Repository: huggingface/transformers
Pull request: Fix logic error in `prepare_inputs_for_generation` cache slicing condition

Fix logic error in `prepare_inputs_for_generation` cache slicing condition:
> TypeError: 'NoneType' object is not subscriptable


### Background

I think the PR
- #41505

introduced a logic error where the condition for calling `_cache_dependant_input_preparation` uses `is None` instead of `is not None`, causing crashes when `prepare_inputs_for_generation` is called with `past_key_values=None` and `use_cache=False`.

### Bug

PR #41505 introduced this condition:
```python
if past_key_values is None or use_cache:
    inputs_embeds, input_ids = self._cache_dependant_input_preparation(...)
```

The condition `past_key_values is None or use_cache` means:
- Do cache-dependent slicing if we DON'T have a cache OR if caching is enabled

This triggers the function even when:
- past_key_values=None (no cache)
- use_cache=False (caching disabled)
- cache_position=None (no position information)

This combination is invalid for cache-dependent preparation and causes a crash when accessing `cache_position[-1]` (line 456).

Note that during normal generation, it works fine because `use_cache=True`, making the buggy `past_key_values is None` part irrelevant.

### Fix

This PR changes the condition to:
```diff
- if past_key_values is None or use_cache:
+ if past_key_values is not None or use_cache:
```

The condition `past_key_values is not None or use_cache` means:
- Do cache-dependent slicing if we DO have a cache OR if caching is enabled

This is semantically correct and matches the intent described in the PR #41505 comment: https://github.com/huggingface/transformers/pull/41505#discussion_r2426080715
 > stateful models like `recurrent_gemma` assume that slicing happens, but don't have a Cache

The `use_cache` part handles stateful models, while `past_key_values is not None` handles normal cached models.

### Testing

This PR fixes the downstream failing test in TRL:
> tests/test_modeling_geometric_mixture_wrapper.py::TestGeometricMixtureWrapper::test_prepare_inputs_for_generation

See the associated issue:
- https://github.com/huggingface/trl/issues/4272

### Related

- This PR addresses a logic error introduced by:
  - #41505

- This PR will fix https://github.com/huggingface/trl/issues/4272

CC:
- @gante, who made the PR #41505
- @zucchini-nlp , who reviewed the PR #41505; see https://github.com/huggingface/transformers/pull/41505#discussion_r2425632292
  > maybe i am missing smth, do we apply cache slicing when the `past_key_values is None`?

Changed files:
filename: src/transformers/generation/utils.py
patch: @@ -608,7 +608,7 @@ def prepare_inputs_for_generation(
         use_cache = kwargs.get("use_cache")
         if use_cache is None:
             use_cache = getattr(self.config, "use_cache", False)
-        if past_key_values is None or use_cache:
+        if past_key_values is not None or use_cache:
             # TODO (joao): handle the case where cache length == input_ids length. The function below results in an
             # exception because we get empty input_ids after slicing. In essence, we need to roll back the cache 1
             # token to recompute the logits for the first token to be generated (but not all caches support roll backs)