save default model chars to the training config file

TTS/utils/arguments.py

@@ -3,17 +3,18 @@
 """Argument parser for training scripts."""
 
 import argparse
-import re
 import glob
 import os
-
-from TTS.utils.generic_utils import (
-    create_experiment_folder, get_git_branch)
-from TTS.utils.console_logger import ConsoleLogger
-from TTS.utils.io import copy_model_files, load_config
-from TTS.utils.tensorboard_logger import TensorboardLogger
+import re
+import json
 
 from TTS.tts.utils.generic_utils import check_config_tts
+from TTS.utils.console_logger import ConsoleLogger
+from TTS.utils.generic_utils import create_experiment_folder, get_git_branch
+from TTS.utils.io import (copy_model_files, load_config,
+                          save_characters_to_config)
+from TTS.utils.tensorboard_logger import TensorboardLogger
+from TTS.tts.utils.text.symbols import parse_symbols
 
 
 def parse_arguments(argv):
@@ -110,38 +111,27 @@ def get_last_checkpoint(path):
 def process_args(args, model_type):
     """Process parsed comand line arguments.
 
-    Parameters
-    ----------
-    args : argparse.Namespace or dict like
-        Parsed input arguments.
-    model_type : str
-        Model type used to check config parameters and setup the TensorBoard
-        logger. One of:
-            - tacotron
-            - glow_tts
-            - speedy_speech
-            - gan
-            - wavegrad
-            - wavernn
+    Args:
+        args (argparse.Namespace or dict like): Parsed input arguments.
+        model_type (str): Model type used to check config parameters and setup the TensorBoard
+            logger. One of:
+                - tacotron
+                - glow_tts
+                - speedy_speech
+                - gan
+                - wavegrad
+                - wavernn
 
-    Raises
-    ------
-    ValueError
-        If `model_type` is not one of implemented choices.
-
-    Returns
-    -------
-    c : TTS.utils.io.AttrDict
-        Config paramaters.
-    out_path : str
-        Path to save models and logging.
-    audio_path : str
-        Path to save generated test audios.
-    c_logger : TTS.utils.console_logger.ConsoleLogger
-        Class that does logging to the console.
-    tb_logger : TTS.utils.tensorboard.TensorboardLogger
-        Class that does the TensorBoard loggind.
+    Raises:
+        ValueError
+            If `model_type` is not one of implemented choices.
 
+    Returns:
+        c (TTS.utils.io.AttrDict): Config paramaters.
+        out_path (str): Path to save models and logging.
+        audio_path (str): Path to save generated test audios.
+        c_logger (TTS.utils.console_logger.ConsoleLogger): Class that does logging to the console.
+        tb_logger (TTS.utils.tensorboard.TensorboardLogger): Class that does the TensorBoard loggind.
     """
     if args.continue_path != "":
         args.output_path = args.continue_path
@@ -156,7 +146,6 @@ def process_args(args, model_type):
 
     # setup output paths and read configs
     c = load_config(args.config_path)
-
     if model_type in "tacotron glow_tts speedy_speech":
         model_class = "TTS"
     elif model_type in "gan wavegrad wavernn":
@@ -192,6 +181,12 @@ def process_args(args, model_type):
         if args.restore_path:
             new_fields["restore_path"] = args.restore_path
         new_fields["github_branch"] = get_git_branch()
+        # if model characters are not set in the config file
+        # save the default set to the config file for future
+        # compatibility.
+        if model_class == 'TTS' and not 'characters' in c.keys():
+            used_characters = parse_symbols()
+            new_fields['characters'] = used_characters
         copy_model_files(c, args.config_path,
                          out_path, new_fields)
         os.chmod(audio_path, 0o775)

TTS/utils/io.py

@@ -67,7 +67,7 @@ def copy_model_files(c, config_file, out_path, new_fields):
         if isinstance(value, str):
             new_line = '"{}":"{}",\n'.format(key, value)
         else:
-            new_line = '"{}":{},\n'.format(key, value)
+            new_line = '"{}":{},\n'.format(key, json.dumps(value, ensure_ascii=False))
         config_lines.insert(1, new_line)
     config_out_file = open(copy_config_path, "w")
     config_out_file.writelines(config_lines)