Natural language processing

https://github.com/huggingface/transformers/blob/546dc24e0883e5e9f5eb06ec8060e3e6ccc5f6d7/src/transformers/models/gpt2/modeling_gpt2.py#L698

Assertions can't be relied upon for control flow because they can be disabled, as per the following:

$ python --help
usage: python [option] ... [-c cmd | -m mod | file | -] [arg] ...
...
-O     : remove assert and __debug__-dependent statem

Describe the bug

https://github.com/jina-ai/jina/blob/master/jina/resources/fluent.conf#L17

It does not work as expected. '${workspace_path}' will be created.

$ ls
'${workspace_path}'   boot   etc    lib     media   opt    root   sbin   sys   usr
 bin                  dev    home   lib64   mnt     proc   run    srv

Is your feature request related to a problem? Please describe.
I typically used compressed datasets (e.g. gzipped) to save disk space. This works fine with AllenNLP during training because I can write my dataset reader to load the compressed data. However, the predict command opens the file and reads lines for the Predictor. This fails when it tries to load data from my compressed files.

Hello everyone,

I need to compute the BLEU score with more than one ngram length (ideally, BLEU2, BLEU3, BLEU4, and BLEU5). In my case, this is a very long task, as every hypothesis has some thousand references.

Reading the implementation of the corpus_bleu function, which takes weights:Tuple between its parameters - and thus calculating BLEU-[len(weights)] - , I found out that it gets all t