| /* |
| * Copyright (c) 2022 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 <cstddef> |
| #include <arm_neon.h> |
| |
| namespace arm_conv { |
| namespace winograd { |
| namespace weight_transform { |
| |
| void arm_fp32_2x2_5x5( |
| unsigned int n_channels, |
| const float *inptr, const size_t ld_weight_row, const size_t ld_weight_col, |
| float *outptr, const size_t matrix_stride |
| ) |
| { |
| #ifdef __aarch64__ |
| // For each output channel |
| for (; n_channels >= 4; n_channels -= 4) |
| { |
| // Matrices used and computed in this kernel |
| float32x4_t w[5][5], Ww[6][5], V[6][6]; |
| |
| // Read weights |
| for (int i = 0; i < 5; i++) |
| { |
| for (int j = 0; j < 5; j++) |
| { |
| w[i][j] = vld1q_f32(inptr + i*ld_weight_row + j*ld_weight_col); |
| } |
| } |
| |
| // Compute the matrix W w |
| for (int j = 0; j < 5; j++) |
| { |
| // Ww[0][j] = w[0][j]/4.0f; |
| Ww[0][j] = vmulq_n_f32(w[0][j], 1.0f/4.0f); |
| |
| // Ww[1][j] = -( w[0][j] + w[1][j] + w[2][j] + w[3][j] + w[4][j])/6.0f; |
| Ww[1][j] = vmulq_n_f32( |
| vaddq_f32( |
| vaddq_f32( |
| vaddq_f32(w[1][j], w[0][j]), |
| vaddq_f32(w[3][j], w[2][j]) |
| ), |
| w[4][j] |
| ), |
| -1.0f/6.0f |
| ); |
| |
| // Ww[2][j] = +(-w[0][j] + w[1][j] - w[2][j] + w[3][j] - w[4][j])/6.0f; |
| // Ww[2][j] = ((w[1][j] - w[0][j]) + (w[3][j] - w[2][j]) - w[4][j])/6.0f; |
| Ww[2][j] = vmulq_n_f32( |
| vsubq_f32( |
| vaddq_f32( |
| vsubq_f32(w[1][j], w[0][j]), |
| vsubq_f32(w[3][j], w[2][j]) |
| ), |
| w[4][j] |
| ), |
| 1.0f/6.0f |
| ); |
| |
| // Ww[3][j] = (w[0][j]/8.0f + w[1][j]/4.0f + w[2][j]/2.0f + w[3][j] + 2*w[4][j])/3.0f; |
| Ww[3][j] = vmulq_n_f32( |
| vmlaq_n_f32( |
| vaddq_f32( |
| vaddq_f32(vmulq_n_f32(w[0][j], 1.0f/8.0f), vmulq_n_f32(w[1][j], 1.0f/4.0f)), |
| vaddq_f32(vmulq_n_f32(w[2][j], 1.0f/2.0f), w[3][j]) |
| ), |
| w[4][j], 2.0f |
| ), |
| 1.0f/3.0f |
| ); |
| |
| // Ww[4][j] = (w[0][j]/8.0f - w[1][j]/4.0f + w[2][j]/2.0f - w[3][j] + 2*w[4][j])/3.0f; |
| Ww[4][j] = vmulq_n_f32( |
| vmlaq_n_f32( |
| vaddq_f32( |
| vsubq_f32(vmulq_n_f32(w[0][j], 1.0f/8.0f), vmulq_n_f32(w[1][j], 1.0f/4.0f)), |
| vsubq_f32(vmulq_n_f32(w[2][j], 1.0f/2.0f), w[3][j]) |
| ), |
| w[4][j], 2.0f |
| ), |
| 1.0f/3.0f |
| ); |
| |
| // Ww[5][j] = w[4][j]; |
| Ww[5][j] = w[4][j]; |
| } |
| |
| // Compute V = W w WT |
| for (int i = 0; i < 6; i++) |
| { |
| // V[i][0] = Ww[i][0]/4.0f; |
| V[i][0] = vmulq_n_f32(Ww[i][0], 1.0f/4.0f); |
| |
| // V[i][1] = -( Ww[i][0] + Ww[i][1] + Ww[i][2] + Ww[i][3] + Ww[i][4])/6.0f; |
| V[i][1] = vmulq_n_f32( |
| vaddq_f32( |
| vaddq_f32( |
| vaddq_f32(Ww[i][1], Ww[i][0]), |
| vaddq_f32(Ww[i][3], Ww[i][2]) |
| ), |
| Ww[i][4] |
| ), |
| -1.0f/6.0f |
| ); |
| |
| // V[i][2] = +(-Ww[i][0] + Ww[i][1] - Ww[i][2] + Ww[i][3] - Ww[i][4])/6.0f; |
| // V[i][2] = ((Ww[i][1] - Ww[i][0]) + (Ww[i][3] - Ww[i][2]) - Ww[i][4])/6.0f; |
| V[i][2] = vmulq_n_f32( |
| vsubq_f32( |
| vaddq_f32( |
| vsubq_f32(Ww[i][1], Ww[i][0]), |
| vsubq_f32(Ww[i][3], Ww[i][2]) |
| ), |
| Ww[i][4] |
| ), |
| 1.0f/6.0f |
| ); |
| |
| // V[i][3] = (Ww[i][0]/8.0f + Ww[i][1]/4.0f + Ww[i][2]/2.0f + Ww[i][3] + 2*Ww[i][4])/3.0f; |
| V[i][3] = vmulq_n_f32( |
| vmlaq_n_f32( |
| vaddq_f32( |
| vaddq_f32(vmulq_n_f32(Ww[i][0], 1.0f/8.0f), vmulq_n_f32(Ww[i][1], 1.0f/4.0f)), |
| vaddq_f32(vmulq_n_f32(Ww[i][2], 1.0f/2.0f), Ww[i][3]) |
| ), |
| Ww[i][4], 2.0f |
| ), |
| 1.0f/3.0f |
| ); |
| |
| // V[i][4] = (Ww[i][0]/8.0f - Ww[i][1]/4.0f + Ww[i][2]/2.0f - Ww[i][3] + 2*Ww[i][4])/3.0f; |
| V[i][4] = vmulq_n_f32( |
| vmlaq_n_f32( |
| vaddq_f32( |
| vsubq_f32(vmulq_n_f32(Ww[i][0], 1.0f/8.0f), vmulq_n_f32(Ww[i][1], 1.0f/4.0f)), |
| vsubq_f32(vmulq_n_f32(Ww[i][2], 1.0f/2.0f), Ww[i][3]) |
| ), |
| Ww[i][4], 2.0f |
| ), |
| 1.0f/3.0f |
| ); |
| |
| // V[i][5] = Ww[i][4]; |
| V[i][5] = Ww[i][4]; |
| } |
| |
| // Store the transformed weights |
| for (int i = 0, m = 0; i < 6; i++) |
| { |
| for (int j = 0; j < 6; j++, m++) |
| { |
| vst1q_f32(outptr + m*matrix_stride, V[i][j]); |
| } |
| } |
| |
| inptr += 4; |
| outptr += 4; |
| } |
| #endif // __aarch64__ |
| for (; n_channels >= 2; n_channels -= 2) |
| { |
| // Matrices used and computed in this kernel |
| float32x2_t w[5][5], Ww[6][5], V[6][6]; |
| |
| // Read weights |
| for (int i = 0; i < 5; i++) |
| { |
| for (int j = 0; j < 5; j++) |
| { |
| w[i][j] = vld1_f32(inptr + i*ld_weight_row + j*ld_weight_col); |
| } |
| } |
| |
| // Compute the matrix W w |
| for (int j = 0; j < 5; j++) |
| { |
| // Ww[0][j] = w[0][j]/4.0f; |
| Ww[0][j] = vmul_n_f32(w[0][j], 1.0f/4.0f); |
| |
| // Ww[1][j] = -( w[0][j] + w[1][j] + w[2][j] + w[3][j] + w[4][j])/6.0f; |
| Ww[1][j] = vmul_n_f32( |
| vadd_f32( |
| vadd_f32( |
| vadd_f32(w[1][j], w[0][j]), |
| vadd_f32(w[3][j], w[2][j]) |
| ), |
| w[4][j] |
| ), |
| -1.0f/6.0f |
| ); |
| |
| // Ww[2][j] = +(-w[0][j] + w[1][j] - w[2][j] + w[3][j] - w[4][j])/6.0f; |
| // Ww[2][j] = ((w[1][j] - w[0][j]) + (w[3][j] - w[2][j]) - w[4][j])/6.0f; |
| Ww[2][j] = vmul_n_f32( |
| vsub_f32( |
| vadd_f32( |
| vsub_f32(w[1][j], w[0][j]), |
| vsub_f32(w[3][j], w[2][j]) |
| ), |
| w[4][j] |
| ), |
| 1.0f/6.0f |
| ); |
| |
| // Ww[3][j] = (w[0][j]/8.0f + w[1][j]/4.0f + w[2][j]/2.0f + w[3][j] + 2*w[4][j])/3.0f; |
| Ww[3][j] = vmul_n_f32( |
| vmla_n_f32( |
| vadd_f32( |
| vadd_f32(vmul_n_f32(w[0][j], 1.0f/8.0f), vmul_n_f32(w[1][j], 1.0f/4.0f)), |
| vadd_f32(vmul_n_f32(w[2][j], 1.0f/2.0f), w[3][j]) |
| ), |
| w[4][j], 2.0f |
| ), |
| 1.0f/3.0f |
| ); |
| |
| // Ww[4][j] = (w[0][j]/8.0f - w[1][j]/4.0f + w[2][j]/2.0f - w[3][j] + 2*w[4][j])/3.0f; |
| Ww[4][j] = vmul_n_f32( |
| vmla_n_f32( |
| vadd_f32( |
| vsub_f32(vmul_n_f32(w[0][j], 1.0f/8.0f), vmul_n_f32(w[1][j], 1.0f/4.0f)), |
| vsub_f32(vmul_n_f32(w[2][j], 1.0f/2.0f), w[3][j]) |
| ), |
| w[4][j], 2.0f |
| ), |
| 1.0f/3.0f |
| ); |
| |
| // Ww[5][j] = w[4][j]; |
| Ww[5][j] = w[4][j]; |
| } |
| |
| // Compute V = W w WT |
| for (int i = 0; i < 6; i++) |
| { |
| // V[i][0] = Ww[i][0]/4.0f; |
| V[i][0] = vmul_n_f32(Ww[i][0], 1.0f/4.0f); |
| |
| // V[i][1] = -( Ww[i][0] + Ww[i][1] + Ww[i][2] + Ww[i][3] + Ww[i][4])/6.0f; |
| V[i][1] = vmul_n_f32( |
| vadd_f32( |
| vadd_f32( |
| vadd_f32(Ww[i][1], Ww[i][0]), |
| vadd_f32(Ww[i][3], Ww[i][2]) |
| ), |
| Ww[i][4] |
| ), |
| -1.0f/6.0f |
| ); |
| |
| // V[i][2] = +(-Ww[i][0] + Ww[i][1] - Ww[i][2] + Ww[i][3] - Ww[i][4])/6.0f; |
| // V[i][2] = ((Ww[i][1] - Ww[i][0]) + (Ww[i][3] - Ww[i][2]) - Ww[i][4])/6.0f; |
| V[i][2] = vmul_n_f32( |
| vsub_f32( |
| vadd_f32( |
| vsub_f32(Ww[i][1], Ww[i][0]), |
| vsub_f32(Ww[i][3], Ww[i][2]) |
| ), |
| Ww[i][4] |
| ), |
| 1.0f/6.0f |
| ); |
| |
| // V[i][3] = (Ww[i][0]/8.0f + Ww[i][1]/4.0f + Ww[i][2]/2.0f + Ww[i][3] + 2*Ww[i][4])/3.0f; |
| V[i][3] = vmul_n_f32( |
| vmla_n_f32( |
| vadd_f32( |
| vadd_f32(vmul_n_f32(Ww[i][0], 1.0f/8.0f), vmul_n_f32(Ww[i][1], 1.0f/4.0f)), |
| vadd_f32(vmul_n_f32(Ww[i][2], 1.0f/2.0f), Ww[i][3]) |
| ), |
| Ww[i][4], 2.0f |
| ), |
| 1.0f/3.0f |
| ); |
| |
| // V[i][4] = (Ww[i][0]/8.0f - Ww[i][1]/4.0f + Ww[i][2]/2.0f - Ww[i][3] + 2*Ww[i][4])/3.0f; |
| V[i][4] = vmul_n_f32( |
| vmla_n_f32( |
| vadd_f32( |
| vsub_f32(vmul_n_f32(Ww[i][0], 1.0f/8.0f), vmul_n_f32(Ww[i][1], 1.0f/4.0f)), |
| vsub_f32(vmul_n_f32(Ww[i][2], 1.0f/2.0f), Ww[i][3]) |
| ), |
| Ww[i][4], 2.0f |
| ), |
| 1.0f/3.0f |
| ); |
| |
| // V[i][5] = Ww[i][4]; |
| V[i][5] = Ww[i][4]; |
| } |
| |
| // Store the transformed weights |
| for (int i = 0, m = 0; i < 6; i++) |
| { |
| for (int j = 0; j < 6; j++, m++) |
| { |
| vst1_f32(outptr + m*matrix_stride, V[i][j]); |
| } |
| } |
| |
| inptr += 2; |
| outptr += 2; |
| } |
| for (; n_channels; n_channels--) |
| { |
| // Matrices used and computed in this kernel |
| float w[5][5], Ww[6][5], V[6][6]; |
| |
| // Read weights |
| for (int i = 0; i < 5; i++) |
| { |
| for (int j = 0; j < 5; j++) |
| { |
| w[i][j] = *(inptr + i*ld_weight_row + j*ld_weight_col); |
| } |
| } |
| |
| // Compute the matrix W w |
| for (int j = 0; j < 5; j++) |
| { |
| Ww[0][j] = w[0][j]/4.0f; |
| Ww[1][j] = -( w[0][j] + w[1][j] + w[2][j] + w[3][j] + w[4][j])/6.0f; |
| Ww[2][j] = +(-w[0][j] + w[1][j] - w[2][j] + w[3][j] - w[4][j])/6.0f; |
| Ww[3][j] = (w[0][j]/8.0f + w[1][j]/4.0f + w[2][j]/2.0f + w[3][j] + 2*w[4][j])/3.0f; |
| Ww[4][j] = (w[0][j]/8.0f - w[1][j]/4.0f + w[2][j]/2.0f - w[3][j] + 2*w[4][j])/3.0f; |
| Ww[5][j] = w[4][j]; |
| } |
| |
| // Compute V = W w WT |
| for (int i = 0; i < 6; i++) |
| { |
| V[i][0] = Ww[i][0]/4.0f; |
| V[i][1] = -( Ww[i][0] + Ww[i][1] + Ww[i][2] + Ww[i][3] + Ww[i][4])/6.0f; |
| V[i][2] = +(-Ww[i][0] + Ww[i][1] - Ww[i][2] + Ww[i][3] - Ww[i][4])/6.0f; |
| V[i][3] = (Ww[i][0]/8.0f + Ww[i][1]/4.0f + Ww[i][2]/2.0f + Ww[i][3] + 2*Ww[i][4])/3.0f; |
| V[i][4] = (Ww[i][0]/8.0f - Ww[i][1]/4.0f + Ww[i][2]/2.0f - Ww[i][3] + 2*Ww[i][4])/3.0f; |
| V[i][5] = Ww[i][4]; |
| } |
| |
| // 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]; |
| } |
| } |
| |
| inptr++; |
| outptr++; |
| } |
| } |
| |
| } // namespace weight_transform |
| } // namespace winograd |
| } // namespace arm_conv |