Update pipeline.py

pipeline.py

@@ -7,7 +7,7 @@ import torch
 
 class MOSDiffusionPipeline(DiffusionPipeline):
 
-    def __init__(self, config_yaml, list_inference, reload_from_ckpt=None, base_folder=None):
+    def __init__(self, reload_from_ckpt=None, base_folder=None):
         """
         Initialize the MOS Diffusion pipeline and download the necessary files/folders.
 
@@ -22,15 +22,12 @@ class MOSDiffusionPipeline(DiffusionPipeline):
 
         self.base_folder = base_folder if base_folder else os.getcwd()
         self.repo_id = "jadechoghari/qa-mdt" 
-        self.config_yaml = config_yaml
-        self.list_inference = list_inference
+        self.config_yaml = "./qa_mdt/audioldm_train/config/mos_as_token/qa_mdt.yaml"
         self.reload_from_ckpt = reload_from_ckpt
         config_yaml_path = os.path.join(self.config_yaml)
         self.configs = self.load_yaml(config_yaml_path)
         if self.reload_from_ckpt is not None:
             self.configs["reload_from_ckpt"] = self.reload_from_ckpt
-
-        self.dataset_key = build_dataset_json_from_list(self.list_inference)
         self.exp_name = os.path.basename(self.config_yaml.split(".")[0])
         self.exp_group_name = os.path.basename(os.path.dirname(self.config_yaml))
 
@@ -95,5 +92,5 @@ class MOSDiffusionPipeline(DiffusionPipeline):
 # Example of how to use the pipeline
 if __name__ == "__main__":
     pipe = MOSDiffusionPipeline()
-    result = pipe("Generate a description of a sunny day.")
+    result = pipe("A modern synthesizer creating futuristic soundscapes.")
     print(result)