feat: accept opaque string envelopes for routed_experts#2089
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Training frameworks attach per-token routed-expert indices ([tokens, num_moe_layers, topk]) to chat responses for MoE router replay. As nested JSON int lists these are multi-MB payloads (~11.7M ints at 30k-token contexts) that every gym hop re-parses, re-validates, and re-serializes at ~1s of single-threaded CPU each, throttling rollout throughput. Widen RoutedExperts to Union[str, List[List[List[int]]]] so a single opaque envelope string (e.g. NeMo-RL's nrlre1:<dtype>:<SxLxK>:<base64>) passes through validation in O(1). Gym never inspects the value; the one non-passthrough site (harbor nemo_gym_llm _extract_routed_experts isinstance-list guard, which would silently drop a string) is widened to match. Nested-list payloads remain fully supported. Companion to the NeMo-RL change that emits the envelope; measured there: gym rollout time 132.2s -> 35.4s per step at 15-28k-token prompts with replay fidelity unchanged. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Signed-off-by: Zeyu Zhou <zezhou@nvidia.com>
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Training frameworks attach per-token routed-expert indices ([tokens, num_moe_layers, topk]) to chat responses for MoE router replay. As nested JSON int lists these are multi-MB payloads that every gym hop re-parses, re-validates, and re-serializes at ~1s of single-threaded CPU each, throttling rollout throughput.
Widen RoutedExperts to Union[str, List[List[List[int]]]] so a single opaque envelope string (e.g. NeMo-RL's nrlre1:::) passes through validation in O(1). Gym never inspects the value; the one non-passthrough site (harbor nemo_gym_llm _extract_routed_experts isinstance-list guard, which would silently drop a string) is widened to match. Nested-list payloads remain fully supported.