clang format

src/targets/gpu/device/layernorm.cpp

@@ -258,7 +258,7 @@ __global__ void triadd_layernorm_kernel_half2(
 
     for(int i = threadIdx.x; i < batch_item_num; i += block_size)
     {
-        in_data[i]        = __hsub2(in_data[i], m);
+        in_data[i] = __hsub2(in_data[i], m);
         // in_data_reduce[i] = __hmul2(__hmul2(in_data[i], in_data[i]), rnum);
         in_data_reduce[i] = __hmul2(in_data[i], in_data[i]);
     }
@@ -383,7 +383,8 @@ __global__ void triadd_layernorm_kernel(
         in_data_reduce[i] = __half2float(in_data[i] * in_data[i]) * rnum;
     }
 
-    m      = __half2float(block_reduce(in_data_reduce, batch_item_num, threadIdx.x, block_size)) + 1.0e-12f;
+    m = __half2float(block_reduce(in_data_reduce, batch_item_num, threadIdx.x, block_size)) +
+        1.0e-12f;
     auto r = rsqrt(m);
 
     for(int i = threadIdx.x; i < batch_item_num; i += block_size)
@@ -409,7 +410,8 @@ void triadd_layernorm(hipStream_t stream,
     //     int shared_size       = batch_item_num * 2 * in_s.type_size();
     //     half2_block_size      = half2_block_size / 4;
     //     triadd_layernorm_kernel_half2<<<block_num, half2_block_size, shared_size, stream>>>(
-    //         arg1.data(), arg2.data(), arg3.data(), result.data(), batch_item_num, half2_block_size);
+    //         arg1.data(), arg2.data(), arg3.data(), result.data(), batch_item_num,
+    //         half2_block_size);
     // }
     // if(type == shape::half_type and (batch_item_num % 2) == 0)
     if(type == shape::half_type)
@@ -418,13 +420,13 @@ void triadd_layernorm(hipStream_t stream,
         int block_num          = in_s.elements() / batch_item_num;
         int shared_size        = batch_item_num * 2 * in_s.type_size();
         reduce_block_size      = reduce_block_size / 2;
-        triadd_layernorm_kernel<__half><<<block_num, reduce_block_size, shared_size, stream>>>(
-            arg1.data(),
-            arg2.data(),
-            arg3.data(),
-            result.data(),
-            batch_item_num,
-            reduce_block_size);
+        triadd_layernorm_kernel<__half>
+            <<<block_num, reduce_block_size, shared_size, stream>>>(arg1.data(),
+                                                                    arg2.data(),
+                                                                    arg3.data(),
+                                                                    result.data(),
+                                                                    batch_item_num,
+                                                                    reduce_block_size);
     }
     else
     {