Force diarizer to use CUDA if cuda is available and if device=None.
# What does this PR do ?

This PR changes clustering_diarizer.py code to use CUDA if cuda is available and if device=None.

**Collection**: 

asr

# Changelog 

`        if speaker_model is not None:
            if self._cfg.device is None and torch.cuda.is_available():
                self._speaker_model = speaker_model.to(torch.device('cuda'))
            else:
                self._speaker_model = speaker_model
`


# Usage
Use diarizaiton examples

```
Run the entire speaker diarization pipeline: VAD, clustering diarizer for initializing clustering then Multi-scale Diarization Decoder (MSDD).
python multiscale_diar_decoder_infer.py --config-path='../conf/inference' --config-name='diar_infer_telephonic.yaml' \
    diarizer.vad.model_path=<NeMo VAD model path> \
    diarizer.msdd_model.model_path=<NeMo MSDD model path> \
    diarizer.oracle_vad=False \
    diarizer.manifest_filepath=<test_manifest> \
    diarizer.out_dir=<test_temp_dir> \
```

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# Before your PR is "Ready for review"
**Pre checks**:
- [x ] Make sure you read and followed [Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md)
- [x] Did you write any new necessary tests?
- [ ] Did you add or update any necessary documentation?
- [ ] Does the PR affect components that are optional to install? (Ex: Numba, Pynini, Apex etc)
  - [ ] Reviewer: Does the PR have correct import guards for all optional libraries?
  
**PR Type**:
- [ ] New Feature
- [x] Bugfix
- [ ] Documentation

If you haven't finished some of the above items you can still open "Draft" PR.


## Who can review?

Anyone in NeMo ASR 
