understanding of the output from TransfoXLModel 
the output of the TransfoXLModel has the size of [1, 3, 1024] if the Input has tree tokens. 

`predictions, mems = model(tokens_tensor, mems=None)`

doc from code is 

```
    Outputs:
        A tuple of (last_hidden_state, new_mems)
        `last_hidden_state`: the encoded-hidden-states at the top of the model
            as a torch.FloatTensor of size [batch_size, sequence_length, self.config.d_model]
        `new_mems`: list (num layers) of updated mem states at the entry of each layer
            each mem state is a torch.FloatTensor of size [self.config.mem_len, batch_size, self.config.d_model]
            Note that the first two dimensions are transposed in `mems` with regards to `input_ids` and `target`
```

could the output be explained more precisely.  I would be very grateful! 
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