VRIS_vip / LAVT-RIS /scripts /baseline_test.sh
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#!/bin/bash
#SBATCH --job-name=lavt_test
#SBATCH --partition=a4000 # a6000 or a100
#SBATCH --gres=gpu:1
#SBATCH --time=7-00:00:00 # d-hh:mm:ss, max time limit
#SBATCH --mem=48000 # cpu memory size
#SBATCH --cpus-per-task=4 # cpu num
#SBATCH --output=./logs/test_gref_m10_mg10_tmp010_4gpu_bs16_ang.txt
ml purge
ml load cuda/11.3
eval "$(conda shell.bash hook)"
conda activate cris
cd /data2/projects/chaeyun/LAVT-RIS/
MODEL_ID="gref_m10_mg10_tmp010_4gpu_bs16_ang"
# MODEL_ID="posonly_mlw005_b32_2"
# python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split val --resume ./models/$MODEL_ID/model_best_$MODEL_ID.pth --workers 4 --ddp_trained_weights --window12 --img_size 480
# python test_mostat.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split static --resume ./models/$MODEL_ID/model_best_$MODEL_ID.pth --workers 4 --ddp_trained_weights --window12 --img_size 480
python test.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split test --resume ./models/$MODEL_ID/model_best_$MODEL_ID.pth --workers 4 --ddp_trained_weights --window12 --img_size 480
python test_mostat.py --model lavt_one --swin_type base --dataset refcocog --splitBy umd --split motion --resume ./models/$MODEL_ID/model_best_$MODEL_ID.pth --workers 4 --ddp_trained_weights --window12 --img_size 480