[TTS]fix open encoding (#2865)

pull/2879/head
TianYuan 3 years ago committed by GitHub
parent a55fd2e556
commit a283f8a57e
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@ -292,19 +292,19 @@ class TTSExecutor(BaseExecutor):
with open(self.voc_config) as f:
self.voc_config = CfgNode(yaml.safe_load(f))
with open(self.phones_dict, "r") as f:
with open(self.phones_dict, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
vocab_size = len(phn_id)
tone_size = None
if self.tones_dict:
with open(self.tones_dict, "r") as f:
with open(self.tones_dict, 'rt', encoding='utf-8') as f:
tone_id = [line.strip().split() for line in f.readlines()]
tone_size = len(tone_id)
spk_num = None
if self.speaker_dict:
with open(self.speaker_dict, 'rt') as f:
with open(self.speaker_dict, 'rt', encoding='utf-8') as f:
spk_id = [line.strip().split() for line in f.readlines()]
spk_num = len(spk_id)

@ -437,7 +437,7 @@ if __name__ == '__main__':
vocab_phones = {}
with open(args.phones_dict, 'rt') as f:
with open(args.phones_dict, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
for phn, id in phn_id:
vocab_phones[phn] = int(id)

@ -109,7 +109,7 @@ def train_sp(args, config):
num_workers=config.num_workers)
print("dataloaders done!")
with open(args.phones_dict, "r") as f:
with open(args.phones_dict, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
vocab_size = len(phn_id)
print("vocab_size:", vocab_size)

@ -67,7 +67,7 @@ def train_sp(args, config):
if args.speaker_dict is not None:
print("multiple speaker fastspeech2!")
collate_fn = fastspeech2_multi_spk_batch_fn
with open(args.speaker_dict, 'rt') as f:
with open(args.speaker_dict, 'rt', encoding='utf-8') as f:
spk_id = [line.strip().split() for line in f.readlines()]
spk_num = len(spk_id)
fields += ["spk_id"]
@ -123,7 +123,7 @@ def train_sp(args, config):
num_workers=config.num_workers)
print("dataloaders done!")
with open(args.phones_dict, "r") as f:
with open(args.phones_dict, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
vocab_size = len(phn_id)
print("vocab_size:", vocab_size)

@ -39,18 +39,18 @@ def evaluate(args, speedyspeech_config, pwg_config):
# construct dataset for evaluation
sentences = []
with open(args.text, 'rt') as f:
with open(args.text, 'rt', encoding='utf-8') as f:
for line in f:
items = line.strip().split()
utt_id = items[0]
sentence = "".join(items[1:])
sentences.append((utt_id, sentence))
with open(args.phones_dict, "r") as f:
with open(args.phones_dict, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
vocab_size = len(phn_id)
print("vocab_size:", vocab_size)
with open(args.tones_dict, "r") as f:
with open(args.tones_dict, 'rt', encoding='utf-8') as f:
tone_id = [line.strip().split() for line in f.readlines()]
tone_size = len(tone_id)
print("tone_size:", tone_size)

@ -70,7 +70,7 @@ def train_sp(args, config):
if args.speaker_dict is not None:
print("multiple speaker speedyspeech!")
collate_fn = speedyspeech_multi_spk_batch_fn
with open(args.speaker_dict, 'rt') as f:
with open(args.speaker_dict, 'rt', encoding='utf-8') as f:
spk_id = [line.strip().split() for line in f.readlines()]
spk_num = len(spk_id)
fields += ["spk_id"]
@ -133,11 +133,11 @@ def train_sp(args, config):
collate_fn=collate_fn,
num_workers=config.num_workers)
print("dataloaders done!")
with open(args.phones_dict, "r") as f:
with open(args.phones_dict, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
vocab_size = len(phn_id)
print("vocab_size:", vocab_size)
with open(args.tones_dict, "r") as f:
with open(args.tones_dict, 'rt', encoding='utf-8') as f:
tone_id = [line.strip().split() for line in f.readlines()]
tone_size = len(tone_id)
print("tone_size:", tone_size)

@ -106,7 +106,7 @@ def get_chunks(data, block_size: int, pad_size: int):
def get_sentences(text_file: Optional[os.PathLike], lang: str='zh'):
# construct dataset for evaluation
sentences = []
with open(text_file, 'rt') as f:
with open(text_file, 'rt', encoding='utf-8') as f:
for line in f:
if line.strip() != "":
items = re.split(r"\s+", line.strip(), 1)
@ -325,17 +325,17 @@ def get_am_inference(am: str='fastspeech2_csmsc',
tones_dict: Optional[os.PathLike]=None,
speaker_dict: Optional[os.PathLike]=None,
return_am: bool=False):
with open(phones_dict, "r") as f:
with open(phones_dict, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
vocab_size = len(phn_id)
tone_size = None
if tones_dict is not None:
with open(tones_dict, "r") as f:
with open(tones_dict, 'rt', encoding='utf-8') as f:
tone_id = [line.strip().split() for line in f.readlines()]
tone_size = len(tone_id)
spk_num = None
if speaker_dict is not None:
with open(speaker_dict, 'rt') as f:
with open(speaker_dict, 'rt', encoding='utf-8') as f:
spk_id = [line.strip().split() for line in f.readlines()]
spk_num = len(spk_id)
odim = am_config.n_mels

@ -119,7 +119,7 @@ def train_sp(args, config):
num_workers=config.num_workers)
print("dataloaders done!")
with open(args.phones_dict, "r") as f:
with open(args.phones_dict, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
vocab_size = len(phn_id)
print("vocab_size:", vocab_size)

@ -114,7 +114,7 @@ def train_sp(args, config):
num_workers=config.num_workers)
print("dataloaders done!")
with open(args.phones_dict, "r") as f:
with open(args.phones_dict, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
vocab_size = len(phn_id)
print("vocab_size:", vocab_size)

@ -78,7 +78,7 @@ def train_sp(args, config):
if args.speaker_dict is not None:
print("multiple speaker vits!")
collate_fn = vits_multi_spk_batch_fn
with open(args.speaker_dict, 'rt') as f:
with open(args.speaker_dict, 'rt', encoding='utf-8') as f:
spk_id = [line.strip().split() for line in f.readlines()]
spk_num = len(spk_id)
fields += ["spk_id"]
@ -132,7 +132,7 @@ def train_sp(args, config):
num_workers=config.num_workers)
print("dataloaders done!")
with open(args.phones_dict, "r") as f:
with open(args.phones_dict, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
vocab_size = len(phn_id)
print("vocab_size:", vocab_size)

@ -58,7 +58,7 @@ class English(Phonetics):
self.punc = ":,;。?!“”‘’':,;.?!"
self.text_normalizer = TextNormalizer()
if phone_vocab_path:
with open(phone_vocab_path, 'rt') as f:
with open(phone_vocab_path, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
for phn, id in phn_id:
self.vocab_phones[phn] = int(id)

@ -144,12 +144,12 @@ class Frontend():
self.vocab_phones = {}
self.vocab_tones = {}
if phone_vocab_path:
with open(phone_vocab_path, 'rt') as f:
with open(phone_vocab_path, 'rt', encoding='utf-8') as f:
phn_id = [line.strip().split() for line in f.readlines()]
for phn, id in phn_id:
self.vocab_phones[phn] = int(id)
if tone_vocab_path:
with open(tone_vocab_path, 'rt') as f:
with open(tone_vocab_path, 'rt', encoding='utf-8') as f:
tone_id = [line.strip().split() for line in f.readlines()]
for tone, id in tone_id:
self.vocab_tones[tone] = int(id)

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