| import sys |
|
|
| import torch |
| from transformers import AutoModelForMaskedLM, AutoTokenizer |
|
|
| from config import config |
| from text.japanese import text2sep_kata |
|
|
| LOCAL_PATH = "./bert/deberta-v2-large-japanese-char-wwm" |
|
|
| tokenizer = AutoTokenizer.from_pretrained(LOCAL_PATH) |
|
|
| models = dict() |
|
|
|
|
| def get_bert_feature( |
| text, |
| word2ph, |
| device=config.bert_gen_config.device, |
| assist_text=None, |
| assist_text_weight=0.7, |
| ): |
| text = "".join(text2sep_kata(text)[0]) |
| if assist_text: |
| assist_text = "".join(text2sep_kata(assist_text)[0]) |
| if ( |
| sys.platform == "darwin" |
| and torch.backends.mps.is_available() |
| and device == "cpu" |
| ): |
| device = "mps" |
| if not device: |
| device = "cuda" |
| if device == "cuda" and not torch.cuda.is_available(): |
| device = "cpu" |
| if device not in models.keys(): |
| models[device] = AutoModelForMaskedLM.from_pretrained(LOCAL_PATH).to(device) |
| with torch.no_grad(): |
| inputs = tokenizer(text, return_tensors="pt") |
| for i in inputs: |
| inputs[i] = inputs[i].to(device) |
| res = models[device](**inputs, output_hidden_states=True) |
| res = torch.cat(res["hidden_states"][-3:-2], -1)[0].cpu() |
| if assist_text: |
| style_inputs = tokenizer(assist_text, return_tensors="pt") |
| for i in style_inputs: |
| style_inputs[i] = style_inputs[i].to(device) |
| style_res = models[device](**style_inputs, output_hidden_states=True) |
| style_res = torch.cat(style_res["hidden_states"][-3:-2], -1)[0].cpu() |
| style_res_mean = style_res.mean(0) |
|
|
| assert len(word2ph) == len(text) + 2, text |
| word2phone = word2ph |
| phone_level_feature = [] |
| for i in range(len(word2phone)): |
| if assist_text: |
| repeat_feature = ( |
| res[i].repeat(word2phone[i], 1) * (1 - assist_text_weight) |
| + style_res_mean.repeat(word2phone[i], 1) * assist_text_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 |
|
|
