Auto download missing model for bert_gen.py (#146)

* auto download missing model

* support openi

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix wrong delete

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* pass pre-commit

* [pre-commit.ci] auto fixes from pre-commit.com hooks

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* fix repeat login

---------

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

text/chinese_bert.py

@@ -1,9 +1,13 @@
-import torch
 import sys
-from transformers import AutoTokenizer, AutoModelForMaskedLM
+
+import torch
+from transformers import AutoModelForMaskedLM, AutoTokenizer
+
 from config import config
 
-tokenizer = AutoTokenizer.from_pretrained("./bert/chinese-roberta-wwm-ext-large")
+LOCAL_PATH = "./bert/chinese-roberta-wwm-ext-large"
+
+tokenizer = AutoTokenizer.from_pretrained(LOCAL_PATH)
 
 models = dict()
 
@@ -18,9 +22,7 @@ def get_bert_feature(text, word2ph, device=config.bert_gen_config.device):
     if not device:
         device = "cuda"
     if device not in models.keys():
-        models[device] = AutoModelForMaskedLM.from_pretrained(
-            "./bert/chinese-roberta-wwm-ext-large"
-        ).to(device)
+        models[device] = AutoModelForMaskedLM.from_pretrained(LOCAL_PATH).to(device)
     with torch.no_grad():
         inputs = tokenizer(text, return_tensors="pt")
         for i in inputs:
@@ -41,8 +43,6 @@ def get_bert_feature(text, word2ph, device=config.bert_gen_config.device):
 
 
 if __name__ == "__main__":
-    import torch
-
     word_level_feature = torch.rand(38, 1024)  # 12个词,每个词1024维特征
     word2phone = [
         1,