|
import argparse |
|
import sys |
|
from multiprocessing import Pool |
|
|
|
import torch |
|
import torch.multiprocessing as mp |
|
from tqdm import tqdm |
|
|
|
import commons |
|
import utils |
|
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 Pool(processes=num_processes) as pool: |
|
for _ in tqdm( |
|
pool.imap_unordered(process_line, zip(lines, add_blank)), |
|
total=len(lines), |
|
file=sys.stdout, |
|
): |
|
|
|
pass |
|
|
|
print(f"bert.pt is generated! total: {len(lines)} bert.pt files.") |
|
|