- Removed BaselineEncoder and CrossAttention classes from models.py.
- Introduced OtherInfoTokenizer for handling additional token types.
- Updated DeepHealth class to integrate OtherInfoTokenizer and manage extra pooling logic.
- Added support for extra_pool_reduce parameter to control pooling behavior.
- Modified forward methods to return structured output using DeepHealthOutput dataclass.
- Updated training scripts to accommodate changes in model architecture and output handling.
- Enhanced error handling and validation for input shapes and types.
- Implement `train_all_future.py` for training with query-conditioned all-future supervision.
- Implement `train_next_step.py` for training with next-token/next-time-point supervision.
- Introduce `train_util.py` for shared utility functions including logging, dataset splitting, and model checkpointing.
- Enhance argument parsing for both training scripts to accommodate new parameters.
- Update loss functions and model configurations to support the new training paradigms.
