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| spec_version: 1 | |
| name: ml-debug-env | |
| version: 3.0.0 | |
| description: > | |
| RL environment where agents debug broken PyTorch training scripts. | |
| Eight tasks of increasing difficulty — from easy single-bug crashes | |
| to expert-level compound tasks with two simultaneous silent bugs. | |
| Graders execute the agent's fixed code in an isolated subprocess | |
| and score 0.01–0.99 with partial credit at each verification stage. | |
| Accepts bug_type="other" for open-ended debugging without category constraints. | |
| author: rehaan | |
| type: space | |
| runtime: fastapi | |
| app: server.app:app | |
| port: 8000 | |
| tasks: | |
| - shape_mismatch | |
| - training_collapse | |
| - data_leakage | |
| - wrong_device | |
| - gradient_not_zeroed | |
| - missing_eval_mode | |
| - compound_shape_device | |
| - compound_leakage_eval | |
| tags: | |
| - openenv | |
| - pytorch | |
| - debugging | |
| - reinforcement-learning | |
| - compound-bugs |