#!/usr/bin/env bash set -uo pipefail ROOT=/lustre/fsw/portfolios/nvr/users/jtremblay/yu RUN=$ROOT/1027_run; TASKS=$ROOT/1027_sim_tasks V5CODE=$TASKS/share_v5_sim2real_20260929/code CONDA=$ROOT/miniconda3; SPY=$CONDA/envs/simfoundry/bin/python; UPY=$CONDA/envs/ur5dp/bin/python HOME_FAKE=$RUN/home_fake YDIR=$TASKS/yu_parts_tasks TASK=${TASK:-battery} NAME=${TASK}_v1 log() { echo "== $(date '+%F %T') [$TASK] $*"; } mkdir -p $HOME_FAKE/ur5_sim2real_v5 $RUN/logs $V5CODE/sim_data $V5CODE/train_runs ln -sfn $CONDA $HOME_FAKE/miniconda3 ln -sfn $TASKS/share_v5_sim2real_20260929 $HOME_FAKE/ur5_sim2real_v5/share_v5_sim2real_20260929 ln -sfn $YDIR $HOME_FAKE/ur5_sim2real_v5/yu_parts_tasks export HOME=$HOME_FAKE source $CONDA/etc/profile.d/conda.sh export TORCHINDUCTOR_COMPILE_THREADS=1 OMNIGIBSON_HEADLESS=1 OMNI_KIT_ACCEPT_EULA=YES PYTHONUNBUFFERED=1 export OMNIGIBSON_RENDER_VIEWER_CAMERA=0 TORCH_COMPILE_DISABLE=1 TORCHDYNAMO_DISABLE=1 export OMNIGIBSON_DATA_PATH=/lustre/fsw/portfolios/nvr/users/jtremblay/yu/SimFoundry/deps/BEHAVIOR-1K/datasets DS_FSW=/lustre/fsw/portfolios/nvr/users/jtremblay/yu/SimFoundry/deps/BEHAVIOR-1K/datasets mkdir -p $DS_FSW/yu-assets/objects for c in $TASKS/yu_parts_tasks/object_assets/objects/*; do nm=$(basename $c); [ ! -e "$DS_FSW/yu-assets/objects/$nm" ] && ln -sfn "$c" "$DS_FSW/yu-assets/objects/$nm" || true done DATA_DIR=$YDIR/data/$TASK/$NAME DATA_A=${DATA_DIR}_a; DATA_B=${DATA_DIR}_b mkdir -p $DATA_A $DATA_B # Get existing kept count existing=$($UPY -c "import json; d=json.load(open('$DATA_DIR/collect_meta.json')); print(d.get('n_kept',0))" 2>/dev/null || echo 0) log "Existing demos: $existing. Collecting 2x parallel to reach 50." CUDA_VISIBLE_DEVICES=0 OMNIGIBSON_GPU_ID=0 \ $SPY -u $YDIR/scripts/yp_collect.py \ --task $TASK --out $DATA_A --seeds 1-100 --max-kept 30 --dart --start-offset --resume \ 2>&1 | tee $RUN/logs/${NAME}_a.log & PID_A=$! sleep 60 CUDA_VISIBLE_DEVICES=2 OMNIGIBSON_GPU_ID=2 \ $SPY -u $YDIR/scripts/yp_collect.py \ --task $TASK --out $DATA_B --seeds 101-200 --max-kept 30 --dart --start-offset --resume \ 2>&1 | tee $RUN/logs/${NAME}_b.log & PID_B=$! wait $PID_A; log "Proc A done" wait $PID_B; log "Proc B done" python3 $RUN/merge_shards.py $DATA_DIR $DATA_A $DATA_B $DATA_DIR 50 kept=$($UPY -c "import json; d=json.load(open('$DATA_DIR/collect_meta.json')); print(d['n_kept'])" 2>/dev/null || echo 0) log "Kept: $kept" [ "$kept" -lt 30 ] && { log "ERROR: only $kept"; exit 1; } ln -sfn $DATA_DIR $V5CODE/sim_data/$NAME log "Packing zarr" cd $V5CODE && $UPY ur5_import/scripts/pack_zarr.py --dir sim_data/$NAME 2>&1 | tee -a $RUN/logs/${NAME}_train.log log "Training DP ($kept demos)" 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 rc=$?; log "Train exit $rc" [ $rc -eq 0 ] && touch $RUN/data/TRAIN_DONE_${NAME} || { log "TRAIN FAILED"; exit 1; } log "DONE: $V5CODE/train_runs/${NAME}_aug_s0/checkpoints/"