TSA / BERT_inference.py
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import transformers
import torch.nn as nn
class BertClassificationModel(nn.Module):
def __init__(self):
super(BertClassificationModel, self).__init__()
pretrained_weights="bert-base-chinese"
self.bert = transformers.BertModel.from_pretrained(pretrained_weights)
for param in self.bert.parameters():
param.requires_grad = True
self.dense = nn.Linear(768, 3)
def forward(self, input_ids,token_type_ids,attention_mask):
bert_output = self.bert(input_ids=input_ids,token_type_ids=token_type_ids, attention_mask=attention_mask)
bert_cls_hidden_state = bert_output[1]
linear_output = self.dense(bert_cls_hidden_state)
return linear_output