| SCRIPTPATH=$(dirname $(readlink -f "$0")) | |
| PROJECT_DIR="${SCRIPTPATH}/../../" | |
| # conda activate loftr | |
| export PYTHONPATH=$PROJECT_DIR:$PYTHONPATH | |
| cd $PROJECT_DIR | |
| data_cfg_path="configs/data/scannet_trainval.py" | |
| main_cfg_path="configs/aspan/indoor/aspan_train.py" | |
| n_nodes=1 | |
| n_gpus_per_node=8 | |
| torch_num_workers=36 | |
| batch_size=3 | |
| pin_memory=true | |
| exp_name="indoor-ds-bs-aspan-bs=$(($n_gpus_per_node * $batch_size))" | |
| CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7' python -u ./train.py \ | |
| ${data_cfg_path} \ | |
| ${main_cfg_path} \ | |
| --exp_name=${exp_name} \ | |
| --gpus=${n_gpus_per_node} --num_nodes=${n_nodes} --accelerator="ddp" \ | |
| --batch_size=${batch_size} --num_workers=${torch_num_workers} --pin_memory=${pin_memory} \ | |
| --check_val_every_n_epoch=1 \ | |
| --log_every_n_steps=100 \ | |
| --flush_logs_every_n_steps=100 \ | |
| --limit_val_batches=1. \ | |
| --num_sanity_val_steps=10 \ | |
| --benchmark=True \ | |
| --max_epochs=30 \ | |
| --parallel_load_data \ | |
| --mode integrated |