Hotfix/format (#1274)

* [NFC] Polish colossalai/kernel/cuda_native/csrc/multi_tensor_lamb.cu code style. (#937)

* [NFC] polish colossalai/kernel/cuda_native/csrc/kernels/include/cuda_util.h code style

* [NFC] polish colossalai/kernel/cuda_native/csrc/scaled_masked_softmax.cpp code style
Co-authored-by: BoxiangW <45734921+BoxiangW@users.noreply.github.com>

colossalai/kernel/cuda_native/csrc/scaled_masked_softmax.cpp

@@ -3,31 +3,24 @@
 
 #include <cuda_fp16.h>
 #include <torch/extension.h>
+
 #include <vector>
 
 namespace multihead_attn {
 namespace fused_softmax {
 namespace scaled_masked_softmax {
 
-torch::Tensor fwd_cuda(
-    torch::Tensor const& input, 
-    torch::Tensor const& mask,
+torch::Tensor fwd_cuda(torch::Tensor const& input, torch::Tensor const& mask,
                        float scale_factor);
 
-torch::Tensor bwd_cuda(
-    torch::Tensor const& output_grads, 
+torch::Tensor bwd_cuda(torch::Tensor const& output_grads,
                        torch::Tensor const& softmax_results,
                        float scale_factor);
 
-int get_batch_per_block_cuda(
-    int query_seq_len,
-    int key_seq_len,
-    int batches,
+int get_batch_per_block_cuda(int query_seq_len, int key_seq_len, int batches,
                              int attn_heads);
 
-torch::Tensor fwd(
-    torch::Tensor const& input,
-    torch::Tensor const& mask,
+torch::Tensor fwd(torch::Tensor const& input, torch::Tensor const& mask,
                   float scale_factor) {
   AT_ASSERTM(input.dim() == 4, "expected 4D tensor");
   AT_ASSERTM((input.scalar_type() == at::ScalarType::Half) ||
@@ -38,11 +31,8 @@ torch::Tensor fwd(
   return fwd_cuda(input, mask, scale_factor);
 }
 
-torch::Tensor bwd(
-    torch::Tensor const& output_grads, 
-    torch::Tensor const& softmax_results,
-    float scale_factor) {
-
+torch::Tensor bwd(torch::Tensor const& output_grads,
+                  torch::Tensor const& softmax_results, float scale_factor) {
   AT_ASSERTM(output_grads.dim() == 4, "expected 3D tensor");
   AT_ASSERTM(softmax_results.dim() == 4, "expected 3D tensor");
 
@@ -56,12 +46,10 @@ torch::Tensor bwd(
   return bwd_cuda(output_grads, softmax_results, scale_factor);
 }
 
-int get_batch_per_block(
-    int query_seq_len,
-    int key_seq_len,
-    int batches,
+int get_batch_per_block(int query_seq_len, int key_seq_len, int batches,
                         int attn_heads) {
-    return get_batch_per_block_cuda(query_seq_len, key_seq_len, batches, attn_heads);
+  return get_batch_per_block_cuda(query_seq_len, key_seq_len, batches,
+                                  attn_heads);
 }
 
 }  // end namespace scaled_masked_softmax
@@ -69,16 +57,14 @@ int get_batch_per_block(
 }  // end namespace multihead_attn
 
 PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {
-  m.def("forward", 
-        &multihead_attn::fused_softmax::scaled_masked_softmax::fwd, 
+  m.def("forward", &multihead_attn::fused_softmax::scaled_masked_softmax::fwd,
         "Self Multihead Attention scaled, time masked softmax -- Forward.");
 
-  m.def("backward",
-        &multihead_attn::fused_softmax::scaled_masked_softmax::bwd,
+  m.def("backward", &multihead_attn::fused_softmax::scaled_masked_softmax::bwd,
         "Self Multihead Attention scaled, time masked softmax -- Backward.");
 
   m.def("get_batch_per_block",
-        &multihead_attn::fused_softmax::scaled_masked_softmax::get_batch_per_block,
-        "Return Batch per block size."
-  );
+        &multihead_attn::fused_softmax::scaled_masked_softmax::
+            get_batch_per_block,
+        "Return Batch per block size.");
 }