adaptive softmax in transformer-xl
I guess there is some incomplete part for adaptive softmax in [modeling_transfo_xl.py](https://github.com/huggingface/pytorch-transformers/blob/master/pytorch_transformers/modeling_transfo_xl.py)
Actually, it is impossible to build model not using adaptive softmax even though `TransfoXLConfig` has `adaptive` parameter.
I can see that if `sample_softmax` is larger than -1, model uses sample softmax other than adaptive softmax, which seems to be the case of not using adaptive softmax.
However, in case of `sample_softmax` > -1 and `tie_weight`=True, there is a problem on [this line](https://github.com/huggingface/pytorch-transformers/blob/master/pytorch_transformers/modeling_transfo_xl.py#L1317)<code><pre>self.out_layer.weight = self.transformer.word_emb.weight</pre></code> because the model always use `AdaptiveEmbedding` as `word_emb`, which has no `weight` property.

Presumably we need some code for not using adaptive softmax and but using standard softmax and usual `nn.Embedding` as a word embedding.
Then we can tie weights between standard `nn.Embedding` and `nn.Linear` when we doesn't need adaptive softmax.

Can you consider about this problem? Thanks.
Yes. At the moment, this library is designed for loading pretrained models mostly and no one has open-sourced a Transformer-XL pretrained model using something else than adaptive softmax so I have not spent time adding these options.

Happy to welcome PR though.

The main thing of interest here, if you want to give it a try would be to add bias to all clusters in PyTorch official [`AdaptiveLogSoftmaxWithLoss`](https://pytorch.org/docs/stable/nn.html?highlight=adaptivelogsoftmaxwithloss#torch.nn.AdaptiveLogSoftmaxWithLoss) module so we could just use the official implementation without maintaining ours.<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
