PreTrainedTokenizerBase.pad() broken on tensordict.TensorDict
Author: ligz08
Pull request: no
Labels: name: bug

### System Info

In `src/transformers/tokenization_utils_base.py` on line 3370:
```python
encoded_inputs = {key: [example[key] for example in encoded_inputs] for key in encoded_inputs[0]}
```
`for key in encoded_inputs[0]` raises `RuntimeError: generator raised StopIteration` when `encoded_inputs` is a list of `tensordict.TensorDict` objects.

[`TensorDict.__iter__()`](https://github.com/pytorch/tensordict/blob/main/tensordict/base.py#L541) is designed to iterate over the first shape-dimension of its value tensors, rather than dict keys. To iterate over keys, it needs `TensorDict.keys()`.

This bug was not there as of `transformers 4.51.3`, at which point the same line in `tokenization_utils_base.py` reads:
```python
encoded_inputs = {key: [example[key] for example in encoded_inputs] for key in encoded_inputs[0].keys()}
```
so I believe the breaking change happened at #37283 where many `.keys()` were removed.


It's up to debate whether `TensorDict.__iter__()` should behave more like a _batch_ or a _dict_, but imo from `transformers` pov, it's better to be safe -- to always call `.keys()` explicitly -- than sorry.

### Who can help?

@cyyever @Cyrilvallez @ArthurZucker @Rocketknight1 

### Information

- [ ] The official example scripts
- [x] My own modified scripts

### Tasks

- [ ] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [x] My own task or dataset (give details below)

### Reproduction

```python
from transformers import AutoTokenizer, DataCollatorWithPadding
from tensordict import TensorDict
tokenizer = AutoTokenizer.from_pretrained('xlm-roberta-base')
collator = DataCollatorWithPadding(tokenizer=tokenizer)
batch = [
    TensorDict({'input_ids': torch.tensor([9,8,7]), 'attention_mask': torch.tensor([1,1,1])}),
    TensorDict({'input_ids': torch.tensor([6,5]), 'attention_mask': torch.tensor([1,1])}),
]
collator(batch)
```

### Expected behavior

Expected:
```
{'input_ids': tensor([[9, 8, 7],
        [6, 5, 1]]), 'attention_mask': tensor([[1, 1, 1],
        [1, 1, 0]])}
```

Actual:
```
  File "/.../.venv/lib/python3.12/site-packages/transformers/data/data_collator.py", line 271, in __call__
    batch = pad_without_fast_tokenizer_warning(
            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/.../.venv/lib/python3.12/site-packages/transformers/data/data_collator.py", line 66, in pad_without_fast_tokenizer_warning
    padded = tokenizer.pad(*pad_args, **pad_kwargs)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/.../.venv/lib/python3.12/site-packages/transformers/tokenization_utils_base.py", line 3370, in pad
    encoded_inputs = {key: [example[key] for example in encoded_inputs] for key in encoded_inputs[0]}
                                                                                   ~~~~~~~~~~~~~~^^^
RuntimeError: generator raised StopIteration
```

Comments:
Thanks for the detailed report! I've traced this back to  #37283 where .keys() was removed. The issue is that TensorDict.__iter__() iterates over batch dimensions rather than keys, which breaks the current assumption.

I agree that transformers should explicitly call .keys() for safety with dict-like objects. I'd like to work on a PR that:

Restores .keys() in the affected code paths
Adds a regression test with TensorDict
Audits other locations from #37283
This affects anyone using TensorDict with data collators, which is common in RL workflows. Should be a straightforward fix. Let me know if you'd like me to proceed with the PR!

It should revert to use `.keys()` for `TensorDict` but keep other changes. Would you mind to propose a PR? @ligz08 @pankajbaid567 

Sounds like @pankajbaid567 already has a plan, feel free to move ahead, Pankaj, thanks!

@cyyever sir could you please review my pr and suggest changes/improvements  if any 

FYI for those who might be faced with the same problem: while this issue is being fixed via #42373, a temporary workaround is to limit transformers version at `transformers<4.55.0`

PR is merged we can close!