请写出Bert+BiLstm+Crf命名实体识别的代码

我可以给您提供一段基于Bert BiLstm Crf的命名实体识别代码：# 导入包
import torch
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
from torch.utils.data import DataLoader# 定义模型
class BertBiLstmCrf(nn.Module):
def __init__(self, num_tags):
super(BertBiLstmCrf, self).__init__()
# 加载预训练bert模型
self.bert = BertModel.from_pretrained('bert-base-uncased')
# 定义双向lstm
self.lstm = nn.LSTM(input_size=768,
hidden_size=256,
num_layers=1,
bidirectional=True,
batch_first=True)
# 定义线性层
self.linear = nn.Linear(in_features=512, out_features=num_tags)
# 定义CRF层
self.crf = CRF(num_tags)

def forward(self, x, mask, y):
# 获取bert的输出
bert_output = self.bert(x, attention_mask=mask)
# 获取bert的隐藏层输出
lstm_input = bert_output[0]
# 获取双向lstm的输出
lstm_output, _ = self.lstm(lstm_input)
# 获取线性层的输出
linear_output = self.linear(lstm_output)
# 获取CRF层的输出
crf_output = self.crf(linear_output, mask)
# 计算损失
loss = -1 * crf_output.log_likelihood(y)
# 返回损失
return loss