Spaces:
Running
Running
File size: 2,846 Bytes
9cca5e6 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 |
import argparse
from concurrent.futures import ThreadPoolExecutor
import torch
import torch.multiprocessing as mp
from tqdm import tqdm
import commons
import utils
from common.log import logger
from common.stdout_wrapper import SAFE_STDOUT
from config import config
from text import cleaned_text_to_sequence, get_bert
def process_line(x):
line, add_blank = x
device = config.bert_gen_config.device
if config.bert_gen_config.use_multi_device:
rank = mp.current_process()._identity
rank = rank[0] if len(rank) > 0 else 0
if torch.cuda.is_available():
gpu_id = rank % torch.cuda.device_count()
device = torch.device(f"cuda:{gpu_id}")
else:
device = torch.device("cpu")
wav_path, _, language_str, text, phones, tone, word2ph = line.strip().split("|")
phone = phones.split(" ")
tone = [int(i) for i in tone.split(" ")]
word2ph = [int(i) for i in word2ph.split(" ")]
word2ph = [i for i in word2ph]
phone, tone, language = cleaned_text_to_sequence(phone, tone, language_str)
if add_blank:
phone = commons.intersperse(phone, 0)
tone = commons.intersperse(tone, 0)
language = commons.intersperse(language, 0)
for i in range(len(word2ph)):
word2ph[i] = word2ph[i] * 2
word2ph[0] += 1
bert_path = wav_path.replace(".WAV", ".wav").replace(".wav", ".bert.pt")
try:
bert = torch.load(bert_path)
assert bert.shape[-1] == len(phone)
except Exception:
bert = get_bert(text, word2ph, language_str, device)
assert bert.shape[-1] == len(phone)
torch.save(bert, bert_path)
preprocess_text_config = config.preprocess_text_config
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument(
"-c", "--config", type=str, default=config.bert_gen_config.config_path
)
parser.add_argument(
"--num_processes", type=int, default=config.bert_gen_config.num_processes
)
args, _ = parser.parse_known_args()
config_path = args.config
hps = utils.get_hparams_from_file(config_path)
lines = []
with open(hps.data.training_files, encoding="utf-8") as f:
lines.extend(f.readlines())
with open(hps.data.validation_files, encoding="utf-8") as f:
lines.extend(f.readlines())
add_blank = [hps.data.add_blank] * len(lines)
if len(lines) != 0:
num_processes = args.num_processes
with ThreadPoolExecutor(max_workers=num_processes) as executor:
_ = list(
tqdm(
executor.map(process_line, zip(lines, add_blank)),
total=len(lines),
file=SAFE_STDOUT,
)
)
logger.info(f"bert.pt is generated! total: {len(lines)} bert.pt files.")
|