Fix duplicate variable assignments in SD3's JointAttnProcessor (#8516)

* Fix duplicate variable assignments.

* Fix duplicate variable assignments.

Author: Prgckwb

src/diffusers/models/attention_processor.py

@@ -1132,9 +1132,7 @@ def __call__(
         key = key.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)
         value = value.view(batch_size, -1, attn.heads, head_dim).transpose(1, 2)
 
-        hidden_states = hidden_states = F.scaled_dot_product_attention(
-            query, key, value, dropout_p=0.0, is_causal=False
-        )
+        hidden_states = F.scaled_dot_product_attention(query, key, value, dropout_p=0.0, is_causal=False)
         hidden_states = hidden_states.transpose(1, 2).reshape(batch_size, -1, attn.heads * head_dim)
         hidden_states = hidden_states.to(query.dtype)
 
@@ -1406,7 +1404,6 @@ def __call__(
 
 
 class AttnProcessorNPU:
-
     r"""
     Processor for implementing flash attention using torch_npu. Torch_npu supports only fp16 and bf16 data types. If
     fp32 is used, F.scaled_dot_product_attention will be used for computation, but the acceleration effect on NPU is

utils/update_metadata.py

@@ -24,6 +24,7 @@
 Script modified from:
 https://github.com/huggingface/transformers/blob/main/utils/update_metadata.py
 """
+
 import argparse
 import os
 import tempfile