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| // Tencent is pleased to support the open source community by making ncnn available. | |
| // | |
| // Copyright (C) 2023 THL A29 Limited, a Tencent company. All rights reserved. | |
| // | |
| // Licensed under the BSD 3-Clause License (the "License"); you may not use this file except | |
| // in compliance with the License. You may obtain a copy of the License at | |
| // | |
| // https://opensource.org/licenses/BSD-3-Clause | |
| // | |
| // Unless required by applicable law or agreed to in writing, software distributed | |
| // under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR | |
| // CONDITIONS OF ANY KIND, either express or implied. See the License for the | |
| // specific language governing permissions and limitations under the License. | |
| static void convolution1d_transform_kernel_packed(const Mat& kernel, Mat& kernel_tm, int inh, int outh, int kernel_w) | |
| { | |
| // src = kw-inh-outh | |
| // dst = pb-pa-kw-inh/pa-outh/pb | |
| // clang-format off | |
| // *INDENT-OFF* | |
| if (outh >= 8) | |
| { | |
| if (inh >= 8) | |
| kernel_tm.create(8 * 8 * kernel_w, inh / 8 + (inh % 8) / 4 + (inh % 4) / 2 + inh % 2, outh / 8 + (outh % 8) / 4 + (outh % 4) / 2 + outh % 2); | |
| else if (inh >= 4) | |
| kernel_tm.create(8 * 4 * kernel_w, inh / 4 + (inh % 4) / 2 + inh % 2, outh / 8 + (outh % 8) / 4 + (outh % 4) / 2 + outh % 2); | |
| else if (inh >= 2) | |
| kernel_tm.create(8 * 2 * kernel_w, inh / 2 + inh % 2, outh / 8 + (outh % 8) / 4 + (outh % 4) / 2 + outh % 2); | |
| else | |
| kernel_tm.create(8 * kernel_w, inh, outh / 8 + (outh % 8) / 4 + (outh % 4) / 2 + outh % 2); | |
| } | |
| else | |
| if (outh >= 4) | |
| { | |
| if (inh >= 8) | |
| kernel_tm.create(4 * 8 * kernel_w, inh / 8 + (inh % 8) / 4 + (inh % 4) / 2 + inh % 2, outh / 4 + (outh % 4) / 2 + outh % 2); | |
| else | |
| if (inh >= 4) | |
| kernel_tm.create(4 * 4 * kernel_w, inh / 4 + (inh % 4) / 2 + inh % 2, outh / 4 + (outh % 4) / 2 + outh % 2); | |
| else if (inh >= 2) | |
| kernel_tm.create(4 * 2 * kernel_w, inh / 2 + inh % 2, outh / 4 + (outh % 4) / 2 + outh % 2); | |
| else | |
| kernel_tm.create(4 * kernel_w, inh, outh / 4 + (outh % 4) / 2 + outh % 2); | |
| } | |
| else | |
| if (outh >= 2) | |
| { | |
| if (inh >= 8) | |
| kernel_tm.create(2 * 8 * kernel_w, inh / 8 + (inh % 8) / 4 + (inh % 4) / 2 + inh % 2, outh / 2 + outh % 2); | |
| else | |
| if (inh >= 4) | |
| kernel_tm.create(2 * 4 * kernel_w, inh / 4 + (inh % 4) / 2 + inh % 2, outh / 2 + outh % 2); | |
| else | |
| if (inh >= 2) | |
| kernel_tm.create(2 * 2 * kernel_w, inh / 2 + inh % 2, outh / 2 + outh % 2); | |
| else | |
| kernel_tm.create(2 * kernel_w, inh, outh / 2 + outh % 2); | |
| } | |
| else | |
| { | |
| if (inh >= 8) | |
| kernel_tm.create(8 * kernel_w, inh / 8 + (inh % 8) / 4 + (inh % 4) / 2 + inh % 2, outh); | |
| else | |
| if (inh >= 4) | |
| kernel_tm.create(4 * kernel_w, inh / 4 + (inh % 4) / 2 + inh % 2, outh); | |
| else | |
| if (inh >= 2) | |
| kernel_tm.create(2 * kernel_w, inh / 2 + inh % 2, outh); | |
| else | |
| kernel_tm.create(kernel_w, inh, outh); | |
| } | |
| // *INDENT-ON* | |
| // clang-format on | |
| int q = 0; | |
| for (; q + 7 < outh; q += 8) | |
| { | |
| const float* kptr0 = (const float*)kernel + q * inh * kernel_w; | |
| const float* kptr1 = (const float*)kernel + (q + 1) * inh * kernel_w; | |
| const float* kptr2 = (const float*)kernel + (q + 2) * inh * kernel_w; | |
| const float* kptr3 = (const float*)kernel + (q + 3) * inh * kernel_w; | |
| const float* kptr4 = (const float*)kernel + (q + 4) * inh * kernel_w; | |
| const float* kptr5 = (const float*)kernel + (q + 5) * inh * kernel_w; | |
| const float* kptr6 = (const float*)kernel + (q + 6) * inh * kernel_w; | |
| const float* kptr7 = (const float*)kernel + (q + 7) * inh * kernel_w; | |
| float* g00 = kernel_tm.channel(q / 8); | |
| int p = 0; | |
| for (; p + 7 < inh; p += 8) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w; | |
| const float* k1 = kptr1 + p * kernel_w; | |
| const float* k2 = kptr2 + p * kernel_w; | |
| const float* k3 = kptr3 + p * kernel_w; | |
| const float* k4 = kptr4 + p * kernel_w; | |
| const float* k5 = kptr5 + p * kernel_w; | |
| const float* k6 = kptr6 + p * kernel_w; | |
| const float* k7 = kptr7 + p * kernel_w; | |
| for (int i = 0; i < 8; i++) | |
| { | |
| g00[0] = k0[k]; | |
| g00[1] = k1[k]; | |
| g00[2] = k2[k]; | |
| g00[3] = k3[k]; | |
| g00[4] = k4[k]; | |
| g00[5] = k5[k]; | |
| g00[6] = k6[k]; | |
| g00[7] = k7[k]; | |
| k0 += kernel_w; | |
| k1 += kernel_w; | |
| k2 += kernel_w; | |
| k3 += kernel_w; | |
| k4 += kernel_w; | |
| k5 += kernel_w; | |
| k6 += kernel_w; | |
| k7 += kernel_w; | |
| g00 += 8; | |
| } | |
| } | |
| } | |
| for (; p + 3 < inh; p += 4) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w; | |
| const float* k1 = kptr1 + p * kernel_w; | |
| const float* k2 = kptr2 + p * kernel_w; | |
| const float* k3 = kptr3 + p * kernel_w; | |
| const float* k4 = kptr4 + p * kernel_w; | |
| const float* k5 = kptr5 + p * kernel_w; | |
| const float* k6 = kptr6 + p * kernel_w; | |
| const float* k7 = kptr7 + p * kernel_w; | |
| for (int i = 0; i < 4; i++) | |
| { | |
| g00[0] = k0[k]; | |
| g00[1] = k1[k]; | |
| g00[2] = k2[k]; | |
| g00[3] = k3[k]; | |
| g00[4] = k4[k]; | |
| g00[5] = k5[k]; | |
| g00[6] = k6[k]; | |
| g00[7] = k7[k]; | |
| k0 += kernel_w; | |
| k1 += kernel_w; | |
| k2 += kernel_w; | |
| k3 += kernel_w; | |
| k4 += kernel_w; | |
| k5 += kernel_w; | |
| k6 += kernel_w; | |
| k7 += kernel_w; | |
| g00 += 8; | |
| } | |
| } | |
| } | |
| for (; p + 1 < inh; p += 2) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w; | |
| const float* k1 = kptr1 + p * kernel_w; | |
| const float* k2 = kptr2 + p * kernel_w; | |
| const float* k3 = kptr3 + p * kernel_w; | |
| const float* k4 = kptr4 + p * kernel_w; | |
| const float* k5 = kptr5 + p * kernel_w; | |
| const float* k6 = kptr6 + p * kernel_w; | |
| const float* k7 = kptr7 + p * kernel_w; | |
| for (int i = 0; i < 2; i++) | |
| { | |
| g00[0] = k0[k]; | |
| g00[1] = k1[k]; | |
| g00[2] = k2[k]; | |
| g00[3] = k3[k]; | |
| g00[4] = k4[k]; | |
| g00[5] = k5[k]; | |
| g00[6] = k6[k]; | |
| g00[7] = k7[k]; | |
| k0 += kernel_w; | |
| k1 += kernel_w; | |
| k2 += kernel_w; | |
| k3 += kernel_w; | |
| k4 += kernel_w; | |
| k5 += kernel_w; | |
| k6 += kernel_w; | |
| k7 += kernel_w; | |
| g00 += 8; | |
| } | |
| } | |
| } | |
| for (; p < inh; p++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w; | |
| const float* k1 = kptr1 + p * kernel_w; | |
| const float* k2 = kptr2 + p * kernel_w; | |
| const float* k3 = kptr3 + p * kernel_w; | |
| const float* k4 = kptr4 + p * kernel_w; | |
| const float* k5 = kptr5 + p * kernel_w; | |
| const float* k6 = kptr6 + p * kernel_w; | |
| const float* k7 = kptr7 + p * kernel_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| g00[0] = k0[k]; | |
| g00[1] = k1[k]; | |
| g00[2] = k2[k]; | |
| g00[3] = k3[k]; | |
| g00[4] = k4[k]; | |
| g00[5] = k5[k]; | |
| g00[6] = k6[k]; | |
| g00[7] = k7[k]; | |
| g00 += 8; | |
| } | |
| } | |
| } | |
| for (; q + 3 < outh; q += 4) | |
| { | |
| const float* kptr0 = (const float*)kernel + q * inh * kernel_w; | |
| const float* kptr1 = (const float*)kernel + (q + 1) * inh * kernel_w; | |
| const float* kptr2 = (const float*)kernel + (q + 2) * inh * kernel_w; | |
| const float* kptr3 = (const float*)kernel + (q + 3) * inh * kernel_w; | |
| float* g00 = kernel_tm.channel(q / 8 + (q % 8) / 4); | |
| float* g00 = kernel_tm.channel(q / 4); | |
| int p = 0; | |
| for (; p + 7 < inh; p += 8) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w; | |
| const float* k1 = kptr1 + p * kernel_w; | |
| const float* k2 = kptr2 + p * kernel_w; | |
| const float* k3 = kptr3 + p * kernel_w; | |
| for (int i = 0; i < 8; i++) | |
| { | |
| g00[0] = k0[k]; | |
| g00[1] = k1[k]; | |
| g00[2] = k2[k]; | |
| g00[3] = k3[k]; | |
| k0 += kernel_w; | |
| k1 += kernel_w; | |
| k2 += kernel_w; | |
| k3 += kernel_w; | |
| g00 += 4; | |
| } | |
| } | |
| } | |
| for (; p + 3 < inh; p += 4) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w; | |
| const float* k1 = kptr1 + p * kernel_w; | |
| const float* k2 = kptr2 + p * kernel_w; | |
| const float* k3 = kptr3 + p * kernel_w; | |
| for (int i = 0; i < 4; i++) | |
| { | |
| g00[0] = k0[k]; | |
| g00[1] = k1[k]; | |
| g00[2] = k2[k]; | |
| g00[3] = k3[k]; | |
| k0 += kernel_w; | |
| k1 += kernel_w; | |
| k2 += kernel_w; | |
| k3 += kernel_w; | |
| g00 += 4; | |
| } | |
| } | |
| } | |
| for (; p + 1 < inh; p += 2) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w; | |
| const float* k1 = kptr1 + p * kernel_w; | |
| const float* k2 = kptr2 + p * kernel_w; | |
| const float* k3 = kptr3 + p * kernel_w; | |
| for (int i = 0; i < 2; i++) | |
| { | |
| g00[0] = k0[k]; | |
| g00[1] = k1[k]; | |
| g00[2] = k2[k]; | |
| g00[3] = k3[k]; | |
| k0 += kernel_w; | |
| k1 += kernel_w; | |
| k2 += kernel_w; | |
| k3 += kernel_w; | |
| g00 += 4; | |
| } | |
| } | |
| } | |
| for (; p < inh; p++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w; | |
| const float* k1 = kptr1 + p * kernel_w; | |
| const float* k2 = kptr2 + p * kernel_w; | |
| const float* k3 = kptr3 + p * kernel_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| g00[0] = k0[k]; | |
| g00[1] = k1[k]; | |
| g00[2] = k2[k]; | |
| g00[3] = k3[k]; | |
| g00 += 4; | |
| } | |
| } | |
| } | |
| for (; q + 1 < outh; q += 2) | |
| { | |
| const float* kptr0 = (const float*)kernel + q * inh * kernel_w; | |
| const float* kptr1 = (const float*)kernel + (q + 1) * inh * kernel_w; | |
| float* g00 = kernel_tm.channel(q / 8 + (q % 8) / 4 + (q % 4) / 2); | |
| float* g00 = kernel_tm.channel(q / 4 + (q % 4) / 2); | |
| float* g00 = kernel_tm.channel(q / 2); | |
| int p = 0; | |
| for (; p + 7 < inh; p += 8) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w + k; | |
| const float* k1 = kptr1 + p * kernel_w + k; | |
| g00[0] = k0[0]; | |
| g00[1] = k0[kernel_w]; | |
| g00[2] = k0[kernel_w * 2]; | |
| g00[3] = k0[kernel_w * 3]; | |
| g00[4] = k0[kernel_w * 4]; | |
| g00[5] = k0[kernel_w * 5]; | |
| g00[6] = k0[kernel_w * 6]; | |
| g00[7] = k0[kernel_w * 7]; | |
| g00[8] = k1[0]; | |
| g00[9] = k1[kernel_w]; | |
| g00[10] = k1[kernel_w * 2]; | |
| g00[11] = k1[kernel_w * 3]; | |
| g00[12] = k1[kernel_w * 4]; | |
| g00[13] = k1[kernel_w * 5]; | |
| g00[14] = k1[kernel_w * 6]; | |
| g00[15] = k1[kernel_w * 7]; | |
| g00 += 16; | |
| } | |
| } | |
| for (; p + 3 < inh; p += 4) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w + k; | |
| const float* k1 = kptr1 + p * kernel_w + k; | |
| g00[0] = k0[0]; | |
| g00[1] = k0[kernel_w]; | |
| g00[2] = k0[kernel_w * 2]; | |
| g00[3] = k0[kernel_w * 3]; | |
| g00[4] = k1[0]; | |
| g00[5] = k1[kernel_w]; | |
| g00[6] = k1[kernel_w * 2]; | |
| g00[7] = k1[kernel_w * 3]; | |
| g00 += 8; | |
| } | |
| } | |
| for (; p + 1 < inh; p += 2) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w; | |
| const float* k1 = kptr1 + p * kernel_w; | |
| for (int i = 0; i < 2; i++) | |
| { | |
| g00[0] = k0[k]; | |
| g00[1] = k1[k]; | |
| k0 += kernel_w; | |
| k1 += kernel_w; | |
| g00 += 2; | |
| } | |
| } | |
| } | |
| for (; p < inh; p++) | |
| { | |
| const float* k0 = kptr0 + p * kernel_w; | |
| const float* k1 = kptr1 + p * kernel_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| g00[0] = k0[k]; | |
| g00[1] = k1[k]; | |
| g00 += 2; | |
| } | |
| } | |
| } | |
| for (; q < outh; q++) | |
| { | |
| const float* kptr = (const float*)kernel + q * inh * kernel_w; | |
| float* g00 = kernel_tm.channel(q / 8 + (q % 8) / 4 + (q % 4) / 2 + q % 2); | |
| float* g00 = kernel_tm.channel(q / 4 + (q % 4) / 2 + q % 2); | |
| float* g00 = kernel_tm.channel(q / 2 + q % 2); | |
| int p = 0; | |
| for (; p + 7 < inh; p += 8) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr + p * kernel_w; | |
| for (int i = 0; i < 8; i++) | |
| { | |
| g00[0] = k0[k]; | |
| k0 += kernel_w; | |
| g00 += 1; | |
| } | |
| } | |
| } | |
| for (; p + 3 < inh; p += 4) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr + p * kernel_w; | |
| for (int i = 0; i < 4; i++) | |
| { | |
| g00[0] = k0[k]; | |
| k0 += kernel_w; | |
| g00 += 1; | |
| } | |
| } | |
| } | |
| for (; p + 1 < inh; p += 2) | |
| { | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| const float* k0 = kptr + p * kernel_w; | |
| for (int i = 0; i < 2; i++) | |
| { | |
| g00[0] = k0[k]; | |
| k0 += kernel_w; | |
| g00 += 1; | |
| } | |
| } | |
| } | |
| for (; p < inh; p++) | |
| { | |
| const float* k0 = kptr + p * kernel_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| g00[0] = k0[k]; | |
| g00++; | |
| } | |
| } | |
| } | |
| } | |
| static void convolution1d_packed(const Mat& bottom_blob, Mat& top_blob, const Mat& weight_data_tm, const Mat& bias_data, int kernel_w, int dilation_w, int stride_w, int activation_type, const Mat& activation_params, const Option& opt) | |
| { | |
| const int elempack = bottom_blob.elempack; | |
| const int inh = bottom_blob.h * elempack; | |
| const int N = bottom_blob.w * elempack; | |
| const int outw = top_blob.w; | |
| const int out_elempack = top_blob.elempack; | |
| const int outh = top_blob.h * out_elempack; | |
| const int M = top_blob.w * out_elempack; | |
| const float* bias_data_ptr = bias_data; | |
| int nn_outh = 0; | |
| int remain_outh_start = 0; | |
| nn_outh = (outh - remain_outh_start) / 8; | |
| for (int pp = 0; pp < nn_outh; pp++) | |
| { | |
| const int p = remain_outh_start + pp * 8; | |
| // shadowed variable for less openmp task args | |
| const int elempack = bottom_blob.elempack; | |
| const int inh = bottom_blob.h * elempack; | |
| const int outw = top_blob.w; | |
| const int out_elempack = top_blob.elempack; | |
| float* outptr = top_blob.row(p / out_elempack); | |
| for (int j = 0; j < outw; j++) | |
| { | |
| float32x4_t _sum0 = vdupq_n_f32(0.f); | |
| float32x4_t _sum1 = vdupq_n_f32(0.f); | |
| float32x4_t _sum2 = vdupq_n_f32(0.f); | |
| float32x4_t _sum3 = vdupq_n_f32(0.f); | |
| float32x4_t _sum4 = vdupq_n_f32(0.f); | |
| float32x4_t _sum5 = vdupq_n_f32(0.f); | |
| float32x4_t _sum6 = vdupq_n_f32(0.f); | |
| float32x4_t _sum7 = vdupq_n_f32(0.f); | |
| if (bias_data_ptr) | |
| { | |
| _sum0 = vld1q_f32(bias_data_ptr + p); | |
| _sum1 = vld1q_f32(bias_data_ptr + p + 4); | |
| } | |
| const float* kptr = weight_data_tm.channel(p / 8); | |
| int q = 0; | |
| for (; q + 7 < inh; q += 8) | |
| { | |
| const float* r0 = bottom_blob.row(q / elempack) + j * stride_w * elempack; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float32x4_t _r0; | |
| float32x4_t _r1; | |
| if (elempack == 4) | |
| { | |
| _r0 = vld1q_f32(r0); | |
| _r1 = vld1q_f32(r0 + N); | |
| r0 += dilation_w * 4; | |
| } | |
| else // if (elempack == 1) | |
| { | |
| _r0 = float32x4_t(); | |
| _r1 = float32x4_t(); | |
| _r0 = vsetq_lane_f32(r0[0], _r0, 0); | |
| _r0 = vsetq_lane_f32(r0[N], _r0, 1); | |
| _r0 = vsetq_lane_f32(r0[N * 2], _r0, 2); | |
| _r0 = vsetq_lane_f32(r0[N * 3], _r0, 3); | |
| _r1 = vsetq_lane_f32(r0[N * 4], _r1, 0); | |
| _r1 = vsetq_lane_f32(r0[N * 5], _r1, 1); | |
| _r1 = vsetq_lane_f32(r0[N * 6], _r1, 2); | |
| _r1 = vsetq_lane_f32(r0[N * 7], _r1, 3); | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w0 = vld1q_f32(kptr); | |
| float32x4_t _w1 = vld1q_f32(kptr + 4); | |
| float32x4_t _w2 = vld1q_f32(kptr + 4 * 2); | |
| float32x4_t _w3 = vld1q_f32(kptr + 4 * 3); | |
| float32x4_t _w4 = vld1q_f32(kptr + 4 * 4); | |
| float32x4_t _w5 = vld1q_f32(kptr + 4 * 5); | |
| float32x4_t _w6 = vld1q_f32(kptr + 4 * 6); | |
| float32x4_t _w7 = vld1q_f32(kptr + 4 * 7); | |
| float32x4_t _w8 = vld1q_f32(kptr + 4 * 8); | |
| float32x4_t _w9 = vld1q_f32(kptr + 4 * 9); | |
| float32x4_t _wa = vld1q_f32(kptr + 4 * 10); | |
| float32x4_t _wb = vld1q_f32(kptr + 4 * 11); | |
| float32x4_t _wc = vld1q_f32(kptr + 4 * 12); | |
| float32x4_t _wd = vld1q_f32(kptr + 4 * 13); | |
| float32x4_t _we = vld1q_f32(kptr + 4 * 14); | |
| float32x4_t _wf = vld1q_f32(kptr + 4 * 15); | |
| _sum0 = vfmaq_laneq_f32(_sum0, _w0, _r0, 0); | |
| _sum1 = vfmaq_laneq_f32(_sum1, _w1, _r0, 0); | |
| _sum2 = vfmaq_laneq_f32(_sum2, _w2, _r0, 1); | |
| _sum3 = vfmaq_laneq_f32(_sum3, _w3, _r0, 1); | |
| _sum4 = vfmaq_laneq_f32(_sum4, _w4, _r0, 2); | |
| _sum5 = vfmaq_laneq_f32(_sum5, _w5, _r0, 2); | |
| _sum6 = vfmaq_laneq_f32(_sum6, _w6, _r0, 3); | |
| _sum7 = vfmaq_laneq_f32(_sum7, _w7, _r0, 3); | |
| _sum0 = vfmaq_laneq_f32(_sum0, _w8, _r1, 0); | |
| _sum1 = vfmaq_laneq_f32(_sum1, _w9, _r1, 0); | |
| _sum2 = vfmaq_laneq_f32(_sum2, _wa, _r1, 1); | |
| _sum3 = vfmaq_laneq_f32(_sum3, _wb, _r1, 1); | |
| _sum4 = vfmaq_laneq_f32(_sum4, _wc, _r1, 2); | |
| _sum5 = vfmaq_laneq_f32(_sum5, _wd, _r1, 2); | |
| _sum6 = vfmaq_laneq_f32(_sum6, _we, _r1, 3); | |
| _sum7 = vfmaq_laneq_f32(_sum7, _wf, _r1, 3); | |
| kptr += 64; | |
| } | |
| } | |
| for (; q + 3 < inh; q += 4) | |
| { | |
| const float* r0 = bottom_blob.row(q / elempack) + j * stride_w * elempack; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float32x4_t _r0; | |
| if (elempack == 4) | |
| { | |
| _r0 = vld1q_f32(r0); | |
| r0 += dilation_w * 4; | |
| } | |
| else // if (elempack == 1) | |
| { | |
| _r0 = float32x4_t(); | |
| _r0 = vsetq_lane_f32(r0[0], _r0, 0); | |
| _r0 = vsetq_lane_f32(r0[N], _r0, 1); | |
| _r0 = vsetq_lane_f32(r0[N * 2], _r0, 2); | |
| _r0 = vsetq_lane_f32(r0[N * 3], _r0, 3); | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w0 = vld1q_f32(kptr); | |
| float32x4_t _w1 = vld1q_f32(kptr + 4); | |
| float32x4_t _w2 = vld1q_f32(kptr + 4 * 2); | |
| float32x4_t _w3 = vld1q_f32(kptr + 4 * 3); | |
| float32x4_t _w4 = vld1q_f32(kptr + 4 * 4); | |
| float32x4_t _w5 = vld1q_f32(kptr + 4 * 5); | |
| float32x4_t _w6 = vld1q_f32(kptr + 4 * 6); | |
| float32x4_t _w7 = vld1q_f32(kptr + 4 * 7); | |
| _sum0 = vfmaq_laneq_f32(_sum0, _w0, _r0, 0); | |
| _sum1 = vfmaq_laneq_f32(_sum1, _w1, _r0, 0); | |
| _sum2 = vfmaq_laneq_f32(_sum2, _w2, _r0, 1); | |
| _sum3 = vfmaq_laneq_f32(_sum3, _w3, _r0, 1); | |
| _sum4 = vfmaq_laneq_f32(_sum4, _w4, _r0, 2); | |
| _sum5 = vfmaq_laneq_f32(_sum5, _w5, _r0, 2); | |
| _sum6 = vfmaq_laneq_f32(_sum6, _w6, _r0, 3); | |
| _sum7 = vfmaq_laneq_f32(_sum7, _w7, _r0, 3); | |
| kptr += 32; | |
| } | |
| } | |
| for (; q + 1 < inh; q += 2) | |
| { | |
| const float* r0 = bottom_blob.row(q) + j * stride_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float val0; | |
| float val1; | |
| // if (elempack == 1) | |
| { | |
| val0 = r0[0]; | |
| val1 = r0[N]; | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w0 = vld1q_f32(kptr); | |
| float32x4_t _w1 = vld1q_f32(kptr + 4); | |
| float32x4_t _w2 = vld1q_f32(kptr + 8); | |
| float32x4_t _w3 = vld1q_f32(kptr + 12); | |
| _sum0 = vfmaq_n_f32(_sum0, _w0, val0); | |
| _sum1 = vfmaq_n_f32(_sum1, _w1, val0); | |
| _sum2 = vfmaq_n_f32(_sum2, _w2, val1); | |
| _sum3 = vfmaq_n_f32(_sum3, _w3, val1); | |
| kptr += 16; | |
| } | |
| } | |
| for (; q < inh; q++) | |
| { | |
| const float* r0 = bottom_blob.row(q) + j * stride_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float32x4_t _val; | |
| // if (elempack == 1) | |
| { | |
| _val = vdupq_n_f32(r0[0]); | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w0 = vld1q_f32(kptr); | |
| float32x4_t _w1 = vld1q_f32(kptr + 4); | |
| _sum0 = vfmaq_f32(_sum0, _w0, _val); | |
| _sum1 = vfmaq_f32(_sum1, _w1, _val); | |
| kptr += 8; | |
| } | |
| } | |
| _sum0 = vaddq_f32(_sum0, _sum2); | |
| _sum1 = vaddq_f32(_sum1, _sum3); | |
| _sum4 = vaddq_f32(_sum4, _sum6); | |
| _sum5 = vaddq_f32(_sum5, _sum7); | |
| _sum0 = vaddq_f32(_sum0, _sum4); | |
| _sum1 = vaddq_f32(_sum1, _sum5); | |
| _sum0 = activation_ps(_sum0, activation_type, activation_params); | |
| _sum1 = activation_ps(_sum1, activation_type, activation_params); | |
| if (out_elempack == 4) | |
| { | |
| vst1q_f32(outptr, _sum0); | |
| vst1q_f32(outptr + M, _sum1); | |
| outptr += 4; | |
| } | |
| else // if (out_elempack == 1) | |
| { | |
| outptr[0] = vgetq_lane_f32(_sum0, 0); | |
| outptr[M] = vgetq_lane_f32(_sum0, 1); | |
| outptr[M * 2] = vgetq_lane_f32(_sum0, 2); | |
| outptr[M * 3] = vgetq_lane_f32(_sum0, 3); | |
| outptr[M * 4] = vgetq_lane_f32(_sum1, 0); | |
| outptr[M * 5] = vgetq_lane_f32(_sum1, 1); | |
| outptr[M * 6] = vgetq_lane_f32(_sum1, 2); | |
| outptr[M * 7] = vgetq_lane_f32(_sum1, 3); | |
| outptr += 1; | |
| } | |
| } | |
| } | |
| remain_outh_start += nn_outh * 8; | |
| nn_outh = (outh - remain_outh_start) / 4; | |
| nn_outh = (outh - remain_outh_start) / 4; | |
| for (int pp = 0; pp < nn_outh; pp++) | |
| { | |
| const int p = remain_outh_start + pp * 4; | |
| // shadowed variable for less openmp task args | |
| const int elempack = bottom_blob.elempack; | |
| const int inh = bottom_blob.h * elempack; | |
| const int outw = top_blob.w; | |
| const int out_elempack = top_blob.elempack; | |
| float* outptr = top_blob.row(p / out_elempack); | |
| for (int j = 0; j < outw; j++) | |
| { | |
| float32x4_t _sum0 = vdupq_n_f32(0.f); | |
| float32x4_t _sum1 = vdupq_n_f32(0.f); | |
| float32x4_t _sum2 = vdupq_n_f32(0.f); | |
| float32x4_t _sum3 = vdupq_n_f32(0.f); | |
| if (bias_data_ptr) | |
| { | |
| _sum0 = vld1q_f32(bias_data_ptr + p); | |
| } | |
| const float* kptr = weight_data_tm.channel(p / 8 + (p % 8) / 4); | |
| const float* kptr = weight_data_tm.channel(p / 4); | |
| int q = 0; | |
| for (; q + 7 < inh; q += 8) | |
| { | |
| const float* r0 = bottom_blob.row(q / elempack) + j * stride_w * elempack; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float32x4_t _r0; | |
| float32x4_t _r1; | |
| if (elempack == 4) | |
| { | |
| _r0 = vld1q_f32(r0); | |
| _r1 = vld1q_f32(r0 + N); | |
| r0 += dilation_w * 4; | |
| } | |
| else // if (elempack == 1) | |
| { | |
| _r0 = float32x4_t(); | |
| _r1 = float32x4_t(); | |
| _r0 = vsetq_lane_f32(r0[0], _r0, 0); | |
| _r0 = vsetq_lane_f32(r0[N], _r0, 1); | |
| _r0 = vsetq_lane_f32(r0[N * 2], _r0, 2); | |
| _r0 = vsetq_lane_f32(r0[N * 3], _r0, 3); | |
| _r1 = vsetq_lane_f32(r0[N * 4], _r1, 0); | |
| _r1 = vsetq_lane_f32(r0[N * 5], _r1, 1); | |
| _r1 = vsetq_lane_f32(r0[N * 6], _r1, 2); | |
| _r1 = vsetq_lane_f32(r0[N * 7], _r1, 3); | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w0 = vld1q_f32(kptr); | |
| float32x4_t _w1 = vld1q_f32(kptr + 4); | |
| float32x4_t _w2 = vld1q_f32(kptr + 8); | |
| float32x4_t _w3 = vld1q_f32(kptr + 12); | |
| float32x4_t _w4 = vld1q_f32(kptr + 16); | |
| float32x4_t _w5 = vld1q_f32(kptr + 20); | |
| float32x4_t _w6 = vld1q_f32(kptr + 24); | |
| float32x4_t _w7 = vld1q_f32(kptr + 28); | |
| _sum0 = vfmaq_laneq_f32(_sum0, _w0, _r0, 0); | |
| _sum1 = vfmaq_laneq_f32(_sum1, _w1, _r0, 1); | |
| _sum2 = vfmaq_laneq_f32(_sum2, _w2, _r0, 2); | |
| _sum3 = vfmaq_laneq_f32(_sum3, _w3, _r0, 3); | |
| _sum0 = vfmaq_laneq_f32(_sum0, _w4, _r1, 0); | |
| _sum1 = vfmaq_laneq_f32(_sum1, _w5, _r1, 1); | |
| _sum2 = vfmaq_laneq_f32(_sum2, _w6, _r1, 2); | |
| _sum3 = vfmaq_laneq_f32(_sum3, _w7, _r1, 3); | |
| kptr += 32; | |
| } | |
| } | |
| for (; q + 3 < inh; q += 4) | |
| { | |
| const float* r0 = bottom_blob.row(q / elempack) + j * stride_w * elempack; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float32x4_t _r0; | |
| if (elempack == 4) | |
| { | |
| _r0 = vld1q_f32(r0); | |
| r0 += dilation_w * 4; | |
| } | |
| else // if (elempack == 1) | |
| { | |
| _r0 = float32x4_t(); | |
| _r0 = vsetq_lane_f32(r0[0], _r0, 0); | |
| _r0 = vsetq_lane_f32(r0[N], _r0, 1); | |
| _r0 = vsetq_lane_f32(r0[N * 2], _r0, 2); | |
| _r0 = vsetq_lane_f32(r0[N * 3], _r0, 3); | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w0 = vld1q_f32(kptr); | |
| float32x4_t _w1 = vld1q_f32(kptr + 4); | |
| float32x4_t _w2 = vld1q_f32(kptr + 8); | |
| float32x4_t _w3 = vld1q_f32(kptr + 12); | |
| _sum0 = vfmaq_laneq_f32(_sum0, _w0, _r0, 0); | |
| _sum1 = vfmaq_laneq_f32(_sum1, _w1, _r0, 1); | |
| _sum2 = vfmaq_laneq_f32(_sum2, _w2, _r0, 2); | |
| _sum3 = vfmaq_laneq_f32(_sum3, _w3, _r0, 3); | |
| _sum0 = vmlaq_lane_f32(_sum0, _w0, vget_low_f32(_r0), 0); | |
| _sum1 = vmlaq_lane_f32(_sum1, _w1, vget_low_f32(_r0), 1); | |
| _sum2 = vmlaq_lane_f32(_sum2, _w2, vget_high_f32(_r0), 0); | |
| _sum3 = vmlaq_lane_f32(_sum3, _w3, vget_high_f32(_r0), 1); | |
| kptr += 16; | |
| } | |
| } | |
| for (; q + 1 < inh; q += 2) | |
| { | |
| const float* r0 = bottom_blob.row(q) + j * stride_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float val0; | |
| float val1; | |
| // if (elempack == 1) | |
| { | |
| val0 = r0[0]; | |
| val1 = r0[N]; | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w0 = vld1q_f32(kptr); | |
| float32x4_t _w1 = vld1q_f32(kptr + 4); | |
| _sum0 = vfmaq_n_f32(_sum0, _w0, val0); | |
| _sum1 = vfmaq_n_f32(_sum1, _w1, val1); | |
| _sum0 = vmlaq_n_f32(_sum0, _w0, val0); | |
| _sum1 = vmlaq_n_f32(_sum1, _w1, val1); | |
| kptr += 8; | |
| } | |
| } | |
| for (; q < inh; q++) | |
| { | |
| const float* r0 = bottom_blob.row(q) + j * stride_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float32x4_t _val; | |
| // if (elempack == 1) | |
| { | |
| _val = vdupq_n_f32(r0[0]); | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w = vld1q_f32(kptr); | |
| _sum0 = vfmaq_f32(_sum0, _val, _w); | |
| _sum0 = vmlaq_f32(_sum0, _val, _w); | |
| kptr += 4; | |
| } | |
| } | |
| _sum0 = vaddq_f32(_sum0, _sum1); | |
| _sum2 = vaddq_f32(_sum2, _sum3); | |
| _sum0 = vaddq_f32(_sum0, _sum2); | |
| _sum0 = activation_ps(_sum0, activation_type, activation_params); | |
| if (out_elempack == 4) | |
| { | |
| vst1q_f32(outptr, _sum0); | |
| outptr += 4; | |
| } | |
| else // if (out_elempack == 1) | |
| { | |
| outptr[0] = vgetq_lane_f32(_sum0, 0); | |
| outptr[M] = vgetq_lane_f32(_sum0, 1); | |
| outptr[M * 2] = vgetq_lane_f32(_sum0, 2); | |
| outptr[M * 3] = vgetq_lane_f32(_sum0, 3); | |
| outptr += 1; | |
| } | |
| } | |
| } | |
| remain_outh_start += nn_outh * 4; | |
| nn_outh = (outh - remain_outh_start) / 2; | |
| nn_outh = (outh - remain_outh_start) / 2; | |
| for (int pp = 0; pp < nn_outh; pp++) | |
| { | |
| const int p = remain_outh_start + pp * 2; | |
| // shadowed variable for less openmp task args | |
| const int elempack = bottom_blob.elempack; | |
| const int inh = bottom_blob.h * elempack; | |
| const int outw = top_blob.w; | |
| float* outptr0 = top_blob.row(p); | |
| float* outptr1 = top_blob.row(p + 1); | |
| for (int j = 0; j < outw; j++) | |
| { | |
| float sum0 = 0.f; | |
| float sum1 = 0.f; | |
| if (bias_data_ptr) | |
| { | |
| sum0 = bias_data_ptr[p]; | |
| sum1 = bias_data_ptr[p + 1]; | |
| } | |
| const float* kptr = weight_data_tm.channel(p / 8 + (p % 8) / 4 + (p % 4) / 2); | |
| const float* kptr = weight_data_tm.channel(p / 4 + (p % 4) / 2); | |
| const float* kptr = weight_data_tm.channel(p / 2); | |
| int q = 0; | |
| float32x4_t _sum0 = vdupq_n_f32(0.f); | |
| float32x4_t _sum1 = vdupq_n_f32(0.f); | |
| float32x4_t _sum2 = vdupq_n_f32(0.f); | |
| float32x4_t _sum3 = vdupq_n_f32(0.f); | |
| for (; q + 7 < inh; q += 8) | |
| { | |
| const float* r0 = bottom_blob.row(q / elempack) + j * stride_w * elempack; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float32x4_t _r0; | |
| float32x4_t _r1; | |
| if (elempack == 4) | |
| { | |
| _r0 = vld1q_f32(r0); | |
| _r1 = vld1q_f32(r0 + N); | |
| r0 += dilation_w * 4; | |
| } | |
| else // if (elempack == 1) | |
| { | |
| _r0 = float32x4_t(); | |
| _r1 = float32x4_t(); | |
| _r0 = vsetq_lane_f32(r0[0], _r0, 0); | |
| _r0 = vsetq_lane_f32(r0[N], _r0, 1); | |
| _r0 = vsetq_lane_f32(r0[N * 2], _r0, 2); | |
| _r0 = vsetq_lane_f32(r0[N * 3], _r0, 3); | |
| _r1 = vsetq_lane_f32(r0[N * 4], _r1, 0); | |
| _r1 = vsetq_lane_f32(r0[N * 5], _r1, 1); | |
| _r1 = vsetq_lane_f32(r0[N * 6], _r1, 2); | |
| _r1 = vsetq_lane_f32(r0[N * 7], _r1, 3); | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w0 = vld1q_f32(kptr); | |
| float32x4_t _w1 = vld1q_f32(kptr + 4); | |
| float32x4_t _w2 = vld1q_f32(kptr + 8); | |
| float32x4_t _w3 = vld1q_f32(kptr + 12); | |
| _sum0 = vfmaq_f32(_sum0, _r0, _w0); | |
| _sum1 = vfmaq_f32(_sum1, _r1, _w1); | |
| _sum2 = vfmaq_f32(_sum2, _r0, _w2); | |
| _sum3 = vfmaq_f32(_sum3, _r1, _w3); | |
| kptr += 16; | |
| } | |
| } | |
| _sum0 = vaddq_f32(_sum0, _sum1); | |
| _sum2 = vaddq_f32(_sum2, _sum3); | |
| sum0 += vaddvq_f32(_sum0); | |
| sum1 += vaddvq_f32(_sum2); | |
| _sum0 = vdupq_n_f32(0.f); | |
| _sum1 = vdupq_n_f32(0.f); | |
| float32x4_t _sum0 = vdupq_n_f32(0.f); | |
| float32x4_t _sum1 = vdupq_n_f32(0.f); | |
| for (; q + 3 < inh; q += 4) | |
| { | |
| const float* r0 = bottom_blob.row(q / elempack) + j * stride_w * elempack; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float32x4_t _r0; | |
| if (elempack == 4) | |
| { | |
| _r0 = vld1q_f32(r0); | |
| r0 += dilation_w * 4; | |
| } | |
| else // if (elempack == 1) | |
| { | |
| _r0 = float32x4_t(); | |
| _r0 = vsetq_lane_f32(r0[0], _r0, 0); | |
| _r0 = vsetq_lane_f32(r0[N], _r0, 1); | |
| _r0 = vsetq_lane_f32(r0[N * 2], _r0, 2); | |
| _r0 = vsetq_lane_f32(r0[N * 3], _r0, 3); | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w0 = vld1q_f32(kptr); | |
| float32x4_t _w1 = vld1q_f32(kptr + 4); | |
| _sum0 = vfmaq_f32(_sum0, _r0, _w0); | |
| _sum1 = vfmaq_f32(_sum1, _r0, _w1); | |
| _sum0 = vmlaq_f32(_sum0, _r0, _w0); | |
| _sum1 = vmlaq_f32(_sum1, _r0, _w1); | |
| kptr += 8; | |
| } | |
| } | |
| sum0 += vaddvq_f32(_sum0); | |
| sum1 += vaddvq_f32(_sum1); | |
| float32x2_t _ss0 = vadd_f32(vget_low_f32(_sum0), vget_high_f32(_sum0)); | |
| float32x2_t _ss1 = vadd_f32(vget_low_f32(_sum1), vget_high_f32(_sum1)); | |
| float32x2_t _ss = vpadd_f32(_ss0, _ss1); | |
| sum0 += vget_lane_f32(_ss, 0); | |
| sum1 += vget_lane_f32(_ss, 1); | |
| for (; q + 1 < inh; q += 2) | |
| { | |
| const float* r0 = bottom_blob.row(q) + j * stride_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float val0; | |
| float val1; | |
| // if (elempack == 1) | |
| { | |
| val0 = r0[0]; | |
| val1 = r0[N]; | |
| r0 += dilation_w; | |
| } | |
| sum0 += val0 * kptr[0]; | |
| sum1 += val0 * kptr[1]; | |
| sum0 += val1 * kptr[2]; | |
| sum1 += val1 * kptr[3]; | |
| kptr += 4; | |
| } | |
| } | |
| for (; q < inh; q++) | |
| { | |
| const float* r0 = bottom_blob.row(q) + j * stride_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float val; | |
| // if (elempack == 1) | |
| { | |
| val = r0[0]; | |
| r0 += dilation_w; | |
| } | |
| sum0 += val * kptr[0]; | |
| sum1 += val * kptr[1]; | |
| kptr += 2; | |
| } | |
| } | |
| sum0 = activation_ss(sum0, activation_type, activation_params); | |
| sum1 = activation_ss(sum1, activation_type, activation_params); | |
| outptr0[0] = sum0; | |
| outptr1[0] = sum1; | |
| outptr0 += 1; | |
| outptr1 += 1; | |
| } | |
| } | |
| remain_outh_start += nn_outh * 2; | |
| for (int p = remain_outh_start; p < outh; p++) | |
| { | |
| float* outptr = top_blob.row(p); | |
| for (int j = 0; j < outw; j++) | |
| { | |
| float sum = 0.f; | |
| if (bias_data_ptr) | |
| { | |
| sum = bias_data_ptr[p]; | |
| } | |
| const float* kptr = weight_data_tm.channel(p / 8 + (p % 8) / 4 + (p % 4) / 2 + p % 2); | |
| const float* kptr = weight_data_tm.channel(p / 4 + (p % 4) / 2 + p % 2); | |
| const float* kptr = weight_data_tm.channel(p / 2 + p % 2); | |
| int q = 0; | |
| float32x4_t _sum0 = vdupq_n_f32(0.f); | |
| float32x4_t _sum1 = vdupq_n_f32(0.f); | |
| for (; q + 7 < inh; q += 8) | |
| { | |
| const float* r0 = bottom_blob.row(q / elempack) + j * stride_w * elempack; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float32x4_t _r0; | |
| float32x4_t _r1; | |
| if (elempack == 4) | |
| { | |
| _r0 = vld1q_f32(r0); | |
| _r1 = vld1q_f32(r0 + N); | |
| r0 += dilation_w * 4; | |
| } | |
| else // if (elempack == 1) | |
| { | |
| _r0 = float32x4_t(); | |
| _r1 = float32x4_t(); | |
| _r0 = vsetq_lane_f32(r0[0], _r0, 0); | |
| _r0 = vsetq_lane_f32(r0[N], _r0, 1); | |
| _r0 = vsetq_lane_f32(r0[N * 2], _r0, 2); | |
| _r0 = vsetq_lane_f32(r0[N * 3], _r0, 3); | |
| _r1 = vsetq_lane_f32(r0[N * 4], _r1, 0); | |
| _r1 = vsetq_lane_f32(r0[N * 5], _r1, 1); | |
| _r1 = vsetq_lane_f32(r0[N * 6], _r1, 2); | |
| _r1 = vsetq_lane_f32(r0[N * 7], _r1, 3); | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w0 = vld1q_f32(kptr); | |
| float32x4_t _w1 = vld1q_f32(kptr + 4); | |
| _sum0 = vfmaq_f32(_sum0, _r0, _w0); | |
| _sum1 = vfmaq_f32(_sum1, _r1, _w1); | |
| kptr += 8; | |
| } | |
| } | |
| _sum0 = vaddq_f32(_sum0, _sum1); | |
| sum += vaddvq_f32(_sum0); | |
| float32x4_t _sum = vdupq_n_f32(0.f); | |
| for (; q + 3 < inh; q += 4) | |
| { | |
| const float* r0 = bottom_blob.row(q / elempack) + j * stride_w * elempack; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float32x4_t _r0; | |
| if (elempack == 4) | |
| { | |
| _r0 = vld1q_f32(r0); | |
| r0 += dilation_w * 4; | |
| } | |
| else // if (elempack == 1) | |
| { | |
| _r0 = float32x4_t(); | |
| _r0 = vsetq_lane_f32(r0[0], _r0, 0); | |
| _r0 = vsetq_lane_f32(r0[N], _r0, 1); | |
| _r0 = vsetq_lane_f32(r0[N * 2], _r0, 2); | |
| _r0 = vsetq_lane_f32(r0[N * 3], _r0, 3); | |
| r0 += dilation_w; | |
| } | |
| float32x4_t _w = vld1q_f32(kptr); | |
| _sum = vfmaq_f32(_sum, _r0, _w); | |
| _sum = vmlaq_f32(_sum, _r0, _w); | |
| kptr += 4; | |
| } | |
| } | |
| sum += vaddvq_f32(_sum); | |
| float32x2_t _ss = vadd_f32(vget_low_f32(_sum), vget_high_f32(_sum)); | |
| _ss = vpadd_f32(_ss, _ss); | |
| sum += vget_lane_f32(_ss, 0); | |
| for (; q + 1 < inh; q += 2) | |
| { | |
| const float* r0 = bottom_blob.row(q) + j * stride_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float val0; | |
| float val1; | |
| // if (elempack == 1) | |
| { | |
| val0 = r0[0]; | |
| val1 = r0[N]; | |
| r0 += dilation_w; | |
| } | |
| sum += val0 * kptr[0]; | |
| sum += val1 * kptr[1]; | |
| kptr += 2; | |
| } | |
| } | |
| for (; q < inh; q++) | |
| { | |
| const float* r0 = bottom_blob.row(q) + j * stride_w; | |
| for (int k = 0; k < kernel_w; k++) | |
| { | |
| float val; | |
| // if (elempack == 1) | |
| { | |
| val = r0[0]; | |
| r0 += dilation_w; | |
| } | |
| sum += val * kptr[0]; | |
| kptr += 1; | |
| } | |
| } | |
| sum = activation_ss(sum, activation_type, activation_params); | |
| outptr[0] = sum; | |
| outptr += 1; | |
| } | |
| } | |
| } | |