Comments (1)
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Related Issues (19)
- select function should populate the mcts_tree. modify test_select to check that children nodes are appended.
- node 0 does not contain the correct max_rollout_reward value for Q_s_a value for child action '3' in test_backpropagate_statistics
- fix test_expand HOT 2
- [p0] Set attention mask and pad token in beam generate HOT 1
- refactor select function HOT 1
- fix backpropagate_statistics HOT 1
- Add test to ensure that Node.current_token indeed only represents the current token in the sequence and not the entire token HOT 1
- code cleanup HOT 1
- [p1] The plots! The plots! Do a comparison with greedy decode and beam decode in a jupyter notebook
- Add option to use some other function f to score trajectories, as currently the MCTS code just implements beam search HOT 1
- Read the APPS paper and import the dataset into codebase HOT 3
- Fix segmentation fault due to load_dataset, optionally bypass the huggingface dataloader HOT 2
- [p2] try some form of parallelization
- decide on some standard for the format of executing python inputs HOT 2
- [p0] apps_dataset playground HOT 1
- [p1] rewrite reward_function_utils.py
- [p1] Build a dataloader that loads the APPS dataset question (prompt) with its associated unit tests, which allows shuffling, and multiple epoch loading, et cetera
- [p1] Refactor code to allow for passing in the question as the prompt to MCTS (main_algorithm) and the accompanying unit tests as the reward function (evaluate_full_paths)
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