, x25, #8\n" - "fadd v9.4s, v9.4s, v31.4s\n" - "add x26, x26, #8\n" - "fsub v7.4s, v7.4s, v31.4s\n" - "fmla v8.4s, v31.4s, v0.s[1]\n" - "mov v11.16b, v11.16b\n" - "mov v15.16b, v13.16b\n" - "mov v14.16b, v30.16b\n" - "mov v13.16b, v30.16b\n" - "fmla v11.4s, v21.4s, v0.s[1]\n" - "fmla v15.4s, v21.4s, v0.s[2]\n" - "fmla v14.4s, v22.4s, v0.s[2]\n" - "fmls v13.4s, v28.4s, v0.s[2]\n" - "mov v21.16b, v30.16b\n" - "mov v22.16b, v30.16b\n" - "fsub v11.4s, v11.4s, v23.4s\n" - "fmls v15.4s, v31.4s, v0.s[3]\n" - "fmls v11.4s, v31.4s, v0.s[1]\n" - "fmls v14.4s, v29.4s, v0.s[3]\n" - "fmls v13.4s, v29.4s, v0.s[2]\n" - "fmla v21.4s, v28.4s, v0.s[2]\n" - "fmls v22.4s, v28.4s, v0.s[1]\n" - "mov v23.16b, v30.16b\n" - "mov v24.16b, v24.16b\n" - "fmls v26.4s, v10.4s, v0.s[2]\n" - "fadd v13.4s, v13.4s, v27.4s\n" - "fmls v21.4s, v29.4s, v0.s[2]\n" - "fsub v22.4s, v22.4s, v29.4s\n" - "fmla v23.4s, v28.4s, v0.s[1]\n" - "fmla v22.4s, v27.4s, v0.s[1]\n" - "fmla v24.4s, v28.4s, v0.s[2]\n" - "fsub v21.4s, v21.4s, v27.4s\n" - "fmls v26.4s, v1.4s, v0.s[2]\n" - "fsub v23.4s, v23.4s, v29.4s\n" - "fmls v25.4s, v9.4s, v0.s[2]\n" - "fmls v23.4s, v27.4s, v0.s[1]\n" - "fmls v24.4s, v27.4s, v0.s[3]\n" - "fadd v26.4s, v26.4s, v14.4s\n" - "mov v27.16b, v20.16b\n" - "str d26, [x28]\n" - "fmls v25.4s, v2.4s, v0.s[2]\n" - "fmls v27.4s, v7.4s, v0.s[2]\n" - "mov v31.16b, v16.16b\n" - "mov v30.16b, v17.16b\n" - "mov v29.16b, v18.16b\n" - "fadd v25.4s, v25.4s, v13.4s\n" - "fmls v31.4s, v8.4s, v0.s[2]\n" - "str d25, [x28, %[output_col_stride1]]\n" - "fmls v27.4s, v3.4s, v0.s[2]\n" - "fmls v30.4s, v11.4s, v0.s[2]\n" - "fmls v29.4s, v15.4s, v0.s[2]\n" - "fmls v31.4s, v4.4s, v0.s[2]\n" - "mov v26.16b, v12.16b\n" - "fadd v27.4s, v27.4s, v21.4s\n" - "mov v25.16b, v19.16b\n" - "str d27, [x28, x11]\n" - "fmls v30.4s, v5.4s, v0.s[2]\n" - "fadd v31.4s, v31.4s, v22.4s\n" - "fmls v29.4s, v6.4s, v0.s[2]\n" - "str d31, [x28, x13]\n" - "fmla v26.4s, v10.4s, v0.s[2]\n" - "fadd v30.4s, v30.4s, v23.4s\n" - "fmla v25.4s, v9.4s, v0.s[2]\n" - "str d30, [x28, x23]\n" - "fadd v29.4s, v29.4s, v24.4s\n" - "str d29, [x28, x15]\n" - "fmls v26.4s, v1.4s, v0.s[2]\n" - "fmls v25.4s, v2.4s, v0.s[2]\n" - "add x28, x28, #8\n" - "mov v30.16b, v20.16b\n" - "mov v29.16b, v16.16b\n" - "fsub v26.4s, v26.4s, v14.4s\n" - "mov v28.16b, v17.16b\n" - "str d26, [x22]\n" - "fsub v25.4s, v25.4s, v13.4s\n" - "str d25, [x22, %[output_col_stride1]]\n" - "fmla v30.4s, v7.4s, v0.s[2]\n" - "fmla v29.4s, v8.4s, v0.s[2]\n" - "fmla v28.4s, v11.4s, v0.s[2]\n" - "mov v26.16b, v18.16b\n" - "mov v25.16b, v12.16b\n" - "fmls v30.4s, v3.4s, v0.s[2]\n" - "mov v31.16b, v19.16b\n" - "fmls v29.4s, v4.4s, v0.s[2]\n" - "fmls v28.4s, v5.4s, v0.s[2]\n" - "fmla v26.4s, v15.4s, v0.s[2]\n" - "fmls v25.4s, v10.4s, v0.s[1]\n" - "fsub v30.4s, v30.4s, v21.4s\n" - "fmls v31.4s, v9.4s, v0.s[1]\n" - "str d30, [x22, x11]\n" - "fsub v29.4s, v29.4s, v22.4s\n" - "str d29, [x22, x13]\n" - "fsub v28.4s, v28.4s, v23.4s\n" - "str d28, [x22, x23]\n" - "fmls v26.4s, v6.4s, v0.s[2]\n" - "fsub v25.4s, v25.4s, v1.4s\n" - "fsub v31.4s, v31.4s, v2.4s\n" - "fmla v25.4s, v14.4s, v0.s[1]\n" - "fmla v31.4s, v13.4s, v0.s[1]\n" - "fsub v26.4s, v26.4s, v24.4s\n" - "mov v27.16b, v20.16b\n" - "str d26, [x22, x15]\n" - "mov v26.16b, v16.16b\n" - "str d25, [x12]\n" - "fmls v27.4s, v7.4s, v0.s[1]\n" - "str d31, [x12, %[output_col_stride1]]\n" - "fmls v26.4s, v8.4s, v0.s[1]\n" - "mov v25.16b, v17.16b\n" - "add x22, x22, #8\n" - "fsub v27.4s, v27.4s, v3.4s\n" - "mov v28.16b, v18.16b\n" - "fmla v27.4s, v21.4s, v0.s[1]\n" - "fsub v26.4s, v26.4s, v4.4s\n" - "fmla v26.4s, v22.4s, v0.s[1]\n" - "fmls v25.4s, v11.4s, v0.s[1]\n" - "fmls v28.4s, v15.4s, v0.s[1]\n" - "mov v12.16b, v12.16b\n" - "str d27, [x12, x11]\n" - "mov v19.16b, v19.16b\n" - "str d26, [x12, x13]\n" - "fsub v25.4s, v25.4s, v5.4s\n" - "fmla v25.4s, v23.4s, v0.s[1]\n" - "fsub v28.4s, v28.4s, v6.4s\n" - "fmla v28.4s, v24.4s, v0.s[1]\n" - "fmla v12.4s, v10.4s, v0.s[1]\n" - "fmla v19.4s, v9.4s, v0.s[1]\n" - "mov v20.16b, v20.16b\n" - "str d25, [x12, x23]\n" - "mov v16.16b, v16.16b\n" - "str d28, [x12, x15]\n" - "fsub v12.4s, v12.4s, v1.4s\n" - "fmls v12.4s, v14.4s, v0.s[1]\n" - "add x12, x12, #8\n" - "fsub v19.4s, v19.4s, v2.4s\n" - "fmla v20.4s, v7.4s, v0.s[1]\n" - "fmls v19.4s, v13.4s, v0.s[1]\n" - "fmla v16.4s, v8.4s, v0.s[1]\n" - "str d12, [x14]\n" - "mov v1.16b, v17.16b\n" - "fsub v20.4s, v20.4s, v3.4s\n" - "mov v17.16b, v18.16b\n" - "str d19, [x14, %[output_col_stride1]]\n" - "fmls v20.4s, v21.4s, v0.s[1]\n" - "fsub v16.4s, v16.4s, v4.4s\n" - "fmla v1.4s, v11.4s, v0.s[1]\n" - "fmls v16.4s, v22.4s, v0.s[1]\n" - "fmla v17.4s, v15.4s, v0.s[1]\n" - "str d20, [x14, x11]\n" - "fsub v1.4s, v1.4s, v5.4s\n" - "str d16, [x14, x13]\n" - "fmls v1.4s, v23.4s, v0.s[1]\n" - "fsub v17.4s, v17.4s, v6.4s\n" - "fmls v17.4s, v24.4s, v0.s[1]\n" - "str d1, [x14, x23]\n" - "str d17, [x14, x15]\n" - "add x14, x14, #8\n" - "ldr d2, [x27, x20]\n" - "mov v4.16b, v2.16b\n" - "ldr d17, [x27, x9]\n" - "mov v12.16b, v2.16b\n" - "ldr d18, [x27]\n" - "fmla v4.4s, v18.4s, v0.s[2]\n" - "ldr d3, [x27, x21]\n" - "mov v6.16b, v2.16b\n" - "ldr d5, [x27, x19]\n" - "mov v1.16b, v2.16b\n" - "ldr d18, [x27, %[input_col_stride1]]\n" - "fmls v4.4s, v17.4s, v0.s[3]\n" - "add x27, x27, #8\n" - "fmls v12.4s, v18.4s, v0.s[2]\n" - "sub %w[n_channels], %w[n_channels], #2\n" - "fmla v6.4s, v18.4s, v0.s[2]\n" - "fmls v1.4s, v18.4s, v0.s[1]\n" - "mov v2.16b, v2.16b\n" - "mov v3.16b, v3.16b\n" - "fmls v12.4s, v17.4s, v0.s[2]\n" - "mov v4.16b, v4.16b\n" - "fmls v6.4s, v17.4s, v0.s[2]\n" - "fsub v1.4s, v1.4s, v17.4s\n" - "fmla v1.4s, v5.4s, v0.s[1]\n" - "fmla v2.4s, v18.4s, v0.s[1]\n" - "fadd v12.4s, v12.4s, v5.4s\n" - "fmla v3.4s, v18.4s, v0.s[2]\n" - "fsub v6.4s, v6.4s, v5.4s\n" - "fmla v4.4s, v10.4s, v0.s[2]\n" - "fsub v2.4s, v2.4s, v17.4s\n" - "mov v16.16b, v12.16b\n" - "fmls v2.4s, v5.4s, v0.s[1]\n" - "fmls v3.4s, v5.4s, v0.s[3]\n" - "fmls v4.4s, v14.4s, v0.s[3]\n" - "fmla v16.4s, v9.4s, v0.s[2]\n" - "mov v5.16b, v6.16b\n" - "mov v6.16b, v1.16b\n" - "mov v9.16b, v2.16b\n" - "mov v10.16b, v3.16b\n" - "str d4, [x24]\n" - "fmls v16.4s, v13.4s, v0.s[3]\n" - "fmla v5.4s, v7.4s, v0.s[2]\n" - "fmla v6.4s, v8.4s, v0.s[2]\n" - "fmla v9.4s, v11.4s, v0.s[2]\n" - "fmla v10.4s, v15.4s, v0.s[2]\n" - "str d16, [x24, %[output_col_stride1]]\n" - "fmls v5.4s, v21.4s, v0.s[3]\n" - "fmls v6.4s, v22.4s, v0.s[3]\n" - "fmls v9.4s, v23.4s, v0.s[3]\n" - "fmls v10.4s, v24.4s, v0.s[3]\n" - "str d5, [x24, x11]\n" - "str d6, [x24, x13]\n" - "str d9, [x24, x23]\n" - "str d10, [x24, x15]\n" - "add x24, x24, #8\n" - "3:\n" - "cbz %w[n_channels], 4f\n" - "ldr s8, [%[inptr0], x20]\n" - "mov v14.16b, v8.16b\n" - "ldr s2, [%[inptr0], x9]\n" - "mov v10.16b, v8.16b\n" - "ldr s9, [%[inptr0]]\n" - "fmla v14.4s, v9.4s, v0.s[2]\n" - "ldr s1, [%[inptr0], x21]\n" - "mov v9.16b, v8.16b\n" - "ldr s4, [%[inptr0], x19]\n" - "mov v7.16b, v8.16b\n" - "ldr s12, [%[inptr0], %[input_col_stride1]]\n" - "fmls v14.4s, v2.4s, v0.s[3]\n" - "ldr s5, [x16, x20]\n" - "fmls v10.4s, v12.4s, v0.s[2]\n" - "ldr s20, [x16, x9]\n" - "fmla v9.4s, v12.4s, v0.s[2]\n" - "ldr s3, [x16]\n" - "fmls v7.4s, v12.4s, v0.s[1]\n" - "ldr s6, [x16, x21]\n" - "fmls v10.4s, v2.4s, v0.s[2]\n" - "ldr s16, [x16, x19]\n" - "fmls v9.4s, v2.4s, v0.s[2]\n" - "ldr s22, [x16, %[input_col_stride1]]\n" - "fsub v7.4s, v7.4s, v2.4s\n" - "ldr s17, [x17, x20]\n" - "fadd v10.4s, v10.4s, v4.4s\n" - "ldr s15, [x17, x9]\n" - "fsub v9.4s, v9.4s, v4.4s\n" - "ldr s19, [x17]\n" - "fmla v7.4s, v4.4s, v0.s[1]\n" - "ldr s18, [x17, x21]\n" - "mov v8.16b, v8.16b\n" - "ldr s13, [x17, x19]\n" - "mov v11.16b, v1.16b\n" - "ldr s21, [x17, %[input_col_stride1]]\n" - "fmla v8.4s, v12.4s, v0.s[1]\n" - "add %[inptr0], %[inptr0], #4\n" - "fmla v11.4s, v12.4s, v0.s[2]\n" - "add x16, x16, #4\n" - "mov v1.16b, v5.16b\n" - "add x17, x17, #4\n" - "fsub v8.4s, v8.4s, v2.4s\n" - "mov v2.16b, v5.16b\n" - "fmls v8.4s, v4.4s, v0.s[1]\n" - "fmls v11.4s, v4.4s, v0.s[3]\n" - "fmla v1.4s, v3.4s, v0.s[2]\n" - "fmls v2.4s, v22.4s, v0.s[2]\n" - "mov v3.16b, v5.16b\n" - "mov v4.16b, v5.16b\n" - "mov v5.16b, v5.16b\n" - "mov v6.16b, v6.16b\n" - "fmls v1.4s, v20.4s, v0.s[3]\n" - "fmls v2.4s, v20.4s, v0.s[2]\n" - "fmla v3.4s, v22.4s, v0.s[2]\n" - "fmls v4.4s, v22.4s, v0.s[1]\n" - "fmla v5.4s, v22.4s, v0.s[1]\n" - "fmla v6.4s, v22.4s, v0.s[2]\n" - "fadd v2.4s, v2.4s, v16.4s\n" - "mov v12.16b, v17.16b\n" - "fmls v3.4s, v20.4s, v0.s[2]\n" - "fsub v4.4s, v4.4s, v20.4s\n" - "fmla v4.4s, v16.4s, v0.s[1]\n" - "fsub v5.4s, v5.4s, v20.4s\n" - "fmls v5.4s, v16.4s, v0.s[1]\n" - "fmls v6.4s, v16.4s, v0.s[3]\n" - "fsub v3.4s, v3.4s, v16.4s\n" - "fmla v12.4s, v19.4s, v0.s[2]\n" - "mov v19.16b, v17.16b\n" - "mov v20.16b, v17.16b\n" - "mov v16.16b, v17.16b\n" - "mov v17.16b, v17.16b\n" - "fmls v12.4s, v15.4s, v0.s[3]\n" - "fmls v19.4s, v21.4s, v0.s[2]\n" - "fmla v20.4s, v21.4s, v0.s[2]\n" - "fmls v16.4s, v21.4s, v0.s[1]\n" - "fmla v17.4s, v21.4s, v0.s[1]\n" - "mov v18.16b, v18.16b\n" - "fmls v19.4s, v15.4s, v0.s[2]\n" - "mov v23.16b, v12.16b\n" - "fmls v20.4s, v15.4s, v0.s[2]\n" - "fsub v16.4s, v16.4s, v15.4s\n" - "fmla v16.4s, v13.4s, v0.s[1]\n" - "fsub v17.4s, v17.4s, v15.4s\n" - "fadd v19.4s, v19.4s, v13.4s\n" - "fmls v17.4s, v13.4s, v0.s[1]\n" - "fsub v20.4s, v20.4s, v13.4s\n" - "fmla v18.4s, v21.4s, v0.s[2]\n" - "fmla v23.4s, v14.4s, v0.s[2]\n" - "mov v15.16b, v19.16b\n" - "mov v14.16b, v20.16b\n" - "mov v24.16b, v16.16b\n" - "fmls v18.4s, v13.4s, v0.s[3]\n" - "fmla v15.4s, v10.4s, v0.s[2]\n" - "fmls v23.4s, v1.4s, v0.s[3]\n" - "fmla v14.4s, v9.4s, v0.s[2]\n" - "fmla v24.4s, v7.4s, v0.s[2]\n" - "mov v10.16b, v17.16b\n" - "fmls v15.4s, v2.4s, v0.s[3]\n" - "mov v7.16b, v18.16b\n" - "str s23, [%[outptr0]]\n" - "fmls v14.4s, v3.4s, v0.s[3]\n" - "fmls v24.4s, v4.4s, v0.s[3]\n" - "fmla v10.4s, v8.4s, v0.s[2]\n" - "str s15, [%[outptr0], %[output_col_stride1]]\n" - "fmla v7.4s, v11.4s, v0.s[2]\n" - "str s14, [%[outptr0], x11]\n" - "fmls v10.4s, v5.4s, v0.s[3]\n" - "str s24, [%[outptr0], x13]\n" - "fmls v7.4s, v6.4s, v0.s[3]\n" - "str s10, [%[outptr0], x23]\n" - "str s7, [%[outptr0], x15]\n" - "add %[outptr0], %[outptr0], #4\n" - "mov v26.16b, v12.16b\n" - "mov v25.16b, v19.16b\n" - "ldr s11, [x25, x20]\n" - "mov v10.16b, v11.16b\n" - "ldr s23, [x25, x9]\n" - "mov v9.16b, v11.16b\n" - "ldr s7, [x25]\n" - "fmla v10.4s, v7.4s, v0.s[2]\n" - "ldr s13, [x25, x21]\n" - "mov v7.16b, v11.16b\n" - "ldr s31, [x25, x19]\n" - "mov v8.16b, v11.16b\n" - "ldr s21, [x25, %[input_col_stride1]]\n" - "fmls v10.4s, v23.4s, v0.s[3]\n" - "ldr s30, [x26, x20]\n" - "fmls v9.4s, v21.4s, v0.s[2]\n" - "ldr s29, [x26, x9]\n" - "fmla v7.4s, v21.4s, v0.s[2]\n" - "ldr s22, [x26]\n" - "fmls v8.4s, v21.4s, v0.s[1]\n" - "ldr s24, [x26, x21]\n" - "fmls v9.4s, v23.4s, v0.s[2]\n" - "ldr s27, [x26, x19]\n" - "fmls v7.4s, v23.4s, v0.s[2]\n" - "ldr s28, [x26, %[input_col_stride1]]\n" - "fsub v8.4s, v8.4s, v23.4s\n" - "add x25, x25, #4\n" - "fadd v9.4s, v9.4s, v31.4s\n" - "add x26, x26, #4\n" - "fsub v7.4s, v7.4s, v31.4s\n" - "fmla v8.4s, v31.4s, v0.s[1]\n" - "mov v11.16b, v11.16b\n" - "mov v15.16b, v13.16b\n" - "mov v14.16b, v30.16b\n" - "mov v13.16b, v30.16b\n" - "fmla v11.4s, v21.4s, v0.s[1]\n" - "fmla v15.4s, v21.4s, v0.s[2]\n" - "fmla v14.4s, v22.4s, v0.s[2]\n" - "fmls v13.4s, v28.4s, v0.s[2]\n" - "mov v21.16b, v30.16b\n" - "mov v22.16b, v30.16b\n" - "fsub v11.4s, v11.4s, v23.4s\n" - "fmls v15.4s, v31.4s, v0.s[3]\n" - "fmls v11.4s, v31.4s, v0.s[1]\n" - "fmls v14.4s, v29.4s, v0.s[3]\n" - "fmls v13.4s, v29.4s, v0.s[2]\n" - "fmla v21.4s, v28.4s, v0.s[2]\n" - "fmls v22.4s, v28.4s, v0.s[1]\n" - "mov v23.16b, v30.16b\n" - "mov v24.16b, v24.16b\n" - "fmls v26.4s, v10.4s, v0.s[2]\n" - "fadd v13.4s, v13.4s, v27.4s\n" - "fmls v21.4s, v29.4s, v0.s[2]\n" - "fsub v22.4s, v22.4s, v29.4s\n" - "fmla v23.4s, v28.4s, v0.s[1]\n" - "fmla v22.4s, v27.4s, v0.s[1]\n" - "fmla v24.4s, v28.4s, v0.s[2]\n" - "fsub v21.4s, v21.4s, v27.4s\n" - "fmls v26.4s, v1.4s, v0.s[2]\n" - "fsub v23.4s, v23.4s, v29.4s\n" - "fmls v25.4s, v9.4s, v0.s[2]\n" - "fmls v23.4s, v27.4s, v0.s[1]\n" - "fmls v24.4s, v27.4s, v0.s[3]\n" - "fadd v26.4s, v26.4s, v14.4s\n" - "mov v27.16b, v20.16b\n" - "str s26, [x28]\n" - "fmls v25.4s, v2.4s, v0.s[2]\n" - "fmls v27.4s, v7.4s, v0.s[2]\n" - "mov v31.16b, v16.16b\n" - "mov v30.16b, v17.16b\n" - "mov v29.16b, v18.16b\n" - "fadd v25.4s, v25.4s, v13.4s\n" - "fmls v31.4s, v8.4s, v0.s[2]\n" - "str s25, [x28, %[output_col_stride1]]\n" - "fmls v27.4s, v3.4s, v0.s[2]\n" - "fmls v30.4s, v11.4s, v0.s[2]\n" - "fmls v29.4s, v15.4s, v0.s[2]\n" - "fmls v31.4s, v4.4s, v0.s[2]\n" - "mov v26.16b, v12.16b\n" - "fadd v27.4s, v27.4s, v21.4s\n" - "mov v25.16b, v19.16b\n" - "str s27, [x28, x11]\n" - "fmls v30.4s, v5.4s, v0.s[2]\n" - "fadd v31.4s, v31.4s, v22.4s\n" - "fmls v29.4s, v6.4s, v0.s[2]\n" - "str s31, [x28, x13]\n" - "fmla v26.4s, v10.4s, v0.s[2]\n" - "fadd v30.4s, v30.4s, v23.4s\n" - "fmla v25.4s, v9.4s, v0.s[2]\n" - "str s30, [x28, x23]\n" - "fadd v29.4s, v29.4s, v24.4s\n" - "str s29, [x28, x15]\n" - "fmls v26.4s, v1.4s, v0.s[2]\n" - "fmls v25.4s, v2.4s, v0.s[2]\n" - "add x28, x28, #4\n" - "mov v30.16b, v20.16b\n" - "mov v29.16b, v16.16b\n" - "fsub v26.4s, v26.4s, v14.4s\n" - "mov v28.16b, v17.16b\n" - "str s26, [x22]\n" - "fsub v25.4s, v25.4s, v13.4s\n" - "str s25, [x22, %[output_col_stride1]]\n" - "fmla v30.4s, v7.4s, v0.s[2]\n" - "fmla v29.4s, v8.4s, v0.s[2]\n" - "fmla v28.4s, v11.4s, v0.s[2]\n" - "mov v26.16b, v18.16b\n" - "mov v25.16b, v12.16b\n" - "fmls v30.4s, v3.4s, v0.s[2]\n" - "mov v31.16b, v19.16b\n" - "fmls v29.4s, v4.4s, v0.s[2]\n" - "fmls v28.4s, v5.4s, v0.s[2]\n" - "fmla v26.4s, v15.4s, v0.s[2]\n" - "fmls v25.4s, v10.4s, v0.s[1]\n" - "fsub v30.4s, v30.4s, v21.4s\n" - "fmls v31.4s, v9.4s, v0.s[1]\n" - "str s30, [x22, x11]\n" - "fsub v29.4s, v29.4s, v22.4s\n" - "str s29, [x22, x13]\n" - "fsub v28.4s, v28.4s, v23.4s\n" - "str s28, [x22, x23]\n" - "fmls v26.4s, v6.4s, v0.s[2]\n" - "fsub v25.4s, v25.4s, v1.4s\n" - "fsub v31.4s, v31.4s, v2.4s\n" - "fmla v25.4s, v14.4s, v0.s[1]\n" - "fmla v31.4s, v13.4s, v0.s[1]\n" - "fsub v26.4s, v26.4s, v24.4s\n" - "mov v27.16b, v20.16b\n" - "str s26, [x22, x15]\n" - "mov v26.16b, v16.16b\n" - "str s25, [x12]\n" - "fmls v27.4s, v7.4s, v0.s[1]\n" - "str s31, [x12, %[output_col_stride1]]\n" - "fmls v26.4s, v8.4s, v0.s[1]\n" - "mov v25.16b, v17.16b\n" - "add x22, x22, #4\n" - "fsub v27.4s, v27.4s, v3.4s\n" - "mov v28.16b, v18.16b\n" - "fmla v27.4s, v21.4s, v0.s[1]\n" - "fsub v26.4s, v26.4s, v4.4s\n" - "fmla v26.4s, v22.4s, v0.s[1]\n" - "fmls v25.4s, v11.4s, v0.s[1]\n" - "fmls v28.4s, v15.4s, v0.s[1]\n" - "mov v12.16b, v12.16b\n" - "str s27, [x12, x11]\n" - "mov v19.16b, v19.16b\n" - "str s26, [x12, x13]\n" - "fsub v25.4s, v25.4s, v5.4s\n" - "fmla v25.4s, v23.4s, v0.s[1]\n" - "fsub v28.4s, v28.4s, v6.4s\n" - "fmla v28.4s, v24.4s, v0.s[1]\n" - "fmla v12.4s, v10.4s, v0.s[1]\n" - "fmla v19.4s, v9.4s, v0.s[1]\n" - "mov v20.16b, v20.16b\n" - "str s25, [x12, x23]\n" - "mov v16.16b, v16.16b\n" - "str s28, [x12, x15]\n" - "fsub v12.4s, v12.4s, v1.4s\n" - "fmls v12.4s, v14.4s, v0.s[1]\n" - "add x12, x12, #4\n" - "fsub v19.4s, v19.4s, v2.4s\n" - "fmla v20.4s, v7.4s, v0.s[1]\n" - "fmls v19.4s, v13.4s, v0.s[1]\n" - "fmla v16.4s, v8.4s, v0.s[1]\n" - "str s12, [x14]\n" - "mov v1.16b, v17.16b\n" - "fsub v20.4s, v20.4s, v3.4s\n" - "mov v17.16b, v18.16b\n" - "str s19, [x14, %[output_col_stride1]]\n" - "fmls v20.4s, v21.4s, v0.s[1]\n" - "fsub v16.4s, v16.4s, v4.4s\n" - "fmla v1.4s, v11.4s, v0.s[1]\n" - "fmls v16.4s, v22.4s, v0.s[1]\n" - "fmla v17.4s, v15.4s, v0.s[1]\n" - "str s20, [x14, x11]\n" - "fsub v1.4s, v1.4s, v5.4s\n" - "str s16, [x14, x13]\n" - "fmls v1.4s, v23.4s, v0.s[1]\n" - "fsub v17.4s, v17.4s, v6.4s\n" - "fmls v17.4s, v24.4s, v0.s[1]\n" - "str s1, [x14, x23]\n" - "str s17, [x14, x15]\n" - "add x14, x14, #4\n" - "ldr s2, [x27, x20]\n" - "mov v4.16b, v2.16b\n" - "ldr s17, [x27, x9]\n" - "mov v12.16b, v2.16b\n" - "ldr s18, [x27]\n" - "fmla v4.4s, v18.4s, v0.s[2]\n" - "ldr s3, [x27, x21]\n" - "mov v6.16b, v2.16b\n" - "ldr s5, [x27, x19]\n" - "mov v1.16b, v2.16b\n" - "ldr s18, [x27, %[input_col_stride1]]\n" - "fmls v4.4s, v17.4s, v0.s[3]\n" - "add x27, x27, #4\n" - "fmls v12.4s, v18.4s, v0.s[2]\n" - "fmla v6.4s, v18.4s, v0.s[2]\n" - "fmls v1.4s, v18.4s, v0.s[1]\n" - "mov v2.16b, v2.16b\n" - "mov v3.16b, v3.16b\n" - "mov v4.16b, v4.16b\n" - "fmls v12.4s, v17.4s, v0.s[2]\n" - "fmls v6.4s, v17.4s, v0.s[2]\n" - "fsub v1.4s, v1.4s, v17.4s\n" - "fmla v2.4s, v18.4s, v0.s[1]\n" - "fmla v1.4s, v5.4s, v0.s[1]\n" - "fmla v3.4s, v18.4s, v0.s[2]\n" - "fadd v12.4s, v12.4s, v5.4s\n" - "fsub v6.4s, v6.4s, v5.4s\n" - "fsub v2.4s, v2.4s, v17.4s\n" - "fmla v4.4s, v10.4s, v0.s[2]\n" - "fmls v2.4s, v5.4s, v0.s[1]\n" - "fmls v3.4s, v5.4s, v0.s[3]\n" - "mov v16.16b, v12.16b\n" - "mov v5.16b, v6.16b\n" - "fmls v4.4s, v14.4s, v0.s[3]\n" - "mov v6.16b, v1.16b\n" - "fmla v16.4s, v9.4s, v0.s[2]\n" - "fmla v5.4s, v7.4s, v0.s[2]\n" - "fmla v6.4s, v8.4s, v0.s[2]\n" - "mov v9.16b, v2.16b\n" - "str s4, [x24]\n" - "mov v10.16b, v3.16b\n" - "fmls v16.4s, v13.4s, v0.s[3]\n" - "fmls v5.4s, v21.4s, v0.s[3]\n" - "fmls v6.4s, v22.4s, v0.s[3]\n" - "fmla v9.4s, v11.4s, v0.s[2]\n" - "fmla v10.4s, v15.4s, v0.s[2]\n" - "str s16, [x24, %[output_col_stride1]]\n" - "str s5, [x24, x11]\n" - "fmls v9.4s, v23.4s, v0.s[3]\n" - "str s6, [x24, x13]\n" - "fmls v10.4s, v24.4s, v0.s[3]\n" - "str s9, [x24, x23]\n" - "str s10, [x24, x15]\n" - "add x24, x24, #4\n" - "4:\n" - : [outptr0] "+r" (matrix_base), - [n_channels] "+r" (n_channels), - [inptr0] "+r" (input_base) - : [pcoeffs] "r" (pcoeffs), - [output_row_stride] "r" (6 * matrix_stride * sizeof(float)), - [output_col_stride1] "r" (matrix_stride * sizeof(float)), - [input_row_stride] "r" (input_row_stride * sizeof(float)), - [input_col_stride1] "r" (input_col_stride * sizeof(float)) - : "cc", "v0", "v1", "v10", "v11", "v12", "v13", "v14", "v15", "v16", "v17", - "v18", "v19", "v2", "v20", "v21", "v22", "v23", "v24", "v25", "v26", - "v27", "v28", "v29", "v3", "v30", "v31", "v4", "v5", "v6", "v7", "v8", - "v9", "x11", "x12", "x13", "x14", "x15", "x16", "x17", "x9", "x19", - "x20", "x21", "x22", "x23", "x24", "x25", "x26", "x27", "x28", "memory" - ); -} - -#else // __arm__ not __aarch64__ - -template <> -void InputTransform<6, 6, float, float, WinogradRoots::Integers>::transform_tile( - const int n_channels, - const float* const input_base, - const int input_row_stride, - const int input_col_stride, - float* outptr, - const int matrix_stride -) -{ - constexpr int inner_tile_rows = 6; - constexpr int inner_tile_cols = 6; - - // Get pointers into the input tile - const float *x_ptrs[inner_tile_rows][inner_tile_cols]; - for (int i = 0, xi = 0; i < inner_tile_rows; i++, xi++) - { - // Get a pointer into the row - const float* const row_ptr = input_base + xi*input_row_stride; - - for (int j = 0, xj = 0; j < inner_tile_cols; j++, xj++) - { - x_ptrs[i][j] = row_ptr + xj*input_col_stride; - } - } - - // Matrices used/computed in this kernel. - float x[inner_tile_rows][inner_tile_cols]; - float XTx[inner_tile_rows][inner_tile_cols]; - float U[inner_tile_rows][inner_tile_cols]; - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = XTx[i][j] = 0.0f; - } - } - - // Perform the Winograd input transformation for each channel in the input - // tensor. - int channels_remaining = n_channels; - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used/computed in this kernel - float32x2_t x[inner_tile_rows][inner_tile_cols]; - float32x2_t XTx[inner_tile_rows][inner_tile_cols]; - float32x2_t U[inner_tile_rows][inner_tile_cols]; - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vdup_n_f32(0.0f); - XTx[i][j] = vdup_n_f32(0.0f); - } - } - - // Read a 6x6 tile in the Winograd domain - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = vld1_f32(x_ptrs[i][j]); - x_ptrs[i][j] += 2; - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - // XTx[0][j] = 4*x[0][j] + -5*x[2][j] + 1*x[4][j]; - XTx[0][j] = vmls_n_f32(vmla_n_f32(x[4][j], x[0][j], 4.0f), x[2][j], 5.0f); - - // XTx[1][j] = -4*x[1][j] + -4*x[2][j] + 1*x[3][j] + 1*x[4][j]; - XTx[1][j] = vmls_n_f32(vadd_f32(x[3][j], x[4][j]), vadd_f32(x[1][j], x[2][j]), 4.0f); - - // XTx[2][j] = 4*x[1][j] + -4*x[2][j] + -1*x[3][j] + 1*x[4][j]; - XTx[2][j] = vmla_n_f32(vsub_f32(x[4][j], x[3][j]), vsub_f32(x[1][j], x[2][j]), 4.0f); - - // XTx[3][j] = -2*x[1][j] + -1*x[2][j] + 2*x[3][j] + 1*x[4][j]; - XTx[3][j] = vmla_n_f32(vsub_f32(x[4][j], x[2][j]), vsub_f32(x[3][j], x[1][j]), 2.0f); - - // XTx[4][j] = 2*x[1][j] + -1*x[2][j] + -2*x[3][j] + 1*x[4][j]; - XTx[4][j] = vmla_n_f32(vsub_f32(x[4][j], x[2][j]), vsub_f32(x[1][j], x[3][j]), 2.0f); - - // XTx[5][j] = 4*x[1][j] + -5*x[3][j] + 1*x[5][j]; - XTx[5][j] = vmls_n_f32(vmla_n_f32(x[5][j], x[1][j], 4.0f), x[3][j], 5.0f); - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - // U[i][0] = 4*XTx[i][0] + -5*XTx[i][2] + 1*XTx[i][4]; - U[i][0] = vmls_n_f32(vmla_n_f32(XTx[i][4], XTx[i][0], 4.0f), XTx[i][2], 5.0f); - - // U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] + 1*XTx[i][3] + 1*XTx[i][4]; - U[i][1] = vmls_n_f32(vadd_f32(XTx[i][3], XTx[i][4]), vadd_f32(XTx[i][1], XTx[i][2]), 4.0f); - - // U[i][2] = 4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] + 1*XTx[i][4]; - U[i][2] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][3]), vsub_f32(XTx[i][1], XTx[i][2]), 4.0f); - - // U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] + 2*XTx[i][3] + 1*XTx[i][4]; - U[i][3] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][2]), vsub_f32(XTx[i][3], XTx[i][1]), 2.0f); - - // U[i][4] = 2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] + 1*XTx[i][4]; - U[i][4] = vmla_n_f32(vsub_f32(XTx[i][4], XTx[i][2]), vsub_f32(XTx[i][1], XTx[i][3]), 2.0f); - - // U[i][5] = 4*XTx[i][1] + -5*XTx[i][3] + 1*XTx[i][5]; - U[i][5] = vmls_n_f32(vmla_n_f32(XTx[i][5], XTx[i][1], 4.0f), XTx[i][3], 5.0f); - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - vst1_f32(outptr + m*matrix_stride, U[i][j]); - } - } - outptr += 2; - } - for (; channels_remaining; channels_remaining--) - { - // Load x - for (int i = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++) - { - x[i][j] = *(x_ptrs[i][j]++); - } - } - - // Compute XT . x - for (int j = 0; j < inner_tile_cols; j++) - { - XTx[0][j] = 4*x[0][j] + -5*x[2][j] + 1*x[4][j]; - XTx[1][j] = -4*x[1][j] + -4*x[2][j] + 1*x[3][j] + 1*x[4][j]; - XTx[2][j] = 4*x[1][j] + -4*x[2][j] + -1*x[3][j] + 1*x[4][j]; - XTx[3][j] = -2*x[1][j] + -1*x[2][j] + 2*x[3][j] + 1*x[4][j]; - XTx[4][j] = 2*x[1][j] + -1*x[2][j] + -2*x[3][j] + 1*x[4][j]; - XTx[5][j] = 4*x[1][j] + -5*x[3][j] + 1*x[5][j]; - } - - // Compute U = XT . x . X - for (int i = 0; i < inner_tile_rows; i++) - { - U[i][0] = 4*XTx[i][0] + -5*XTx[i][2] + 1*XTx[i][4]; - U[i][1] = -4*XTx[i][1] + -4*XTx[i][2] + 1*XTx[i][3] + 1*XTx[i][4]; - U[i][2] = 4*XTx[i][1] + -4*XTx[i][2] + -1*XTx[i][3] + 1*XTx[i][4]; - U[i][3] = -2*XTx[i][1] + -1*XTx[i][2] + 2*XTx[i][3] + 1*XTx[i][4]; - U[i][4] = 2*XTx[i][1] + -1*XTx[i][2] + -2*XTx[i][3] + 1*XTx[i][4]; - U[i][5] = 4*XTx[i][1] + -5*XTx[i][3] + 1*XTx[i][5]; - } - - // Store the transformed matrix - for (int i = 0, m = 0; i < inner_tile_rows; i++) - { - for (int j = 0; j < inner_tile_cols; j++, m++) - { - *(outptr + m*matrix_stride) = U[i][j]; - } - } - outptr++; - } -} - -#endif - -template class InputTransform<6, 6, float, float, WinogradRoots::Integers>; - -} // namespace winograd diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/kernel.hpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/kernel.hpp deleted file mode 100644 index e45f1863e3..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/kernel.hpp +++ /dev/null @@ -1,78 +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. - */ - -#pragma once -#include "winograd.hpp" -using namespace winograd; - -#define MEMBERFN(RTYPE) template <\ - int KernelRows, int KernelCols, int InnerTileRows, int InnerTileCols, typename TIn, typename TOut, WinogradRoots Roots\ -> RTYPE WeightTransform<KernelRows, KernelCols, InnerTileRows, InnerTileCols, TIn, TOut, Roots> - -MEMBERFN()::WeightTransform( - const int n_output_channels, - const int n_input_channels -) : _n_output_channels(n_output_channels), _n_input_channels(n_input_channels), - _matrices(nullptr), _matrix_stride(0), _matrix_row_stride(0), _weights(nullptr) -{ - -} - -MEMBERFN(void)::set_weight_tensor(const void * const weights) -{ - _weights = static_cast<const TIn *>(weights); -} - -MEMBERFN(void)::set_output_matrices(void * const mptr, const int ldmatrix, const int ldrow) -{ - _matrices = static_cast<TOut *>(mptr); - _matrix_stride = ldmatrix; - _matrix_row_stride = ldrow; -} - -MEMBERFN(size_t)::get_working_space_size(unsigned int) const -{ - return 0; -} - -MEMBERFN(void)::set_working_space(void *) -{ -} - -MEMBERFN(unsigned int)::get_window(void) const -{ - // TODO When the weights transform supports multithreading, return the number - // of output channels. For now we return 1 to indicate that the weights must - // be transformed as a single block. - // return n_output_channels; - return 1; -} - -MEMBERFN(void)::run(const unsigned int, const unsigned int, unsigned int) -{ - execute( - _n_output_channels, _n_input_channels, _weights, - _matrices, _matrix_stride, _matrix_row_stride - ); -} diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output.hpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output.hpp deleted file mode 100644 index ed88098938..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output.hpp +++ /dev/null @@ -1,252 +0,0 @@ -/* - * 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. - */ - -#pragma once - -#include <algorithm> -#include "winograd.hpp" -#include "padding.hpp" -#include "utils.hpp" - -#define MEMBERFN(RTYPE) template<\ - int KernelRows, int KernelCols, int InnerTileRows, int InnerTileCols,\ - typename TIn, typename TOut, WinogradRoots Roots\ -> RTYPE OutputTransform<KernelRows, KernelCols, InnerTileRows, InnerTileCols, TIn, TOut, Roots> - -#define Nx1MEMBERFN(RTYPE) template<\ - int KernelRows, int InnerTileRows, typename TIn, typename TOut, WinogradRoots Roots\ -> RTYPE OutputTransform<KernelRows, 1, InnerTileRows, 1, TIn, TOut, Roots> - -namespace winograd -{ - -MEMBERFN() -::OutputTransform(const int n_batches, const int n_rows, const int n_cols, - const int n_channels, const arm_gemm::Activation &activation) - : _n_batches(n_batches), _n_rows(n_rows), _n_cols(n_cols), - _n_channels(n_channels), - _output_min((activation.type == arm_gemm::Activation::Type::ReLU || - activation.type == arm_gemm::Activation::Type::BoundedReLU) - ? static_cast<TOut>(0.0f) : TypeBounds<TOut>::lower()), - _output_max((activation.type == arm_gemm::Activation::Type::BoundedReLU) - ? static_cast<TOut>(activation.param1) : TypeBounds<TOut>::upper()), - _matrix_base(nullptr), _biases(nullptr), _matrix_stride(0), - _matrix_row_stride(0), _matrix_batch_stride(0), _outptr(nullptr), - _tiles_M(iceildiv(n_rows, output_tile_rows)), - _tiles_N(iceildiv(n_cols, output_tile_cols)), _out_col_stride(0), - _out_row_stride(0), _out_batch_stride(0), - _working_space_col_stride(n_channels), - _working_space_row_stride(output_tile_cols * _working_space_col_stride), - _working_space(nullptr) {} - -MEMBERFN(void)::set_input_matrices(const void * const mptr, const int ldmatrix, const int ldrow) -{ - _matrix_base = static_cast<const TIn *>(mptr); - _matrix_stride = ldmatrix; - _matrix_row_stride = ldrow; - _matrix_batch_stride = _tiles_M * _tiles_N * ldrow; -} - -MEMBERFN(void)::set_bias(const void * const bias) -{ - _biases = static_cast<const TOut *>(bias); -} - -MEMBERFN(void)::set_output_tensor(void * const outptr) -{ - set_output_tensor(outptr, _n_channels); -} - -MEMBERFN(void)::set_output_tensor(void * const outptr, const int ldcol) -{ - set_output_tensor(outptr, _n_cols * ldcol, ldcol); -} - -MEMBERFN(void)::set_output_tensor(void * const outptr, const int ldrow, const int ldcol) -{ - set_output_tensor(outptr, _n_rows * ldrow, ldrow, ldcol); -} - -MEMBERFN(void)::set_output_tensor(void * const outptr, const int ldbatch, const int ldrow, const int ldcol) -{ - _outptr = static_cast<TOut *>(outptr); - _out_batch_stride = ldbatch; - _out_row_stride = ldrow; - _out_col_stride = ldcol; -} - -Nx1MEMBERFN()::OutputTransform( - const int n_batches, - const int n_rows, - const int n_cols, - const int n_channels, - const arm_gemm::Activation &activation -) : OutputTransform<1, KernelRows, 1, InnerTileRows, TIn, TOut, Roots>::OutputTransform( - n_batches, n_cols, n_rows, n_channels, activation /* Transpose rows and columns */ - ) -{ -} - -Nx1MEMBERFN(void)::set_output_tensor(void * const outptr) -{ - set_output_tensor(outptr, this->_n_channels); -} - -Nx1MEMBERFN(void)::set_output_tensor(void * const outptr, const int ldcol) -{ - set_output_tensor(outptr, this->_n_cols * ldcol, ldcol); -} - -Nx1MEMBERFN(void)::set_output_tensor(void * const outptr, const int ldrow, const int ldcol) -{ - set_output_tensor(outptr, this->_n_rows * ldrow, ldrow, ldcol); -} - -Nx1MEMBERFN(void)::set_output_tensor(void * const outptr, const int ldbatch, const int ldrow, const int ldcol) -{ - // Transpose rows and columns - Base::set_output_tensor(outptr, ldbatch, ldcol, ldrow); -} - -MEMBERFN(size_t)::get_working_space_size(const unsigned int nthreads) const -{ - return sizeof(TOut) * output_tile_rows * _working_space_row_stride * nthreads; -} - -MEMBERFN(void)::set_working_space(void * const buffer) -{ - _working_space = static_cast<TOut *>(buffer); -} - -MEMBERFN(unsigned int)::get_window(void) const -{ - return iceildiv(_n_channels, WINDOW_BLOCK); -} - -MEMBERFN(void)::run( - const unsigned int start, - const unsigned int stop, - const unsigned int threadid -) -{ - // Determine the channels on which to work - if (start >= get_window()) - { - return; // No work to do beyond the end of the window - } - const unsigned int start_channel = start * WINDOW_BLOCK; - const unsigned int stop_channel = std::min<unsigned int>(_n_channels, stop * WINDOW_BLOCK); - const unsigned int n_channels = stop_channel - start_channel; - - const auto matrix_tile_col_stride = _matrix_row_stride; - const auto matrix_tile_row_stride = _tiles_N * matrix_tile_col_stride; - - const TOut* const bptr = (_biases == nullptr) ? nullptr : _biases + start_channel; - - // Loop over batches - for (int batch = 0; batch < _n_batches; batch++) - { - const TIn* const matrix_batch = _matrix_base + start_channel + batch * _matrix_batch_stride; - TOut* const outptr_batch = _outptr + start_channel + batch * _out_batch_stride; - - for (int tile_i = 0; tile_i < _tiles_M; tile_i++) - { - // Compute properties of the row of output tiles - const int row_pad_bottom = std::max(0, (tile_i + 1)*output_tile_rows - _n_rows); - const TIn* const matrix_tile_row = matrix_batch + tile_i * matrix_tile_row_stride; - TOut* const outptr_row = outptr_batch + tile_i * output_tile_rows * _out_row_stride; - - for (int tile_j = 0; tile_j < _tiles_N; tile_j++) - { - // Compute property of this specific tile - const int tile_pad_right = std::max(0, (tile_j + 1)*output_tile_cols - _n_cols); - const TIn* const matrix_tile = matrix_tile_row + tile_j * matrix_tile_col_stride; - TOut* const outptr_tile = outptr_row + tile_j * output_tile_cols * _out_col_stride; - - // Perform the transformation - if (row_pad_bottom || tile_pad_right) - { - transform_cropped_tile( - threadid, n_channels, outptr_tile, matrix_tile, bptr, - row_pad_bottom, tile_pad_right - ); - } - else - { - transform_uncropped_tile( - threadid, n_channels, outptr_tile, matrix_tile, bptr - ); - } - } - } - } -} - -MEMBERFN(void)::transform_uncropped_tile( - const unsigned int /* threadid unused */, - const int n_channels, - TOut * const outptr, - const TIn * const inptr, - const TOut * const biases -) -{ - transform_tile( - n_channels, inptr, _matrix_stride, biases, - outptr, _out_row_stride, _out_col_stride, - _output_min, _output_max - ); -} - -MEMBERFN(void)::transform_cropped_tile( - const unsigned int threadid, - const int n_channels, - TOut * const outptr, - const TIn * const inptr, - const TOut * const biases, - const int pad_bottom, - const int pad_right -) -{ - // Transform into working space and then copy the relevant section out. - TOut *wsptr = static_cast<TOut *>(get_working_space(threadid)); - transform_tile( - n_channels, inptr, _matrix_stride, biases, - wsptr, _working_space_row_stride, _working_space_col_stride, - _output_min, _output_max - ); - - padding::crop_and_copy_tile( - output_tile_rows, output_tile_cols, n_channels, - wsptr, _working_space_row_stride, _working_space_col_stride, - outptr, _out_row_stride, _out_col_stride, - 0u, 0u, pad_bottom, pad_right - ); -} - -MEMBERFN(void *)::get_working_space(const unsigned int threadid) const -{ - return _working_space + output_tile_rows * _working_space_row_stride * threadid; -} - -} // namespace winograd diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_2_7_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_2_7_fp32_fp32_integers.cpp deleted file mode 100644 index f231bdd67e..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_2_7_fp32_fp32_integers.cpp +++ /dev/null @@ -1,143 +0,0 @@ -/* - * 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 "arm.hpp" -#include "output.hpp" - -namespace winograd -{ - -template <> -void OutputTransform<1, 7, 1, 8, float, float, WinogradRoots::Integers>::transform_tile( - const int n_channels, - const float* inptr, - const int matrix_stride, - const float* bptr, - float* const output, - const int, // No need to stride across rows - const int output_col_stride, - const float output_min, - const float output_max -) -{ - // Construct a map to the output cells - float *outptrs[output_tile_cols]; - for (int j = 0; j < output_tile_cols; j++) - { - outptrs[j] = output + j*output_col_stride; - } - - // For each channel of the output - int channels_remaining = n_channels; -#ifdef __arm_any__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed during this transform - float32x4_t F[inner_tile_cols], f[output_tile_cols], b = vdupq_n_f32(0.0f); - - // Read a 1x8 tile in the Winograd domain - for (int j = 0; j < inner_tile_cols; j++) - { - F[j] = vld1q_f32(inptr + j*matrix_stride); - } - inptr += 4; - - f[0] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[6], 1), F[5], 1), F[4], 1), F[3], 1), F[2], 1), F[1], 1), F[0], 1); - f[1] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[7], 1), F[2], 1), F[6], 3), F[4], 2), F[3], -2), F[5], -3), F[1], -1); - - // Write out the output tile - if (bptr != 0) - { - b = vld1q_f32(bptr); - bptr += 4; - } - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = vminq_f32(vmaxq_f32(f[j] + b, vdupq_n_f32(output_min)), - vdupq_n_f32(output_max)); - vst1q_f32(outptrs[j], y); - outptrs[j] += 4; - } - } - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used and computed during this transform - float32x2_t F[inner_tile_cols], f[output_tile_cols], b = vdup_n_f32(0.0f); - - // Read a 1x8 tile in the Winograd domain - for (int j = 0; j < inner_tile_cols; j++) - { - F[j] = vld1_f32(inptr + j*matrix_stride); - } - inptr += 2; - - f[0] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[6], 1), F[5], 1), F[4], 1), F[3], 1), F[2], 1), F[1], 1), F[0], 1); - f[1] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[7], 1), F[2], 1), F[6], 3), F[4], 2), F[3], -2), F[5], -3), F[1], -1); - - // Write out the output tile - if (bptr != 0) - { - b = vld1_f32(bptr); - bptr += 2; - } - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = vmin_f32(vmax_f32(f[j] + b, vdup_n_f32(output_min)), - vdup_n_f32(output_max)); - vst1_f32(outptrs[j], y); - outptrs[j] += 2; - } - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed during this transform - float F[inner_tile_cols], f[output_tile_cols], b = 0.0f; - - // Read a 1x8 tile in the Winograd domain - for (int j = 0; j < inner_tile_cols; j++) - { - F[j] = *(inptr + j*matrix_stride); - } - inptr++; - - f[0] = F[0]*1 + F[1]*1 + F[2]*1 + F[3]*1 + F[4]*1 + F[5]*1 + F[6]*1; - f[1] = F[1]*-1 + F[5]*-3 + F[3]*-2 + F[4]*2 + F[6]*3 + F[2]*1 + F[7]*1; - - // Write out the output tile - if (bptr != 0) - { - b = *(bptr++); - } - for (int j = 0; j < output_tile_cols; j++) - { - *(outptrs[j]++) = std::max(std::min(f[j] + b, output_max), output_min); - } - } -} - -template class OutputTransform<1, 7, 1, 8, float, float, WinogradRoots::Integers>; -template class OutputTransform<7, 1, 8, 1, float, float, WinogradRoots::Integers>; - -} // namespace winograd diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_2x2_3x3_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_2x2_3x3_fp32_fp32_integers.cpp deleted file mode 100644 index 5136bc15c4..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_2x2_3x3_fp32_fp32_integers.cpp +++ /dev/null @@ -1,231 +0,0 @@ -/* - * 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 "arm.hpp" -#include "output.hpp" - -namespace winograd -{ - -template <> -void OutputTransform<3, 3, 4, 4, float, float, WinogradRoots::Integers>::transform_tile( - const int n_channels, - const float* inptr, - const int matrix_stride, - const float* bptr, - float* const output, - const int output_row_stride, - const int output_col_stride, - const float output_min, - const float output_max -) -{ - // Construct a map to the output cells - float *outptrs[output_tile_rows][output_tile_cols]; - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - outptrs[i][j] = output + i*output_row_stride + j*output_col_stride; - } - } - - // For each channel of the output - int channels_remaining = n_channels; -#ifdef __aarch64__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed during this transform - float32x4_t F[4][4], FZ[4][2], f[2][2], b; - - // Read a 4x4 tile in the Winograd domain - for (int i = 0, m = 0; i < 4; i++) - { - for (int j = 0; j < 4; j++, m++) - { - F[i][j] = vld1q_f32(inptr + m*matrix_stride); - } - } - inptr += 4; - - // Compute the matrix F Z - for (int i = 0; i < 4; i++) - { - // FZ[i][0] = F[i][0] + F[i][1] + F[i][2]; - FZ[i][0] = vaddq_f32(vaddq_f32(F[i][0], F[i][1]), F[i][2]); - - // FZ[i][1] = F[i][1] - F[i][2] - F[i][3]; - FZ[i][1] = vsubq_f32(vsubq_f32(F[i][1], F[i][2]), F[i][3]); - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 2; j++) - { - // f[0][j] = FZ[0][j] + FZ[1][j] + FZ[2][j]; - f[0][j] = vaddq_f32(vaddq_f32(FZ[0][j], FZ[1][j]), FZ[2][j]); - - // f[1][j] = FZ[1][j] - FZ[2][j] - FZ[3][j]; - f[1][j] = vsubq_f32(vsubq_f32(FZ[1][j], FZ[2][j]), FZ[3][j]); - } - - // Load the bias vector - if (bptr != nullptr) - { - b = vld1q_f32(bptr); - bptr += 4; - } - else - { - b = vdupq_n_f32(0.0f); - } - - // Write out the output tile - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = - vmaxq_f32(vminq_f32(vaddq_f32(f[i][j], b), vdupq_n_f32(output_max)), - vdupq_n_f32(output_min)); - vst1q_f32(outptrs[i][j], y); - outptrs[i][j] += 4; - } - } - } -#endif // __aarch64__ -#ifdef __arm_any__ - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used and computed during this transform - float32x2_t F[4][4], FZ[4][2], f[2][2], b; - - // Read a 4x4 tile in the Winograd domain - for (int i = 0, m = 0; i < 4; i++) - { - for (int j = 0; j < 4; j++, m++) - { - F[i][j] = vld1_f32(inptr + m*matrix_stride); - } - } - inptr += 2; - - // Compute the matrix F Z - for (int i = 0; i < 4; i++) - { - // FZ[i][0] = F[i][0] + F[i][1] + F[i][2]; - FZ[i][0] = vadd_f32(vadd_f32(F[i][0], F[i][1]), F[i][2]); - - // FZ[i][1] = F[i][1] - F[i][2] - F[i][3]; - FZ[i][1] = vsub_f32(vsub_f32(F[i][1], F[i][2]), F[i][3]); - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 2; j++) - { - // f[0][j] = FZ[0][j] + FZ[1][j] + FZ[2][j]; - f[0][j] = vadd_f32(vadd_f32(FZ[0][j], FZ[1][j]), FZ[2][j]); - - // f[1][j] = FZ[1][j] - FZ[2][j] - FZ[3][j]; - f[1][j] = vsub_f32(vsub_f32(FZ[1][j], FZ[2][j]), FZ[3][j]); - } - - // Load the bias vector - if (bptr != nullptr) - { - b = vld1_f32(bptr); - bptr += 2; - } - else - { - b = vdup_n_f32(0.0f); - } - - // Write out the output tile - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = - vmax_f32(vmin_f32(vadd_f32(f[i][j], b), vdup_n_f32(output_max)), - vdup_n_f32(output_min)); - vst1_f32(outptrs[i][j], y); - outptrs[i][j] += 2; - } - } - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed during this transform - float F[4][4], FZ[4][2], f[2][2], b; - - // Read a 4x4 tile in the Winograd domain - for (int i = 0, m = 0; i < 4; i++) - { - for (int j = 0; j < 4; j++, m++) - { - F[i][j] = *(inptr + m*matrix_stride); - } - } - inptr++; - - // Compute the matrix F Z - for (int i = 0; i < 4; i++) - { - FZ[i][0] = F[i][0] + F[i][1] + F[i][2]; - FZ[i][1] = F[i][1] - F[i][2] - F[i][3]; - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 2; j++) - { - f[0][j] = FZ[0][j] + FZ[1][j] + FZ[2][j]; - f[1][j] = FZ[1][j] - FZ[2][j] - FZ[3][j]; - } - - // Load the bias - if (bptr != nullptr) - { - b = *(bptr++); - } - else - { - b = 0.0f; - } - - // Write out the output tile - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = std::max(std::min(f[i][j] + b, output_max), output_min); - *(outptrs[i][j]++) = y; - } - } - } -} - -template class OutputTransform<3, 3, 4, 4, float, float, WinogradRoots::Integers>; - -} // namespace diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_2x2_5x5_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_2x2_5x5_fp32_fp32_integers.cpp deleted file mode 100644 index 0f911f14a3..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_2x2_5x5_fp32_fp32_integers.cpp +++ /dev/null @@ -1,225 +0,0 @@ -/* - * 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 "output.hpp" -#include "arm.hpp" - -namespace winograd -{ - -template <> -void OutputTransform<5, 5, 6, 6, float, float, WinogradRoots::Integers>::transform_tile( - const int n_channels, - const float* inptr, - const int matrix_stride, - const float* bptr, - float* const output, - const int output_row_stride, - const int output_col_stride, - const float output_min, - const float output_max -) -{ - // Construct a map to the output cells - float *outptrs[output_tile_rows][output_tile_cols]; - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - outptrs[i][j] = output + i*output_row_stride + j*output_col_stride; - } - } - - // For each channel of the output - int channels_remaining = n_channels; -#ifdef __aarch64__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed during this transform - float32x4_t F[6][6], FZ[6][2], f[2][2], b; - - // Read a 6x6 tile in the Winograd domain - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - F[i][j] = vld1q_f32(inptr + m*matrix_stride); - } - } - inptr += 4; - - // Compute the matrix F Z - for (int i = 0; i < 6; i++) - { - // FZ[i][0] = 1*F[i][0] + 1*F[i][1] + 1*F[i][2] + 1*F[i][3] + 1*F[i][4]; - FZ[i][0] = vaddq_f32(vaddq_f32(vaddq_f32(F[i][0], F[i][1]), vaddq_f32(F[i][2], F[i][3])), F[i][4]); - - // FZ[i][1] = 1*F[i][1] + -1*F[i][2] + 2*F[i][3] + -2*F[i][4] + 1*F[i][5]; - FZ[i][1] = vaddq_f32(vmlaq_n_f32(vsubq_f32(F[i][1], F[i][2]), vsubq_f32(F[i][3], F[i][4]), 2.0f), F[i][5]); - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 2; j++) - { - // f[0][j] = 1*FZ[0][j] + 1*FZ[1][j] + 1*FZ[2][j] + 1*FZ[3][j] + 1*FZ[4][j]; - f[0][j] = vaddq_f32(vaddq_f32(vaddq_f32(FZ[0][j], FZ[1][j]), vaddq_f32(FZ[2][j], FZ[3][j])), FZ[4][j]); - - // f[1][j] = 1*FZ[1][j] + -1*FZ[2][j] + 2*FZ[3][j] + -2*FZ[4][j] + 1*FZ[5][j]; - f[1][j] = vaddq_f32(vmlaq_n_f32(vsubq_f32(FZ[1][j], FZ[2][j]), vsubq_f32(FZ[3][j], FZ[4][j]), 2.0f), FZ[5][j]); - } - - // Write out the output tile - if (bptr != nullptr) - { - b = vld1q_f32(bptr); - bptr += 4; - } - else - { - b = vdupq_n_f32(0.0f); - } - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = - vmaxq_f32(vminq_f32(vaddq_f32(f[i][j], b), vdupq_n_f32(output_max)), - vdupq_n_f32(output_min)); - vst1q_f32(outptrs[i][j], y); - outptrs[i][j] += 4; - } - } - } -#endif // __aarch64__ -#ifdef __arm_any__ - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used and computed during this transform - float32x2_t F[6][6], FZ[6][2], f[2][2], b; - - // Read a 6x6 tile in the Winograd domain - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - F[i][j] = vld1_f32(inptr + m*matrix_stride); - } - } - inptr += 2; - - // Compute the matrix F Z - for (int i = 0; i < 6; i++) - { - // FZ[i][0] = 1*F[i][0] + 1*F[i][1] + 1*F[i][2] + 1*F[i][3] + 1*F[i][4]; - FZ[i][0] = vadd_f32(vadd_f32(vadd_f32(F[i][0], F[i][1]), vadd_f32(F[i][2], F[i][3])), F[i][4]); - - // FZ[i][1] = 1*F[i][1] + -1*F[i][2] + 2*F[i][3] + -2*F[i][4] + 1*F[i][5]; - FZ[i][1] = vadd_f32(vmla_n_f32(vsub_f32(F[i][1], F[i][2]), vsub_f32(F[i][3], F[i][4]), 2.0f), F[i][5]); - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 2; j++) - { - // f[0][j] = 1*FZ[0][j] + 1*FZ[1][j] + 1*FZ[2][j] + 1*FZ[3][j] + 1*FZ[4][j]; - f[0][j] = vadd_f32(vadd_f32(vadd_f32(FZ[0][j], FZ[1][j]), vadd_f32(FZ[2][j], FZ[3][j])), FZ[4][j]); - - // f[1][j] = 1*FZ[1][j] + -1*FZ[2][j] + 2*FZ[3][j] + -2*FZ[4][j] + 1*FZ[5][j]; - f[1][j] = vadd_f32(vmla_n_f32(vsub_f32(FZ[1][j], FZ[2][j]), vsub_f32(FZ[3][j], FZ[4][j]), 2.0f), FZ[5][j]); - } - - // Write out the output tile - if (bptr != nullptr) - { - b = vld1_f32(bptr); - bptr += 2; - } - else - { - b = vdup_n_f32(0.0f); - } - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = - vmax_f32(vmin_f32(vadd_f32(f[i][j], b), vdup_n_f32(output_max)), - vdup_n_f32(output_min)); - vst1_f32(outptrs[i][j], y); - outptrs[i][j] += 2; - } - } - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed during this transform - float F[6][6], FZ[6][2], f[2][2], b; - - // Read a 6x6 tile in the Winograd domain - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - F[i][j] = *(inptr + m*matrix_stride); - } - } - inptr++; - - // Compute the matrix F Z - for (int i = 0; i < 6; i++) - { - FZ[i][0] = 1*F[i][0] + 1*F[i][1] + 1*F[i][2] + 1*F[i][3] + 1*F[i][4]; - FZ[i][1] = 1*F[i][1] + -1*F[i][2] + 2*F[i][3] + -2*F[i][4] + 1*F[i][5]; - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 2; j++) - { - f[0][j] = 1*FZ[0][j] + 1*FZ[1][j] + 1*FZ[2][j] + 1*FZ[3][j] + 1*FZ[4][j]; - f[1][j] = 1*FZ[1][j] + -1*FZ[2][j] + 2*FZ[3][j] + -2*FZ[4][j] + 1*FZ[5][j]; - } - - // Write out the output tile - if (bptr != nullptr) - { - b = *(bptr++); - } - else - { - b = 0.0f; - } - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = std::max(std::min(f[i][j] + b, output_max), output_min); - *(outptrs[i][j]++) = y; - } - } - } -} - -template class OutputTransform<5, 5, 6, 6, float, float, WinogradRoots::Integers>; - -} // namespace diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_4_5_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_4_5_fp32_fp32_integers.cpp deleted file mode 100644 index 49a3f41182..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_4_5_fp32_fp32_integers.cpp +++ /dev/null @@ -1,152 +0,0 @@ -/* - * 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 "output.hpp" -#include "arm.hpp" - -namespace winograd -{ - -template <> -void OutputTransform<1, 5, 1, 8, float, float, WinogradRoots::Integers>::transform_tile( - const int n_channels, - const float* inptr, - const int matrix_stride, - const float* bptr, - float* const output, - const int, // No need to stride across rows - const int output_col_stride, - const float output_min, - const float output_max -) -{ - // Construct a map to the output cells - float *outptrs[output_tile_cols]; - for (int j = 0; j < output_tile_cols; j++) - { - outptrs[j] = output + j*output_col_stride; - } - - // For each channel of the output - int channels_remaining = n_channels; -#ifdef __arm_any__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed during this transform - float32x4_t F[inner_tile_cols], f[output_tile_cols], b = vdupq_n_f32(0.0f); - - // Read a 1x8 tile in the Winograd domain - for (int j = 0; j < inner_tile_cols; j++) - { - F[j] = vld1q_f32(inptr + j*matrix_stride); - } - inptr += 4; - - f[0] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[6], 1), F[5], 1), F[4], 1), F[3], 1), F[2], 1), F[1], 1), F[0], 1); - f[1] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[2], 1), F[6], 3), F[4], 2), F[3], -2), F[5], -3), F[1], -1); - f[2] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[2], 1), F[1], 1), F[6], 9), F[5], 9), F[4], 4), F[3], 4); - f[3] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[7], 1), F[2], 1), F[6], 27), F[4], 8), F[3], -8), F[5], -27), F[1], -1); - - // Write out the output tile - if (bptr != 0) - { - b = vld1q_f32(bptr); - bptr += 4; - } - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = - vmaxq_f32(vminq_f32(vaddq_f32(f[j], b), vdupq_n_f32(output_max)), - vdupq_n_f32(output_min)); - vst1q_f32(outptrs[j], y); - outptrs[j] += 4; - } - } - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used and computed during this transform - float32x2_t F[inner_tile_cols], f[output_tile_cols], b = vdup_n_f32(0.0f); - - // Read a 1x8 tile in the Winograd domain - for (int j = 0; j < inner_tile_cols; j++) - { - F[j] = vld1_f32(inptr + j*matrix_stride); - } - inptr += 2; - - f[0] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[6], 1), F[5], 1), F[4], 1), F[3], 1), F[2], 1), F[1], 1), F[0], 1); - f[1] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[2], 1), F[6], 3), F[4], 2), F[3], -2), F[5], -3), F[1], -1); - f[2] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[2], 1), F[1], 1), F[6], 9), F[5], 9), F[4], 4), F[3], 4); - f[3] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[7], 1), F[2], 1), F[6], 27), F[4], 8), F[3], -8), F[5], -27), F[1], -1); - - // Write out the output tile - if (bptr != 0) - { - b = vld1_f32(bptr); - bptr += 2; - } - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = - vmax_f32(vmin_f32(vadd_f32(f[j], b), vdup_n_f32(output_max)), - vdup_n_f32(output_min)); - vst1_f32(outptrs[j], y); - outptrs[j] += 2; - } - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed during this transform - float F[inner_tile_cols], f[output_tile_cols], b = 0.0f; - - // Read a 1x8 tile in the Winograd domain - for (int j = 0; j < inner_tile_cols; j++) - { - F[j] = *(inptr + j*matrix_stride); - } - inptr++; - - f[0] = F[0]*1 + F[1]*1 + F[2]*1 + F[3]*1 + F[4]*1 + F[5]*1 + F[6]*1; - f[1] = F[1]*-1 + F[5]*-3 + F[3]*-2 + F[4]*2 + F[6]*3 + F[2]*1; - f[2] = F[3]*4 + F[4]*4 + F[5]*9 + F[6]*9 + F[1]*1 + F[2]*1; - f[3] = F[1]*-1 + F[5]*-27 + F[3]*-8 + F[4]*8 + F[6]*27 + F[2]*1 + F[7]*1; - - // Write out the output tile - if (bptr != 0) - { - b = *(bptr++); - } - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = std::max(std::min(f[j] + b, output_max), output_min); - *(outptrs[j]++) = y; - } - } -} - -template class OutputTransform<1, 5, 1, 8, float, float, WinogradRoots::Integers>; -template class OutputTransform<5, 1, 8, 1, float, float, WinogradRoots::Integers>; - -} // namespace winograd diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_4x4_3x3_fp16_fp16_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_4x4_3x3_fp16_fp16_integers.cpp deleted file mode 100644 index 37b890d1bc..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_4x4_3x3_fp16_fp16_integers.cpp +++ /dev/null @@ -1,255 +0,0 @@ -/* - * Copyright (c) 2020 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. - */ -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC -#include "arm.hpp" -#include "output.hpp" - -namespace winograd -{ - -template <> -void winograd::OutputTransform<3, 3, 6, 6, __fp16, __fp16, winograd::WinogradRoots::Integers>::transform_tile( - const int n_channels, - const __fp16* inptr, - const int matrix_stride, - const __fp16* bptr, - __fp16* const output, - const int output_row_stride, - const int output_col_stride, - const __fp16 output_min, - const __fp16 output_max -) -{ - // Construct a map to the output cells - __fp16 *outptrs[output_tile_rows][output_tile_cols]; - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - outptrs[i][j] = output + i*output_row_stride + j*output_col_stride; - } - } - - // For each channel of the output - int channels_remaining = n_channels; - -#ifdef __aarch64__ - for (; channels_remaining >= 8; channels_remaining -= 8) - { - // Matrices used and computed during this transform - float16x8_t F[6][6], FZ[6][4], f[4][4], b; - - // Read a 6x6 tile in the Winograd domain - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - F[i][j] = vld1q_f16(inptr + m*matrix_stride); - } - } - inptr += 8; - - // Compute the matrix F Z - for (int i = 0; i < 6; i++) - { - // FZ[i][0] = 1*F[i][0] + 1*F[i][1] + 1*F[i][2] + 1*F[i][3] + 1*F[i][4]; - FZ[i][0] = vaddq_f16(vaddq_f16(vaddq_f16(F[i][0], F[i][1]), vaddq_f16(F[i][2], F[i][3])), F[i][4]); - - // FZ[i][1] = 1*F[i][1] + -1*F[i][2] + 2*F[i][3] + -2*F[i][4]; - FZ[i][1] = vaddq_f16(vsubq_f16(F[i][1], F[i][2]), vmulq_f16(vsubq_f16(F[i][3], F[i][4]), vdupq_n_f16(2.0f))); - - // FZ[i][2] = 1*F[i][1] + 1*F[i][2] + 4*F[i][3] + 4*F[i][4]; - FZ[i][2] = vaddq_f16(vaddq_f16(F[i][1], F[i][2]), vmulq_f16(vaddq_f16(F[i][3], F[i][4]), vdupq_n_f16(4.0f))); - - // FZ[i][3] = 1*F[i][1] + -1*F[i][2] + 8*F[i][3] + -8*F[i][4] + 1*F[i][5]; - FZ[i][3] = vaddq_f16(vaddq_f16(vsubq_f16(F[i][1], F[i][2]), vmulq_f16(vsubq_f16(F[i][3], F[i][4]), vdupq_n_f16(8.0f))), F[i][5]); - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 4; j++) - { - // f[0][j] = 1*FZ[0][j] + 1*FZ[1][j] + 1*FZ[2][j] + 1*FZ[3][j] + 1*FZ[4][j]; - f[0][j] = vaddq_f16(vaddq_f16(vaddq_f16(FZ[0][j], FZ[1][j]), vaddq_f16(FZ[2][j], FZ[3][j])), FZ[4][j]); - - // f[1][j] = 1*FZ[1][j] + -1*FZ[2][j] + 2*FZ[3][j] + -2*FZ[4][j]; - f[1][j] = vaddq_f16(vsubq_f16(FZ[1][j], FZ[2][j]), vmulq_f16(vsubq_f16(FZ[3][j], FZ[4][j]), vdupq_n_f16(2.0f))); - - // f[2][j] = 1*FZ[1][j] + 1*FZ[2][j] + 4*FZ[3][j] + 4*FZ[4][j]; - f[2][j] = vaddq_f16(vaddq_f16(FZ[1][j], FZ[2][j]), vmulq_f16(vaddq_f16(FZ[3][j], FZ[4][j]), vdupq_n_f16(4.0f))); - - // f[3][j] = 1*FZ[1][j] + -1*FZ[2][j] + 8*FZ[3][j] + -8*FZ[4][j] + 1*FZ[5][j]; - f[3][j] = vaddq_f16(vaddq_f16(vsubq_f16(FZ[1][j], FZ[2][j]), vmulq_f16(vsubq_f16(FZ[3][j], FZ[4][j]), vdupq_n_f16(8.0f))), FZ[5][j]); - } - - // Write out the output tile - if (bptr != nullptr) - { - b = vld1q_f16(bptr); - bptr += 8; - } - else - { - b = vdupq_n_f16(0.0f); - } - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = - vmaxq_f16(vminq_f16(vaddq_f16(f[i][j], b), vdupq_n_f16(output_max)), - vdupq_n_f16(output_min)); - vst1q_f16(outptrs[i][j], y); - outptrs[i][j] += 8; - } - } - } -#endif // __aarch64__ -#ifdef __arm_any__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed during this transform - float16x4_t F[6][6], FZ[6][4], f[4][4], b; - - // Read a 6x6 tile in the Winograd domain - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - F[i][j] = vld1_f16(inptr + m*matrix_stride); - } - } - inptr += 4; - - // Compute the matrix F Z - for (int i = 0; i < 6; i++) - { - // FZ[i][0] = 1*F[i][0] + 1*F[i][1] + 1*F[i][2] + 1*F[i][3] + 1*F[i][4]; - FZ[i][0] = vadd_f16(vadd_f16(vadd_f16(F[i][0], F[i][1]), vadd_f16(F[i][2], F[i][3])), F[i][4]); - - // FZ[i][1] = 1*F[i][1] + -1*F[i][2] + 2*F[i][3] + -2*F[i][4]; - FZ[i][1] = vadd_f16(vsub_f16(F[i][1], F[i][2]), vmul_f16(vsub_f16(F[i][3], F[i][4]), vdup_n_f16(2.0f))); - - // FZ[i][2] = 1*F[i][1] + 1*F[i][2] + 4*F[i][3] + 4*F[i][4]; - FZ[i][2] = vadd_f16(vadd_f16(F[i][1], F[i][2]), vmul_f16(vadd_f16(F[i][3], F[i][4]), vdup_n_f16(4.0f))); - - // FZ[i][3] = 1*F[i][1] + -1*F[i][2] + 8*F[i][3] + -8*F[i][4] + 1*F[i][5]; - FZ[i][3] = vadd_f16(vadd_f16(vsub_f16(F[i][1], F[i][2]), vmul_f16(vsub_f16(F[i][3], F[i][4]), vdup_n_f16(8.0f))), F[i][5]); - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 4; j++) - { - // f[0][j] = 1*FZ[0][j] + 1*FZ[1][j] + 1*FZ[2][j] + 1*FZ[3][j] + 1*FZ[4][j]; - f[0][j] = vadd_f16(vadd_f16(vadd_f16(FZ[0][j], FZ[1][j]), vadd_f16(FZ[2][j], FZ[3][j])), FZ[4][j]); - - // f[1][j] = 1*FZ[1][j] + -1*FZ[2][j] + 2*FZ[3][j] + -2*FZ[4][j]; - f[1][j] = vadd_f16(vsub_f16(FZ[1][j], FZ[2][j]), vmul_f16(vsub_f16(FZ[3][j], FZ[4][j]), vdup_n_f16(2.0f))); - - // f[2][j] = 1*FZ[1][j] + 1*FZ[2][j] + 4*FZ[3][j] + 4*FZ[4][j]; - f[2][j] = vadd_f16(vadd_f16(FZ[1][j], FZ[2][j]), vmul_f16(vadd_f16(FZ[3][j], FZ[4][j]), vdup_n_f16(4.0f))); - - // f[3][j] = 1*FZ[1][j] + -1*FZ[2][j] + 8*FZ[3][j] + -8*FZ[4][j] + 1*FZ[5][j]; - f[3][j] = vadd_f16(vadd_f16(vsub_f16(FZ[1][j], FZ[2][j]), vmul_f16(vsub_f16(FZ[3][j], FZ[4][j]), vdup_n_f16(8.0f))), FZ[5][j]); - } - - // Write out the output tile - if (bptr != nullptr) - { - b = vld1_f16(bptr); - bptr += 4; - } - else - { - b = vdup_n_f16(0.0f); - } - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = - vmax_f16(vmin_f16(vadd_f16(f[i][j], b), vdup_n_f16(output_max)), - vdup_n_f16(output_min)); - vst1_f16(outptrs[i][j], y); - outptrs[i][j] += 4; - } - } - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed during this transform - __fp16 F[6][6], FZ[6][4], f[4][4], b; - - // Read a 6x6 tile in the Winograd domain - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - F[i][j] = *(inptr + m*matrix_stride); - } - } - inptr++; - - // Compute the matrix F Z - for (int i = 0; i < 6; i++) - { - FZ[i][0] = 1*F[i][0] + 1*F[i][1] + 1*F[i][2] + 1*F[i][3] + 1*F[i][4]; - FZ[i][1] = 1*F[i][1] + -1*F[i][2] + 2*F[i][3] + -2*F[i][4]; - FZ[i][2] = 1*F[i][1] + 1*F[i][2] + 4*F[i][3] + 4*F[i][4]; - FZ[i][3] = 1*F[i][1] + -1*F[i][2] + 8*F[i][3] + -8*F[i][4] + 1*F[i][5]; - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 4; j++) - { - f[0][j] = 1*FZ[0][j] + 1*FZ[1][j] + 1*FZ[2][j] + 1*FZ[3][j] + 1*FZ[4][j]; - f[1][j] = 1*FZ[1][j] + -1*FZ[2][j] + 2*FZ[3][j] + -2*FZ[4][j]; - f[2][j] = 1*FZ[1][j] + 1*FZ[2][j] + 4*FZ[3][j] + 4*FZ[4][j]; - f[3][j] = 1*FZ[1][j] + -1*FZ[2][j] + 8*FZ[3][j] + -8*FZ[4][j] + 1*FZ[5][j]; - } - - // Write out the output tile - if (bptr != nullptr) - { - b = *(bptr++); - } - else - { - b = 0.0f; - } - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = std::max(std::min<__fp16>(f[i][j] + b, output_max), output_min); - *(outptrs[i][j]++) = y; - } - } - } -} - -template class OutputTransform<3, 3, 6, 6, __fp16, __fp16, winograd::WinogradRoots::Integers>; - -} // namespace winograd -#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_4x4_3x3_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_4x4_3x3_fp32_fp32_integers.cpp deleted file mode 100644 index 292999c8bc..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_4x4_3x3_fp32_fp32_integers.cpp +++ /dev/null @@ -1,254 +0,0 @@ -/* - * 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 "arm.hpp" -#include "output.hpp" - -namespace winograd -{ - -template <> -void winograd::OutputTransform<3, 3, 6, 6, float, float, winograd::WinogradRoots::Integers>::transform_tile( - const int n_channels, - const float* inptr, - const int matrix_stride, - const float* bptr, - float* const output, - const int output_row_stride, - const int output_col_stride, - const float output_min, - const float output_max -) -{ - // Construct a map to the output cells - float *outptrs[output_tile_rows][output_tile_cols]; - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - outptrs[i][j] = output + i*output_row_stride + j*output_col_stride; - } - } - - // For each channel of the output - int channels_remaining = n_channels; - -#ifdef __aarch64__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed during this transform - float32x4_t F[6][6], FZ[6][4], f[4][4], b; - - // Read a 6x6 tile in the Winograd domain - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - F[i][j] = vld1q_f32(inptr + m*matrix_stride); - } - } - inptr += 4; - - // Compute the matrix F Z - for (int i = 0; i < 6; i++) - { - // FZ[i][0] = 1*F[i][0] + 1*F[i][1] + 1*F[i][2] + 1*F[i][3] + 1*F[i][4]; - FZ[i][0] = vaddq_f32(vaddq_f32(vaddq_f32(F[i][0], F[i][1]), vaddq_f32(F[i][2], F[i][3])), F[i][4]); - - // FZ[i][1] = 1*F[i][1] + -1*F[i][2] + 2*F[i][3] + -2*F[i][4]; - FZ[i][1] = vmlaq_n_f32(vsubq_f32(F[i][1], F[i][2]), vsubq_f32(F[i][3], F[i][4]), 2.0f); - - // FZ[i][2] = 1*F[i][1] + 1*F[i][2] + 4*F[i][3] + 4*F[i][4]; - FZ[i][2] = vmlaq_n_f32(vaddq_f32(F[i][1], F[i][2]), vaddq_f32(F[i][3], F[i][4]), 4.0f); - - // FZ[i][3] = 1*F[i][1] + -1*F[i][2] + 8*F[i][3] + -8*F[i][4] + 1*F[i][5]; - FZ[i][3] = vaddq_f32(vmlaq_n_f32(vsubq_f32(F[i][1], F[i][2]), vsubq_f32(F[i][3], F[i][4]), 8.0f), F[i][5]); - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 4; j++) - { - // f[0][j] = 1*FZ[0][j] + 1*FZ[1][j] + 1*FZ[2][j] + 1*FZ[3][j] + 1*FZ[4][j]; - f[0][j] = vaddq_f32(vaddq_f32(vaddq_f32(FZ[0][j], FZ[1][j]), vaddq_f32(FZ[2][j], FZ[3][j])), FZ[4][j]); - - // f[1][j] = 1*FZ[1][j] + -1*FZ[2][j] + 2*FZ[3][j] + -2*FZ[4][j]; - f[1][j] = vmlaq_n_f32(vsubq_f32(FZ[1][j], FZ[2][j]), vsubq_f32(FZ[3][j], FZ[4][j]), 2.0f); - - // f[2][j] = 1*FZ[1][j] + 1*FZ[2][j] + 4*FZ[3][j] + 4*FZ[4][j]; - f[2][j] = vmlaq_n_f32(vaddq_f32(FZ[1][j], FZ[2][j]), vaddq_f32(FZ[3][j], FZ[4][j]), 4.0f); - - // f[3][j] = 1*FZ[1][j] + -1*FZ[2][j] + 8*FZ[3][j] + -8*FZ[4][j] + 1*FZ[5][j]; - f[3][j] = vaddq_f32(vmlaq_n_f32(vsubq_f32(FZ[1][j], FZ[2][j]), vsubq_f32(FZ[3][j], FZ[4][j]), 8.0f), FZ[5][j]); - } - - // Write out the output tile - if (bptr != nullptr) - { - b = vld1q_f32(bptr); - bptr += 4; - } - else - { - b = vdupq_n_f32(0.0f); - } - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = - vmaxq_f32(vminq_f32(vaddq_f32(f[i][j], b), vdupq_n_f32(output_max)), - vdupq_n_f32(output_min)); - vst1q_f32(outptrs[i][j], y); - outptrs[i][j] += 4; - } - } - } -#endif // __aarch64__ -#ifdef __arm_any__ - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used and computed during this transform - float32x2_t F[6][6], FZ[6][4], f[4][4], b; - - // Read a 6x6 tile in the Winograd domain - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - F[i][j] = vld1_f32(inptr + m*matrix_stride); - } - } - inptr += 2; - - // Compute the matrix F Z - for (int i = 0; i < 6; i++) - { - // FZ[i][0] = 1*F[i][0] + 1*F[i][1] + 1*F[i][2] + 1*F[i][3] + 1*F[i][4]; - FZ[i][0] = vadd_f32(vadd_f32(vadd_f32(F[i][0], F[i][1]), vadd_f32(F[i][2], F[i][3])), F[i][4]); - - // FZ[i][1] = 1*F[i][1] + -1*F[i][2] + 2*F[i][3] + -2*F[i][4]; - FZ[i][1] = vmla_n_f32(vsub_f32(F[i][1], F[i][2]), vsub_f32(F[i][3], F[i][4]), 2.0f); - - // FZ[i][2] = 1*F[i][1] + 1*F[i][2] + 4*F[i][3] + 4*F[i][4]; - FZ[i][2] = vmla_n_f32(vadd_f32(F[i][1], F[i][2]), vadd_f32(F[i][3], F[i][4]), 4.0f); - - // FZ[i][3] = 1*F[i][1] + -1*F[i][2] + 8*F[i][3] + -8*F[i][4] + 1*F[i][5]; - FZ[i][3] = vadd_f32(vmla_n_f32(vsub_f32(F[i][1], F[i][2]), vsub_f32(F[i][3], F[i][4]), 8.0f), F[i][5]); - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 4; j++) - { - // f[0][j] = 1*FZ[0][j] + 1*FZ[1][j] + 1*FZ[2][j] + 1*FZ[3][j] + 1*FZ[4][j]; - f[0][j] = vadd_f32(vadd_f32(vadd_f32(FZ[0][j], FZ[1][j]), vadd_f32(FZ[2][j], FZ[3][j])), FZ[4][j]); - - // f[1][j] = 1*FZ[1][j] + -1*FZ[2][j] + 2*FZ[3][j] + -2*FZ[4][j]; - f[1][j] = vmla_n_f32(vsub_f32(FZ[1][j], FZ[2][j]), vsub_f32(FZ[3][j], FZ[4][j]), 2.0f); - - // f[2][j] = 1*FZ[1][j] + 1*FZ[2][j] + 4*FZ[3][j] + 4*FZ[4][j]; - f[2][j] = vmla_n_f32(vadd_f32(FZ[1][j], FZ[2][j]), vadd_f32(FZ[3][j], FZ[4][j]), 4.0f); - - // f[3][j] = 1*FZ[1][j] + -1*FZ[2][j] + 8*FZ[3][j] + -8*FZ[4][j] + 1*FZ[5][j]; - f[3][j] = vadd_f32(vmla_n_f32(vsub_f32(FZ[1][j], FZ[2][j]), vsub_f32(FZ[3][j], FZ[4][j]), 8.0f), FZ[5][j]); - } - - // Write out the output tile - if (bptr != nullptr) - { - b = vld1_f32(bptr); - bptr += 2; - } - else - { - b = vdup_n_f32(0.0f); - } - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = - vmax_f32(vmin_f32(vadd_f32(f[i][j], b), vdup_n_f32(output_max)), - vdup_n_f32(output_min)); - vst1_f32(outptrs[i][j], y); - outptrs[i][j] += 2; - } - } - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed during this transform - float F[6][6], FZ[6][4], f[4][4], b; - - // Read a 6x6 tile in the Winograd domain - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - F[i][j] = *(inptr + m*matrix_stride); - } - } - inptr++; - - // Compute the matrix F Z - for (int i = 0; i < 6; i++) - { - FZ[i][0] = 1*F[i][0] + 1*F[i][1] + 1*F[i][2] + 1*F[i][3] + 1*F[i][4]; - FZ[i][1] = 1*F[i][1] + -1*F[i][2] + 2*F[i][3] + -2*F[i][4]; - FZ[i][2] = 1*F[i][1] + 1*F[i][2] + 4*F[i][3] + 4*F[i][4]; - FZ[i][3] = 1*F[i][1] + -1*F[i][2] + 8*F[i][3] + -8*F[i][4] + 1*F[i][5]; - } - - // Compute the output tile f = ZT F Z - for (int j = 0; j < 4; j++) - { - f[0][j] = 1*FZ[0][j] + 1*FZ[1][j] + 1*FZ[2][j] + 1*FZ[3][j] + 1*FZ[4][j]; - f[1][j] = 1*FZ[1][j] + -1*FZ[2][j] + 2*FZ[3][j] + -2*FZ[4][j]; - f[2][j] = 1*FZ[1][j] + 1*FZ[2][j] + 4*FZ[3][j] + 4*FZ[4][j]; - f[3][j] = 1*FZ[1][j] + -1*FZ[2][j] + 8*FZ[3][j] + -8*FZ[4][j] + 1*FZ[5][j]; - } - - // Write out the output tile - if (bptr != nullptr) - { - b = *(bptr++); - } - else - { - b = 0.0f; - } - for (int i = 0; i < output_tile_rows; i++) - { - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = std::max(std::min(f[i][j] + b, output_max), output_min); - *(outptrs[i][j]++) = y; - } - } - } -} - -template class OutputTransform<3, 3, 6, 6, float, float, winograd::WinogradRoots::Integers>; - -} // namespace winograd diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_6_3_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_6_3_fp32_fp32_integers.cpp deleted file mode 100644 index 05f06a81ee..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_6_3_fp32_fp32_integers.cpp +++ /dev/null @@ -1,155 +0,0 @@ -/* - * 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 "output.hpp" -#include "arm.hpp" - -namespace winograd -{ - -template <> -void OutputTransform<1, 3, 1, 8, float, float, WinogradRoots::Integers>::transform_tile( - const int n_channels, - const float* inptr, - const int matrix_stride, - const float* bptr, - float* const output, - const int, // No need to stride across rows - const int output_col_stride, - const float output_min, - const float output_max -) -{ - // Construct a map to the output cells - float *outptrs[output_tile_cols]; - for (int j = 0; j < output_tile_cols; j++) - { - outptrs[j] = output + j*output_col_stride; - } - - // For each channel of the output - int channels_remaining = n_channels; -#ifdef __arm_any__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed during this transform - float32x4_t F[inner_tile_cols], f[output_tile_cols], b = vdupq_n_f32(0.0f); - - // Read a 1x8 tile in the Winograd domain - for (int j = 0; j < inner_tile_cols; j++) - { - F[j] = vld1q_f32(inptr + j*matrix_stride); - } - inptr += 4; - - f[0] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[6], 1), F[5], 1), F[4], 1), F[3], 1), F[2], 1), F[1], 1), F[0], 1); - f[1] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[2], 1), F[6], 3), F[4], 2), F[3], -2), F[5], -3), F[1], -1); - f[2] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[2], 1), F[1], 1), F[6], 9), F[5], 9), F[4], 4), F[3], 4); - f[3] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[2], 1), F[6], 27), F[4], 8), F[3], -8), F[5], -27), F[1], -1); - f[4] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[2], 1), F[1], 1), F[6], 81), F[5], 81), F[4], 16), F[3], 16); - f[5] = vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmlaq_n_f32(vmulq_n_f32(F[7], 1), F[2], 1), F[6], 243), F[4], 32), F[3], -32), F[5], -243), F[1], -1); - - // Write out the output tile - if (bptr != 0) - { - b = vld1q_f32(bptr); - bptr += 4; - } - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = vminq_f32(vmaxq_f32(f[j] + b, vdupq_n_f32(output_min)), - vdupq_n_f32(output_max)); - vst1q_f32(outptrs[j], y); - outptrs[j] += 4; - } - } - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used and computed during this transform - float32x2_t F[inner_tile_cols], f[output_tile_cols], b = vdup_n_f32(0.0f); - - // Read a 1x8 tile in the Winograd domain - for (int j = 0; j < inner_tile_cols; j++) - { - F[j] = vld1_f32(inptr + j*matrix_stride); - } - inptr += 2; - - f[0] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[6], 1), F[5], 1), F[4], 1), F[3], 1), F[2], 1), F[1], 1), F[0], 1); - f[1] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[2], 1), F[6], 3), F[4], 2), F[3], -2), F[5], -3), F[1], -1); - f[2] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[2], 1), F[1], 1), F[6], 9), F[5], 9), F[4], 4), F[3], 4); - f[3] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[2], 1), F[6], 27), F[4], 8), F[3], -8), F[5], -27), F[1], -1); - f[4] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[2], 1), F[1], 1), F[6], 81), F[5], 81), F[4], 16), F[3], 16); - f[5] = vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmla_n_f32(vmul_n_f32(F[7], 1), F[2], 1), F[6], 243), F[4], 32), F[3], -32), F[5], -243), F[1], -1); - - // Write out the output tile - if (bptr != 0) - { - b = vld1_f32(bptr); - bptr += 2; - } - for (int j = 0; j < output_tile_cols; j++) - { - const auto y = vmin_f32(vmax_f32(f[j] + b, vdup_n_f32(output_min)), - vdup_n_f32(output_max)); - vst1_f32(outptrs[j], y); - outptrs[j] += 2; - } - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed during this transform - float F[inner_tile_cols], f[output_tile_cols], b = 0.0f; - - // Read a 1x8 tile in the Winograd domain - for (int j = 0; j < inner_tile_cols; j++) - { - F[j] = *(inptr + j*matrix_stride); - } - inptr++; - - f[0] = F[0]*1 + F[1]*1 + F[2]*1 + F[3]*1 + F[4]*1 + F[5]*1 + F[6]*1; - f[1] = F[1]*-1 + F[5]*-3 + F[3]*-2 + F[4]*2 + F[6]*3 + F[2]*1; - f[2] = F[3]*4 + F[4]*4 + F[5]*9 + F[6]*9 + F[1]*1 + F[2]*1; - f[3] = F[1]*-1 + F[5]*-27 + F[3]*-8 + F[4]*8 + F[6]*27 + F[2]*1; - f[4] = F[3]*16 + F[4]*16 + F[5]*81 + F[6]*81 + F[1]*1 + F[2]*1; - f[5] = F[1]*-1 + F[5]*-243 + F[3]*-32 + F[4]*32 + F[6]*243 + F[2]*1 + F[7]*1; - - // Write out the output tile - if (bptr != 0) - { - b = *(bptr++); - } - for (int j = 0; j < output_tile_cols; j++) - { - *(outptrs[j]++) = std::max(std::min(f[j] + b, output_max), output_min); - } - } -} - -template class OutputTransform<1, 3, 1, 8, float, float, WinogradRoots::Integers>; -template class OutputTransform<3, 1, 8, 1, float, float, WinogradRoots::Integers>; - -} // namespace diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2_7_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2_7_fp32_fp32_integers.cpp deleted file mode 100644 index 37ae43fdb0..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2_7_fp32_fp32_integers.cpp +++ /dev/null @@ -1,90 +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 "arm.hpp" -#include "kernel.hpp" - -namespace winograd -{ - -template <> -void WeightTransform<1, 7, 1, 8, float, float, WinogradRoots::Integers>::execute( - const int n_output_channels, - const int n_input_channels, - const float* const input, // NOTE: Data in HWIO order - float* const output, - const int matrix_stride, - const int matrix_row_stride -) -{ - // Get pointers to each cell of the weight tensor - const auto weight_col_stride = n_input_channels * n_output_channels; - const float *inptrs[kernel_cols]; - for (int j = 0; j < kernel_cols; j++) - { - inptrs[j] = input + j*weight_col_stride; - } - - // For each input channel - for (int ic = 0; ic < n_input_channels; ic++) - { - float *outptr = output + ic * matrix_row_stride; - - // For each output channel - int channels_remaining = n_output_channels; - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed in this kernel - float w[kernel_cols], V[inner_tile_cols]; - - // Read weights - for (int j = 0; j < kernel_cols; j++) - { - w[j] = *(inptrs[j]++); - } - - // Compute V = w WT - V[0] = (w[0]*-1) / 36.0f; - V[1] = (w[1]*-1 + w[3]*-1 + w[5]*-1 + w[0]*1 + w[2]*1 + w[4]*1 + w[6]*1) / 48.0f; - V[2] = (w[0]*1 + w[1]*1 + w[2]*1 + w[3]*1 + w[4]*1 + w[5]*1 + w[6]*1) / 48.0f; - V[3] = (w[0]*-1 + w[6]*-64 + w[4]*-16 + w[2]*-4 + w[1]*2 + w[3]*8 + w[5]*32) / 120.0f; - V[4] = (w[0]*-1 + w[6]*-64 + w[5]*-32 + w[4]*-16 + w[3]*-8 + w[2]*-4 + w[1]*-2) / 120.0f; - V[5] = (w[5]*-243 + w[3]*-27 + w[1]*-3 + w[2]*9 + w[4]*81 + w[6]*729 + w[0]*1) / 720.0f; - V[6] = (w[1]*3 + w[2]*9 + w[3]*27 + w[4]*81 + w[5]*243 + w[6]*729 + w[0]*1) / 720.0f; - V[7] = (w[6]*1) / 1.0f; - - // Store the transformed weights - for (int j = 0; j < inner_tile_cols; j++) - { - *(outptr + j*matrix_stride) = V[j]; - } - outptr++; - } - } -} - -template class WeightTransform<1, 7, 1, 8, float, float, WinogradRoots::Integers>; -template class WeightTransform<7, 1, 8, 1, float, float, WinogradRoots::Integers>; - -} // namespace winograd diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_3x3_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_3x3_fp32_fp32_integers.cpp deleted file mode 100644 index 8fab6db1ba..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_3x3_fp32_fp32_integers.cpp +++ /dev/null @@ -1,220 +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 "arm.hpp" -#include "kernel.hpp" - -namespace winograd -{ - -template <> -void WeightTransform<3, 3, 4, 4, float, float, WinogradRoots::Integers>::execute( - const int n_output_channels, - const int n_input_channels, - const float* const input, - float* const output, - const int matrix_stride, - const int matrix_row_stride -) -{ - constexpr int inner_tile_i = 4; - constexpr int inner_tile_j = 4; - - // Get pointers to each cell of the weight tensor - const auto weight_col_stride = n_input_channels * n_output_channels; - const auto weight_row_stride = 3 * weight_col_stride; - const float *inptrs[3][3]; - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - inptrs[i][j] = input + i*weight_row_stride + j*weight_col_stride; - } - } - - // For each input channel - for (int ic = 0; ic < n_input_channels; ic++) - { - float *outptr = output + ic * matrix_row_stride; - - // For each output channel - int channels_remaining = n_output_channels; -#ifdef __aarch64__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed in this kernel - float32x4_t w[3][3], Ww[inner_tile_i][3], V[inner_tile_i][inner_tile_j]; - - // Read weights - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - w[i][j] = vld1q_f32(inptrs[i][j]); - inptrs[i][j] += 4; - } - } - - // Compute the matrix W w - for (int j = 0; j < 3; j++) - { - Ww[0][j] = w[0][j]; - - // Ww[1][j] = 0.5*(w[0][j] + w[1][j] + w[2][j]); - Ww[1][j] = vmulq_n_f32(vaddq_f32(vaddq_f32(w[0][j], w[1][j]), w[2][j]), 0.5f); - - // Ww[2][j] = 0.5*(w[0][j] - w[1][j] + w[2][j]); - Ww[2][j] = vmulq_n_f32(vaddq_f32(vsubq_f32(w[0][j], w[1][j]), w[2][j]), 0.5f); - - Ww[3][j] = w[2][j]; - } - - // Compute V = W w WT - for (int i = 0; i < inner_tile_i; i++) - { - V[i][0] = Ww[i][0]; - - // V[i][1] = 0.5*(Ww[i][0] + Ww[i][1] + Ww[i][2]); - V[i][1] = vmulq_n_f32(vaddq_f32(vaddq_f32(Ww[i][0], Ww[i][1]), Ww[i][2]), 0.5f); - - // V[i][2] = 0.5*(Ww[i][0] - Ww[i][1] + Ww[i][2]); - V[i][2] = vmulq_n_f32(vaddq_f32(vsubq_f32(Ww[i][0], Ww[i][1]), Ww[i][2]), 0.5f); - - V[i][3] = Ww[i][2]; - } - - // Store the transformed weights - for (int i = 0, m = 0; i < inner_tile_i; i++) - { - for (int j = 0; j < inner_tile_j; j++, m++) - { - vst1q_f32(outptr + m*matrix_stride, V[i][j]); - } - } - outptr += 4; - } -#endif // __aarch64__ -#ifdef __arm_any__ - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used and computed in this kernel - float32x2_t w[3][3], Ww[inner_tile_i][3], V[inner_tile_i][inner_tile_j]; - - // Read weights - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - w[i][j] = vld1_f32(inptrs[i][j]); - inptrs[i][j] += 2; - } - } - - // Compute the matrix W w - for (int j = 0; j < 3; j++) - { - Ww[0][j] = w[0][j]; - - // Ww[1][j] = 0.5*(w[0][j] + w[1][j] + w[2][j]); - Ww[1][j] = vmul_n_f32(vadd_f32(vadd_f32(w[0][j], w[1][j]), w[2][j]), 0.5f); - - // Ww[2][j] = 0.5*(w[0][j] - w[1][j] + w[2][j]); - Ww[2][j] = vmul_n_f32(vadd_f32(vsub_f32(w[0][j], w[1][j]), w[2][j]), 0.5f); - - Ww[3][j] = w[2][j]; - } - - // Compute V = W w WT - for (int i = 0; i < inner_tile_i; i++) - { - V[i][0] = Ww[i][0]; - - // V[i][1] = 0.5*(Ww[i][0] + Ww[i][1] + Ww[i][2]); - V[i][1] = vmul_n_f32(vadd_f32(vadd_f32(Ww[i][0], Ww[i][1]), Ww[i][2]), 0.5f); - - // V[i][2] = 0.5*(Ww[i][0] - Ww[i][1] + Ww[i][2]); - V[i][2] = vmul_n_f32(vadd_f32(vsub_f32(Ww[i][0], Ww[i][1]), Ww[i][2]), 0.5f); - - V[i][3] = Ww[i][2]; - } - - // Store the transformed weights - for (int i = 0, m = 0; i < inner_tile_i; i++) - { - for (int j = 0; j < inner_tile_j; j++, m++) - { - vst1_f32(outptr + m*matrix_stride, V[i][j]); - } - } - outptr += 2; - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed in this kernel - float w[3][3], Ww[inner_tile_i][3], V[inner_tile_i][inner_tile_j]; - - // Read weights - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - w[i][j] = *(inptrs[i][j]++); - } - } - - // Compute the matrix W w - for (int j = 0; j < 3; j++) - { - Ww[0][j] = w[0][j]; - Ww[1][j] = 0.5*(w[0][j] + w[1][j] + w[2][j]); - Ww[2][j] = 0.5*(w[0][j] - w[1][j] + w[2][j]); - Ww[3][j] = w[2][j]; - } - - // Compute V = W w WT - for (int i = 0; i < inner_tile_i; i++) - { - V[i][0] = Ww[i][0]; - V[i][1] = 0.5*(Ww[i][0] + Ww[i][1] + Ww[i][2]); - V[i][2] = 0.5*(Ww[i][0] - Ww[i][1] + Ww[i][2]); - V[i][3] = Ww[i][2]; - } - - // Store the transformed weights - for (int i = 0, m = 0; i < inner_tile_i; i++) - { - for (int j = 0; j < inner_tile_j; j++, m++) - { - *(outptr + m*matrix_stride) = V[i][j]; - } - } - outptr++; - } - } -} - -template class WeightTransform<3, 3, 4, 4, float, float, WinogradRoots::Integers>; - -} // namespace diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_5x5_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_5x5_fp32_fp32_integers.cpp deleted file mode 100644 index 79f4fa30c4..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_2x2_5x5_fp32_fp32_integers.cpp +++ /dev/null @@ -1,401 +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 "arm.hpp" -#include "kernel.hpp" - -namespace winograd -{ - -template <> -void WeightTransform<5, 5, 6, 6, float, float, WinogradRoots::Integers>::execute( - const int n_output_channels, - const int n_input_channels, - const float* const input, - float* const output, - const int matrix_stride, - const int matrix_row_stride -) -{ - // Get pointers to each cell of the weight tensor - const auto weight_col_stride = n_input_channels * n_output_channels; - const auto weight_row_stride = 5 * weight_col_stride; - const float *inptrs[5][5]; - for (int i = 0; i < 5; i++) - { - for (int j = 0; j < 5; j++) - { - inptrs[i][j] = input + i*weight_row_stride + j*weight_col_stride; - } - } - - // For each input channel - for (int ic = 0; ic < n_input_channels; ic++) - { - float *outptr = output + ic * matrix_row_stride; - - // For each output channel - int channels_remaining = n_output_channels; -#ifdef __aarch64__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed in this kernel - float32x4_t w[5][5], Ww[6][5], V[6][6]; - - // Read weights - for (int i = 0; i < 5; i++) - { - for (int j = 0; j < 5; j++) - { - w[i][j] = vld1q_f32(inptrs[i][j]); - inptrs[i][j] += 4; - } - } - - // Compute the matrix W w - for (int j = 0; j < 5; j++) - { - // Ww[0][j] = w[0][j]/4.0f; - Ww[0][j] = vmulq_n_f32(w[0][j], 1.0f/4.0f); - - // Ww[1][j] = -( w[0][j] + w[1][j] + w[2][j] + w[3][j] + w[4][j])/6.0f; - Ww[1][j] = vmulq_n_f32( - vaddq_f32( - vaddq_f32( - vaddq_f32(w[1][j], w[0][j]), - vaddq_f32(w[3][j], w[2][j]) - ), - w[4][j] - ), - -1.0f/6.0f - ); - - // Ww[2][j] = +(-w[0][j] + w[1][j] - w[2][j] + w[3][j] - w[4][j])/6.0f; - // Ww[2][j] = ((w[1][j] - w[0][j]) + (w[3][j] - w[2][j]) - w[4][j])/6.0f; - Ww[2][j] = vmulq_n_f32( - vsubq_f32( - vaddq_f32( - vsubq_f32(w[1][j], w[0][j]), - vsubq_f32(w[3][j], w[2][j]) - ), - w[4][j] - ), - 1.0f/6.0f - ); - - // Ww[3][j] = (w[0][j]/8.0f + w[1][j]/4.0f + w[2][j]/2.0f + w[3][j] + 2*w[4][j])/3.0f; - Ww[3][j] = vmulq_n_f32( - vmlaq_n_f32( - vaddq_f32( - vaddq_f32(vmulq_n_f32(w[0][j], 1.0f/8.0f), vmulq_n_f32(w[1][j], 1.0f/4.0f)), - vaddq_f32(vmulq_n_f32(w[2][j], 1.0f/2.0f), w[3][j]) - ), - w[4][j], 2.0f - ), - 1.0f/3.0f - ); - - // Ww[4][j] = (w[0][j]/8.0f - w[1][j]/4.0f + w[2][j]/2.0f - w[3][j] + 2*w[4][j])/3.0f; - Ww[4][j] = vmulq_n_f32( - vmlaq_n_f32( - vaddq_f32( - vsubq_f32(vmulq_n_f32(w[0][j], 1.0f/8.0f), vmulq_n_f32(w[1][j], 1.0f/4.0f)), - vsubq_f32(vmulq_n_f32(w[2][j], 1.0f/2.0f), w[3][j]) - ), - w[4][j], 2.0f - ), - 1.0f/3.0f - ); - - // Ww[5][j] = w[4][j]; - Ww[5][j] = w[4][j]; - } - - // Compute V = W w WT - for (int i = 0; i < 6; i++) - { - // V[i][0] = Ww[i][0]/4.0f; - V[i][0] = vmulq_n_f32(Ww[i][0], 1.0f/4.0f); - - // V[i][1] = -( Ww[i][0] + Ww[i][1] + Ww[i][2] + Ww[i][3] + Ww[i][4])/6.0f; - V[i][1] = vmulq_n_f32( - vaddq_f32( - vaddq_f32( - vaddq_f32(Ww[i][1], Ww[i][0]), - vaddq_f32(Ww[i][3], Ww[i][2]) - ), - Ww[i][4] - ), - -1.0f/6.0f - ); - - // V[i][2] = +(-Ww[i][0] + Ww[i][1] - Ww[i][2] + Ww[i][3] - Ww[i][4])/6.0f; - // V[i][2] = ((Ww[i][1] - Ww[i][0]) + (Ww[i][3] - Ww[i][2]) - Ww[i][4])/6.0f; - V[i][2] = vmulq_n_f32( - vsubq_f32( - vaddq_f32( - vsubq_f32(Ww[i][1], Ww[i][0]), - vsubq_f32(Ww[i][3], Ww[i][2]) - ), - Ww[i][4] - ), - 1.0f/6.0f - ); - - // V[i][3] = (Ww[i][0]/8.0f + Ww[i][1]/4.0f + Ww[i][2]/2.0f + Ww[i][3] + 2*Ww[i][4])/3.0f; - V[i][3] = vmulq_n_f32( - vmlaq_n_f32( - vaddq_f32( - vaddq_f32(vmulq_n_f32(Ww[i][0], 1.0f/8.0f), vmulq_n_f32(Ww[i][1], 1.0f/4.0f)), - vaddq_f32(vmulq_n_f32(Ww[i][2], 1.0f/2.0f), Ww[i][3]) - ), - Ww[i][4], 2.0f - ), - 1.0f/3.0f - ); - - // V[i][4] = (Ww[i][0]/8.0f - Ww[i][1]/4.0f + Ww[i][2]/2.0f - Ww[i][3] + 2*Ww[i][4])/3.0f; - V[i][4] = vmulq_n_f32( - vmlaq_n_f32( - vaddq_f32( - vsubq_f32(vmulq_n_f32(Ww[i][0], 1.0f/8.0f), vmulq_n_f32(Ww[i][1], 1.0f/4.0f)), - vsubq_f32(vmulq_n_f32(Ww[i][2], 1.0f/2.0f), Ww[i][3]) - ), - Ww[i][4], 2.0f - ), - 1.0f/3.0f - ); - - // V[i][5] = Ww[i][4]; - V[i][5] = Ww[i][4]; - } - - // Store the transformed weights - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - vst1q_f32(outptr + m*matrix_stride, V[i][j]); - } - } - outptr += 4; - } -#endif // __aarch64__ -#ifdef __arm_any__ - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used and computed in this kernel - float32x2_t w[5][5], Ww[6][5], V[6][6]; - - // Read weights - for (int i = 0; i < 5; i++) - { - for (int j = 0; j < 5; j++) - { - w[i][j] = vld1_f32(inptrs[i][j]); - inptrs[i][j] += 2; - } - } - - // Compute the matrix W w - for (int j = 0; j < 5; j++) - { - // Ww[0][j] = w[0][j]/4.0f; - Ww[0][j] = vmul_n_f32(w[0][j], 1.0f/4.0f); - - // Ww[1][j] = -( w[0][j] + w[1][j] + w[2][j] + w[3][j] + w[4][j])/6.0f; - Ww[1][j] = vmul_n_f32( - vadd_f32( - vadd_f32( - vadd_f32(w[1][j], w[0][j]), - vadd_f32(w[3][j], w[2][j]) - ), - w[4][j] - ), - -1.0f/6.0f - ); - - // Ww[2][j] = +(-w[0][j] + w[1][j] - w[2][j] + w[3][j] - w[4][j])/6.0f; - // Ww[2][j] = ((w[1][j] - w[0][j]) + (w[3][j] - w[2][j]) - w[4][j])/6.0f; - Ww[2][j] = vmul_n_f32( - vsub_f32( - vadd_f32( - vsub_f32(w[1][j], w[0][j]), - vsub_f32(w[3][j], w[2][j]) - ), - w[4][j] - ), - 1.0f/6.0f - ); - - // Ww[3][j] = (w[0][j]/8.0f + w[1][j]/4.0f + w[2][j]/2.0f + w[3][j] + 2*w[4][j])/3.0f; - Ww[3][j] = vmul_n_f32( - vmla_n_f32( - vadd_f32( - vadd_f32(vmul_n_f32(w[0][j], 1.0f/8.0f), vmul_n_f32(w[1][j], 1.0f/4.0f)), - vadd_f32(vmul_n_f32(w[2][j], 1.0f/2.0f), w[3][j]) - ), - w[4][j], 2.0f - ), - 1.0f/3.0f - ); - - // Ww[4][j] = (w[0][j]/8.0f - w[1][j]/4.0f + w[2][j]/2.0f - w[3][j] + 2*w[4][j])/3.0f; - Ww[4][j] = vmul_n_f32( - vmla_n_f32( - vadd_f32( - vsub_f32(vmul_n_f32(w[0][j], 1.0f/8.0f), vmul_n_f32(w[1][j], 1.0f/4.0f)), - vsub_f32(vmul_n_f32(w[2][j], 1.0f/2.0f), w[3][j]) - ), - w[4][j], 2.0f - ), - 1.0f/3.0f - ); - - // Ww[5][j] = w[4][j]; - Ww[5][j] = w[4][j]; - } - - // Compute V = W w WT - for (int i = 0; i < 6; i++) - { - // V[i][0] = Ww[i][0]/4.0f; - V[i][0] = vmul_n_f32(Ww[i][0], 1.0f/4.0f); - - // V[i][1] = -( Ww[i][0] + Ww[i][1] + Ww[i][2] + Ww[i][3] + Ww[i][4])/6.0f; - V[i][1] = vmul_n_f32( - vadd_f32( - vadd_f32( - vadd_f32(Ww[i][1], Ww[i][0]), - vadd_f32(Ww[i][3], Ww[i][2]) - ), - Ww[i][4] - ), - -1.0f/6.0f - ); - - // V[i][2] = +(-Ww[i][0] + Ww[i][1] - Ww[i][2] + Ww[i][3] - Ww[i][4])/6.0f; - // V[i][2] = ((Ww[i][1] - Ww[i][0]) + (Ww[i][3] - Ww[i][2]) - Ww[i][4])/6.0f; - V[i][2] = vmul_n_f32( - vsub_f32( - vadd_f32( - vsub_f32(Ww[i][1], Ww[i][0]), - vsub_f32(Ww[i][3], Ww[i][2]) - ), - Ww[i][4] - ), - 1.0f/6.0f - ); - - // V[i][3] = (Ww[i][0]/8.0f + Ww[i][1]/4.0f + Ww[i][2]/2.0f + Ww[i][3] + 2*Ww[i][4])/3.0f; - V[i][3] = vmul_n_f32( - vmla_n_f32( - vadd_f32( - vadd_f32(vmul_n_f32(Ww[i][0], 1.0f/8.0f), vmul_n_f32(Ww[i][1], 1.0f/4.0f)), - vadd_f32(vmul_n_f32(Ww[i][2], 1.0f/2.0f), Ww[i][3]) - ), - Ww[i][4], 2.0f - ), - 1.0f/3.0f - ); - - // V[i][4] = (Ww[i][0]/8.0f - Ww[i][1]/4.0f + Ww[i][2]/2.0f - Ww[i][3] + 2*Ww[i][4])/3.0f; - V[i][4] = vmul_n_f32( - vmla_n_f32( - vadd_f32( - vsub_f32(vmul_n_f32(Ww[i][0], 1.0f/8.0f), vmul_n_f32(Ww[i][1], 1.0f/4.0f)), - vsub_f32(vmul_n_f32(Ww[i][2], 1.0f/2.0f), Ww[i][3]) - ), - Ww[i][4], 2.0f - ), - 1.0f/3.0f - ); - - // V[i][5] = Ww[i][4]; - V[i][5] = Ww[i][4]; - } - - // Store the transformed weights - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - vst1_f32(outptr + m*matrix_stride, V[i][j]); - } - } - outptr += 2; - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed in this kernel - float w[5][5], Ww[6][5], V[6][6]; - - // Read weights - for (int i = 0; i < 5; i++) - { - for (int j = 0; j < 5; j++) - { - w[i][j] = *(inptrs[i][j]++); - } - } - - // Compute the matrix W w - for (int j = 0; j < 5; j++) - { - Ww[0][j] = w[0][j]/4.0f; - Ww[1][j] = -( w[0][j] + w[1][j] + w[2][j] + w[3][j] + w[4][j])/6.0f; - Ww[2][j] = +(-w[0][j] + w[1][j] - w[2][j] + w[3][j] - w[4][j])/6.0f; - Ww[3][j] = (w[0][j]/8.0f + w[1][j]/4.0f + w[2][j]/2.0f + w[3][j] + 2*w[4][j])/3.0f; - Ww[4][j] = (w[0][j]/8.0f - w[1][j]/4.0f + w[2][j]/2.0f - w[3][j] + 2*w[4][j])/3.0f; - Ww[5][j] = w[4][j]; - } - - // Compute V = W w WT - for (int i = 0; i < 6; i++) - { - V[i][0] = Ww[i][0]/4.0f; - V[i][1] = -( Ww[i][0] + Ww[i][1] + Ww[i][2] + Ww[i][3] + Ww[i][4])/6.0f; - V[i][2] = +(-Ww[i][0] + Ww[i][1] - Ww[i][2] + Ww[i][3] - Ww[i][4])/6.0f; - V[i][3] = (Ww[i][0]/8.0f + Ww[i][1]/4.0f + Ww[i][2]/2.0f + Ww[i][3] + 2*Ww[i][4])/3.0f; - V[i][4] = (Ww[i][0]/8.0f - Ww[i][1]/4.0f + Ww[i][2]/2.0f - Ww[i][3] + 2*Ww[i][4])/3.0f; - V[i][5] = Ww[i][4]; - } - - // Store the transformed weights - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - *(outptr + m*matrix_stride) = V[i][j]; - } - } - outptr++; - } - } -} - -template class WeightTransform<5, 5, 6, 6, float, float, WinogradRoots::Integers>; - -} // namespace winograd diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4_5_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4_5_fp32_fp32_integers.cpp deleted file mode 100644 index fb3d712954..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4_5_fp32_fp32_integers.cpp +++ /dev/null @@ -1,90 +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 "arm.hpp" -#include "kernel.hpp" - -namespace winograd -{ - -template <> -void WeightTransform<1, 5, 1, 8, float, float, WinogradRoots::Integers>::execute( - const int n_output_channels, - const int n_input_channels, - const float* const input, // NOTE: Data in HWIO order - float* const output, - const int matrix_stride, - const int matrix_row_stride -) -{ - // Get pointers to each cell of the weight tensor - const auto weight_col_stride = n_input_channels * n_output_channels; - const float *inptrs[kernel_cols]; - for (int j = 0; j < kernel_cols; j++) - { - inptrs[j] = input + j*weight_col_stride; - } - - // For each input channel - for (int ic = 0; ic < n_input_channels; ic++) - { - float *outptr = output + ic * matrix_row_stride; - - // For each output channel - int channels_remaining = n_output_channels; - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed in this kernel - float w[kernel_cols], V[inner_tile_cols]; - - // Read weights - for (int j = 0; j < kernel_cols; j++) - { - w[j] = *(inptrs[j]++); - } - - // Compute V = w WT - V[0] = (w[0]*-1) / 36; - V[1] = (w[1]*-1 + w[3]*-1 + w[0]*1 + w[2]*1 + w[4]*1) / 48; - V[2] = (w[0]*1 + w[1]*1 + w[2]*1 + w[3]*1 + w[4]*1) / 48; - V[3] = (w[0]*-1 + w[4]*-16 + w[2]*-4 + w[1]*2 + w[3]*8) / 120; - V[4] = (w[0]*-1 + w[4]*-16 + w[3]*-8 + w[2]*-4 + w[1]*-2) / 120; - V[5] = (w[3]*-27 + w[1]*-3 + w[2]*9 + w[4]*81 + w[0]*1) / 720; - V[6] = (w[1]*3 + w[2]*9 + w[3]*27 + w[4]*81 + w[0]*1) / 720; - V[7] = (w[4]*1) / 1; - - // Store the transformed weights - for (int j = 0; j < inner_tile_cols; j++) - { - *(outptr + j*matrix_stride) = V[j]; - } - outptr++; - } - } -} - -template class WeightTransform<1, 5, 1, 8, float, float, WinogradRoots::Integers>; -template class WeightTransform<5, 1, 8, 1, float, float, WinogradRoots::Integers>; - -} // namespace winograd diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4x4_3x3_fp16_fp16_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4x4_3x3_fp16_fp16_integers.cpp deleted file mode 100644 index 3c4f8b426c..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4x4_3x3_fp16_fp16_integers.cpp +++ /dev/null @@ -1,259 +0,0 @@ -/* - * Copyright (c) 2020 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. - */ -#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC - -#include "arm.hpp" -#include "kernel.hpp" - -namespace winograd -{ - -template <> -void WeightTransform<3, 3, 6, 6, __fp16, __fp16, WinogradRoots::Integers>::execute( - const int n_output_channels, - const int n_input_channels, - const __fp16* const input, // NOTE: Data in HWIO order - __fp16* const output, - const int matrix_stride, - const int matrix_row_stride -) -{ - // Get pointers to each cell of the weight tensor - const auto weight_col_stride = n_input_channels * n_output_channels; - const auto weight_row_stride = 3 * weight_col_stride; - const __fp16 *inptrs[3][3]; - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - inptrs[i][j] = input + i*weight_row_stride + j*weight_col_stride; - } - } - - // For each input channel - for (int ic = 0; ic < n_input_channels; ic++) - { - __fp16 *outptr = output + ic * matrix_row_stride; - - // For each output channel - int channels_remaining = n_output_channels; -#ifdef __aarch64__ - for (; channels_remaining >= 8; channels_remaining -= 8) - { - // Matrices used and computed in this kernel - float16x8_t w[3][3], Ww[6][3], V[6][6]; - - // Read weights - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - w[i][j] = vld1q_f16(inptrs[i][j]); - inptrs[i][j] += 8; - } - } - - // Compute the matrix W w - for (int j = 0; j < 3; j++) - { - // Ww[0][j] = 6*w[0][j]; - Ww[0][j] = vmulq_n_f16(w[0][j], 6.0); - - // Ww[1][j] = -4*w[0][j] + -4*w[1][j] + -4*w[2][j]; - Ww[1][j] = vmulq_n_f16(vaddq_f16(vaddq_f16(w[0][j], w[1][j]), w[2][j]), -4.0); - - // Ww[2][j] = -4*w[0][j] + 4*w[1][j] + -4*w[2][j]; - Ww[2][j] = vmulq_n_f16(vsubq_f16(vsubq_f16(w[1][j], w[0][j]), w[2][j]), 4.0); - - // Ww[3][j] = 1*w[0][j] + 2*w[1][j] + 4*w[2][j]; - Ww[3][j] = vaddq_f16(vaddq_f16(w[0][j], vmulq_f16(w[1][j], vdupq_n_f16(2.0f))), vmulq_f16(w[2][j], vdupq_n_f16(4.0f))); - - // Ww[4][j] = 1*w[0][j] + -2*w[1][j] + 4*w[2][j]; - Ww[4][j] = vaddq_f16(vsubq_f16(w[0][j], vmulq_f16(w[1][j], vdupq_n_f16(2.0f))), vmulq_f16(w[2][j], vdupq_n_f16(4.0f))); - - // Ww[5][j] = 24*w[2][j]; - Ww[5][j] = vmulq_n_f16(w[2][j], 24.0f); - } - - // Compute V = W w WT - for (int i = 0; i < 6; i++) - { - const float recip576 = 1.0f / 576.0f; - - // V[i][0] = 6*Ww[i][0]; - V[i][0] = vmulq_n_f16(vmulq_n_f16(Ww[i][0], 6.0), recip576); - - // V[i][1] = -4*Ww[i][0] + -4*Ww[i][1] + -4*Ww[i][2]; - V[i][1] = vmulq_n_f16(vmulq_n_f16(vaddq_f16(vaddq_f16(Ww[i][0], Ww[i][1]), Ww[i][2]), -4.0), recip576); - - // V[i][2] = -4*Ww[i][0] + 4*Ww[i][1] + -4*Ww[i][2]; - V[i][2] = vmulq_n_f16(vmulq_n_f16(vsubq_f16(vsubq_f16(Ww[i][1], Ww[i][0]), Ww[i][2]), 4.0), recip576); - - // V[i][3] = 1*Ww[i][0] + 2*Ww[i][1] + 4*Ww[i][2]; - V[i][3] = vmulq_n_f16(vaddq_f16(vaddq_f16(Ww[i][0], vmulq_f16(Ww[i][1], vdupq_n_f16(2.0f))), vmulq_f16(Ww[i][2], vdupq_n_f16(4.0f))), recip576); - - // V[i][4] = 1*Ww[i][0] + -2*Ww[i][1] + 4*Ww[i][2]; - V[i][4] = vmulq_n_f16(vaddq_f16(vsubq_f16(Ww[i][0], vmulq_f16(Ww[i][1], vdupq_n_f16(2.0f))), vmulq_f16(Ww[i][2], vdupq_n_f16(4.0f))), recip576); - - // V[i][5] = 24*Ww[i][2]; - V[i][5] = vmulq_n_f16(vmulq_n_f16(Ww[i][2], 24.0f), recip576); - } - - // Store the transformed weights - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - vst1q_f16(outptr + m*matrix_stride, V[i][j]); - } - } - outptr += 8; - } -#endif // __aarch64__ -#ifdef __arm_any__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed in this kernel - float16x4_t w[3][3], Ww[6][3], V[6][6]; - - // Read weights - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - w[i][j] = vld1_f16(inptrs[i][j]); - inptrs[i][j] += 4; - } - } - - // Compute the matrix W w - for (int j = 0; j < 3; j++) - { - // Ww[0][j] = 6*w[0][j]; - Ww[0][j] = vmul_n_f16(w[0][j], 6.0); - - // Ww[1][j] = -4*w[0][j] + -4*w[1][j] + -4*w[2][j]; - Ww[1][j] = vmul_n_f16(vadd_f16(vadd_f16(w[0][j], w[1][j]), w[2][j]), -4.0); - - // Ww[2][j] = -4*w[0][j] + 4*w[1][j] + -4*w[2][j]; - Ww[2][j] = vmul_n_f16(vsub_f16(vsub_f16(w[1][j], w[0][j]), w[2][j]), 4.0); - - // Ww[3][j] = 1*w[0][j] + 2*w[1][j] + 4*w[2][j]; - Ww[3][j] = vadd_f16(vadd_f16(w[0][j], vmul_f16(w[1][j], vdup_n_f16(2.0f))), vmul_f16(w[2][j], vdup_n_f16(4.0f))); - - // Ww[4][j] = 1*w[0][j] + -2*w[1][j] + 4*w[2][j]; - Ww[4][j] = vadd_f16(vsub_f16(w[0][j], vmul_f16(w[1][j], vdup_n_f16(2.0f))), vmul_f16(w[2][j], vdup_n_f16(4.0f))); - - // Ww[5][j] = 24*w[2][j]; - Ww[5][j] = vmul_n_f16(w[2][j], 24.0f); - } - - // Compute V = W w WT - for (int i = 0; i < 6; i++) - { - const float recip576 = 1.0f / 576.0f; - - // V[i][0] = 6*Ww[i][0]; - V[i][0] = vmul_n_f16(vmul_n_f16(Ww[i][0], 6.0), recip576); - - // V[i][1] = -4*Ww[i][0] + -4*Ww[i][1] + -4*Ww[i][2]; - V[i][1] = vmul_n_f16(vmul_n_f16(vadd_f16(vadd_f16(Ww[i][0], Ww[i][1]), Ww[i][2]), -4.0), recip576); - - // V[i][2] = -4*Ww[i][0] + 4*Ww[i][1] + -4*Ww[i][2]; - V[i][2] = vmul_n_f16(vmul_n_f16(vsub_f16(vsub_f16(Ww[i][1], Ww[i][0]), Ww[i][2]), 4.0), recip576); - - // V[i][3] = 1*Ww[i][0] + 2*Ww[i][1] + 4*Ww[i][2]; - V[i][3] = vmul_n_f16(vadd_f16(vadd_f16(Ww[i][0], vmul_f16(Ww[i][1], vdup_n_f16(2.0f))), vmul_f16(Ww[i][2], vdup_n_f16(4.0f))), recip576); - - // V[i][4] = 1*Ww[i][0] + -2*Ww[i][1] + 4*Ww[i][2]; - V[i][4] = vmul_n_f16(vadd_f16(vsub_f16(Ww[i][0], vmul_f16(Ww[i][1], vdup_n_f16(2.0f))), vmul_f16(Ww[i][2], vdup_n_f16(4.0f))), recip576); - - // V[i][5] = 24*Ww[i][2]; - V[i][5] = vmul_n_f16(vmul_n_f16(Ww[i][2], 24.0f), recip576); - } - - // Store the transformed weights - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - vst1_f16(outptr + m*matrix_stride, V[i][j]); - } - } - outptr += 4; - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed in this kernel - __fp16 w[3][3], Ww[6][3], V[6][6]; - - // Read weights - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - w[i][j] = *(inptrs[i][j]++); - } - } - - // Compute the matrix W w - for (int j = 0; j < 3; j++) - { - Ww[0][j] = 6*w[0][j]; - Ww[1][j] = -4*w[0][j] + -4*w[1][j] + -4*w[2][j]; - Ww[2][j] = -4*w[0][j] + 4*w[1][j] + -4*w[2][j]; - Ww[3][j] = 1*w[0][j] + 2*w[1][j] + 4*w[2][j]; - Ww[4][j] = 1*w[0][j] + -2*w[1][j] + 4*w[2][j]; - Ww[5][j] = 24*w[2][j]; - } - - // Compute V = W w WT - for (int i = 0; i < 6; i++) - { - V[i][0] = ( 6*Ww[i][0]) / 576.0; - V[i][1] = (-4*Ww[i][0] + -4*Ww[i][1] + -4*Ww[i][2]) / 576.0; - V[i][2] = (-4*Ww[i][0] + 4*Ww[i][1] + -4*Ww[i][2]) / 576.0; - V[i][3] = ( 1*Ww[i][0] + 2*Ww[i][1] + 4*Ww[i][2]) / 576.0; - V[i][4] = ( 1*Ww[i][0] + -2*Ww[i][1] + 4*Ww[i][2]) / 576.0; - V[i][5] = (24*Ww[i][2]) / 576.0; - } - - // Store the transformed weights - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - *(outptr + m*matrix_stride) = V[i][j]; - } - } - outptr++; - } - } -} - -template class WeightTransform<3, 3, 6, 6, __fp16, __fp16, WinogradRoots::Integers>; - -} // namespace -#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4x4_3x3_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4x4_3x3_fp32_fp32_integers.cpp deleted file mode 100644 index 9e7040bca8..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4x4_3x3_fp32_fp32_integers.cpp +++ /dev/null @@ -1,257 +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 "arm.hpp" -#include "kernel.hpp" - -namespace winograd -{ - -template <> -void WeightTransform<3, 3, 6, 6, float, float, WinogradRoots::Integers>::execute( - const int n_output_channels, - const int n_input_channels, - const float* const input, // NOTE: Data in HWIO order - float* const output, - const int matrix_stride, - const int matrix_row_stride -) -{ - // Get pointers to each cell of the weight tensor - const auto weight_col_stride = n_input_channels * n_output_channels; - const auto weight_row_stride = 3 * weight_col_stride; - const float *inptrs[3][3]; - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - inptrs[i][j] = input + i*weight_row_stride + j*weight_col_stride; - } - } - - // For each input channel - for (int ic = 0; ic < n_input_channels; ic++) - { - float *outptr = output + ic * matrix_row_stride; - - // For each output channel - int channels_remaining = n_output_channels; -#ifdef __aarch64__ - for (; channels_remaining >= 4; channels_remaining -= 4) - { - // Matrices used and computed in this kernel - float32x4_t w[3][3], Ww[6][3], V[6][6]; - - // Read weights - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - w[i][j] = vld1q_f32(inptrs[i][j]); - inptrs[i][j] += 4; - } - } - - // Compute the matrix W w - for (int j = 0; j < 3; j++) - { - // Ww[0][j] = 6*w[0][j]; - Ww[0][j] = vmulq_n_f32(w[0][j], 6.0); - - // Ww[1][j] = -4*w[0][j] + -4*w[1][j] + -4*w[2][j]; - Ww[1][j] = vmulq_n_f32(vaddq_f32(vaddq_f32(w[0][j], w[1][j]), w[2][j]), -4.0); - - // Ww[2][j] = -4*w[0][j] + 4*w[1][j] + -4*w[2][j]; - Ww[2][j] = vmulq_n_f32(vsubq_f32(vsubq_f32(w[1][j], w[0][j]), w[2][j]), 4.0); - - // Ww[3][j] = 1*w[0][j] + 2*w[1][j] + 4*w[2][j]; - Ww[3][j] = vmlaq_n_f32(vmlaq_n_f32(w[0][j], w[1][j], 2.0f), w[2][j], 4.0f); - - // Ww[4][j] = 1*w[0][j] + -2*w[1][j] + 4*w[2][j]; - Ww[4][j] = vmlaq_n_f32(vmlsq_n_f32(w[0][j], w[1][j], 2.0f), w[2][j], 4.0f); - - // Ww[5][j] = 24*w[2][j]; - Ww[5][j] = vmulq_n_f32(w[2][j], 24.0f); - } - - // Compute V = W w WT - for (int i = 0; i < 6; i++) - { - const float recip576 = 1.0f / 576.0f; - - // V[i][0] = 6*Ww[i][0]; - V[i][0] = vmulq_n_f32(vmulq_n_f32(Ww[i][0], 6.0), recip576); - - // V[i][1] = -4*Ww[i][0] + -4*Ww[i][1] + -4*Ww[i][2]; - V[i][1] = vmulq_n_f32(vmulq_n_f32(vaddq_f32(vaddq_f32(Ww[i][0], Ww[i][1]), Ww[i][2]), -4.0), recip576); - - // V[i][2] = -4*Ww[i][0] + 4*Ww[i][1] + -4*Ww[i][2]; - V[i][2] = vmulq_n_f32(vmulq_n_f32(vsubq_f32(vsubq_f32(Ww[i][1], Ww[i][0]), Ww[i][2]), 4.0), recip576); - - // V[i][3] = 1*Ww[i][0] + 2*Ww[i][1] + 4*Ww[i][2]; - V[i][3] = vmulq_n_f32(vmlaq_n_f32(vmlaq_n_f32(Ww[i][0], Ww[i][1], 2.0f), Ww[i][2], 4.0f), recip576); - - // V[i][4] = 1*Ww[i][0] + -2*Ww[i][1] + 4*Ww[i][2]; - V[i][4] = vmulq_n_f32(vmlaq_n_f32(vmlsq_n_f32(Ww[i][0], Ww[i][1], 2.0f), Ww[i][2], 4.0f), recip576); - - // V[i][5] = 24*Ww[i][2]; - V[i][5] = vmulq_n_f32(vmulq_n_f32(Ww[i][2], 24.0f), recip576); - } - - // Store the transformed weights - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - vst1q_f32(outptr + m*matrix_stride, V[i][j]); - } - } - outptr += 4; - } -#endif // __aarch64__ -#ifdef __arm_any__ - for (; channels_remaining >= 2; channels_remaining -= 2) - { - // Matrices used and computed in this kernel - float32x2_t w[3][3], Ww[6][3], V[6][6]; - - // Read weights - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - w[i][j] = vld1_f32(inptrs[i][j]); - inptrs[i][j] += 2; - } - } - - // Compute the matrix W w - for (int j = 0; j < 3; j++) - { - // Ww[0][j] = 6*w[0][j]; - Ww[0][j] = vmul_n_f32(w[0][j], 6.0); - - // Ww[1][j] = -4*w[0][j] + -4*w[1][j] + -4*w[2][j]; - Ww[1][j] = vmul_n_f32(vadd_f32(vadd_f32(w[0][j], w[1][j]), w[2][j]), -4.0); - - // Ww[2][j] = -4*w[0][j] + 4*w[1][j] + -4*w[2][j]; - Ww[2][j] = vmul_n_f32(vsub_f32(vsub_f32(w[1][j], w[0][j]), w[2][j]), 4.0); - - // Ww[3][j] = 1*w[0][j] + 2*w[1][j] + 4*w[2][j]; - Ww[3][j] = vmla_n_f32(vmla_n_f32(w[0][j], w[1][j], 2.0f), w[2][j], 4.0f); - - // Ww[4][j] = 1*w[0][j] + -2*w[1][j] + 4*w[2][j]; - Ww[4][j] = vmla_n_f32(vmls_n_f32(w[0][j], w[1][j], 2.0f), w[2][j], 4.0f); - - // Ww[5][j] = 24*w[2][j]; - Ww[5][j] = vmul_n_f32(w[2][j], 24.0f); - } - - // Compute V = W w WT - for (int i = 0; i < 6; i++) - { - const float recip576 = 1.0f / 576.0f; - - // V[i][0] = 6*Ww[i][0]; - V[i][0] = vmul_n_f32(vmul_n_f32(Ww[i][0], 6.0), recip576); - - // V[i][1] = -4*Ww[i][0] + -4*Ww[i][1] + -4*Ww[i][2]; - V[i][1] = vmul_n_f32(vmul_n_f32(vadd_f32(vadd_f32(Ww[i][0], Ww[i][1]), Ww[i][2]), -4.0), recip576); - - // V[i][2] = -4*Ww[i][0] + 4*Ww[i][1] + -4*Ww[i][2]; - V[i][2] = vmul_n_f32(vmul_n_f32(vsub_f32(vsub_f32(Ww[i][1], Ww[i][0]), Ww[i][2]), 4.0), recip576); - - // V[i][3] = 1*Ww[i][0] + 2*Ww[i][1] + 4*Ww[i][2]; - V[i][3] = vmul_n_f32(vmla_n_f32(vmla_n_f32(Ww[i][0], Ww[i][1], 2.0f), Ww[i][2], 4.0f), recip576); - - // V[i][4] = 1*Ww[i][0] + -2*Ww[i][1] + 4*Ww[i][2]; - V[i][4] = vmul_n_f32(vmla_n_f32(vmls_n_f32(Ww[i][0], Ww[i][1], 2.0f), Ww[i][2], 4.0f), recip576); - - // V[i][5] = 24*Ww[i][2]; - V[i][5] = vmul_n_f32(vmul_n_f32(Ww[i][2], 24.0f), recip576); - } - - // Store the transformed weights - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - vst1_f32(outptr + m*matrix_stride, V[i][j]); - } - } - outptr += 2; - } -#endif // __arm_any__ - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed in this kernel - float w[3][3], Ww[6][3], V[6][6]; - - // Read weights - for (int i = 0; i < 3; i++) - { - for (int j = 0; j < 3; j++) - { - w[i][j] = *(inptrs[i][j]++); - } - } - - // Compute the matrix W w - for (int j = 0; j < 3; j++) - { - Ww[0][j] = 6*w[0][j]; - Ww[1][j] = -4*w[0][j] + -4*w[1][j] + -4*w[2][j]; - Ww[2][j] = -4*w[0][j] + 4*w[1][j] + -4*w[2][j]; - Ww[3][j] = 1*w[0][j] + 2*w[1][j] + 4*w[2][j]; - Ww[4][j] = 1*w[0][j] + -2*w[1][j] + 4*w[2][j]; - Ww[5][j] = 24*w[2][j]; - } - - // Compute V = W w WT - for (int i = 0; i < 6; i++) - { - V[i][0] = ( 6*Ww[i][0]) / 576.0; - V[i][1] = (-4*Ww[i][0] + -4*Ww[i][1] + -4*Ww[i][2]) / 576.0; - V[i][2] = (-4*Ww[i][0] + 4*Ww[i][1] + -4*Ww[i][2]) / 576.0; - V[i][3] = ( 1*Ww[i][0] + 2*Ww[i][1] + 4*Ww[i][2]) / 576.0; - V[i][4] = ( 1*Ww[i][0] + -2*Ww[i][1] + 4*Ww[i][2]) / 576.0; - V[i][5] = (24*Ww[i][2]) / 576.0; - } - - // Store the transformed weights - for (int i = 0, m = 0; i < 6; i++) - { - for (int j = 0; j < 6; j++, m++) - { - *(outptr + m*matrix_stride) = V[i][j]; - } - } - outptr++; - } - } -} - -template class WeightTransform<3, 3, 6, 6, float, float, WinogradRoots::Integers>; - -} // namespace diff --git a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_6_3_fp32_fp32_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_6_3_fp32_fp32_integers.cpp deleted file mode 100644 index 45723482a2..0000000000 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_6_3_fp32_fp32_integers.cpp +++ /dev/null @@ -1,90 +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 "arm.hpp" -#include "kernel.hpp" - -namespace winograd -{ - -template <> -void WeightTransform<1, 3, 1, 8, float, float, WinogradRoots::Integers>::execute( - const int n_output_channels, - const int n_input_channels, - const float* const input, // NOTE: Data in HWIO order - float* const output, - const int matrix_stride, - const int matrix_row_stride -) -{ - // Get pointers to each cell of the weight tensor - const auto weight_col_stride = n_input_channels * n_output_channels; - const float *inptrs[3]; - for (int j = 0; j < 3; j++) - { - inptrs[j] = input + j*weight_col_stride; - } - - // For each input channel - for (int ic = 0; ic < n_input_channels; ic++) - { - float *outptr = output + ic * matrix_row_stride; - - // For each output channel - int channels_remaining = n_output_channels; - for (; channels_remaining; channels_remaining--) - { - // Matrices used and computed in this kernel - float w[3], V[inner_tile_cols]; - - // Read weights - for (int j = 0; j < 3; j++) - { - w[j] = *(inptrs[j]++); - } - - // Compute V = w WT - V[0] = (w[0]*-1) / 36.0f; - V[1] = (w[1]*-1 + w[0]*1 + w[2]*1) / 48.0f; - V[2] = (w[0]*1 + w[1]*1 + w[2]*1) / 48.0f; - V[3] = (w[0]*-1 + w[2]*-4 + w[1]*2) / 120.0f; - V[4] = (w[0]*-1 + w[2]*-4 + w[1]*-2) / 120.0f; - V[5] = (w[1]*-3 + w[2]*9 + w[0]*1) / 720.0f; - V[6] = (w[1]*3 + w[2]*9 + w[0]*1) / 720.0f; - V[7] = (w[2]*1) / 1; - - // Store the transformed weights - for (int j = 0; j < inner_tile_cols; j++) - { - *(outptr + j*matrix_stride) = V[j]; - } - outptr++; - } - } -} - -template class WeightTransform<1, 3, 1, 8, float, float, WinogradRoots::Integers>; -template class WeightTransform<3, 1, 8, 1, float, float, WinogradRoots::Integers>; - -} // namespace |