#!/usr/bin/env bash
source "$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd)/block_white_box_common.sh"
if [[ "${DRY_RUN:-0}" != 1 && ! -f "$DATASET_ROOT/meta/info.json" ]]; then
  echo "请先录制并检查数据：$DATASET_ROOT" >&2; exit 1
fi
if [[ "${DRY_RUN:-0}" != 1 ]]; then
  python -c 'import torch; import sys; sys.exit(0 if torch.cuda.is_available() else "CUDA 不可用，请先修复 NVIDIA 驱动；已停止训练以避免回退到 CPU。")'
fi
TRAIN_OUTPUT="${TRAIN_OUTPUT:-$LEROBOT_PROJECT_DIR/outputs/train/act_block_white_box_$(date +%Y%m%d_%H%M%S)}"
run_task lerobot-train --policy.type=act --policy.device=cuda --policy.push_to_hub=false \
  "--dataset.repo_id=$DATASET_ID" "--dataset.root=$DATASET_ROOT" \
  "--output_dir=$TRAIN_OUTPUT" --job_name=act_block_white_box \
  "--batch_size=${BATCH_SIZE:-8}" "--steps=${STEPS:-20000}" --num_workers=4 \
  --save_freq=2000 --env_eval_freq=0 --seed=42 --wandb.enable=false "$@"