Nemo Gym Reward Profiling

Invocation Check

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:

gym env start starts model/resources servers, gym eval run --no-serve writes rollout artifacts, and gym eval 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.

Basic Workflow

1. Identify the environment config paths and input JSONL.
2. Start Gym servers with gym env start.
3. Collect rollouts with gym eval run --no-serve; this writes rollouts.jsonl and *_materialized_inputs.jsonl.
4. Run gym eval profile on the materialized inputs and rollout JSONL to generate *_reward_profiling.jsonl.
5. Inspect line counts and profile rows.

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.