BART summarization, tokenizer not working
@patil-suraj 
When I am running pytorch/summarization, the logs are as below:
```
Adding AddedToken(content='<s>', single_word=False, lstrip=False, rstrip=False, normalized=True) to the vocabulary
Adding AddedToken(content='</s>', single_word=False, lstrip=False, rstrip=False, normalized=True) to the vocabulary
Adding AddedToken(content='<pad>', single_word=False, lstrip=False, rstrip=False, normalized=True) to the vocabulary
Adding AddedToken(content='<mask>', single_word=False, lstrip=True, rstrip=False, normalized=True) to the vocabulary
Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.
https://huggingface.co/facebook/bart-large-cnn/resolve/main/pytorch_model.bin not found in cache or force_download set to True, downloading to /home/sdiaoaa/.cache/huggingface/transformers/tmpama_iuh8
```
But the embedding did not fit for the added tokens.
The embedding is still [50264] but the token_ides ranges from [0, 50269]
Did you resize the embeddings after adding the new tokens ? To resize the embedding 
```python3
model.resize_token_embeddings(len(tokenizer))
```<|||||>> Did you resize the embeddings after adding the new tokens ? To resize the embedding
> 
> ```python
> model.resize_token_embeddings(len(tokenizer))
> ```

Thanks so much for your reply!
The issue has been solved by adding that line.
Just curious, is it a common practice to add 'resize_token_emb' function?  because previously, I have not seen this happens and was wondering why it is not included in the official run_summarization code.

Thanks!<|||||>Yes, the embeddings need to be resized after adding new tokens.

And yes, you are right, the embedding should be resized in the example.