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| import os | |
| import config | |
| import torch | |
| from transformers import AutoTokenizer, AutoModelForMaskedLM | |
| from logger import logger | |
| from utils.download import download_and_verify | |
| from config import DEVICE as device | |
| URLS = [ | |
| "https://huggingface.co/hfl/chinese-roberta-wwm-ext-large/resolve/main/pytorch_model.bin", | |
| ] | |
| TARGET_PATH = os.path.join(config.ABS_PATH, "bert_vits2/bert/chinese-roberta-wwm-ext-large/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 chinese-roberta-wwm-ext-large...") | |
| tokenizer = AutoTokenizer.from_pretrained(config.ABS_PATH + "/bert_vits2/bert/chinese-roberta-wwm-ext-large") | |
| model = AutoModelForMaskedLM.from_pretrained(config.ABS_PATH + "/bert_vits2/bert/chinese-roberta-wwm-ext-large").to( | |
| device) | |
| logger.info("Loading finished.") | |
| except Exception as e: | |
| logger.error(e) | |
| logger.error(f"Please download pytorch_model.bin from hfl/chinese-roberta-wwm-ext-large.") | |
| 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 len(word2ph) == len(text) + 2 | |
| 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 | |
| if __name__ == '__main__': | |
| import torch | |
| word_level_feature = torch.rand(38, 1024) # 12个词,每个词1024维特征 | |
| word2phone = [1, 2, 1, 2, 2, 1, 2, 2, 1, 2, 2, 1, 2, 2, 2, 2, 2, 1, 1, 2, 2, 1, 2, 2, 2, 2, 1, 2, 2, 2, 2, 2, 1, 2, | |
| 2, 2, 2, 1] | |
| # 计算总帧数 | |
| total_frames = sum(word2phone) | |
| print(word_level_feature.shape) | |
| print(word2phone) | |
| phone_level_feature = [] | |
| for i in range(len(word2phone)): | |
| print(word_level_feature[i].shape) | |
| # 对每个词重复word2phone[i]次 | |
| repeat_feature = word_level_feature[i].repeat(word2phone[i], 1) | |
| phone_level_feature.append(repeat_feature) | |
| phone_level_feature = torch.cat(phone_level_feature, dim=0) | |
| print(phone_level_feature.shape) # torch.Size([36, 1024]) | |