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instancenorm x86 simd #6097
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ead4508
instancenorm x86 simd
futz12 54a07bd
apply code-format changes
futz12 6225151
fix code style
futz12 f1cc628
apply code-format changes
futz12 c8d4a54
fix usage of simd function
futz12 1ccccf8
Merge remote-tracking branch 'origin/instancenorm_x86' into instancen…
futz12 0fc080c
fix loop logic(make nihui happy)
futz12 b44c4b4
Make the code style of this consistent with that of layernorm_x86.cpp.
futz12 2ecfba1
Update src/layer/x86/instancenorm_x86.cpp
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,248 @@ | ||
| // Tencent is pleased to support the open source community by making ncnn available. | ||
| // | ||
| // Copyright (C) 2025 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. | ||
|
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| #include "instancenorm_x86.h" | ||
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| #if __SSE2__ | ||
| #include <emmintrin.h> | ||
| #if __AVX__ | ||
| #include <immintrin.h> | ||
| #endif | ||
| #endif // __SSE2__ | ||
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| namespace ncnn { | ||
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| InstanceNorm_x86::InstanceNorm_x86() | ||
| { | ||
| one_blob_only = true; | ||
| support_inplace = true; | ||
| } | ||
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| int InstanceNorm_x86::load_param(const ParamDict& pd) | ||
| { | ||
| channels = pd.get(0, 0); | ||
| eps = pd.get(1, 0.001f); | ||
| affine = pd.get(2, 1); | ||
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| return 0; | ||
| } | ||
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| int InstanceNorm_x86::load_model(const ModelBin& mb) | ||
| { | ||
| if (affine == 0) | ||
| return 0; | ||
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| gamma_data = mb.load(channels, 1); | ||
| if (gamma_data.empty()) | ||
| return -100; | ||
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| beta_data = mb.load(channels, 1); | ||
| if (beta_data.empty()) | ||
| return -100; | ||
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| return 0; | ||
| } | ||
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| int InstanceNorm_x86::forward_inplace(Mat& bottom_top_blob, const Option& opt) const | ||
| { | ||
| // x = (x - mean) / (sqrt(var + eps)) * gamma + beta | ||
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| int w = bottom_top_blob.w; | ||
| int h = bottom_top_blob.h; | ||
| int c = bottom_top_blob.c; | ||
| int size = w * h; | ||
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| #pragma omp parallel for num_threads(opt.num_threads) | ||
| for (int q = 0; q < c; q++) | ||
| { | ||
| float* ptr = bottom_top_blob.channel(q); | ||
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| // mean and var | ||
| float sum = 0.f; | ||
| float sqsum = 0.f; | ||
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| int i = 0; | ||
| #if __SSE2__ | ||
| #if __AVX__ | ||
| #if __AVX512F__ | ||
| __m512 _sum_vec_16 = _mm512_setzero_ps(); | ||
| for (; i <= size - 16; i += 16) | ||
| { | ||
| __m512 _p = _mm512_loadu_ps(ptr + i); | ||
| _sum_vec_16 = _mm512_add_ps(_sum_vec_16, _p); | ||
| } | ||
| sum = _mm512_reduce_add_ps(_sum_vec_16); | ||
| #endif // __AVX512F__ | ||
| __m256 _sum_vec_8 = _mm256_setzero_ps(); | ||
| for (; i <= size - 8; i += 8) | ||
| { | ||
| __m256 _p = _mm256_loadu_ps(ptr + i); | ||
| _sum_vec_8 = _mm256_add_ps(_sum_vec_8, _p); | ||
| } | ||
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| __m128 vlow = _mm256_castps256_ps128(_sum_vec_8); | ||
| __m128 vhigh = _mm256_extractf128_ps(_sum_vec_8, 1); | ||
| __m128 hsum_128 = _mm_add_ps(vlow, vhigh); | ||
| hsum_128 = _mm_hadd_ps(hsum_128, hsum_128); | ||
| hsum_128 = _mm_hadd_ps(hsum_128, hsum_128); | ||
| sum += _mm_cvtss_f32(hsum_128); | ||
| #endif // __AVX__ | ||
| __m128 _sum_vec_4 = _mm_setzero_ps(); | ||
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| for (; i <= size - 4; i += 4) | ||
| { | ||
| __m128 _p = _mm_loadu_ps(ptr + i); | ||
| _sum_vec_4 = _mm_add_ps(_sum_vec_4, _p); | ||
| } | ||
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| _sum_vec_4 = _mm_add_ps(_sum_vec_4, _mm_movehl_ps(_sum_vec_4, _sum_vec_4)); // _sum_vec_4 = [s0+s2, s1+s3, s2+s2, s3+s3] | ||
| _sum_vec_4 = _mm_add_ss(_sum_vec_4, _mm_shuffle_ps(_sum_vec_4, _sum_vec_4, _MM_SHUFFLE(1, 1, 1, 1))); // h_sum_tmp[0] = (s0+s2) + (s1+s3) | ||
| sum += _mm_cvtss_f32(_sum_vec_4); | ||
| #endif //__SSE2__ | ||
| for (; i < size; i++) | ||
| { | ||
| sum += ptr[i]; | ||
| } | ||
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| i = 0; | ||
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| float mean = sum / size; | ||
| float tmp = 0.f; | ||
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| #if __SSE2__ | ||
| #if __AVX__ | ||
| #if __AVX512F__ | ||
| __m512 _sqsum_vec_16 = _mm512_setzero_ps(); | ||
| __m512 _mean_vec_16 = _mm512_set1_ps(mean); | ||
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| for (; i <= size - 16; i += 16) | ||
| { | ||
| __m512 _p = _mm512_loadu_ps(ptr + i); | ||
| __m512 _diff = _mm512_sub_ps(_p, _mean_vec_16); | ||
| _sqsum_vec_16 = _mm512_add_ps(_sqsum_vec_16, _mm512_mul_ps(_diff, _diff)); | ||
| } | ||
| sqsum += _mm512_reduce_add_ps(_sqsum_vec_16); | ||
| #endif // __AVX512F | ||
| __m256 _sqsum_vec_8 = _mm256_setzero_ps(); | ||
| __m256 _mean_vec_8 = _mm256_set1_ps(mean); | ||
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| for (; i <= size - 8; i += 8) | ||
| { | ||
| __m256 _p = _mm256_loadu_ps(ptr + i); | ||
| __m256 _diff = _mm256_sub_ps(_p, _mean_vec_8); | ||
| _sqsum_vec_8 = _mm256_add_ps(_sqsum_vec_8, _mm256_mul_ps(_diff, _diff)); | ||
| } | ||
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| __m128 vlow_sq = _mm256_castps256_ps128(_sqsum_vec_8); | ||
| __m128 vhigh_sq = _mm256_extractf128_ps(_sqsum_vec_8, 1); | ||
| __m128 hsqsum_128 = _mm_add_ps(vlow_sq, vhigh_sq); | ||
| hsqsum_128 = _mm_hadd_ps(hsqsum_128, hsqsum_128); | ||
| hsqsum_128 = _mm_hadd_ps(hsqsum_128, hsqsum_128); | ||
| sqsum += _mm_cvtss_f32(hsqsum_128); | ||
| #endif // __AVX__ | ||
| __m128 _sqsum_vec_4 = _mm_setzero_ps(); | ||
| __m128 _mean_vec_4 = _mm_set1_ps(mean); | ||
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| for (; i <= size - 4; i += 4) | ||
| { | ||
| __m128 _p = _mm_loadu_ps(ptr + i); | ||
| __m128 _diff = _mm_sub_ps(_p, _mean_vec_4); | ||
| _sqsum_vec_4 = _mm_add_ps(_sqsum_vec_4, _mm_mul_ps(_diff, _diff)); | ||
| } | ||
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| __m128 h_sqsum_tmp = _sqsum_vec_4; | ||
| h_sqsum_tmp = _mm_add_ps(h_sqsum_tmp, _mm_movehl_ps(h_sqsum_tmp, h_sqsum_tmp)); | ||
| h_sqsum_tmp = _mm_add_ss(h_sqsum_tmp, _mm_shuffle_ps(h_sqsum_tmp, h_sqsum_tmp, _MM_SHUFFLE(1, 1, 1, 1))); | ||
| sqsum += _mm_cvtss_f32(h_sqsum_tmp); | ||
| #endif // __SSE2__ | ||
|
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| for (; i < size; i++) | ||
| { | ||
| tmp = ptr[i] - mean; | ||
| sqsum += tmp * tmp; | ||
| } | ||
| float var = sqsum / size; | ||
| // the var maybe minus due to accuracy | ||
| //float var = sqsum / size - mean * mean; | ||
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| float a; | ||
| float b; | ||
| if (affine) | ||
| { | ||
| float gamma = gamma_data[q]; | ||
| float beta = beta_data[q]; | ||
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| a = gamma / (sqrtf(var + eps)); | ||
| b = -mean * a + beta; | ||
| } | ||
| else | ||
| { | ||
| a = 1.f / (sqrtf(var + eps)); | ||
| b = -mean * a; | ||
| } | ||
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| i = 0; | ||
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| #if __SSE2__ | ||
| #if __AVX__ | ||
| #if __AVX512F__ | ||
| __m512 _va_16 = _mm512_set1_ps(a); | ||
| __m512 _vb_16 = _mm512_set1_ps(b); | ||
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| for (; i <= size - 16; i += 16) | ||
|
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| { | ||
| __m512 _p = _mm512_loadu_ps(ptr + i); | ||
| _p = _mm512_fmadd_ps(_p, _va_16, _vb_16); // Fused Multiply-Add | ||
| _mm512_storeu_ps(ptr + i, _p); | ||
| } | ||
| #endif // __AVX512F__ | ||
| __m256 _va_8 = _mm256_set1_ps(a); | ||
| __m256 _vb_8 = _mm256_set1_ps(b); | ||
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| for (; i <= size - 8; i += 8) | ||
| { | ||
| __m256 _p = _mm256_loadu_ps(ptr + i); | ||
| #if defined(__FMA__) // Check for FMA support (usually with AVX2) | ||
| _p = _mm256_fmadd_ps(_p, _va_8, _vb_8); | ||
| #else | ||
| _p = _mm256_mul_ps(_p, _va_8); | ||
| _p = _mm256_add_ps(_p, _vb_8); | ||
| #endif | ||
| _mm256_storeu_ps(ptr + i, _p); | ||
| } | ||
| #endif // __AVX__ | ||
| __m128 _va_4 = _mm_set1_ps(a); | ||
| __m128 _vb_4 = _mm_set1_ps(b); | ||
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| for (; i <= size - 4; i += 4) | ||
| { | ||
| __m128 _p = _mm_loadu_ps(ptr + i); | ||
| // SSE2 does not have FMA instructions directly; FMA is part of FMA3 extension. | ||
| // Compilers might fuse mul+add if target architecture supports it (e.g. compiling with -mfma). | ||
| _p = _mm_mul_ps(_p, _va_4); | ||
| _p = _mm_add_ps(_p, _vb_4); | ||
| _mm_storeu_ps(ptr + i, _p); | ||
| } | ||
| #endif // __SSE2__ | ||
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| for (; i < size; i++) | ||
| { | ||
| ptr[i] = ptr[i] * a + b; | ||
| } | ||
| } | ||
|
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| return 0; | ||
| } | ||
|
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| } // namespace ncnn | ||
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,46 @@ | ||
| // Tencent is pleased to support the open source community by making ncnn available. | ||
| // | ||
| // Copyright (C) 2025 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. | ||
|
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| #ifndef LAYER_INSTANCENORM_X86_H | ||
| #define LAYER_INSTANCENORM_X86_H | ||
|
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| #include "instancenorm.h" | ||
|
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| namespace ncnn { | ||
|
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| class InstanceNorm_x86 : public InstanceNorm | ||
| { | ||
| public: | ||
| InstanceNorm_x86(); | ||
|
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| virtual int load_param(const ParamDict& pd); | ||
|
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| virtual int load_model(const ModelBin& mb); | ||
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| virtual int forward_inplace(Mat& bottom_top_blob, const Option& opt) const; | ||
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| public: | ||
| // param | ||
| int channels; | ||
| float eps; | ||
| int affine; | ||
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| // model | ||
| Mat gamma_data; | ||
| Mat beta_data; | ||
| }; | ||
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| } // namespace ncnn | ||
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| #endif // LAYER_INSTANCENORM_X86_H |
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