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Diffstat (limited to 'src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_3x3_fp32.cpp')
| -rw-r--r-- | src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_3x3_fp32.cpp | 409 |
1 files changed, 409 insertions, 0 deletions
diff --git a/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_3x3_fp32.cpp b/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_3x3_fp32.cpp new file mode 100644 index 0000000000..6d8afc0def --- /dev/null +++ b/src/core/NEON/kernels/convolution/winograd/transforms/input_2x2_3x3_fp32.cpp @@ -0,0 +1,409 @@ +/* + * 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<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 |