Use a trained model

[Davinho10]

I want to use the agent which I trained in from your rl-agents instead of the stablebaseline implementation. How can I use it in a code like this:

import warnings import gym import highway_env from stable_baselines3 import DQN import json import os import cv2 import numpy as np

ACTIONS_ALL = { 0: 'LANE_LEFT', 1: 'IDLE', 2: 'LANE_RIGHT', 3: 'FASTER', 4: 'SLOWER' }

config = { "observation": { "type": "Kinematics", "features": ["presence", "x", "y", "vx", "vy"], "normalize": False } }

env = gym.make("highway-fast-v0") env.configure(config) env.reset()

model = DQN.load( "C:\Users\davin\Documents\Studium\Bachelorarbeit\davin-holten-bachelor\highway_dqn\highway_dqn\DQNFast2\rl_model_500000_steps.zip")

basic_traces_folder = "basic_traces" simb_traces_folderRL = "simb_tracesRL"

if not os.path.exists(basic_traces_folder): os.makedirs(basic_traces_folder)

if not os.path.exists(simb_traces_folderRL): os.makedirs(simb_traces_folderRL)

fileCounter = 1 Crash = False critical_distance = False critical_distanceY = False

for i in range(1,50): frames = [] steps = 0 done = truncated = False obs = env.reset() dest_state = obs.tolist() Crash = False critical_distance = False critical_distanceY = False videoCounter=i

while not (done or truncated):
    action, _states = model.predict(obs, deterministic=True)
    obs, reward, done, info = env.step(int(action))
    dest_state = obs.tolist()
    check= False
    checkY = False
    steps += 1

   # Trace Creation

[Davinho10]

I would like to generate traces to track the performance of the agents. Thats why I want to use it inside of another program.

[eleurent]

Please see e.g. this colab