def run_weights():
env = gym.make('Mario-Kart-Luigi-Raceway-v0')
resolution = (120, 160)
actions = [
[-60, 0, 1, 0, 0], # left
[60, 0, 1, 0, 0], # right
[0, -80, 0, 1, 0], # back
[0, 0, 1, 0, 0]
] # go straight
# [ 0, 0, 0, 1, 0]] # brake
# Load Model and Weights
model = DQNModel(resolution=resolution,
nb_frames=test_param['nb_frames'],
actions=actions)
model.load_weights(model_weights)
agent = RLAgent(model, **test_param)
agent.test(env)
# Initiates the env
env = gym.make('Mario-Kart-Luigi-Raceway-v0')
resolution = (120, 160)
actions = [
[-60, 0, 1, 0, 0], # left
[60, 0, 1, 0, 0], # right
[0, -80, 0, 1, 0], # back
[0, 0, 1, 0, 0]
] # go straight
# [ 0, 0, 0, 1, 0]] # brake
# Initiates Model
model = DQNModel(resolution=resolution,
nb_frames=learn_param['nb_frames'],
actions=actions)
# print("number of actions: ", len(doom.actions)) # 16
if model_weights:
model.load_weights(model_weights)
else:
print("Please provide a model_weights file")
agent = RLAgent(model, **learn_param)
# give a step number randomly to catch a random screen shot
agent.visualize(env)
