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#!/bin/bash -l
SCRIPTPATH=$(dirname $(readlink -f "$0"))
PROJECT_DIR="${SCRIPTPATH}/../../"
# conda activate loftr
export PYTHONPATH=$PROJECT_DIR:$PYTHONPATH
cd $PROJECT_DIR
data_cfg_path="configs/data/scannet_trainval.py"
main_cfg_path="configs/loftr/indoor/loftr_ds_dense.py"
n_nodes=1
n_gpus_per_node=4
torch_num_workers=4
batch_size=1
pin_memory=true
exp_name="indoor-ds-bs=$(($n_gpus_per_node * $n_nodes * $batch_size))"
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