code style

Author: eaidova

optimum/exporters/openvino/__main__.py

@@ -213,7 +213,7 @@ def main_export(
             subfolder=subfolder,
             revision=revision,
             cache_dir=cache_dir,
-            token=token
+            token=token,
         )
         if library_name == "sentence_transformers":
             logger.warning(

optimum/exporters/openvino/convert.py

@@ -631,7 +631,7 @@ def export_from_model(
         task = TasksManager.map_from_synonym(task)
     else:
         try:
-            task = TasksManager._infer_task_from_model_or_model_class(model=model, library_name=library_name)
+            task = TasksManager._infer_task_from_model_or_model_class(model=model)
         except (ValueError, KeyError) as e:
             raise RuntimeError(
                 f"The model task could not be automatically inferred in `export_from_model`. Please provide the argument `task` with the relevant task from {', '.join(TasksManager.get_all_tasks())}. Detailed error: {e}"

optimum/exporters/openvino/model_patcher.py

@@ -3944,10 +3944,7 @@ def __exit__(self, exc_type, exc_value, traceback):
 
 class JanusVisionGenEmbeddingModelPatcher(ModelPatcher):
     def __init__(
-        self,
-        config: "OnnxConfig",
-        model: Union["PreTrainedModel", "TFPreTrainedModel"],
-        model_kwargs: Dict[str, Any]
+        self, config: "OnnxConfig", model: Union["PreTrainedModel", "TFPreTrainedModel"], model_kwargs: Dict[str, Any]
     ):
         model.__orig_forward = model.forward
         model.forward = model.prepare_gen_img_embeds

optimum/intel/openvino/modeling_visual_language.py

@@ -719,7 +719,7 @@ def _submodel_names(self):
         for part in self.additional_parts:
             if part == "lm_head" and getattr(self, part + "_model", None) is not None:
                 model_names.append(part + "_model")
-                continue 
+                continue
             if getattr(self, part, None) is not None:
                 model_names.append(part + "_model")
         return model_names
@@ -2475,7 +2475,7 @@ def generate_image(
         image_token_num_per_image: int = 576,
         img_size: int = 384,
         patch_size: int = 16,
-        generator=None
+        generator=None,
     ):
         from PIL import Image
 
@@ -2524,7 +2524,11 @@ def generate_image(
             logits = logit_uncond + cfg_weight * (logit_cond - logit_uncond)
             probs = torch.softmax(logits / temperature, dim=-1)
 
-            next_token = torch.multinomial(probs, num_samples=1) if generator is None else torch.multinomial(probs, num_samples=1, generator=generator)
+            next_token = (
+                torch.multinomial(probs, num_samples=1)
+                if generator is None
+                else torch.multinomial(probs, num_samples=1, generator=generator)
+            )
             generated_tokens[:, i] = next_token.squeeze(dim=-1)
 
             next_token = torch.cat([next_token.unsqueeze(dim=1), next_token.unsqueeze(dim=1)], dim=1).view(-1)

tests/openvino/utils_tests.py

@@ -170,7 +170,7 @@
     "st-bert": "sentence-transformers/all-MiniLM-L6-v2",
     "st-mpnet": "sentence-transformers/all-mpnet-base-v2",
     "sana": "katuni4ka/tiny-random-sana",
-    "janus": "katuni4ka/tiny-random-janus"
+    "janus": "katuni4ka/tiny-random-janus",
 }