| set -e | |
| ROOT=/lustre/fsw/portfolios/nvr/users/jtremblay/yu | |
| V5CODE=$ROOT/1027_sim_tasks/share_v5_sim2real_20260929/code | |
| CONDA=$ROOT/miniconda3 | |
| UPY=$CONDA/envs/ur5dp/bin/python | |
| NAME=blb_v1 | |
| DATA_DIR=$ROOT/1027_run/data/$NAME | |
| RUN=$ROOT/1027_run | |
| source $CONDA/etc/profile.d/conda.sh | |
| kept=$($UPY -c "import json; d=json.load(open('$DATA_DIR/collect_meta.json')); print(d['n_kept'])" 2>/dev/null || echo 47) | |
| echo "== Training DP blb_v1 ($kept demos)" | |
| ln -sfn $DATA_DIR $V5CODE/sim_data/$NAME | |
| cd $V5CODE/ur5_lab_code && export PYTHONPATH=src:. | |
| $UPY train.py --config-name=train_baseline_diffusion_unet task=sim_baseline \ | |
| task_name=$NAME dataset_path=$DATA_DIR n_demo=$kept \ | |
| training.device=cuda:0 training.seed=0 training.num_epochs=130 \ | |
| training.checkpoint_every=129 checkpoint.topk.k=0 \ | |
| training.resume=True checkpoint.save_last_ckpt=True \ | |
| dataloader.batch_size=256 dataloader.num_workers=16 logging.mode=offline \ | |
| "policy._target_=algorithms.policy.diffusion_unet_baseline_aug_policy.DiffusionUnetBaselineAugPolicy" \ | |
| +policy.cam1_dropout=0.1 +policy.cam1_aug_p=0.5 +policy.cam1_erase_p=0.3 +policy.cam0_aug_p=0.3 \ | |
| "hydra.run.dir=$V5CODE/train_runs/${NAME}_aug_s0" \ | |
| 2>&1 | tee $RUN/logs/${NAME}_train.log | |
| echo "== DONE" | |