apply code-format changes

Author: nihui

src/layer/x86/convolution_3x3_winograd_bf16s.h

@@ -1090,7 +1090,6 @@ static inline void conv3x3s1_winograd23_transform_output_tile_bf16s(const Mat& t
                 tmp10 = activation_ss(tmp10, activation_type, activation_params);
                 tmp11 = activation_ss(tmp11, activation_type, activation_params);
 
-
                 // if (out_elempack == 1)
                 {
                     unsigned short* outptr1 = outptr0 + N;
@@ -1153,7 +1152,6 @@ static inline void conv3x3s1_winograd23_transform_output_tile_bf16s(const Mat& t
                 tmp0 = activation_ss(tmp0, activation_type, activation_params);
                 tmp1 = activation_ss(tmp1, activation_type, activation_params);
 
-
                 // if (out_elempack == 1)
                 {
                     outptr0[0] = float32_to_bfloat16(tmp0);
@@ -2866,7 +2864,6 @@ static inline void conv3x3s1_winograd43_transform_output_tile_bf16s(const Mat& t
                 tmp30 = activation_ss(tmp30, activation_type, activation_params);
                 tmp31 = activation_ss(tmp31, activation_type, activation_params);
 
-
                 // if (out_elempack == 1)
                 {
                     unsigned short* outptr1 = outptr0 + N;
@@ -2961,7 +2958,6 @@ static inline void conv3x3s1_winograd43_transform_output_tile_bf16s(const Mat& t
                 tmp2 = activation_ss(tmp2, activation_type, activation_params);
                 tmp3 = activation_ss(tmp3, activation_type, activation_params);
 
-
                 // if (out_elempack == 1)
                 {
                     outptr0[0] = float32_to_bfloat16(tmp0);
@@ -4132,7 +4128,6 @@ static inline void conv3x3s1_winograd63_transform_input_tile_bf16s(const Mat& bo
     }
 }
 
-
 #if NCNN_RUNTIME_CPU && NCNN_AVX512BF16 && __AVX512F__ && !__AVX512BF16__
 void conv3x3s1_winograd63_transform_output_tile_bf16s_avx512bf16(const Mat& top_tile, Mat& top_blob, const Mat& bias, int i, int max_ii, int j, int max_jj, int activation_type, const Mat& activation_params);
 #endif
@@ -5102,7 +5097,6 @@ static inline void conv3x3s1_winograd63_transform_output_tile_bf16s(const Mat& t
                 tmp50 = activation_ss(tmp50, activation_type, activation_params);
                 tmp51 = activation_ss(tmp51, activation_type, activation_params);
 
-
                 // if (out_elempack == 1)
                 {
                     unsigned short* outptr1 = outptr0 + N;
@@ -5223,7 +5217,6 @@ static inline void conv3x3s1_winograd63_transform_output_tile_bf16s(const Mat& t
                 tmp4 = activation_ss(tmp4, activation_type, activation_params);
                 tmp5 = activation_ss(tmp5, activation_type, activation_params);
 
-
                 // if (out_elempack == 1)
                 {
                     outptr0[0] = float32_to_bfloat16(tmp0);
@@ -5240,7 +5233,6 @@ static inline void conv3x3s1_winograd63_transform_output_tile_bf16s(const Mat& t
     }
 }
 
-
 #if NCNN_RUNTIME_CPU && NCNN_AVX512BF16 && __AVX512F__ && !__AVX512BF16__
 int conv3x3s1_winograd63_bf16s_avx512bf16(const Mat& bottom_blob, Mat& top_blob, const Mat& AT, const Mat& bias, int nT, int activation_type, const Mat& activation_params, const Option& opt);
 #endif
@@ -5373,4 +5365,3 @@ static int conv3x3s1_winograd63_bf16s(const Mat& bottom_blob, Mat& top_blob, con
 
     return 0;
 }
-

src/layer/x86/convolution_x86.cpp

@@ -1317,13 +1317,23 @@ int Convolution_x86::create_pipeline_bf16s(const Option& opt)
             bool prefer_winograd23 = test_prefer_winograd23(num_input, num_output, w, h);
             bool prefer_winograd43 = !prefer_winograd63 && !prefer_winograd23;
 
-            if (prefer_winograd23 && !opt.use_winograd23_convolution) { prefer_winograd23 = false; prefer_winograd43 = true; }
-            if (prefer_winograd63 && !opt.use_winograd63_convolution) { prefer_winograd63 = false; prefer_winograd43 = true; }
+            if (prefer_winograd23 && !opt.use_winograd23_convolution)
+            {
+                prefer_winograd23 = false;
+                prefer_winograd43 = true;
+            }
+            if (prefer_winograd63 && !opt.use_winograd63_convolution)
+            {
+                prefer_winograd63 = false;
+                prefer_winograd43 = true;
+            }
             if (prefer_winograd43 && !opt.use_winograd43_convolution)
             {
                 prefer_winograd43 = false;
-                if (opt.use_winograd63_convolution) prefer_winograd63 = true;
-                else prefer_winograd23 = true;
+                if (opt.use_winograd63_convolution)
+                    prefer_winograd63 = true;
+                else
+                    prefer_winograd23 = true;
             }
 
             if (prefer_winograd23)
@@ -1445,7 +1455,6 @@ int Convolution_x86::forward_bf16s(const Mat& bottom_blob, Mat& top_blob, const
     if (top_blob.empty())
         return -100;
 
-
     const int num_input = channels * elempack;
 
     bool prefer_winograd = (opt.use_winograd23_convolution || opt.use_winograd43_convolution || opt.use_winograd63_convolution) && (num_input > 8 || num_output > 8);
@@ -1456,13 +1465,23 @@ int Convolution_x86::forward_bf16s(const Mat& bottom_blob, Mat& top_blob, const
         bool prefer_winograd23 = test_prefer_winograd23(num_input, num_output, w, h);
         bool prefer_winograd43 = !prefer_winograd63 && !prefer_winograd23;
 
-        if (prefer_winograd23 && (!opt.use_winograd23_convolution || weight_winograd23_data.empty())) { prefer_winograd23 = false; prefer_winograd43 = true; }
-        if (prefer_winograd63 && (!opt.use_winograd63_convolution || weight_winograd63_data.empty())) { prefer_winograd63 = false; prefer_winograd43 = true; }
+        if (prefer_winograd23 && (!opt.use_winograd23_convolution || weight_winograd23_data.empty()))
+        {
+            prefer_winograd23 = false;
+            prefer_winograd43 = true;
+        }
+        if (prefer_winograd63 && (!opt.use_winograd63_convolution || weight_winograd63_data.empty()))
+        {
+            prefer_winograd63 = false;
+            prefer_winograd43 = true;
+        }
         if (prefer_winograd43 && (!opt.use_winograd43_convolution || weight_winograd43_data.empty()))
         {
             prefer_winograd43 = false;
-            if (opt.use_winograd63_convolution && !weight_winograd63_data.empty()) prefer_winograd63 = true;
-            else prefer_winograd23 = true;
+            if (opt.use_winograd63_convolution && !weight_winograd63_data.empty())
+                prefer_winograd63 = true;
+            else
+                prefer_winograd23 = true;
         }
 
         int _nT = nT ? nT : opt.num_threads;