diff options
Diffstat (limited to 'src/core/NEON/kernels/convolution')
7 files changed, 1080 insertions, 8 deletions
diff --git a/src/core/NEON/kernels/convolution/winograd/padding.cpp b/src/core/NEON/kernels/convolution/winograd/padding.cpp index 46fe57c7c9..04aa472c3c 100644 --- a/src/core/NEON/kernels/convolution/winograd/padding.cpp +++ b/src/core/NEON/kernels/convolution/winograd/padding.cpp @@ -85,6 +85,15 @@ template void copy_and_pad_tile( unsigned int, unsigned int, unsigned int, unsigned int, float ); +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +template void copy_and_pad_tile( + unsigned int, unsigned int, unsigned int, + const __fp16 *, unsigned int, unsigned int, + __fp16 *, unsigned int, unsigned int, + unsigned int, unsigned int, unsigned int, unsigned int, __fp16 +); +#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC + template <unsigned int TileRows, unsigned int TileCols> void CopyCropped<TileRows, TileCols>::execute( const size_t size, @@ -163,4 +172,21 @@ template void crop_and_copy_tile( unsigned int crop_right ); +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +template void crop_and_copy_tile( + unsigned int tile_rows, + unsigned int tile_cols, + unsigned int n_channels, + const __fp16 *inptr, + unsigned int in_row_stride, + unsigned int in_col_stride, + __fp16 *outptr, + unsigned int out_row_stride, + unsigned int out_col_stride, + unsigned int crop_top, + unsigned int crop_left, + unsigned int crop_bottom, + unsigned int crop_right +); +#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC } // namespace padding diff --git a/src/core/NEON/kernels/convolution/winograd/winograd.cpp b/src/core/NEON/kernels/convolution/winograd/winograd.cpp index a4eb9fce59..867bb3c7f3 100644 --- a/src/core/NEON/kernels/convolution/winograd/winograd.cpp +++ b/src/core/NEON/kernels/convolution/winograd/winograd.cpp @@ -176,3 +176,7 @@ template class WinogradGEMM<4, 1, 5, 1, WinogradRoots::Integers>::Convolution<fl template class WinogradGEMM<1, 2, 1, 7, WinogradRoots::Integers>::Convolution<float, float, float, float>; template class WinogradGEMM<2, 1, 7, 1, WinogradRoots::Integers>::Convolution<float, float, float, float>; + +#ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC +template class WinogradGEMM<4, 4, 3, 3, WinogradRoots::Integers>::Convolution<__fp16, __fp16, __fp16, __fp16>; +#endif // __ARM_FEATURE_FP16_VECTOR_ARITHMETIC 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 new file mode 100644 index 0000000000..1ea68b5938 --- /dev/null +++ b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_4x4_fp16_fp16_integers.cpp @@ -0,0 +1,257 @@ +/* + * 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_6x6_fp16_fp16_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_6x6_fp16_fp16_integers.cpp new file mode 100644 index 0000000000..3eaf977826 --- /dev/null +++ b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/input_6x6_fp16_fp16_integers.cpp @@ -0,0 +1,277 @@ +/* + * 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/output.hpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output.hpp index fe47ccbde9..ed88098938 100644 --- a/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output.hpp +++ b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output.hpp @@ -48,15 +48,9 @@ MEMBERFN() _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) - : (std::numeric_limits<TOut>::has_infinity) - ? -std::numeric_limits<TOut>::infinity() - : std::numeric_limits<TOut>::lowest()), + ? static_cast<TOut>(0.0f) : TypeBounds<TOut>::lower()), _output_max((activation.type == arm_gemm::Activation::Type::BoundedReLU) - ? static_cast<TOut>(activation.param1) - : (std::numeric_limits<TOut>::has_infinity) - ? std::numeric_limits<TOut>::infinity() - : std::numeric_limits<TOut>::max()), + ? 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)), 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 new file mode 100644 index 0000000000..37b890d1bc --- /dev/null +++ b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/output_4x4_3x3_fp16_fp16_integers.cpp @@ -0,0 +1,255 @@ +/* + * 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/weights_4x4_3x3_fp16_fp16_integers.cpp b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4x4_3x3_fp16_fp16_integers.cpp new file mode 100644 index 0000000000..3c4f8b426c --- /dev/null +++ b/src/core/NEON/kernels/convolution/winograd/winograd_transforms/weights_4x4_3x3_fp16_fp16_integers.cpp @@ -0,0 +1,259 @@ +/* + * 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 |