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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 |