🚀 Feature request

Currently we have a mixture of negative and positive formulated arguments, e.g. no_cuda and training here: https://github.com/huggingface/transformers/blob/0054a48cdd64e7309184a64b399ab2c58d75d4e5/src/transformers/benchmark/benchmark_args_utils.py#L61.

We should change all arguments to be positively formulated, *e.g. from no_cuda to cuda. These arguments should

From paper, it mentioned

Instead, the training data generator chooses 15% of tokens at random, e.g., in the sentence my
dog is hairy it chooses hairy.

It means that 15% of token will be choose for sure.

From https://github.com/codertimo/BERT-pytorch/blob/master/bert_pytorch/dataset/dataset.py#L68,
for every single token, it has 15% of chance that go though the followup procedure.

Describe the feature

I think enforcing typing in methods parameters can be helpful for robustness, readability and stability of the code.

By using mypy static type checker, we can see potential improvements for jina:

Usage:

pip install mypy
mypy --ignore-missing-imports jina

Do not get overwhelmed by the errors. Let's slowly keep improving until we can eve

If I want to use both of them, how to modify code in aen.py? Thanks a lot.