Implement BaseTTS

TTS/tts/models/base_tts.py

@@ -9,7 +9,7 @@ from torch import nn
 from torch.utils.data import DataLoader
 from torch.utils.data.distributed import DistributedSampler
 
-from TTS.model import BaseModel
+from TTS.model import BaseTrainerModel
 from TTS.tts.datasets.dataset import TTSDataset
 from TTS.tts.utils.languages import LanguageManager, get_language_weighted_sampler
 from TTS.tts.utils.speakers import SpeakerManager, get_speaker_manager, get_speaker_weighted_sampler
@@ -19,27 +19,22 @@ from TTS.tts.utils.visual import plot_alignment, plot_spectrogram
 # pylint: skip-file
 
 
-class BaseTTS(BaseModel):
+class BaseTTS(BaseTrainerModel):
     """Base `tts` class. Every new `tts` model must inherit this.
 
     It defines common `tts` specific functions on top of `Model` implementation.
-
-    Notes on input/output tensor shapes:
-        Any input or output tensor of the model must be shaped as
-
-        - 3D tensors `batch x time x channels`
-        - 2D tensors `batch x channels`
-        - 1D tensors `batch x 1`
     """
 
     def __init__(
-        self, config: Coqpit, ap: "AudioProcessor", tokenizer: "TTSTokenizer", speaker_manager: SpeakerManager = None
+        self, config: Coqpit, ap: "AudioProcessor", tokenizer: "TTSTokenizer", speaker_manager: SpeakerManager = None,
+        language_manager: LanguageManager = None
     ):
-        super().__init__(config)
+        super().__init__()
         self.config = config
         self.ap = ap
         self.tokenizer = tokenizer
         self.speaker_manager = speaker_manager
+        self.language_manager = language_manager
         self._set_model_args(config)
 
     def _set_model_args(self, config: Coqpit):
@@ -262,7 +257,7 @@ class BaseTTS(BaseModel):
                 d_vector_mapping = None
 
             # setup multi-lingual attributes
-            if hasattr(self, "language_manager"):
+            if hasattr(self, "language_manager") and self.language_manager is not None:
                 language_id_mapping = (
                     self.language_manager.language_id_mapping if self.args.use_language_embedding else None
                 )

TTS/tts/utils/text/tokenizer.py

@@ -119,6 +119,10 @@ class TTSTokenizer:
         return [self.characters.bos] + list(char_sequence) + [self.characters.eos]
 
     def intersperse_blank_char(self, char_sequence: List[str], use_blank_char: bool = False):
+        """Intersperses the blank character between characters in a sequence.
+
+        Use the ```blank``` character if defined else use the ```pad``` character.
+        """
         char_to_use = self.characters.blank if use_blank_char else self.characters.pad
         result = [char_to_use] * (len(char_sequence) * 2 + 1)
         result[1::2] = char_sequence