| /* |
| * Copyright (c) 2017 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 "transforms/input.hpp" |
| #include "winograd_gemm.hpp" |
| #include "arm.hpp" |
| |
| namespace winograd |
| { |
| |
| using Transform = WinogradGEMM<2, 2, 3, 3>::InputTransform<float>; |
| |
| /****************************************************************************** |
| * Cost methods for the input transform. |
| * ===================================== |
| */ |
| template <> |
| template <> |
| int Transform::ops_performed(const Tensor4DShape &input_shape) |
| { |
| // NOTE: Cost in FLOPs rather than instructions or uops. |
| const int tile_M = iceildiv(input_shape.n_rows, inner_tile_rows); |
| const int tile_N = iceildiv(input_shape.n_cols, inner_tile_cols); |
| return 16 * 16 * tile_M * tile_N * input_shape.n_channels; |
| } |
| /*****************************************************************************/ |
| |
| /***************************************************************************** |
| * F(2x2, 3x3) implies the use of a 4x4 input tile. Such tiles can require a |
| * variety of padding types. For example, tiles at the top and left of an image |
| * can require one row or column of padding on their top and left sides if the |
| * padding type is SAME (where X represents a padded value): |
| * |
| * _______ _______ |
| * |X X X X| |X X X X| |
| * |X | | | . . . |
| * |X | | | |
| * |X______| |_______| |
| * _______ |
| * |X | . |
| * |X | . . . . |
| * |X | . |
| * |X______| |
| * |
| * For tiles near the right or bottom of the image it is more complicated. Such |
| * tiles might require padding by 0 or 1 rows or columns if the padding type is |
| * VALID or 1 or 2 rows or columns if the padding type is SAME: |
| * |
| * _______ _______ _______ _______ |
| * |X X X X| |X X X X| |X X X X| |X X X X| |
| * |X | | | | X| | X X| |
| * |X | | | | X| | X X| |
| * |X______| |_______| |______X| |____X_X| |
| * _______ _______ _______ _______ |
| * |X | | | | X| | X X| |
| * |X | | | | X| | X X| |
| * |X | | | | X| | X X| |
| * |X______| |_______| |______X| |____X_X| |
| * _______ _______ _______ _______ |
| * |X | | | | X| | X X| |
| * |X | | | | X| | X X| |
| * |X | | | | X| | X X| |
| * |X_X_X_X| |X_X_X_X| |X_X_X_X| |X_X_X_X| |
| * _______ _______ _______ _______ |
| * |X | | | | X| | X X| |
| * |X | | | | X| | X X| |
| * |X X X X| |X X X X| |X X X X| |X X X X| |
| * |X_X_X_X| |X_X_X_X| |X_X_X_X| |X_X_X_X| |
| * |
| * Additional tiles are required for especially small input images. |
| * |
| * Build an array of the specialised methods that deal with each of the |
| * different padding combinations which may be required. These padding |
| * constraints are the space: |
| * |
| * Padding top in {0, 1} |
| * Padding left in {0, 1} |
| * Padding bottom in {0, 1, 2} |
| * Padding right in {0, 1, 2} |
| */ |
| template <> |
| template <> |
| template <int pad_top, int pad_left, int pad_bottom, int pad_right> |
| void Transform::process_tile( |
| int n_channels, |
| const float* const input_base, |
| const int input_row_stride, |
| const int input_col_stride, |
| float* const matrix_base, |
| const int matrix_stride |
| ) |
| { |
| constexpr int inner_tile_i = 4, inner_tile_j = 4; |
| constexpr int cells_i = inner_tile_i - pad_bottom; |
| constexpr int cells_j = inner_tile_i - pad_right; |
| |
| float *outptr = matrix_base; |
| |
| // Get pointers into the input tile |
| const float *x_ptrs[inner_tile_i][inner_tile_j]; |
| for (int i = pad_top, xi = 0; i < cells_i; i++, xi++) |
| { |
| // Get a pointer into the row |
| const float* const row_ptr = input_base + xi*input_row_stride; |
| |
| for (int j = pad_left, xj = 0; j < cells_j; j++, xj++) |
| { |
| x_ptrs[i][j] = row_ptr + xj*input_col_stride; |
| } |
| } |
| |
| // Matrices used/computed in this kernel. |
| float x[inner_tile_i][inner_tile_j]; |
| float XTx[inner_tile_i][inner_tile_j]; |
| float U[inner_tile_i][inner_tile_j]; |
| |
| for (int i = 0; i < inner_tile_i; i++) |
| { |
| for (int j = 0; j < inner_tile_j; 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_i][inner_tile_j]; |
| float32x4_t XTx[inner_tile_i][inner_tile_j]; |
| float32x4_t U[inner_tile_i][inner_tile_j]; |
| |
| for (int i = 0; i < inner_tile_i; i++) |
| { |
| for (int j = 0; j < inner_tile_j; j++) |
| { |
| x[i][j] = vdupq_n_f32(0.0f); |
| XTx[i][j] = vdupq_n_f32(0.0f); |
| } |
| } |
| |
| // Load x |
| for (int i = pad_top; i < cells_i; i++) |
| { |
| for (int j = pad_left; j < cells_j; j++) |
| { |
| x[i][j] = vld1q_f32(x_ptrs[i][j]); |
| x_ptrs[i][j] += 4; |
| } |
| } |
| |
| // Compute XT . x |
| for (int j = pad_left; j < cells_j; 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_i; 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_i; i++) |
| { |
| for (int j = 0; j < inner_tile_j; 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_i][inner_tile_j]; |
| float32x2_t XTx[inner_tile_i][inner_tile_j]; |
| float32x2_t U[inner_tile_i][inner_tile_j]; |
| |
| for (int i = 0; i < inner_tile_i; i++) |
| { |
| for (int j = 0; j < inner_tile_j; j++) |
| { |
| x[i][j] = vdup_n_f32(0.0f); |
| XTx[i][j] = vdup_n_f32(0.0f); |
| } |
| } |
| |
| // Load x |
| for (int i = pad_top; i < cells_i; i++) |
| { |
| for (int j = pad_left; j < cells_j; j++) |
| { |
| x[i][j] = vld1_f32(x_ptrs[i][j]); |
| x_ptrs[i][j] += 2; |
| } |
| } |
| |
| // Compute XT . x |
| for (int j = pad_left; j < cells_j; 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_i; 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_i; i++) |
| { |
| for (int j = 0; j < inner_tile_j; 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 = pad_top; i < cells_i; i++) |
| { |
| for (int j = pad_left; j < cells_j; j++) |
| { |
| x[i][j] = *(x_ptrs[i][j]++); |
| } |
| } |
| |
| // Compute XT . x |
| for (int j = pad_left; j < cells_j; 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_i; 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_i; i++) |
| { |
| for (int j = 0; j < inner_tile_j; j++, m++) |
| { |
| *(outptr + m*matrix_stride) = U[i][j]; |
| } |
| } |
| outptr++; |
| } |
| } |
| |
| template <> |
| template <> |
| const Transform::TileFn Transform::tile_fns[2][2][max_pad_bottom][max_pad_right] = |
| { |
| { |
| { |
| { |
| Transform::template process_tile<0, 0, 0, 0>, // No padding |
| Transform::template process_tile<0, 0, 0, 1>, // Right |
| Transform::template process_tile<0, 0, 0, 2>, // Right |
| }, |
| { |
| Transform::template process_tile<0, 0, 1, 0>, // Bottom |
| Transform::template process_tile<0, 0, 1, 1>, // Bottom-right |
| Transform::template process_tile<0, 0, 1, 2>, // Bottom-right |
| }, |
| { |
| Transform::template process_tile<0, 0, 2, 0>, // Bottom |
| Transform::template process_tile<0, 0, 2, 1>, // Bottom-right |
| Transform::template process_tile<0, 0, 2, 2>, // Bottom-right |
| } |
| }, |
| { |
| { |
| Transform::template process_tile<0, 1, 0, 0>, // Left |
| Transform::template process_tile<0, 1, 0, 1>, // Left AND right |
| Transform::template process_tile<0, 1, 0, 2>, // Left AND right |
| }, |
| { |
| Transform::template process_tile<0, 1, 1, 0>, // Left-bottom |
| Transform::template process_tile<0, 1, 1, 1>, // Left, bottom AND right |
| Transform::template process_tile<0, 1, 1, 2>, // Left, bottom AND right |
| }, |
| { |
| Transform::template process_tile<0, 1, 2, 0>, // Left-bottom |
| Transform::template process_tile<0, 1, 2, 1>, // Left, bottom AND right |
| Transform::template process_tile<0, 1, 2, 2>, // Left, bottom AND right |
| } |
| }, |
| }, |
| { |
| { |
| { |
| Transform::template process_tile<1, 0, 0, 0>, // Top |
| Transform::template process_tile<1, 0, 0, 1>, // Top-right |
| Transform::template process_tile<1, 0, 0, 2>, // Top-right |
| }, |
| { |
| Transform::template process_tile<1, 0, 1, 0>, // Top AND bottom |
| Transform::template process_tile<1, 0, 1, 1>, // Top, bottom AND right |
| Transform::template process_tile<1, 0, 1, 2>, // Top, bottom AND right |
| }, |
| { |
| Transform::template process_tile<1, 0, 2, 0>, // Top AND bottom |
| Transform::template process_tile<1, 0, 2, 1>, // Top, bottom AND right |
| Transform::template process_tile<1, 0, 2, 2>, // Top, bottom AND right |
| } |
| }, |
| { |
| { |
| Transform::template process_tile<1, 1, 0, 0>, // Top-left |
| Transform::template process_tile<1, 1, 0, 1>, // Top, left AND right |
| Transform::template process_tile<1, 1, 0, 2>, // Top, left AND right |
| }, |
| { |
| Transform::template process_tile<1, 1, 1, 0>, // Top, left AND bottom |
| Transform::template process_tile<1, 1, 1, 1>, // All padded |
| Transform::template process_tile<1, 1, 1, 2>, // All padded |
| }, |
| { |
| Transform::template process_tile<1, 1, 2, 0>, // Top, left AND bottom |
| Transform::template process_tile<1, 1, 2, 1>, // All padded |
| Transform::template process_tile<1, 1, 2, 2>, // All padded |
| } |
| } |
| } |
| }; |
| |
| template struct WinogradGEMM<2, 2, 3, 3>::InputTransform<float>; |
| } // namespace winograd |