[rl] Add optional Verifiers rollout integration - #4356
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| @dataclass(kw_only=True, slots=True) | ||
| class Config(VerifiersRollouter.Config): | ||
| train_dataset: VerifiersTaskDataset.Config = field( |
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Dataset is defined through verifiers
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| include = ["torchtitan*", "torchtitan_recipes*"] | ||
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| [tool.setuptools.package-data] | ||
| "torchtitan.experiments.rl.examples.verifiers" = ["verifiers_env.toml"] |
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This is because when release, python packaging includes .py files automatically, but not .toml files. This will not make verifiers a hard dependency
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not a review, just a general comment: Its unclear to me what the But it seems that you also need a If this example is about Also, it might be worth checking how other libraries integrate with verifiers. Example: https://github.com/thinking-machines-lab/tinker-cookbook/tree/main/tinker_cookbook/recipes/verifiers_rl |
In terms of folder organization, we are very similar. In-terms of integration point, I will take more look into details! |
Summary
verifiersexample that reuses the DAPO Math dataset and training setup while delegating episode execution and reward calculation to Verifiers.verifiers.nullharness with a local subprocess runtime. No Docker or remote sandbox is required, and no tools are exposed to the model.dapo_mathimplementation unchanged as the native comparison path.The example can be launched with:
100-step comparison
Both runs loaded Qwen3-4B-Base from the same HF checkpoint on four H100 GPUs and used identical overrides:
The table reports the mean across all 100 W&B training steps unless otherwise noted.
dapo_mathverifiersThe 2 DAPO math run shows similar reward and rollout:
