Always got RuntimeError while converting ALBERT model to TorchScript (.pt file)
I am trying to convert ALBERT to a `.pt` file from the original albert model from transformers.(I am not very familiar with TorchScript so I want the `.pt` to be clean)

The code I ran (following the tutorial from [https://huggingface.co/transformers/torchscript.html](https://huggingface.co/transformers/torchscript.html)):
```

from transformers import AlbertModel, AlbertTokenizer, AlbertConfig
import torch

enc = AlbertTokenizer.from_pretrained("albert-xxlarge-v2")
text = "[CLS] Who was Jim Henson ? [SEP] Jim Henson was a puppeteer [SEP]"
tokenized_text = enc.tokenize(text)
masked_index = 8
tokenized_text[masked_index] = '[MASK]'
indexed_tokens = enc.convert_tokens_to_ids(tokenized_text)
segments_ids = [0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1]
tokens_tensor = torch.tensor([indexed_tokens])
segments_tensors = torch.tensor([segments_ids])
dummy_input = [tokens_tensor, segments_tensors]
config = AlbertConfig(vocab_size_or_config_json_file=73000, hidden_size=4096,
    num_hidden_layers=12, num_attention_heads=64, intermediate_size=16384, torchscript=True)
model = AlbertModel(config)
model.eval()
model = AlbertModel.from_pretrained("albert-xxlarge-v2", torchscript=True)
traced_model = torch.jit.trace(model, [tokens_tensor, segments_tensors])
torch.jit.save(traced_model, "albert-xxlarge-v2.pt")
```
But the second last line threw out a error:
`RuntimeError: The size of tensor a (15) must match the size of tensor b (14) at non-singleton dimension 3`

From the tutorial:
```
The trace is created relatively to the inputs’ dimensions. It is therefore constrained by the dimensions of the dummy input, and will not work for any other sequence length or batch size. When trying with a different size, an error such as:

The expanded size of the tensor (3) must match the existing size (7) at non-singleton dimension 2
```

So I tried changing `vocab_size_or_config_json_file` to a larger value, but still got the same error.
Am I doing something wrong? Thanks for any advice.

