conv1x1s1 bf16s neon kernel

src/layer/arm/convolution_arm.cpp

@@ -37,6 +37,8 @@ namespace ncnn {
 #include "convolution_1x1_int8.h"
 #include "convolution_3x3_int8.h"
 
+#include "convolution_1x1_bf16s.h"
+
 #if __ARM_NEON
 #include "convolution_1x1_pack4.h"
 #include "convolution_1x1_pack4to1.h"
@@ -1192,7 +1194,14 @@ int Convolution_arm::create_pipeline_bf16s(const Option& opt)
     // pack1
     if (elempack == 1 && out_elempack == 1)
     {
-        ncnn::cast_float32_to_bfloat16(weight_data, weight_data_bf16, opt);
+        if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
+        {
+            conv1x1s1_sgemm_transform_kernel_bf16s_neon(weight_data, weight_data_bf16, num_input, num_output);
+        }
+        else
+        {
+            ncnn::cast_float32_to_bfloat16(weight_data, weight_data_bf16, opt);
+        }
     }
 
     return 0;
@@ -1542,6 +1551,16 @@ int Convolution_arm::forward_bf16s(const Mat& bottom_blob, Mat& top_blob, const
 
     if (elempack == 1 && out_elempack == 1)
     {
+        if (kernel_w == 1 && kernel_h == 1 && dilation_w == 1 && dilation_h == 1 && stride_w == 1 && stride_h == 1)
+        {
+            conv1x1s1_sgemm_bf16s_neon(bottom_blob_bordered, top_blob, weight_data_bf16, bias_data, opt);
+
+            if (activation)
+            {
+                activation->forward_inplace(top_blob, opt);
+            }
+        }
+        else
         {
             // num_output
             #pragma omp parallel for num_threads(opt.num_threads)