agent="hydra_pe"
cache="null"
bs=32
lr=0.0002
epoch=20
config="competition_training"
dir=${agent}_lr2_ckpt

ngc batch run \
-in dgx1v.32g.8.norm \
--ace nv-us-west-2 \
--label _wl___computer_vision \
-n ml-model.lkl_train._wl___computer_vision \
--result /result \
-i nvcr.io/nvidian/swaiinf/lzx-navsim \
--workspace q-2TlPKESo62ktTxOc8rYg:/zhenxinl_nuplan \
--port 6007 \
--commandline "
    git pull;
    pip install --upgrade diffusers[torch];
    python \${NAVSIM_DEVKIT_ROOT}/navsim/planning/script/run_training.py \
        --config-name $config \
        agent=$agent \
        experiment_name=$dir \
        agent.config.ckpt_path=$dir \
        +agent.config.backbone_wd=$wd \
        agent.lr=$lr \
        cache_path=$cache \
        dataloader.params.batch_size=$bs \
        ~trainer.params.strategy \
        trainer.params.max_epochs=$epoch \
        split=trainval \
        scene_filter=navtrain"