| 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" |