transfer labert model to pytorch

Hi,
I'm trying to transfer the labert model to pytorch, I used the code online :
```
path="./chinese_labert-base-std-512/"
tf_checkpoint_path = path + "model.ckpt/"#自己BERT模型文件夹下的ckpt文件（共3个一组）
bert_config_file = path + "labert_config.json" #自己BERT模型文件夹下的config
pytorch_dump_path = path + "pytorch_model.bin"

def convert_tf_checkpoint_to_pytorch(tf_checkpoint_path, bert_config_file, pytorch_dump_path):
# Initialise PyTorch model
config = BertConfig.from_json_file(bert_config_file)
print(f"Building PyTorch model from configuration: {config}")
model = BertForPreTraining(config)

# Load weights from tf checkpoint
load_tf_weights_in_bert(model, config, tf_checkpoint_path)

# Save pytorch-model
print(f"Save PyTorch model to {pytorch_dump_path}")
torch.save(model.state_dict(), pytorch_dump_path)

convert_tf_checkpoint_to_pytorch(tf_checkpoint_path, bert_config_file, pytorch_dump_path)
```

But I got this:


Does anyone know if there's a way to make it work？Thanks a lot!!

Start with the provided convert_tf_checkpoint_to_pytorch function and the referenced model.ckpt/ and labert_config.json paths, then inspect the error shown in the linked screenshot. Reproduce the conversion and determine what prevents the LABERT TensorFlow checkpoint from loading into BertForPreTraining; done means producing a valid pytorch_model.bin.

Written by the indexing model from the issue text.