Saving and Loading Rl model - DQN algorithm-CodePudding

I am training a RL model using the DQN algorithm. At every iteration, I save the model as follows:

agent = dqn.DQNTrainer(env=CustomEnv,config=config)
for n in range(100):
    result = agent.train()    
    agent.save()

I want to evluate the trained RL model using on a different environment. I am not sure how to load the checkpoint and evaluate in a different environment.

I try to load the trained model (the last checkpoint) but it throws me an error. I do the following:

agent.restore('./RL_saved/checkpoint-100.tune_metadata')

It throws me an error saying

unsupported pickle protocol: 5

and when I do

agent.restore('./RL_saved/checkpoint-100.tune_metadata')

It throws me an error saying

Invalid magic number; corrupt file?

Am I loading the model in the right way? And how do I pass the environment to the loaded model?

CodePudding user response：

I found the answer to this incase it helps any.

so we first create an object of the class DQN and then load the chenkpoint without using the extension .tune_metadata

agent = dqn.DQNTrainer(env=CustomEnv,config=config)
agent.restore(''./RL_saved/checkpoint-100')