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382cb2e b5baf9e 382cb2e 3b7a278 fe51acc 3b7a278 382cb2e 7c341d3 382cb2e c5a7268 382cb2e 29f0504 382cb2e b5baf9e 382cb2e fe51acc b5baf9e fe51acc b5baf9e fe51acc b5baf9e 382cb2e fe51acc 382cb2e fe51acc 382cb2e fe51acc 382cb2e fe51acc 382cb2e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 | #!/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."
|