diff options
Diffstat (limited to 'src/core/NEON/kernels/convolution/winograd/transforms/input_4x4_3x3_fp32.cpp')
-rw-r--r-- | src/core/NEON/kernels/convolution/winograd/transforms/input_4x4_3x3_fp32.cpp | 486 |
1 files changed, 486 insertions, 0 deletions
diff --git a/src/core/NEON/kernels/convolution/winograd/transforms/input_4x4_3x3_fp32.cpp b/src/core/NEON/kernels/convolution/winograd/transforms/input_4x4_3x3_fp32.cpp new file mode 100644 index 0000000000..04d1573e4c --- /dev/null +++ b/src/core/NEON/kernels/convolution/winograd/transforms/input_4x4_3x3_fp32.cpp @@ -0,0 +1,486 @@ +/* + * 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 "arm_compute/core/NEON/kernels/convolution/winograd/transforms/input.hpp" +#include "arm_compute/core/NEON/kernels/convolution/winograd/winograd_gemm.hpp" +#include "arm_compute/core/NEON/kernels/convolution/common/arm.hpp" + +namespace winograd +{ + +using Transform = WinogradGEMM<4, 4, 3, 3>::InputTransform<float>; + +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 12 * 24 * tile_M * tile_N * input_shape.n_channels; +} + +/* F(4x4, 3x3) implies the use of a 6x6 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 | | | +* |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, 1, 2 or 3 rows or columns if the +* padding type is VALID or 1, 2, 3 or 4 rows or columns if the padding +* type is SAME. +* +* 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, 3, 4} +* Padding right in {0, 1, 2, 3, 4} +*/ +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 cells_i = 6 - pad_bottom; + constexpr int cells_j = 6 - pad_right; + + float *outptr = matrix_base; + + // Get pointers into the input tile + const float *x_ptrs[6][6]; + 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[6][6], XTx[6][6], U[6][6]; + for (int i = 0; i < 6; i++) + { + for (int j = 0; j < 6; 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[6][6], XTx[6][6], U[6][6]; + for (int i = 0; i < 6; i++) + { + for (int j = 0; j < 6; j++) + { + x[i][j] = vdupq_n_f32(0.0f); + XTx[i][j] = vdupq_n_f32(0.0f); + } + } + + // Read a 6x6 tile in the Winograd domain + 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] = 4*x[0][j] + -5*x[2][j] + 1*x[4][j]; + XTx[0][j] = vmlsq_n_f32(vmlaq_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] = vmlsq_n_f32(vaddq_f32(x[3][j], x[4][j]), vaddq_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] = vmlaq_n_f32(vsubq_f32(x[4][j], x[3][j]), vsubq_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] = vmlaq_n_f32(vsubq_f32(x[4][j], x[2][j]), vsubq_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] = vmlaq_n_f32(vsubq_f32(x[4][j], x[2][j]), vsubq_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] = vmlsq_n_f32(vmlaq_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 < 6; i++) + { + // U[i][0] = 4*XTx[i][0] + -5*XTx[i][2] + 1*XTx[i][4]; + U[i][0] = vmlsq_n_f32(vmlaq_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] = vmlsq_n_f32(vaddq_f32(XTx[i][3], XTx[i][4]), vaddq_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] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][3]), vsubq_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] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][2]), vsubq_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] = vmlaq_n_f32(vsubq_f32(XTx[i][4], XTx[i][2]), vsubq_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] = vmlsq_n_f32(vmlaq_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 < 6; i++) + { + for (int j = 0; j < 6; 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[6][6], XTx[6][6], U[6][6]; + for (int i = 0; i < 6; i++) + { + for (int j = 0; j < 6; 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 = 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] = 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 < 6; 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 < 6; i++) + { + for (int j = 0; j < 6; 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] = 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 < 6; 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 < 6; i++) + { + for (int j = 0; j < 6; j++, m++) + { + *(outptr + m*matrix_stride) = U[i][j]; + } + } + outptr++; + } +} + +/* In the below, unusual or especially small tiles are routed via the slow + * path whereas common or large tiles are routed through a faster path. + */ +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>, // " " + Transform::template process_tile<0, 0, 0, 3>, // " " + Transform::template process_tile<0, 0, 0, 4>, // " " + }, + { + 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>, // " " + Transform::template process_tile<0, 0, 1, 3>, // " " + Transform::template process_tile<0, 0, 1, 4>, // " " + }, + { + 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>, // " " + Transform::template process_tile<0, 0, 2, 3>, // " " + Transform::template process_tile<0, 0, 2, 4>, // " " + }, + { + Transform::template process_tile<0, 0, 3, 0>, // Bottom + Transform::template process_tile<0, 0, 3, 1>, // Bottom right + Transform::template process_tile<0, 0, 3, 2>, // " " + Transform::template process_tile<0, 0, 3, 3>, // " " + Transform::template process_tile<0, 0, 3, 4>, // " " + }, + { + Transform::template process_tile<0, 0, 4, 0>, // Bottom + Transform::template process_tile<0, 0, 4, 1>, // Bottom right + Transform::template process_tile<0, 0, 4, 2>, // " " + Transform::template process_tile<0, 0, 4, 3>, // " " + Transform::template process_tile<0, 0, 4, 4>, // " " + } + }, + { + { + Transform::template process_tile<0, 1, 0, 0>, // Left + Transform::template process_tile<0, 1, 0, 1>, + Transform::template process_tile<0, 1, 0, 2>, + Transform::template process_tile<0, 1, 0, 3>, + Transform::template process_tile<0, 1, 0, 4>, + }, + { + Transform::template process_tile<0, 1, 1, 0>, // Bottom left + Transform::template process_tile<0, 1, 1, 1>, + Transform::template process_tile<0, 1, 1, 2>, + Transform::template process_tile<0, 1, 1, 3>, + Transform::template process_tile<0, 1, 1, 4>, + }, + { + Transform::template process_tile<0, 1, 2, 0>, // " " + Transform::template process_tile<0, 1, 2, 1>, + Transform::template process_tile<0, 1, 2, 2>, + Transform::template process_tile<0, 1, 2, 3>, + Transform::template process_tile<0, 1, 2, 4>, + }, + { + Transform::template process_tile<0, 1, 3, 0>, // " " + Transform::template process_tile<0, 1, 3, 1>, + Transform::template process_tile<0, 1, 3, 2>, + Transform::template process_tile<0, 1, 3, 3>, + Transform::template process_tile<0, 1, 3, 4>, + }, + { + Transform::template process_tile<0, 1, 4, 0>, // " " + Transform::template process_tile<0, 1, 4, 1>, + Transform::template process_tile<0, 1, 4, 2>, + Transform::template process_tile<0, 1, 4, 3>, + Transform::template process_tile<0, 1, 4, 4>, + } + } + }, + { + { + { + 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>, // " " + Transform::template process_tile<1, 0, 0, 3>, // " " + Transform::template process_tile<1, 0, 0, 4>, // " " + }, + { + Transform::template process_tile<1, 0, 1, 0>, + Transform::template process_tile<1, 0, 1, 1>, + Transform::template process_tile<1, 0, 1, 2>, + Transform::template process_tile<1, 0, 1, 3>, + Transform::template process_tile<1, 0, 1, 4>, + }, + { + Transform::template process_tile<1, 0, 2, 0>, + Transform::template process_tile<1, 0, 2, 1>, + Transform::template process_tile<1, 0, 2, 2>, + Transform::template process_tile<1, 0, 2, 3>, + Transform::template process_tile<1, 0, 2, 4>, + }, + { + Transform::template process_tile<1, 0, 3, 0>, + Transform::template process_tile<1, 0, 3, 1>, + Transform::template process_tile<1, 0, 3, 2>, + Transform::template process_tile<1, 0, 3, 3>, + Transform::template process_tile<1, 0, 3, 4>, + }, + { + Transform::template process_tile<1, 0, 4, 0>, + Transform::template process_tile<1, 0, 4, 1>, + Transform::template process_tile<1, 0, 4, 2>, + Transform::template process_tile<1, 0, 4, 3>, + Transform::template process_tile<1, 0, 4, 4>, + }, + }, + { + { + Transform::template process_tile<1, 1, 0, 0>, // Top left + Transform::template process_tile<1, 1, 0, 1>, + Transform::template process_tile<1, 1, 0, 2>, + Transform::template process_tile<1, 1, 0, 3>, + Transform::template process_tile<1, 1, 0, 4>, + }, + { + Transform::template process_tile<1, 1, 1, 0>, + Transform::template process_tile<1, 1, 1, 1>, + Transform::template process_tile<1, 1, 1, 2>, + Transform::template process_tile<1, 1, 1, 3>, + Transform::template process_tile<1, 1, 1, 4>, + }, + { + Transform::template process_tile<1, 1, 2, 0>, + Transform::template process_tile<1, 1, 2, 1>, + Transform::template process_tile<1, 1, 2, 2>, + Transform::template process_tile<1, 1, 2, 3>, + Transform::template process_tile<1, 1, 2, 4>, + }, + { + Transform::template process_tile<1, 1, 3, 0>, + Transform::template process_tile<1, 1, 3, 1>, + Transform::template process_tile<1, 1, 3, 2>, + Transform::template process_tile<1, 1, 3, 3>, + Transform::template process_tile<1, 1, 3, 4>, + }, + { + Transform::template process_tile<1, 1, 4, 0>, + Transform::template process_tile<1, 1, 4, 1>, + Transform::template process_tile<1, 1, 4, 2>, + Transform::template process_tile<1, 1, 4, 3>, + Transform::template process_tile<1, 1, 4, 4>, + } + } + } +}; + +template struct WinogradGEMM<4, 4, 3, 3>::InputTransform<float>; +} // namespace winograd |