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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" |