Add multi-control transfer inference smoke test

[lfengad]

What

Adds test_nano_inference_multi_control_transfer to tests/nano_inference_smoke_test.py, giving the Cosmos3-Nano generator inference smoke test coverage for the multi-control transfer feature (two control hints blended by multi_control_two_way_attention).

It mirrors the existing single-control transfer run (same latency preset, 4 ranks → cfgp=2/cp=2), but the generated spec sets two hints (edge + blur) with per-hint weight and no control_path, so both controls are computed on the fly from a single vision_path (the pinned public robot_pouring.mp4 clip) and aggregated by the weighted N-pass multi-control attention.

What it verifies

• Multi-control path executes: 2 hints → control_weights set → the network routes to multi_control_two_way_attention (both controls computed on the fly).
• Process stays within expected invariants: the framework's multi-control runtime asserts (weights length == #controls, packing consistency, batch_size==1) must hold or the run exits non-zero → the test fails. Plus the test's own asserts: exactly one output; both edge and blur active with a weight and no control_path; vision_path set; control_guidance and guidance > 1.0.
• Output is valid: non-degenerate vision.mp4 via the existing _assert_video_has_content (≥16 frames, finite pixels, pixel std > 3).

Smoke-level (output validity + path executed under asserts), not numeric goldens — consistent with the rest of the module.

Test

Runs on the same 8-GPU gate as test_nano_inference_omni:

pytest -s tests/nano_inference_smoke_test.py --num-gpus=8 --levels=2 -o addopts=

Verified end to end on a 4-rank latency run (exit 0; log shows both Computing edge control input on the fly and Computing blur control input on the fly; all assertions pass). Collection confirmed both tests register (MAX_GPUS=8).

🤖 Generated with Claude Code