- 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.
8 lines
106 B
Python
8 lines
106 B
Python
from __future__ import annotations
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from evaluate_auc import main
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if __name__ == "__main__":
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main()
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