agent="vadv2_4096_pdm_rel_extra"
# cache="navtrain_vadv2_4f_cache"
cache="navtrain_vadv2+map_img256x1024_cache"
bs=32
lr=0.0001


ngc batch run \
-in dgx1v.32g.8.norm \
--ace nv-us-west-2 \
--label _wl___computer_vision \
-n ml-model.lzx_train._wl___computer_vision \
--result /result \
-i nvcr.io/nvidian/swaiinf/lzx-navsim \
--workspace q-2TlPKESo62ktTxOc8rYg:/zhenxinl_nuplan \
--port 6007 \
--commandline "
    git pull;
    python \${NAVSIM_DEVKIT_ROOT}/navsim/planning/script/run_training.py \
        agent=$agent \
        experiment_name=${agent}_ckpt \
        cache_path=\${NAVSIM_EXP_ROOT}/$cache \
        agent.config.ckpt_path=${agent}_ckpt \
        split=trainval \
        dataloader.params.batch_size=$bs \
        agent.lr=$lr \
        scene_filter=navtrain"