Fixes small compat. issues

TTS/tts/datasets/__init__.py

@@ -111,8 +111,8 @@ def load_tts_samples(
             meta_data_eval_all += meta_data_eval
         meta_data_train_all += meta_data_train
         # load attention masks for the duration predictor training
-        if d.meta_file_attn_mask:
+        if dataset.meta_file_attn_mask:
-            meta_data = dict(load_attention_mask_meta_data(d["meta_file_attn_mask"]))
+            meta_data = dict(load_attention_mask_meta_data(dataset["meta_file_attn_mask"]))
             for idx, ins in enumerate(meta_data_train_all):
                 attn_file = meta_data[ins["audio_file"]].strip()
                 meta_data_train_all[idx].update({"alignment_file": attn_file})

TTS/tts/datasets/dataset.py

@@ -13,7 +13,7 @@ from TTS.utils.audio import AudioProcessor
 
 # to prevent too many open files error as suggested here
 # https://github.com/pytorch/pytorch/issues/11201#issuecomment-421146936
-torch.multiprocessing.set_sharing_strategy('file_system')
+torch.multiprocessing.set_sharing_strategy("file_system")
 
 
 def _parse_sample(item):

TTS/tts/datasets/formatters.py

@@ -291,7 +291,7 @@ def brspeech(root_path, meta_file, ignored_speakers=None):
 
 def vctk(root_path, meta_files=None, wavs_path="wav48_silence_trimmed", mic="mic2", ignored_speakers=None):
     """https://datashare.ed.ac.uk/bitstream/handle/10283/3443/VCTK-Corpus-0.92.zip"""
-    file_ext = 'flac'
+    file_ext = "flac"
     test_speakers = meta_files
     items = []
     meta_files = glob(f"{os.path.join(root_path,'txt')}/**/*.txt", recursive=True)

TTS/tts/models/base_tts.py

@@ -261,7 +261,7 @@ class BaseTTS(BaseModel):
                 speaker_id_mapping = None
                 d_vector_mapping = None
 
-            # setup custom symbols if needed
+            # setup multi-lingual attributes
             if hasattr(self, "language_manager"):
                 language_id_mapping = (
                     self.language_manager.language_id_mapping if self.args.use_language_embedding else None
@@ -290,6 +290,7 @@ class BaseTTS(BaseModel):
                 speaker_id_mapping=speaker_id_mapping,
                 d_vector_mapping=d_vector_mapping if config.use_d_vector_file else None,
                 tokenizer=self.tokenizer,
+                language_id_mapping=language_id_mapping,
             )
 
             # wait all the DDP process to be ready
@@ -303,6 +304,7 @@ class BaseTTS(BaseModel):
             sampler = DistributedSampler(dataset) if num_gpus > 1 else None
 
             # Weighted samplers
+            # TODO: make this DDP amenable
             assert not (
                 num_gpus > 1 and getattr(config, "use_language_weighted_sampler", False)
             ), "language_weighted_sampler is not supported with DistributedSampler"
@@ -313,10 +315,10 @@ class BaseTTS(BaseModel):
             if sampler is None:
                 if getattr(config, "use_language_weighted_sampler", False):
                     print(" > Using Language weighted sampler")
-                    sampler = get_language_weighted_sampler(dataset.items)
+                    sampler = get_language_weighted_sampler(dataset.samples)
                 elif getattr(config, "use_speaker_weighted_sampler", False):
                     print(" > Using Language weighted sampler")
-                    sampler = get_speaker_weighted_sampler(dataset.items)
+                    sampler = get_speaker_weighted_sampler(dataset.samples)
 
             loader = DataLoader(
                 dataset,

TTS/tts/utils/languages.py

@@ -98,6 +98,15 @@ class LanguageManager:
         """
         self._save_json(file_path, self.language_id_mapping)
 
+    @staticmethod
+    def init_from_config(config: Coqpit) -> "LanguageManager":
+        """Initialize the language manager from a Coqpit config.
+
+        Args:
+            config (Coqpit): Coqpit config.
+        """
+        return LanguageManager(config=config)
+
 
 def _set_file_path(path):
     """Find the language_ids.json under the given path or the above it.

TTS/tts/utils/speakers.py

@@ -9,7 +9,7 @@ import torch
 from coqpit import Coqpit
 from torch.utils.data.sampler import WeightedRandomSampler
 
-from TTS.config import load_config
+from TTS.config import get_from_config_or_model_args_with_default, load_config
 from TTS.speaker_encoder.utils.generic_utils import setup_speaker_encoder_model
 from TTS.utils.audio import AudioProcessor
 
@@ -331,19 +331,27 @@ class SpeakerManager:
             SpeakerEncoder: Speaker encoder object.
         """
         speaker_manager = None
-        if hasattr(config, "use_speaker_embedding") and config.use_speaker_embedding:
+        if get_from_config_or_model_args_with_default(config, "use_speaker_embedding", False):
             if samples:
                 speaker_manager = SpeakerManager(data_items=samples)
-            if config.get("speaker_file", None):
+            if get_from_config_or_model_args_with_default(config, "speaker_file", None):
-                speaker_manager = SpeakerManager(speaker_id_file_path=config.speaker_file)
+                speaker_manager = SpeakerManager(
-            if config.get("speakers_file", None):
+                    speaker_id_file_path=get_from_config_or_model_args_with_default(config, "speaker_file", None)
-                speaker_manager = SpeakerManager(speaker_id_file_path=config.speakers_file)
+                )
+            if get_from_config_or_model_args_with_default(config, "speakers_file", None):
+                speaker_manager = SpeakerManager(
+                    speaker_id_file_path=get_from_config_or_model_args_with_default(config, "speakers_file", None)
+                )
 
-        if hasattr(config, "use_d_vector_file") and config.use_d_vector_file:
+        if get_from_config_or_model_args_with_default(config, "use_d_vector_file", False):
-            if config.get("speakers_file", None):
+            if get_from_config_or_model_args_with_default(config, "speakers_file", None):
-                speaker_manager = SpeakerManager(d_vectors_file_path=config.speaker_file)
+                speaker_manager = SpeakerManager(
-            if config.get("d_vector_file", None):
+                    d_vectors_file_path=get_from_config_or_model_args_with_default(config, "speaker_file", None)
-                speaker_manager = SpeakerManager(d_vectors_file_path=config.d_vector_file)
+                )
+            if get_from_config_or_model_args_with_default(config, "d_vector_file", None):
+                speaker_manager = SpeakerManager(
+                    d_vectors_file_path=get_from_config_or_model_args_with_default(config, "d_vector_file", None)
+                )
         return speaker_manager
 
 

recipes/vctk/fast_pitch/train_fast_pitch.py

@@ -90,4 +90,3 @@ trainer = Trainer(
 
 # AND... 3,2,1... 🚀
 trainer.fit()
-

recipes/vctk/fast_speech/train_fast_speech.py

@@ -87,4 +87,4 @@ trainer = Trainer(
 )
 
 # AND... 3,2,1... 🚀
-trainer.fit()
+trainer.fit()

recipes/vctk/glow_tts/train_glow_tts.py

@@ -87,4 +87,4 @@ trainer = Trainer(
 )
 
 # AND... 3,2,1... 🚀
-trainer.fit()
+trainer.fit()

tests/text_tests/test_phonemizer.py

@@ -109,10 +109,11 @@ class TestEspeakNgPhonemizer(unittest.TestCase):
 class TestGruutPhonemizer(unittest.TestCase):
     def setUp(self):
         self.phonemizer = Gruut(language="en-us", use_espeak_phonemes=True, keep_stress=False)
-        self.EXPECTED_PHONEMES = ["ɹ|i|ː|s|ə|n|t| ɹ|ᵻ|s|ɜ|ː|t|ʃ| æ|ɾ| h|ɑ|ː|ɹ|v|ɚ|d| h|ɐ|z| ʃ|o|ʊ|n| m|ɛ|d|ᵻ|t|e|ɪ|ɾ|ɪ|ŋ",
+        self.EXPECTED_PHONEMES = [
-                                  "f|ɔ|ː|ɹ| æ|z| l|ɪ|ɾ|ə|l| æ|z| e|ɪ|t| w|i|ː|k|s| k|æ|ŋ| æ|k|t|ʃ|u|ː|ə|l|i| ɪ|ŋ|k|ɹ|i|ː|s, ð|ə| ɡ|ɹ|e|ɪ| m|æ|ɾ|ɚ",
+            "ɹ|i|ː|s|ə|n|t| ɹ|ᵻ|s|ɜ|ː|t|ʃ| æ|ɾ| h|ɑ|ː|ɹ|v|ɚ|d| h|ɐ|z| ʃ|o|ʊ|n| m|ɛ|d|ᵻ|t|e|ɪ|ɾ|ɪ|ŋ",
-                                  "ɪ|n| ð|ə| p|ɑ|ː|ɹ|t|s| ʌ|v| ð|ə| b|ɹ|e|ɪ|n| ɹ|ᵻ|s|p|ɑ|ː|n|s|ᵻ|b|ə|l",
+            "f|ɔ|ː|ɹ| æ|z| l|ɪ|ɾ|ə|l| æ|z| e|ɪ|t| w|i|ː|k|s| k|æ|ŋ| æ|k|t|ʃ|u|ː|ə|l|i| ɪ|ŋ|k|ɹ|i|ː|s, ð|ə| ɡ|ɹ|e|ɪ| m|æ|ɾ|ɚ",
-                                  "f|ɔ|ː|ɹ| ɪ|m|o|ʊ|ʃ|ə|n|ə|l| ɹ|ɛ|ɡ|j|ʊ|l|e|ɪ|ʃ|ə|n| æ|n|d| l|ɜ|ː|n|ɪ|ŋ!"
+            "ɪ|n| ð|ə| p|ɑ|ː|ɹ|t|s| ʌ|v| ð|ə| b|ɹ|e|ɪ|n| ɹ|ᵻ|s|p|ɑ|ː|n|s|ᵻ|b|ə|l",
+            "f|ɔ|ː|ɹ| ɪ|m|o|ʊ|ʃ|ə|n|ə|l| ɹ|ɛ|ɡ|j|ʊ|l|e|ɪ|ʃ|ə|n| æ|n|d| l|ɜ|ː|n|ɪ|ŋ!",
         ]
 
     def test_phonemize(self):