diff --git a/modules/intel/ipex/attention.py b/modules/intel/ipex/attention.py
index 22c74a78b..32e8d271a 100644
--- a/modules/intel/ipex/attention.py
+++ b/modules/intel/ipex/attention.py
@@ -136,11 +136,11 @@ def scaled_dot_product_attention_32_bit(query, key, value, attn_mask=None, dropo
     if do_split:
         batch_size_attention, query_tokens, shape_three = query.shape[0], query.shape[1], query.shape[2]
         hidden_states = torch.zeros(query.shape, device=query.device, dtype=query.dtype)
-        if attn_mask is not None and attn_mask.shape != query.shape:
+        if attn_mask is not None and attn_mask.shape[:-1] != query.shape[:-1]:
             if len(query.shape) == 4:
                 attn_mask = attn_mask.repeat((batch_size_attention // attn_mask.shape[0], query_tokens // attn_mask.shape[1], shape_three // attn_mask.shape[2], 1))
             else:
-                attn_mask = attn_mask.repeat((batch_size_attention // attn_mask.shape[0], query_tokens // attn_mask.shape[1], shape_three // attn_mask.shape[2]))
+                attn_mask = attn_mask.repeat((batch_size_attention // attn_mask.shape[0], query_tokens // attn_mask.shape[1], 1))
         for i in range(batch_size_attention // split_slice_size):
             start_idx = i * split_slice_size
             end_idx = (i + 1) * split_slice_size
diff --git a/modules/sd_hijack_dynamic_atten.py b/modules/sd_hijack_dynamic_atten.py
index cb64482a5..5ad1eb079 100644
--- a/modules/sd_hijack_dynamic_atten.py
+++ b/modules/sd_hijack_dynamic_atten.py
@@ -57,11 +57,11 @@ def sliced_scaled_dot_product_attention(query, key, value, attn_mask=None, dropo
     if do_split:
         batch_size_attention, query_tokens, shape_three = query.shape[0], query.shape[1], query.shape[2]
         hidden_states = torch.zeros(query.shape, device=query.device, dtype=query.dtype)
-        if attn_mask is not None and attn_mask.shape != query.shape:
+        if attn_mask is not None and attn_mask.shape[:-1] != query.shape[:-1]:
             if len(query.shape) == 4:
                 attn_mask = attn_mask.repeat((batch_size_attention // attn_mask.shape[0], query_tokens // attn_mask.shape[1], shape_three // attn_mask.shape[2], 1))
             else:
-                attn_mask = attn_mask.repeat((batch_size_attention // attn_mask.shape[0], query_tokens // attn_mask.shape[1], shape_three // attn_mask.shape[2]))
+                attn_mask = attn_mask.repeat((batch_size_attention // attn_mask.shape[0], query_tokens // attn_mask.shape[1], 1))
         for i in range(batch_size_attention // split_slice_size):
             start_idx = i * split_slice_size
             end_idx = (i + 1) * split_slice_size