| /* |
| * 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/output.hpp" |
| #include "winograd_gemm.hpp" |
| #include "arm.hpp" |
| |
| namespace winograd |
| { |
| |
| using Transform = WinogradGEMM<2, 2, 5, 5>::OutputTransform<float>; |
| |
| template <> |
| template <> |
| int Transform::ops_performed(const Tensor4DShape &shape) |
| { |
| return 0; // TODO |
| } |
| |
| /* F(2x2, 5x5) constructs 2x2 output tiles from a 5x5 convolution. Since we use |
| * enough tiles to cover the output space each output tile may contain 0 or 1 |
| * padded values to the right and bottom columns or rows of the tile, e.g.: |
| * |
| * ___ ___ |
| * | | | X| |
| * |___| |__X| |
| * |
| * ___ ___ |
| * | | | X| |
| * |X_X| |X_X| |
| * |
| * |
| * We provide a specialised output transform for each of these instances. |
| * Consequently we below construct an array of the various padding options, the |
| * array contains pointers to the specific implementations. |
| */ |
| template <> |
| template <> |
| template <int pad_bottom, int pad_right> |
| void Transform::process_tile( |
| const int n_channels, |
| const float* const matrix_base, |
| const int matrix_stride, |
| const float* const biases, |
| float* const output, |
| const int output_row_stride, |
| const int output_col_stride |
| ) |
| { |
| constexpr int cells_i = 2 - pad_bottom; |
| constexpr int cells_j = 2 - pad_right; |
| |
| // Construct a map to the output cells |
| float *outptrs[cells_i][cells_j]; |
| for (int i = 0; i < cells_i; i++) |
| { |
| for (int j = 0; j < cells_j; j++) |
| { |
| outptrs[i][j] = output + i*output_row_stride + j*output_col_stride; |
| } |
| } |
| const float *inptr = matrix_base; |
| const float *bptr = biases; |
| |
| // 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 |
| b = vld1q_f32(bptr); |
| bptr += 4; |
| for (int i = 0; i < cells_i; i++) |
| { |
| for (int j = 0; j < cells_j; j++) |
| { |
| vst1q_f32(outptrs[i][j], vaddq_f32(f[i][j], b)); |
| 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 |
| b = vld1_f32(bptr); |
| bptr += 2; |
| for (int i = 0; i < cells_i; i++) |
| { |
| for (int j = 0; j < cells_j; j++) |
| { |
| vst1_f32(outptrs[i][j], vadd_f32(f[i][j], b)); |
| 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 |
| b = *(bptr++); |
| for (int i = 0; i < cells_i; i++) |
| { |
| for (int j = 0; j < cells_j; j++) |
| { |
| *(outptrs[i][j]++) = f[i][j] + b; |
| } |
| } |
| } |
| } |
| |
| template <> |
| template <> |
| const Transform::TileFn Transform::tile_fns[max_pad_bottom][max_pad_right] = |
| { |
| { |
| Transform::template process_tile<0, 0>, // No padding |
| Transform::template process_tile<0, 1>, // Right padding |
| }, |
| { |
| Transform::template process_tile<1, 0>, // Bottom padding |
| Transform::template process_tile<1, 1>, // Bottom and right padding |
| } |
| }; |
| |
| template struct WinogradGEMM<2, 2, 5, 5>::OutputTransform<float>; |
| } // namespace winograd |