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| # Smoke test for Hugging Face Jobs with the official LeRobot GPU image. | |
| # Submit from the repo root: | |
| # hf jobs run --flavor l4x1 --timeout 20m --secrets HF_TOKEN --name act-smoke \ | |
| # huggingface/lerobot-gpu:latest bash -c "$(cat scripts/cloud_smoke_test.sh)" | |
| set -euo pipefail | |
| cd /lerobot | |
| echo "== hardware" | |
| nvidia-smi --query-gpu=name,memory.total,driver_version --format=csv,noheader | |
| echo "cpu cores: $(nproc)" | |
| echo "== versions" | |
| python - <<'EOF' | |
| import platform, torch, lerobot | |
| print("python", platform.python_version(), "| torch", torch.__version__, "| cuda", torch.cuda.is_available(), | |
| "|", torch.cuda.get_device_name(0)) | |
| print("lerobot", lerobot.__version__) | |
| EOF | |
| git -C /lerobot log -1 --format='lerobot commit %H %cd' 2>/dev/null || echo "lerobot commit: no .git in image" | |
| echo "== hub auth" | |
| hf auth whoami | head -1 | |
| echo "== headless sim rendering" | |
| python - <<'EOF' | |
| import time, gymnasium as gym, gym_aloha # noqa: F401 | |
| env = gym.make("gym_aloha/AlohaTransferCube-v0", obs_type="pixels_agent_pos") | |
| obs, _ = env.reset(seed=1000) | |
| t = time.time() | |
| for _ in range(100): | |
| obs, *_ = env.step(env.action_space.sample()) | |
| print("render ok:", obs["pixels"]["top"].shape, f"{(time.time() - t) * 10:.1f} ms/step") | |
| EOF | |
| echo "== official checkpoint, seeds 1000-1009" | |
| python src/lerobot/processor/migrate_policy_normalization.py \ | |
| --pretrained-path lerobot/act_aloha_sim_transfer_cube_human --output-dir /tmp/official > /tmp/migrate.log 2>&1 \ | |
| && echo "migration ok" || { tail -20 /tmp/migrate.log; exit 1; } | |
| start=$(date +%s) | |
| # use_async_envs=false: LeRobot starts AsyncVectorEnv workers with context="forkserver", and those | |
| # workers never import gym_aloha, so gym.make fails with "Namespace gym_aloha not found". | |
| lerobot-eval --policy.path=/tmp/official --env.type=aloha --env.task=AlohaTransferCube-v0 \ | |
| --eval.n_episodes=10 --eval.batch_size=10 --eval.use_async_envs=false --policy.device=cuda --seed=1000 \ | |
| --output_dir=/tmp/eval_smoke > /tmp/eval.log 2>&1 || { tail -40 /tmp/eval.log; exit 1; } | |
| echo "eval wall time: $(( $(date +%s) - start )) s for 10 episodes (10 envs in one process)" | |
| python - <<'EOF' | |
| import json | |
| m = json.load(open("/tmp/eval_smoke/eval_info.json"))["per_task"][0]["metrics"] | |
| official = [False, True, True, True, True, False, True, True, True, False] # official eval_info.json, seeds 1000-1009 | |
| print("successes:", m["successes"]) | |
| print("sum_rewards:", m["sum_rewards"]) | |
| print(f"same outcome as the official run on {sum(a == b for a, b in zip(m['successes'], official))}/10 seeds") | |
| EOF | |