fix format error

Signed-off-by: Jinzhen Lin <[email protected]>

Author: jinzhen-lin

csrc/moe/moe_align_sum_kernels.cu

@@ -8,7 +8,7 @@
 #include "../cuda_compat.h"
 #include "../dispatch_utils.h"
 
-#define CEILDIV(x, y) (((x) + (y) - 1) / (y))
+#define CEILDIV(x, y) (((x) + (y)-1) / (y))
 
 namespace vllm {
 namespace moe {
@@ -33,7 +33,7 @@ __global__ void moe_align_block_size_kernel(scalar_t* __restrict__ topk_ids,
 
   extern __shared__ int32_t shared_mem[];
   int32_t* cumsum = shared_mem;  // 1d tensor with shape (num_experts + 1)
-  token_cnts_t* tokens_cnts = (token_cnts_t *) (shared_mem + blockDim.x + 1);
+  token_cnts_t* tokens_cnts = (token_cnts_t*)(shared_mem + blockDim.x + 1);
 
   for (int i = 0; i < num_experts; ++i) {
     tokens_cnts[index(num_experts, threadIdx.x + 1, i)] = 0;
@@ -70,7 +70,7 @@ __global__ void moe_align_block_size_kernel(scalar_t* __restrict__ topk_ids,
                           block_size) *
                       block_size;
     }
-    *total_tokens_post_pad = (int32_t) cumsum[num_experts];
+    *total_tokens_post_pad = (int32_t)cumsum[num_experts];
   }
 
   __syncthreads();
@@ -222,20 +222,21 @@ void moe_align_block_size(torch::Tensor topk_ids, int64_t num_experts,
 
   int device_max_shared_mem;
   auto dev = topk_ids.get_device();
-  cudaDeviceGetAttribute(&device_max_shared_mem, cudaDevAttrMaxSharedMemoryPerBlockOptin, dev);
+  cudaDeviceGetAttribute(&device_max_shared_mem,
+                         cudaDevAttrMaxSharedMemoryPerBlockOptin, dev);
 
   const int32_t num_thread = max((int32_t)num_experts, WARP_SIZE);
   const int32_t shared_mem_i32 =
-      ((num_thread + 1) * num_experts + (num_experts + 1)) *
-      sizeof(int32_t);
+      ((num_thread + 1) * num_experts + (num_experts + 1)) * sizeof(int32_t);
   const int32_t shared_mem_i16 =
-      ((num_thread + 1) * num_experts) * sizeof(uint16_t) + (num_experts + 1) *
-      sizeof(int32_t);
+      ((num_thread + 1) * num_experts) * sizeof(uint16_t) +
+      (num_experts + 1) * sizeof(int32_t);
 
   bool use_global_memory = false, use_i16 = false;
   if (shared_mem_i16 > device_max_shared_mem) {
     use_global_memory = true;
-  } else if (shared_mem_i32 > device_max_shared_mem && topk_ids.numel() <= 65535) {
+  } else if (shared_mem_i32 > device_max_shared_mem &&
+             topk_ids.numel() <= 65535) {
     // when nelements of topk_ids is smaller than 65535 (max value of uint16),
     // element value of token_cnts would also smaller than 65535,
     // so we can use uint16 as dtype of token_cnts
@@ -249,8 +250,9 @@ void moe_align_block_size(torch::Tensor topk_ids, int64_t num_experts,
           // tensors
           const int32_t num_thread = max((int32_t)num_experts, WARP_SIZE);
 
-          auto options_int =
-              torch::TensorOptions().dtype(torch::kInt).device(topk_ids.device());
+          auto options_int = torch::TensorOptions()
+                                 .dtype(torch::kInt)
+                                 .device(topk_ids.device());
           torch::Tensor token_cnts_buffer =
               torch::empty({(num_experts + 1) * num_experts}, options_int);
           torch::Tensor cumsum_buffer =
@@ -270,7 +272,8 @@ void moe_align_block_size(torch::Tensor topk_ids, int64_t num_experts,
     VLLM_DISPATCH_INTEGRAL_TYPES(
         topk_ids.scalar_type(), "moe_align_block_size_kernel", [&] {
           // set dynamic shared mem
-          auto kernel = vllm::moe::moe_align_block_size_kernel<scalar_t, uint16_t>;
+          auto kernel =
+              vllm::moe::moe_align_block_size_kernel<scalar_t, uint16_t>;
           AT_CUDA_CHECK(VLLM_DevFuncAttribute_SET_MaxDynamicSharedMemorySize(
               (void*)kernel, shared_mem_i16));
           kernel<<<1, num_thread, shared_mem_i16, stream>>>(
@@ -282,8 +285,9 @@ void moe_align_block_size(torch::Tensor topk_ids, int64_t num_experts,
         });
   } else {
     VLLM_DISPATCH_INTEGRAL_TYPES(
-      topk_ids.scalar_type(), "moe_align_block_size_kernel", [&] {
-          auto kernel = vllm::moe::moe_align_block_size_kernel<scalar_t, int32_t>;
+        topk_ids.scalar_type(), "moe_align_block_size_kernel", [&] {
+          auto kernel =
+              vllm::moe::moe_align_block_size_kernel<scalar_t, int32_t>;
           AT_CUDA_CHECK(VLLM_DevFuncAttribute_SET_MaxDynamicSharedMemorySize(
               (void*)kernel, shared_mem_i32));
           kernel<<<1, num_thread, shared_mem_i32, stream>>>(