rename adv_estimator param to advantage_estimator in compute_advantages_and_returns#1793
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rename adv_estimator param to advantage_estimator in compute_advantages_and_returns#1793KTanmay1 wants to merge 1 commit into
KTanmay1 wants to merge 1 commit into
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…es_and_returns The function parameter name `adv_estimator` diverged from the config field name `advantage_estimator` (AlgorithmConfig). This mismatch causes a confusing startup crash (ValueError from validate_dict_keys_against_dataclass) when writing new integrations that copy the function parameter name as a CLI config key. Rename the parameter and its one internal use to match the config field. Update the two keyword-argument call sites in trainer.py accordingly. Fixes NovaSky-AI#1792
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This pull request renames the parameter adv_estimator to advantage_estimator in the compute_advantages_and_returns function signature and updates its corresponding usages in skyrl/train/trainer.py to maintain consistency. I have no feedback to provide as the changes are straightforward and there are no review comments.
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Summary
Closes #1792.
The function
compute_advantages_and_returnsinppo_utils.pyusedadv_estimatoras its parameter name, while the corresponding config field onAlgorithmConfigisadvantage_estimator. These two names diverged silently — the internal plumbing worked correctly becausetrainer.pyreads the config field and passes it positionally-by-keyword, but the mismatch is a footgun for anyone writing a new integration or launch script.If a developer uses
trainer.algorithm.adv_estimator=<value>on the CLI (copying the function parameter name),validate_dict_keys_against_dataclassraises at startup:Changes
skyrl/backends/skyrl_train/utils/ppo_utils.py: rename parameteradv_estimator→advantage_estimatorand update its one internal useskyrl/train/trainer.py: update both keyword-argument call sites fromadv_estimator=→advantage_estimator=No behavior change — purely a naming fix.
Test plan
uv run --extra dev pytest tests/train/ tests/backends/skyrl_train/ --ignore=tests/backends/skyrl_train/gpu/