Hello,

I am using beam search with the pretrained T5ForConditionalGeneration model. I am trying to implement some sort of uncertainty estimation at a token level. Therefore, I was looking at the ‘scores’ by setting `return_dict_in_generate=True`

and ` output_scores=True`

.

```
output=self.model.module.model.generate(input_ids=input['input_ids'],
attention_mask=input['attention_mask'],
num_beams=8,
return_dict_in_generate=True,output_scores=True,
output_hidden_states=True,output_attentions=True,
early_stopping=True, max_length=200)
```

Now, `output['scores']`

returns a tuple as instructed by the docs. What does each tuple mean? Each tuple is a tensor of size tensor of shape `(batch_size*num_beams*num_return_sequences, config.vocab_size)`

. I can’t seem to visualize what each tuple represent. Any help would be greatly appreciated.