diff --git a/src/diffusers/models/attention_processor.py b/src/diffusers/models/attention_processor.py
index 88e7072e6..c66b29030 100644
--- a/src/diffusers/models/attention_processor.py
+++ b/src/diffusers/models/attention_processor.py
@@ -20,11 +20,14 @@
 from torch import nn
 
 from ..image_processor import IPAdapterMaskProcessor
-from ..utils import deprecate, logging, is_torch_xla_available
+from ..utils import deprecate, is_torch_xla_available, logging
 from ..utils.import_utils import is_torch_npu_available, is_xformers_available
 from ..utils.torch_utils import is_torch_version, maybe_allow_in_graph
 
+
 if is_torch_xla_available():
+    import torch_xla.distributed.spmd as xs
+    import torch_xla.runtime as xr
     from torch_xla.experimental.custom_kernel import flash_attention
     XLA_AVAILABLE = True
 else:
@@ -2369,17 +2372,19 @@ def __call__(
 
         # the output of sdp = (batch, num_heads, seq_len, head_dim)
         # TODO: add support for attn.scale when we move to Torch 2.1
-       
+
+        mesh = xs.get_global_mesh()
         if XLA_AVAILABLE and all(tensor.shape[2] >= 4096 for tensor in [query, key, value]):
             if attention_mask is not None:
                 attention_mask = attention_mask.view(batch_size, 1, 1, attention_mask.shape[-1])
                 # Convert mask to float and replace 0s with -inf and 1s with 0
                 attention_mask = attention_mask.float().masked_fill(attention_mask == 0, float('-inf')).masked_fill(attention_mask == 1, float(0.0))
-            
+
                 # Apply attention mask to key
                 key = key + attention_mask
             query /= math.sqrt(query.shape[3])
-            hidden_states = flash_attention(query, key, value, causal=False, partition_spec=('data', None, None, None))
+            partition_spec = ('data', None, None, None) if xr.use_spmd() else None
+            hidden_states = flash_attention(query, key, value, causal=False, partition_spec=partition_spec, mesh=mesh)
         else:
             hidden_states = F.scaled_dot_product_attention(
                 query, key, value, attn_mask=attention_mask, dropout_p=0.0, is_causal=False
@@ -4317,4 +4322,4 @@ def __init__(self):
     PAGIdentitySelfAttnProcessor2_0,
     PAGCFGHunyuanAttnProcessor2_0,
     PAGHunyuanAttnProcessor2_0,
-]
+]
\ No newline at end of file