follow https://www.nature.com/articles/nature14236
#1.train DQN python train_DQN.py GPU_id [pretrained_path] #The GPU_id value should be one of ['cpu','0','1','2','3']
#default model checkpoint path is DQN/results
#2.test DQN #Method 1 python test_DQN.py GPU_id PORT [pretrained_path]
#method 2 #or you can modify inference.py and execute python inference.py > inference.sh bash inference.sh
#and you can execute bash start_reboot.sh to reboot inference server when it crash because of torch.cuda.OutOfMemoryError