TypeError: __init__() got an unexpected keyword argument 'force_bos_token_to_be_generated'

Environment info

• transformers version: 4.6.1
• Platform: Linux-3.10.0-1160.15.2.el7.x86_64-x86_64-with-glibc2.10
• Python version: 3.8.8
• PyTorch version (GPU?): 1.7.1 (False)
• Tensorflow version (GPU?): 2.4.1 (False)
• Using GPU in script?: no
• Using distributed or parallel set-up in script?: no

Who can help

@patrickvonplaten, @patil-suraj

Information

The model I am using is BART

The problem arises when using:

• the official example scripts: (https://huggingface.co/transformers/model_doc/bart.html)

To reproduce

Steps to reproduce the behavior:

1. Install transformers library
2. run the following code-snipped as presented in the official example:

from transformers import BartForConditionalGeneration, BartTokenizer
model = BartForConditionalGeneration.from_pretrained("facebook/bart-large", force_bos_token_to_be_generated=True)

1. Receive error:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-21-216ff3421f95> in <module>
      1 from transformers import BartForConditionalGeneration, BartTokenizer
----> 2 model = BartForConditionalGeneration.from_pretrained("facebook/bart-large", force_bos_token_to_be_generated=True)
      3 tok = BartTokenizer.from_pretrained("facebook/bart-large")
      4 example_english_phrase = "UN Chief Says There Is No <mask> in Syria"
      5 batch = tok(example_english_phrase, return_tensors='pt')

~/.conda/envs/groundwork/lib/python3.8/site-packages/transformers/modeling_utils.py in from_pretrained(cls, pretrained_model_name_or_path, *model_args, **kwargs)
   1171         else:
   1172             with no_init_weights(_enable=_fast_init):
-> 1173                 model = cls(config, *model_args, **model_kwargs)
   1174 
   1175         if from_tf:

TypeError: __init__() got an unexpected keyword argument 'force_bos_token_to_be_generated'

Expected behavior

I expect the code to not raise an exception and that the final assertion is true.

If there are more information needed, please let me know.

[piegu]

It’s not necessary to use forced_bos_token_id with facebook/bart-large, it’s only needed for bart-cnn models

Hello @patil-suraj,

I’m not sure to understand your answer.

1. If you run my code about facebook/bart-large with forced_bos_token_id, you get a clear output: UN Chief Says There Is No Plan to Stop Chemical Weapons in Syria
2. If you run it without (generated_ids = model.generate(batch['input_ids']), you get this: UNALSO SEE
3. There is clearly a difference that shows that forced_bos_token_id has an impact with facebook/bart-large, no?
4. bart-cnn models are finetuned model for summarization, no? (like https://huggingface.co/ainize/bart-base-cnn). How do you use forced_bos_token_id with them?
5. I think the HF doc is not updated about this: https://huggingface.co/transformers/model_doc/bart.html#mask-filling

Note: just to give an overview of this discussion, I’m researching the right code to get the BART, mBART, and MBART-50 language models making multiple token masks (ie writing zero or more tokens in the output sentence when there is a <mask> token in the input one) with the objective to get the full output sentence.

[patil-suraj]

Hi there,

force_bos_token_to_be_generated is now depricated, instead you could use forced_bos_token_id argument, which should be set to the token id that needs to be forced as first token.