[feature request] A more flexible `free_memory` function

After looking at the existing issues and PRs, I'm opening this feature request since I couldn't find my use case.
https://github.com/huggingface/accelerate/blob/7889ba6b6dd094e72fa222194146a40426fb3d5a/src/accelerate/accelerator.py#L1788-L1799
1. In my case, I'm using a custom cache system instead of regular dataloaders and I need to load and unload the same objects multiple times in the `Accelerator` for each iteration to free up memory. For now, I need to access the different internal objects of the `Accelerator` class individually. This could happen in different non-standard training loop (e.g. reloading a model and corresponding optimizers, ...).
2. It only needs a quick modification of the `free_memory` function. I'm not sure how you would implement that to be coherent with the whole library though.
3. This feature could be used as followed:
```python
# load cache
# prepare it with the Accelerator
for iteration in range(nb_iterations):
# take random batch from cache
# Forward pass
if iteration % reload_frequency == 0:
# unload the cache from the Accelerator to free up memory
# load new cache
# prepare it with the Accelerator
```

Thank you for this library by the way. It makes things much easier for everyone!