Update train_vits-2.py

train_vits-2.py

@@ -17,41 +17,6 @@ output_path = os.path.dirname(os.path.abspath(__file__))
 
 
 
-def mozilla_with_speaker(root_path, meta_file, **kwargs):  
-    """Loades three kaggle datasets in Mozilla format as a multispeaker dataset
-    Kaggle datasets are:
-    magnoliasis/persian-tts-dataset-famale
-    magnoliasis/persian-tts-dataset
-    magnoliasis/persian-tts-dataset-male
-    
-    This function is very usefull while using kaggle notebooks.
-    
-    Args:
-        root_path (str): root folder where all three datasets downloaded. for example on kaggle notebooks: /kaggle/input
-        meta_files (str):  list of meta files to be used in the training.
-    """
-    dataset_names={
-    "persian-tts-dataset-famale":"dilara",
-    "persian-tts-dataset":"changiz",
-    "persian-tts-dataset-male":"farid"
-    }
-    items = []
-    for data_root_path in dataset_names.keys():
-        new_root_path=os.path.join(root_path,data_root_path)
-        txt_file = os.path.join(new_root_path, meta_file)
-        speaker_name = dataset_names[data_root_path]
-        print(speaker_name)
-        with open(txt_file, "r", encoding="utf-8") as ttf:
-            for line in ttf:
-                cols = line.split("|")
-                wav_file = cols[1].strip()
-                text = cols[0].strip()
-                wav_file = os.path.join(new_root_path, "wavs", wav_file)
-                items.append({"text": text, "audio_file": wav_file, "speaker_name": speaker_name, "root_path": new_root_path})
-    return items
-
-
-