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import os
import torch
from transformers import AutoTokenizer, AutoModelForMaskedLM
import config
from logger import logger
from utils.download import download_and_verify
from config import DEVICE as device
URLS = [
"https://huggingface.co./cl-tohoku/bert-base-japanese-v3/resolve/main/pytorch_model.bin",
]
TARGET_PATH = os.path.join(config.ABS_PATH, "bert_vits2/bert/bert-base-japanese-v3/pytorch_model.bin")
EXPECTED_MD5 = None
if not os.path.exists(TARGET_PATH):
success, message = download_and_verify(URLS, TARGET_PATH, EXPECTED_MD5)
try:
logger.info("Loading bert-base-japanese-v3...")
tokenizer = AutoTokenizer.from_pretrained(config.ABS_PATH + "/bert_vits2/bert/bert-base-japanese-v3")
model = AutoModelForMaskedLM.from_pretrained(config.ABS_PATH + "/bert_vits2/bert/bert-base-japanese-v3").to(
device)
logger.info("Loading finished.")
except Exception as e:
logger.error(e)
logger.error(f"Please download pytorch_model.bin from cl-tohoku/bert-base-japanese-v3.")
def get_bert_feature(text, word2ph, device=config.DEVICE):
with torch.no_grad():
inputs = tokenizer(text, return_tensors="pt")
for i in inputs:
inputs[i] = inputs[i].to(device)
res = model(**inputs, output_hidden_states=True)
res = torch.cat(res["hidden_states"][-3:-2], -1)[0].cpu()
assert inputs["input_ids"].shape[-1] == len(word2ph)
word2phone = word2ph
phone_level_feature = []
for i in range(len(word2phone)):
repeat_feature = res[i].repeat(word2phone[i], 1)
phone_level_feature.append(repeat_feature)
phone_level_feature = torch.cat(phone_level_feature, dim=0)
return phone_level_feature.T
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