Fix compatibility issue of symbols

synthesizer/train.py

@@ -67,8 +67,17 @@ def train(run_id: str, syn_dir: str, models_dir: str, save_every: int,
 
     # Instantiate Tacotron Model
     print("\nInitialising Tacotron Model...\n")
+    num_chars = len(symbols)
+    if weights_fpath.exists():
+        # for compatibility purpose, change symbols accordingly:
+        loaded_shape = torch.load(str(weights_fpath), map_location=device)["model_state"]["encoder.embedding.weight"].shape
+        if num_chars != loaded_shape[0]:
+            print("WARNING: you are using compatible mode due to wrong sympols length, please modify varible _characters in `utils\symbols.py`")
+            num_chars != loaded_shape[0]
+
+
     model = Tacotron(embed_dims=hparams.tts_embed_dims,
-                     num_chars=len(symbols),
+                     num_chars=num_chars,
                      encoder_dims=hparams.tts_encoder_dims,
                      decoder_dims=hparams.tts_decoder_dims,
                      n_mels=hparams.num_mels,

synthesizer/utils/symbols.py

@@ -9,6 +9,8 @@ through Unidecode. For other data, you can modify _characters. See TRAINING_DATA
 _pad        = "_"
 _eos        = "~"
 _characters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz1234567890!\'(),-.:;? '
+
+#_characters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz12340!\'(),-.:;? ' # use this old one if you want to train old model 
 # Prepend "@" to ARPAbet symbols to ensure uniqueness (some are the same as uppercase letters):
 #_arpabet = ["@' + s for s in cmudict.valid_symbols]