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G05 newdata step2000 — IROS 2026 Docker image
This image is built on the official challenge_base:20260806 image and keeps
its CUDA 12.2, ROS 2 Humble, Redis/tmux control flow, working directory, and
NVIDIA entrypoint.
Image tag: g05-newdata-step2000:iros2026-fa2-fmonly-pathfix
Checkpoint inside the image:
/opt/g05/run/checkpoints/step_2000.pt
The zero-byte training lock file .step_2000.pt.lock is intentionally not
included. The actual checkpoint, model source, processor assets, dataset
statistics, and offline Python/CUDA dependencies are included.
The official InferenceNode.load_model() and InferenceNode.predict() hooks
are implemented. predict() returns a finite float32 NumPy array with shape
(32, 25).
Load
Either archive can be loaded; the gzip archive is smaller:
docker load -i QQ.tar.gz
Run
docker run --rm --gpus all --network host --ipc host -it \
g05-newdata-step2000:iros2026-fa2-fmonly-pathfix /bin/bash
Inside the container:
bash scripts/run_infer.sh
The deployment action path is FM-only by default (G05_ENABLE_AR_ACTION=0).
It replans a 32-step action chunk at approximately 2 Hz while the independent
publisher sends steps at 30 Hz; a newly inferred trajectory replaces the
remaining old trajectory. For diagnosis only, set G05_ENABLE_AR_ACTION=1 to
restore AR+FM inference; this substantially reduces the replanning rate.
eval/infer_setting.py is the single runtime source for ckpt_path and
config_path. The corresponding optional environment overrides are
G05_CHECKPOINT and G05_CONFIG_PATH; both resolved paths are validated and
printed before model loading.
The model runs fully offline (HF_HUB_OFFLINE=1 and
TRANSFORMERS_OFFLINE=1). FlashAttention 2.8.3.post1 is installed and used by
the vision encoder. GitPython's optional repository probe is disabled with
GIT_PYTHON_REFRESH=quiet; model inference does not use git.
Validation performed
- Official base archive SHA-256 verified before import.
- Final Docker archive manifest parsed successfully: linux/amd64.
- NVIDIA entrypoint and official ROS environment preserved.
- Embedded checkpoint SHA-256 matches the source checkpoint.
- Container-root imports passed for Torch, NumPy, OpenCV, Transformers, Hydra, G05, and the challenge adapter.
- Real checkpoint load and synthetic
(32, 25)inference passed on an A100 from the assembled image root filesystem with host GPU devices and driver libraries injected as a container runtime would provide them.
Before an official submission, run the image once on the competition-equivalent RTX 4090 48 GB host and follow any final upload/naming instructions announced by the organizers.