1. Add CI test for building documentations (Do not ignore warnings and add spellcheck).
2. Fix docstrings with incorrect/inconsistent Sphinx format. Currently, such issues are treated as warnings in the docs building.

I'm playing around with this wonderful code but I'm running into a curious issue when I try to train the model with my own data.

I replicated the personachat_self_original.json file structure and added my own data. I deleted dataset_cache_OpenAIGPTTokenizer file but when I try to train, I get this error:

INFO:train.py:Pad inputs and convert to Tensor
Traceback (most recent call last)

Hi,
When we try to tokenize the following sentence:

If we use spacy

a = spacy.load('en_core_web_lg')

doc = a("I like the link http://www.idph.iowa.gov/ohds/oral-health-center/coordinator")

list(doc)

We got

[I, like, the, link, http://www.idph.iowa.gov, /, ohds, /, oral, -, health, -, center, /, coordinator]

But if we use the Spacy transformer tokenizer:

谢谢分享
@imcaspar 能写一下怎样使用吗?

1. 使用该模型继续进行预训练的步骤
2. 使用该模型进行inference的步骤

谢谢

• TransformerDecoder.forward: where does self.training come from?
  https://github.com/asyml/texar-pytorch/blob/d17d502b50da1d95cb70435ed21c6603370ce76d/texar/torch/modules/decoders/transformer_decoders.py#L448-L449

• All arguments should say their types explicitly in the docstring. E.g., what is the type of infer_mode? The [method signature](https://texar-pytorch.readthedocs.