raises value error for bert tokenizer for long sequences
addesses #125 

(all pre-trained bert models have a positional embedding matrix with 512 embeddings. Sequences longer than 512 tokens will cause indexing errors when you attempt to run a bert forward pass on them)

added a max_len arg to bert tokenizer. the function convert_tokens_to_indices will raise a value error if the inputted list of tokens is longer than max_len.

if no max_len is supplied, then no value error will be raised, however long the sequence is

Pre-trained bert models have max_len set to 512 at object construction time (in BertTokenizer.from_pretrained. It can be overridden by explicitly passing max_len to BertTokenizer.from_pretrained as a kwarg

if bert models with larger positional embedding matrices are released, it is possible to have different max_lens for different pretrained_models.
Thanks @patrick-s-h-lewis, this is nice.

The max number of positional embeddings is also available in the pretrained models configuration files (as `max_position_embeddings`) but accessing this requires some change in the models stored on S3 (not storing them as tar.gz files) so I will take care of it in the next release.