change custom pipeline init issue

wrapper.py

@@ -183,14 +183,11 @@ def peca(pipeline, save_path = "./weight", n_layer = 10):
     return encoder, feature_encoder.get_text_feature, size, num_inference_steps, skip
 
 class DrUM(DiffusionPipeline):
-    def __init__(self, pipeline = None, repo_id = "Burf/DrUM", weight = None, pretrained_model_name_or_path = None, torch_dtype = torch.bfloat16, device = "cuda"):
+    def __init__(self, pipeline, repo_id = "Burf/DrUM", weight = None, torch_dtype = torch.bfloat16, device = "cuda"):
         """
         DrUM for various T2I diffusion models
         """
-        if pipeline is None and pretrained_model_name_or_path is None:
-            raise ValueError("pipeline or pretrained_model_name_or_path must be provided")
-
-        self.pipeline = pipeline if pipeline is not None else self.load_pipeline(pretrained_model_name_or_path, torch_dtype = torch_dtype, device = device)
+        self.pipeline = pipeline if not isinstance(pipeline, str) else self.load_pipeline(pipeline, torch_dtype = torch_dtype, device = device)
         self.repo_id = repo_id
         
         self.adapter, self.feature_encoder, self.size, self.num_inference_steps, self.skip = self.load_peca(self.pipeline, repo_id, weight)