Merge pull request #264 from idiap/fix-fairseq

fix(fairseq): handle change of model file name

TTS/tts/models/vits.py

@@ -3,7 +3,8 @@
 import os
 from dataclasses import dataclass, field, replace
 from itertools import chain
-from typing import Dict, List, Tuple, Union
+from pathlib import Path
+from typing import Any, Dict, List, Tuple, Union
 
 import numpy as np
 import torch
@@ -1581,13 +1582,16 @@ def load_fairseq_checkpoint(
 
         self.disc = None
         # set paths
-        config_file = os.path.join(checkpoint_dir, "config.json")
-        checkpoint_file = os.path.join(checkpoint_dir, "G_100000.pth")
-        vocab_file = os.path.join(checkpoint_dir, "vocab.txt")
+        checkpoint_dir = Path(checkpoint_dir)
+        config_file = checkpoint_dir / "config.json"
+        checkpoint_file = checkpoint_dir / "model.pth"
+        if not checkpoint_file.is_file():
+            checkpoint_file = checkpoint_dir / "G_100000.pth"
+        vocab_file = checkpoint_dir / "vocab.txt"
         # set config params
-        with open(config_file, "r", encoding="utf-8") as file:
+        with open(config_file, "r", encoding="utf-8") as f:
             # Load the JSON data as a dictionary
-            config_org = json.load(file)
+            config_org = json.load(f)
         self.config.audio.sample_rate = config_org["data"]["sampling_rate"]
         # self.config.add_blank = config['add_blank']
         # set tokenizer
@@ -1821,7 +1825,7 @@ def to_config(self) -> "CharactersConfig":
 
 
 class FairseqVocab(BaseVocabulary):
-    def __init__(self, vocab: str):
+    def __init__(self, vocab: Union[str, os.PathLike[Any]]):
         super(FairseqVocab).__init__()
         self.vocab = vocab
 
@@ -1831,7 +1835,7 @@ def vocab(self):
         return self._vocab
 
     @vocab.setter
-    def vocab(self, vocab_file):
+    def vocab(self, vocab_file: Union[str, os.PathLike[Any]]):
         with open(vocab_file, encoding="utf-8") as f:
             self._vocab = [x.replace("\n", "") for x in f.readlines()]
         self.blank = self._vocab[0]

pyproject.toml

@@ -25,7 +25,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "coqui-tts"
-version = "0.25.2"
+version = "0.25.3"
 description = "Deep learning for Text to Speech."
 readme = "README.md"
 requires-python = ">=3.9, <3.13"

tests/zoo_tests/test_models.py

@@ -37,6 +37,7 @@ def manager(tmp_path):
 num_partitions = int(os.getenv("NUM_PARTITIONS", "1"))
 partition = int(os.getenv("TEST_PARTITION", "0"))
 model_names = [name for name in TTS.list_models() if name not in MODELS_WITH_SEP_TESTS]
+model_names.extend(["tts_models/deu/fairseq/vits", "tts_models/sqi/fairseq/vits"])
 model_names = [name for i, name in enumerate(model_names) if i % num_partitions == partition]