[feat] add VACE sequence parallel (#1345)

* add VACE sequence parallel

* resolve conflict

---------

Co-authored-by: yuan <yuan@yuandeMacBook-Pro.local>
Co-authored-by: Hong Zhang <41229682+mi804@users.noreply.github.com>

diffsynth/utils/xfuser/xdit_context_parallel.py

@@ -117,6 +117,39 @@ def usp_dit_forward(self,
     return x
 
 
+def usp_vace_forward(
+    self, x, vace_context, context, t_mod, freqs,
+    use_gradient_checkpointing: bool = False,
+    use_gradient_checkpointing_offload: bool = False,
+):
+    # Compute full sequence length from the sharded x
+    full_seq_len = x.shape[1] * get_sequence_parallel_world_size()
+
+    # Embed vace_context via patch embedding
+    c = [self.vace_patch_embedding(u.unsqueeze(0)) for u in vace_context]
+    c = [u.flatten(2).transpose(1, 2) for u in c]
+    c = torch.cat([
+        torch.cat([u, u.new_zeros(1, full_seq_len - u.size(1), u.size(2))],
+                  dim=1) for u in c
+    ])
+
+    # Chunk VACE context along sequence dim BEFORE processing through blocks
+    c = torch.chunk(c, get_sequence_parallel_world_size(), dim=1)[get_sequence_parallel_rank()]
+
+    # Process through vace_blocks (self_attn already monkey-patched to usp_attn_forward)
+    for block in self.vace_blocks:
+        c = gradient_checkpoint_forward(
+            block,
+            use_gradient_checkpointing,
+            use_gradient_checkpointing_offload,
+            c, x, context, t_mod, freqs
+        )
+
+    # Hints are already sharded per-rank
+    hints = torch.unbind(c)[:-1]
+    return hints
+
+
 def usp_attn_forward(self, x, freqs):
     q = self.norm_q(self.q(x))
     k = self.norm_k(self.k(x))