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import torch | |
from contants import config | |
def get_bert_feature(text, word2ph, tokenizer, model, device=config.system.device, style_text=None, style_weight=0.7, | |
**kwargs): | |
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].float().cpu() | |
if style_text: | |
style_inputs = tokenizer(style_text, return_tensors="pt") | |
for i in style_inputs: | |
style_inputs[i] = style_inputs[i].to(device) | |
style_res = model(**style_inputs, output_hidden_states=True) | |
style_res = torch.cat(style_res["hidden_states"][-3:-2], -1)[0].float().cpu() | |
style_res_mean = style_res.mean(0) | |
assert len(word2ph) == len(text) + 2 | |
word2phone = word2ph | |
phone_level_feature = [] | |
for i in range(len(word2phone)): | |
if style_text: | |
repeat_feature = ( | |
res[i].repeat(word2phone[i], 1) * (1 - style_weight) | |
+ style_res_mean.repeat(word2phone[i], 1) * style_weight | |
) | |
else: | |
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__': | |
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]) | |