Force diarizer to use CUDA if cuda is available and if device=None.

[tango4j]

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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• New Feature
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Who can review?

Anyone in NeMo ASR

[nithinraok]

LGTM