[NeMo Megatron] use worker processes for data preprocessing
# What does this PR do ?

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Update Megatron style `BatchSampler`s and `GPTDataset` to prepare data samples in worker processes.


# Changelog 
- BatchSamplers return a list of `num_micro_batch x micro_batch_size` indices: https://github.com/NVIDIA/NeMo/compare/main...crcrpar:megatron/update_data_loading?expand=1#diff-a78cf82731c4e37f487037ab45cab0183aac6216ee96e08d3b81ff111495d3caR36 and https://github.com/NVIDIA/NeMo/compare/main...crcrpar:megatron/update_data_loading?expand=1#diff-a78cf82731c4e37f487037ab45cab0183aac6216ee96e08d3b81ff111495d3caR106
- A new arguments of `eos_id` is added to `GPTDataset` in order to change the callsite of `get_ltor_masks_and_position_ids` to `GPTDataset`. [`eos_id`](url) is an attribute of a `Tokenizer` instance.
- `process_micro_batch` is removed in favor of updated `GPTDataset.__getitem__`: https://github.com/NVIDIA/NeMo/compare/main...crcrpar:megatron/update_data_loading?expand=1#diff-e93ccae74f4b67d341676afc9f3c7e2c50f751ec64df84eb3b2a86b62029ef76L456
- `NLPDataConnector` isn't needed thanks to the updated `GPTDataset` and `BatchSampler`s: https://github.com/NVIDIA/NeMo/compare/main...crcrpar:megatron/update_data_loading?expand=1#diff-424bb19c0b7c9dba2aebb3459972c5a8bf8c902dca48a8762f12bc5cde5fea5fL68

# Usage

To utilize worker processes, it'd be better to set `model.data.num_workers` > 0.
See https://pytorch.org/docs/stable/data.html#torch.utils.data.DataLoader.

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**PR Type**:
- [x] New Feature
- [ ] Bugfix
- [ ] Documentation

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## Who can review?

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[Contributor guidelines](https://github.com/NVIDIA/NeMo/blob/main/CONTRIBUTING.md) contains specific people who can review PRs to various areas.

# Additional Information
* Related to # (issue)
