make style; make quality; make fix-copies

Author: dg845

src/diffusers/utils/dummy_pt_objects.py

@@ -843,6 +843,21 @@ def from_pretrained(cls, *args, **kwargs):
         requires_backends(cls, ["torch"])
 
 
+class Flux2Transformer2DModel(metaclass=DummyObject):
+    _backends = ["torch"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch"])
+
+
 class FluxControlNetModel(metaclass=DummyObject):
     _backends = ["torch"]
 

tests/models/transformers/test_models_transformer_flux2.py

@@ -212,9 +212,7 @@ def test_lora_exclude_modules(self):
             f"{target_module}.lora_B.weight": torch.ones(target_mod_shape[0], lora_rank) * 33,
         }
         # Passing exclude_modules should no longer be necessary (or even passing target_modules, for that matter).
-        config = LoraConfig(
-            r=lora_rank, target_modules=[target_module], exclude_modules=["to_out"]
-        )
+        config = LoraConfig(r=lora_rank, target_modules=[target_module], exclude_modules=["to_out"])
         inject_adapter_in_model(config, model, adapter_name=adapter_name, state_dict=lora_state_dict)
         set_peft_model_state_dict(model, lora_state_dict, adapter_name)
         retrieved_lora_state_dict = get_peft_model_state_dict(model, adapter_name=adapter_name)