Add SpeechLM to main

[stevehuang52]

What does this PR do ?

Add SpeechLLM training/inference scripts to NeMo, along with dataset, model, examples and test.

Main features

• Model class for SALM-style architecture, which supports SFT&PEFT.
• Some auxiliary modules to support multi-layer feature extraction, and multiple audio encoders.
• Dataset class for audio-text-question-answering tasks (generalized for any audio-to-text tasks)
• Detailed examples on training and evaluating SpeechLLMs
• Minor updates to data utils that move dict data to cuda and split into micro batches.

Collection: [common,nlp,multimodal]

PR Type:

• New Feature
• Bugfix
• Documentation

[zhehuaichen]

@arendu suggested by Abhinav, could you please help review the small changes to the NLP collection? There're mainly two changes:

• Modifying get_iterator_k_split to support splitting non-tensor objects (e.g., lists), while the behavior is same as before if the batch only has tensor objects.
• Changing hard assert to raising warnings when loading adapters that have different params from the actual adapters in LLM. This is needed since we store the ASR encoders in the same checkpoint as the GPT adapters, where it leads to additional params when loading the adapter checkpoint for the GPT adapter.

Please let us know if you have any questions, thanks~!