Revert "XTTS redownload if needed"

TTS/utils/manage.py

@@ -6,7 +6,6 @@ from pathlib import Path
 from shutil import copyfile, rmtree
 from typing import Dict, List, Tuple
 
-import fsspec
 import requests
 from tqdm import tqdm
 
@@ -321,7 +320,26 @@ class ModelManager(object):
             return False
         return True
 
-    def create_dir_and_download_model(self, model_name, model_item, output_path):
+    def download_model(self, model_name):
+        """Download model files given the full model name.
+        Model name is in the format
+            'type/language/dataset/model'
+            e.g. 'tts_model/en/ljspeech/tacotron'
+
+        Every model must have the following files:
+            - *.pth : pytorch model checkpoint file.
+            - config.json : model config file.
+            - scale_stats.npy (if exist): scale values for preprocessing.
+
+        Args:
+            model_name (str): model name as explained above.
+        """
+        model_item, model_full_name, model = self._set_model_item(model_name)
+        # set the model specific output path
+        output_path = os.path.join(self.output_prefix, model_full_name)
+        if os.path.exists(output_path):
+            print(f" > {model_name} is already downloaded.")
+        else:
             os.makedirs(output_path, exist_ok=True)
             # handle TOS
             if not self.tos_agreed(model_item, output_path):
@@ -342,55 +360,6 @@ class ModelManager(object):
                 rmtree(output_path)
                 raise e
             self.print_model_license(model_item=model_item)
-
-    def check_if_configs_are_equal(self, model_name, model_item, output_path):
-        with fsspec.open(self._find_files(output_path)[1], "r", encoding="utf-8") as f:
-            config_local = json.load(f)
-        remote_url = None
-        for url in model_item["hf_url"]:
-            if "config.json" in url:
-                remote_url = url
-                break
-
-        with fsspec.open(remote_url, "r", encoding="utf-8") as f:
-            config_remote = json.load(f)
-
-        if not config_local == config_remote:
-            print(f" > {model_name} is already downloaded however it has been changed. Redownloading it...")
-            self.create_dir_and_download_model(model_name, model_item, output_path)
-        else:
-            print(f" > {model_name} is already downloaded.")
-
-    def download_model(self, model_name):
-        """Download model files given the full model name.
-        Model name is in the format
-            'type/language/dataset/model'
-            e.g. 'tts_model/en/ljspeech/tacotron'
-
-        Every model must have the following files:
-            - *.pth : pytorch model checkpoint file.
-            - config.json : model config file.
-            - scale_stats.npy (if exist): scale values for preprocessing.
-
-        Args:
-            model_name (str): model name as explained above.
-        """
-        model_item, model_full_name, model = self._set_model_item(model_name)
-        # set the model specific output path
-        output_path = os.path.join(self.output_prefix, model_full_name)
-        if os.path.exists(output_path):
-            # if the configs are different, redownload it
-            # ToDo: we need a better way to handle it
-            if "xtts_v1" in model_name:
-                try:
-                    self.check_if_configs_are_equal(model_name, model_item, output_path)
-                except:
-                    pass
-            else:
-                print(f" > {model_name} is already downloaded.")
-        else:
-            self.create_dir_and_download_model(model_name, model_item, output_path)
-
         # find downloaded files
         output_model_path = output_path
         output_config_path = None