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You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or planning anything new, in software or out of it (a talk, a business, a renovation).
nvidia-nemo-gym-reward-profilingUse to help users get started with Nemo Gym reward profiling. Covers the basic ng_run, ng_collect_rollouts, and ng_reward_profile workflow, repeated rollouts, materialized inputs, rollout JSONL artifacts, task and rollout identity, output inspection, partial profiling, and rollout_infos. For failed jobs, prefer nemo-gym-debugging.
Independent GitHub snapshot · Automated classification · Original documentation governs
Use this skill when the user wants to run, understand, or lightly modify Nemo Gym reward profiling. Keep the answer oriented around the normal workflow:
ng_run starts model/resource servers, ng_collect_rollouts writes rollout artifacts, and ng_reward_profile generates profiling output from those artifacts.
If the user is primarily debugging a failed job or stack trace, use the nemo-gym-debugging skill first.
ng_run.ng_collect_rollouts; this writes rollouts.jsonl and *_materialized_inputs.jsonl.ng_reward_profile on the materialized inputs and rollout JSONL to generate *_reward_profiling.jsonl.Repeated rollouts are the main profiling lever. num_repeats=1 is valid, but per-task averages and variance are only meaningful with multiple rollouts per task.
*_materialized_inputs.jsonl: expanded collection inputs after repeat expansion, agent defaults, and task/rollout id assignment.rollouts.jsonl: one completed rollout/result per materialized input row.*_reward_profiling.jsonl: one summarized profile row per original task with at least one completed rollout._ng_task_index: original task/sample id._ng_rollout_index: repeated rollout id for that task.rollout_infos: compact per-rollout info inside each task profile row, including reward, token usage, and numeric rollout metrics when available.Keep reward-to-length or reward-to-token analysis keyed by both _ng_task_index and _ng_rollout_index.
Load references only when the user needs that detail:
references/quick-start.md for a generic command template and the minimal run sequence.references/output-format.md to explain materialized inputs, rollout JSONL, reward profile rows, rollout_infos, and partial profiling.ng_reward_profile as the reward profiling step; rollout collection does not write reward profile files.++allow_partial_rollouts=True to profile completed rollouts and drop original input rows with no completed rollout.nemo_gym/reward_profile.py over memory if flags differ.