#!/bin/bash
##ENVIRONMENT SETTINGS; CHANGE WITH CAUTION
#SBATCH --export=NONE                #Do not propagate environment
#SBATCH --get-user-env=L             #Replicate login environment

##NECESSARY JOB SPECIFICATIONS
#SBATCH --job-name=VDSR_test_0_1    #Set the job name to "JobExample5"
#SBATCH --time=00:03:00              #Set the wall clock limit to 1hr and 30min
#SBATCH --ntasks=1                    #Request 1 node
#SBATCH --mem=64G                 #Request 2560MB (2.5GB) per node
#SBATCH --output=VDSR_test_0_1.out      #Send stdout/err to "Example5Out.[jobID]"
#SBATCH --gres=gpu:2                 #Request 2 GPU per node can be 1 or 2
#SBATCH --partition=gpu              #Request the GPU partition/queue

##OPTIONAL JOB SPECIFICATIONS
#SBATCH --mail-user=xujiaxi@tamu.edu    #Send all emails to email_addres

ml purge
ml Python/3.5.2-intel-2017A

source ../../../Mask_RCNN/samples/materials/tdenv/bin/activate
# python main.py --model RCAN --save RCAN_X2self_60_1 --scale 2 --n_resgroups 10 --n_resblocks 20 --n_feats 64  --n_colors 1 --reset --chop --save_results --patch_size 96
# CUDA_VISIBLE_DEVICES=0 python main.py --data_test MyImage --scale 2 --model VDSR --n_resgroups 10 --n_resblocks 20 --n_feats 64 --pre_train ../../RCAN_TrainCode/experiment/VDSR_X2self_0_1/model/model_best.pt --test_only --save_results --chop --save 'testVDSR0_1' --testpath ../../DIV2K/0_1/LR --testset fortestVDSR0_1
# python main.py --model VDSR --save VDSR_X2self_60_1 --scale 2 --reset --chop --save_results
# CUDA_VISIBLE_DEVICES=0 python main.py --data_test MyImage --scale 1 --model VDSR --n_resgroups 10 --n_resblocks 20 --n_feats 64 --pre_train ../../RCAN_TrainCode/experiment/latest_VDSR_0_1/model/model_best.pt --test_only --save_results --chop --save 'bestepoch_VDSR_0_1' --testpath ../../DIV2K/0_1/BI --testset image0_1
