Improvement to error handling in subclasses

Feature request

I encountered a fascinating (though very frustrating 😃) scenario about error handling in transformers. When subclassing a tokenizer that relies on sentencepiece, and not having it installed, you will get an unhelpful error message that sends you down a lot of rabbit holes.

Consider this minimal example:

from transformers import MBartTokenizer


class CustomMBartTokenizer(MBartTokenizer):
    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        inst = super().from_pretrained(*args, **kwargs)
        # Do other stuff with it...


a = CustomMBartTokenizer.from_pretrained("facebook/mbart-large-cc25")

If you run this in a new environment where sentencepiece is not installed, you get the following error:

AttributeError: ‘super’ object has no attribute ‘from_existing’

This error message had me comparing Windows vs. Linux and python 3.8 vs 3.9 vs 3.10 because I could not figure out why it was working on my home machine and not on our cluster. In the end, the reason was that sentencepiece was not yet installed on the cluster but the error message does not show that. It seems that the sentencepiece error does not show or does not stop execution, which then leads the class to not be successfully initialized. Although admittedly I have not dug much farther.

Motivation

The error message does not seem to correctly propagate when subclassing a tokenizer. The error message that indicates that sentencepiece is not installed and needs to be installed is not correctly shown. Instead the user gets a vague error message about the from_pretrained call.

While this may be an exceptional case, I have found that subclassing tokenizers for a specific task is common in research.

Your contribution

I do not have the time to work on figuring out what the exact cause is unfortunately. Posting this here for posterity. For anyone getting this issue: you probably just need to make sure all necessary third party libraries (such as sentencepiece) are installed.

[mariosasko]

I think DummyObject should override __getattribute__ instead of __getattr__ to get the expected error.

EDIT:

Tested locally, and it works. I’ve linked a PR with the fix.

[jacwalte]

Thanks @mariosasko!

@jacwalte That is the expected behavior. sentencepiece is not installed by default because not all tokenizers need it. You’ll get the error message if you need it for your use-case and then you just have to install it manually. Or you can install transformers with the extra sentencepiece, transformers[sentencepiece]. The problem in my case was that the error message did not show up. This has now been quickly fixed by @mariosasko!

Thanks! - will update the requirements with that