Improve greedy search memory usage
Author: regisss
Pull request: yes

# What does this PR do?

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When doing greedy search, inputs go through `_expand_inputs_for_generation` [here](https://github.com/huggingface/transformers/blob/85345bb439652d3f03bb4e123cef7a440f2ba95b/src/transformers/generation/utils.py#L1988) where they are expanded (see [here](https://github.com/huggingface/transformers/blob/85345bb439652d3f03bb4e123cef7a440f2ba95b/src/transformers/generation/utils.py#L632)). As the expand size is always 1 in the case of greedy search, `torch.repeat_interleave` do not modify the inputs. However, it does increase the memory usage as the input to `torch.repeat_interleave` is cloned.

Here is a code snippet to check this behaviour:
```py
import torch

a = torch.ones(1000, 1000, 1000, device="cuda")
print(torch.cuda.max_memory_allocated())

expand_size = 1
a = a.repeat_interleave(expand_size, dim=0)
print(torch.cuda.max_memory_allocated())
```
which returns
```
4000000000
8000000000
```

Thus, if the expand size is 1, we can return the model inputs before calling `torch.repeat_interleave`. That's the change introduced in this PR.

More context in this Slack thread: https://huggingface.slack.com/archives/C01N44FJDHT/p1723827436938589


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Comments:
The docs for this PR live [here](https://moon-ci-docs.huggingface.co/docs/transformers/pr_32895). All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update.

cc @gante @zucchini-nlp 

CI failed but it doesn't seem to be related to this PR