Removes unnecessary cloning (#6761)
`clone_tensors_for_torch_save()` function:
When the `item.device` is different from `device` input,
`tensor.clone()` is not actually required because `to()` function also
clones the original tensor.
+) I observed memory bloat under following conditions:
* Training a Whisper model w/ `transformers` framework with `ZeRO-0` and
`ZeRO-1` configuration.
* Memory bloating can be observed every time the model state_dict is
cloned using `clone_tensors_for_torch_save()`
After I removed the unnecessary `clone()`, seems like the problem is
solved.
Co-authored-by: Logan Adams <114770087+loadams@users.noreply.github.com>
Co-authored-by: Olatunji Ruwase <olruwase@microsoft.com>
