Add a fix for single-GPU nsys.
@tfogal NeMo commits need to have --signoff can you amend and push again? In the meantime I've started CI since it takes a few hours to complete. If CI has passed before you push we can ask someone to force merge if needed. The `Isort and ...` issues are apparently coming up because the source branch is in another repo:

```
  Warning: Unable to find merge base between 34f740822a11802c2f0cea1c8039163b2b8bff92 and ecc8a1f3a2d532bf771746ed5a81367acf866da9
  Error: Unable to locate the commit sha: 34f740822a11802c2f0cea1c8039163b2b8bff92
  Error: Please verify that the commit sha is correct, and increase the 'fetch_depth' input if needed
  Warning: fatal: bad object 34f740822a11802c2f0cea1c8039163b2b8bff92
  
  Warning: If this pull request is from a forked repository, please set the checkout action `repository` input to the same repository as the pull request.
  Warning: This can be done by setting actions/checkout `repository` to ${{ github.event.pull_request.head.repo.full_name }}
  Error: Unable to determine a difference between 34f740822a11802c2f0cea1c8039163b2b8bff92..ecc8a1f3a2d532bf771746ed5a81367acf866da9
```

This is not something I can fix, though, since I can't make branches in NeMo.

Unrelatedly, marking ready for review. I still question whether this is the *correct* fix but it's definitely an improvement and we could always refine. <!-- pylint-output-strict-mode-false -->

beep boop 🤖: 🙏 The following files have warnings. In case you are familiar with these, please try helping us to improve the code base.

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Thank you for improving NeMo's documentation! @pablo-garay https://github.com/NVIDIA/NeMo/pull/11354#issuecomment-2498721924 any solution?
The SingleDeviceStrategy never sets the requisite attribute; workaround it in the profiling code.

# What does this PR do ?

Fixes using the nsys callback for single-GPU benchmarking.

**Collection**: core

# Changelog 
- Fix for cuda profiling of single-GPU runs

# Usage

```python
   nsyscb = nl.pytorch.callbacks.nsys.NsysCallback(
     start_step=0,
     end_step=40,
     ranks=[0],
     gen_shape=False,
   )
  llm.api.finetune(..., callbacks=[nsyscb])
```
is how I am using it.

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# Additional Information
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