fix(inference): keep single-process model loads off the training dp mesh

[lfengad]

Unblocks the five red checks on #208 (the 2026-08-19 i4 sync). Lands on main first; #208 then picks it up by updating/rebasing its release branch, which is also where the fix actually gets exercised — the GPU suite only triggers on pull_request: branches: [main], so on this PR it runs against code that does not yet contain the i4 change and can only show the fix is inert here.

All three touched files are OSS-only (none appear in .file_mapping.json), so the next i4 release will not clobber them and no imaginaire4 MR is needed.

Root cause 1 — single-process scripts are forced to build a device mesh

#208 flips ParallelDims.dp_enabled to True unconditionally under training semantics, so the FSDP2 wrap always has somewhere to install the MixedPrecisionPolicy. As a consequence build_meshes() always builds the dp mesh, even at world_size == 1, and init_device_mesh implicitly calls init_process_group(), which needs an env:// rendezvous. Reproduced directly against ParallelDims on #208's tree:

enable_inference_mode=False -> dp_enabled=True  -> ValueError: environment variable RANK expected, but not set
enable_inference_mode=True  -> dp_enabled=False -> no mesh built, no process group needed

Cosmos3OmniModel is only ever built for inference and export, including plain single-process runs with no torchrun rendezvous:

• the conversion scripts (convert_model_to_dcp, convert_model_to_vlm_safetensors, _convert_model_to_diffusers) reach it via from_pretrained_dcp's default ParallelismConfig(), which is training semantics;
• export_model constructs it directly from a training config.

convert_model_to_dcp.sh even runs with CUDA_VISIBLE_DEVICES= and COSMOS_DEVICE=cpu, so there is no rendezvous to inherit. This one cause accounts for generator-training-regression, reasoner-training-regression, reasoner-inference-smoke, training-smoke, and unittest's scripts/_test.py::test_level_0[convert_model_to_dcp] on #208 — all failed in fixture setup, not in the code under test.

The fix pins enable_inference_mode = True in Cosmos3OmniModel.__init__, next to the ema.enabled / activation_checkpointing.mode overrides the wrapper already applies for the same reason. Doing it in __init__ rather than in from_pretrained_dcp's default also covers export_model's direct construction. Real inference is unaffected: OmniInference._get_parallelism_config already passes enable_inference_mode=True. On main it is a no-op, since a single-rank dp_replicate=1, dp_shard=1 already leaves dp_enabled False.

Root cause 2 — OSS-only test does not know about the new LiDAR config field

As of #208 set_up_tokenizers reads config.lidar_tokenizer. omni_mot_model_test.py is OSS-only and builds its config from SimpleNamespace, so it raised AttributeError: 'types.SimpleNamespace' object has no attribute 'lidar_tokenizer'. Added lidar_tokenizer=None to both stand-in configs; the extra attribute is inert against main's tokenizer setup.

Verification

• pytest cosmos_framework/model/generator/omni_mot_model_test.py — 2 failed then 2 passed on Release 2026-08-19 (i4 02f21ec8) #208's tree; 2 passed on this branch.
• Root cause 1 reproduced directly against ParallelDims (output quoted above). The end-to-end convert_model_to_dcp run is left to Release 2026-08-19 (i4 02f21ec8) #208's GPU suite once it picks this up.
• ruff check and ruff format --check clean on the three files.

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