add support for FA3 on multi-gpu inference

wan/distributed/xdit_context_parallel.py

@@ -1,6 +1,10 @@
 # Copyright 2024-2025 The Alibaba Wan Team Authors. All rights reserved.
 import torch
 import torch.cuda.amp as amp
+
+import yunchang
+from yunchang.kernels import AttnType
+
 from xfuser.core.distributed import (
     get_sequence_parallel_rank,
     get_sequence_parallel_world_size,
@@ -10,6 +14,12 @@ from xfuser.core.long_ctx_attention import xFuserLongContextAttention
 
 from ..modules.model import sinusoidal_embedding_1d
 
+try:
+    import flash_attn_interface
+    FLASH_ATTN_3_AVAILABLE = True
+except ModuleNotFoundError:
+    FLASH_ATTN_3_AVAILABLE = False
+
 
 def pad_freqs(original_tensor, target_len):
     seq_len, s1, s2 = original_tensor.shape
@@ -210,6 +220,21 @@ def usp_attn_forward(self,
     #     k = torch.cat([u[:l] for u, l in zip(k, k_lens)]).unsqueeze(0)
     #     v = torch.cat([u[:l] for u, l in zip(v, k_lens)]).unsqueeze(0)
 
+    if FLASH_ATTN_3_AVAILABLE:
+        x = xFuserLongContextAttention(attn_type=AttnType.FA3)(
+            None,
+            query=half(q),
+            key=half(k),
+            value=half(v),
+            window_size=self.window_size)
+    else:
+        x = xFuserLongContextAttention()(
+            None,
+            query=half(q),
+            key=half(k),
+            value=half(v),
+            window_size=self.window_size)
+
     x = xFuserLongContextAttention()(
         None,
         query=half(q),