multiturn training support for SALM 
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## Manifest format
```
{
  “id”: “some_id_14323452”,
  "conversations": [
    {
      "value": "Can you help summarize the following?",
      "from": "User",
      "type": "text",
    },
    {
      "value": "123.wav",
      "from": "User",
      "type": "audio",
      “duration”: 5.73,
    },
    {
      "value": "I'm glad to assist you with your request. The information can be summarized as the following: ….",
      "from": "Assistant",
      "type": "text",
    },
    {
      "value": "123_answer.wav",
      "from": "Assistant",
      "type": "audio",
      “duration”: 7.11,
    },
    {
      "value": "Can you further shorten it?",
      "from": "User",
      "type": "text",
    },
    …
}
```
## Input CFG format
```
 - type: group
   input_cfg:
    - manifest_filepath: /media/data/datasets/LibriSpeech/dev_clean_10.conv.json
      type: multimodal_conversation
      audio_locator_tag: "<unused0>"
```
- Note:  we need seprate ICFG for single turn and multi turn data mixing because we need to measure length / calibrate batch size differently.
##  Example usage
- check here https://docs.google.com/document/d/15BppG_IyP7DWRh5Lw20bRVHdOXt1uvfhJZhIVmzh8AQ/edit#bookmark=id.5i9bljw374yo mainly needs to add the following flags
```
    ++model.data.validation_ds.force_finite=True \
    ++model.data.train_ds.prompt_format="gemma" \
    ++model.data.validation_ds.prompt_format="gemma" \
    ++model.data.validation_ds.drop_last=False \
    ++model.data.train_ds.drop_last=False \
    ++model.data.train_ds.input_cfg=manifests/train2.conv2.yaml \
    ++model.data.validation_ds.input_cfg=manifests/train2.conv2.yaml
```
## TODO
- Tar/sharding the audios
- BESTOW support https://github.com/zhehuaichen/NeMo/tree/speechllm-develop-prompt