#!/bin/bash # Training entry point inside an HF Jobs container. # Expects (env): ARTIFACTS_REPO, EXP_NAME, TRAIN_FLAGS; HF_TOKEN secret set. # Mounted: the artifacts dataset repo read-only at /artifacts. set -euo pipefail mkdir -p /work/logs LOG=/work/logs/job.log exec > >(tee "$LOG") 2>&1 || true echo "[job] host: $(hostname)" nvidia-smi || echo "[job] WARNING: no GPU visible" # --- deps: jax + CUDA 12, mujoco playground, wandb -------------------------- pip install --no-cache-dir \ "jax[cuda12]==0.11.1" jaxlib==0.11.1 \ mujoco==3.12.0 mujoco-mjx==3.12.0 playground==0.2.0 \ brax==0.14.2 mediapy tensorboardX wandb # W&B: authenticate from the HF secret if provided if [[ -n "${WANDB_API_KEY:-}" ]]; then wandb login --relogin "$WANDB_API_KEY" > /dev/null 2>&1 || echo "[job] wandb login failed (continuing without W&B)" fi export MUJOCO_GL=egl export XLA_PYTHON_CLIENT_PREALLOCATE=false export XLA_PYTHON_CLIENT_MEM_FRACTION=0.85 export XLA_FLAGS="--xla_gpu_triton_gemm_any=True" # --- unpack the code snapshot ------------------------------------------------ mkdir -p /work/repo && cd /work/repo tar xzf /artifacts/code/code.tar.gz # --- artifacts uploader: pushes new checkpoints/logs every 5 min ------------- ( while true; do sleep 300 python - <<'PY' || echo "[artifacts] sync failed this round; retrying in 5 min" import os from huggingface_hub import HfApi api = HfApi() api.upload_folder( repo_id=os.environ["ARTIFACTS_REPO"], repo_type="dataset", folder_path="/work/logs", path_in_repo=f"runs/{os.environ['EXP_NAME']}", ) print("[job] artifacts synced to", os.environ["ARTIFACTS_REPO"], flush=True) PY done ) & ARTIFACT_UPLOADER_PID=$! trap 'kill $ARTIFACT_UPLOADER_PID 2>/dev/null || true' EXIT echo "[job] training starting: $TRAIN_FLAGS" python rl/scripts/train_jax_ppo.py $TRAIN_FLAGS --logdir /work/logs || \ echo "[job] training exited nonzero — uploading logs anyway" # --- final full upload -------------------------------------------------------- python - <<'PY' import os, traceback from huggingface_hub import HfApi try: api = HfApi() repo = os.environ["ARTIFACTS_REPO"] exp = os.environ["EXP_NAME"] api.upload_folder( repo_id=repo, repo_type="dataset", folder_path="/work/logs", path_in_repo=f"runs/{exp}", ) print("[job] artifacts uploaded to", repo, "runs/", exp) except Exception: import traceback; traceback.print_exc() PY echo "[job] done."