make style + make fix-copies

Author: miguelmartin75

src/diffusers/pipelines/cosmos/pipeline_cosmos2_5_predict.py

@@ -233,7 +233,6 @@ def __init__(
         if self.latents_mean is None or self.latents_std is None:
             raise ValueError("VAE configuration must define both `latents_mean` and `latents_std`.")
 
-    # Copied from diffusers.pipelines.cosmos.pipeline_cosmos_text2world.CosmosTextToWorldPipeline._get_prompt_embeds
     def _get_prompt_embeds(
         self,
         prompt: Union[str, List[str]] = None,
@@ -384,7 +383,7 @@ def encode_prompt(
 
         return prompt_embeds, negative_prompt_embeds
 
-    # Modified from diffusers.pipelines.cosmos.pipeline_cosmos2_video2world.Cosmos2VideoToWorldPipeline.prepare_latents and 
+    # Modified from diffusers.pipelines.cosmos.pipeline_cosmos2_video2world.Cosmos2VideoToWorldPipeline.prepare_latents and
     # diffusers.pipelines.cosmos.pipeline_cosmos2_video2world.Cosmos2TextToImagePipeline.prepare_latents
     def prepare_latents(
         self,

src/diffusers/utils/dummy_torch_and_transformers_objects.py

@@ -767,6 +767,66 @@ def from_pretrained(cls, *args, **kwargs):
         requires_backends(cls, ["torch", "transformers"])
 
 
+class Cosmos2_5_PredictBasePipeline(metaclass=DummyObject):
+    _backends = ["torch", "transformers"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch", "transformers"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+
+class Cosmos2_5_PredictImage2World(metaclass=DummyObject):
+    _backends = ["torch", "transformers"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch", "transformers"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+
+class Cosmos2_5_PredictText2World(metaclass=DummyObject):
+    _backends = ["torch", "transformers"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch", "transformers"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+
+class Cosmos2_5_PredictVideo2World(metaclass=DummyObject):
+    _backends = ["torch", "transformers"]
+
+    def __init__(self, *args, **kwargs):
+        requires_backends(self, ["torch", "transformers"])
+
+    @classmethod
+    def from_config(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+    @classmethod
+    def from_pretrained(cls, *args, **kwargs):
+        requires_backends(cls, ["torch", "transformers"])
+
+
 class Cosmos2TextToImagePipeline(metaclass=DummyObject):
     _backends = ["torch", "transformers"]
 

tests/schedulers/test_scheduler_unipc.py

@@ -414,7 +414,7 @@ def test_flow_and_karras_sigmas_values(self):
             num_train_timesteps=num_train_timesteps,
         )
         scheduler.set_timesteps(num_inference_steps=num_inference_steps)
- 
+
         expected_sigmas = [
             0.9950248599052429,
             0.9787454605102539,