Medix-AI/coqui-tts
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coqui-tts
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make static methods for faster multiprocess call

This commit is contained in:
erogol 2020-12-07 11:29:10 +01:00
parent affe1c1138
commit 20c86489d7
1 changed files with 29 additions and 20 deletions
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49
TTS/tts/datasets/TTSDataset.py
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@ -1,12 +1,16 @@
import os
import numpy as np
import collections
import torch
import os
import random
from torch.utils.data import Dataset
from multiprocessing import Manager, Pool
from TTS.tts.utils.text import text_to_sequence, phoneme_to_sequence, pad_with_eos_bos
from TTS.tts.utils.data import prepare_data, prepare_tensor, prepare_stop_target
import numpy as np
import torch
import tqdm
from torch.utils.data import Dataset
from TTS.tts.utils.data import (prepare_data, prepare_stop_target,
prepare_tensor)
from TTS.tts.utils.text import (pad_with_eos_bos, phoneme_to_sequence,
text_to_sequence)
class MyDataset(Dataset):
@ -82,35 +86,40 @@ class MyDataset(Dataset):
data = np.load(filename).astype('float32')
return data
def _generate_and_cache_phoneme_sequence(self, text, cache_path):
@staticmethod
def _generate_and_cache_phoneme_sequence(text, cache_path, cleaners, language, tp, add_blank):
"""generate a phoneme sequence from text.
since the usage is for subsequent caching, we never add bos and
eos chars here. Instead we add those dynamically later; based on the
config option."""
phonemes = phoneme_to_sequence(text, [self.cleaners],
language=self.phoneme_language,
phonemes = phoneme_to_sequence(text, [cleaners],
language=language,
enable_eos_bos=False,
tp=self.tp, add_blank=self.add_blank)
tp=tp, add_blank=add_blank)
phonemes = np.asarray(phonemes, dtype=np.int32)
np.save(cache_path, phonemes)
return phonemes
def _load_or_generate_phoneme_sequence(self, wav_file, text):
@staticmethod
def _load_or_generate_phoneme_sequence(wav_file, text, phoneme_cache_path, enable_eos_bos, cleaners, language, tp, add_blank):
file_name = os.path.splitext(os.path.basename(wav_file))[0]
cache_path = os.path.join(self.phoneme_cache_path,
file_name + '_phoneme.npy')
# different names for normal phonemes and with blank chars.
file_name_ext = '_blanked_phoneme.npy' if add_blank else '_phoneme.npy'
cache_path = os.path.join(phoneme_cache_path,
file_name + file_name_ext)
try:
phonemes = np.load(cache_path)
except FileNotFoundError:
phonemes = self._generate_and_cache_phoneme_sequence(
text, cache_path)
phonemes = MyDataset._generate_and_cache_phoneme_sequence(
text, cache_path, cleaners, language, tp, add_blank)
except (ValueError, IOError):
print(" > ERROR: failed loading phonemes for {}. "
print(" [!] failed loading phonemes for {}. "
"Recomputing.".format(wav_file))
phonemes = self._generate_and_cache_phoneme_sequence(
text, cache_path)
if self.enable_eos_bos:
phonemes = pad_with_eos_bos(phonemes, tp=self.tp)
phonemes = MyDataset._generate_and_cache_phoneme_sequence(
text, cache_path, cleaners, language, tp, add_blank)
if enable_eos_bos:
phonemes = pad_with_eos_bos(phonemes, tp=tp)
phonemes = np.asarray(phonemes, dtype=np.int32)
return phonemes