def predictor_with_train_config(train_config):
brain = Brain(train_config)
predictor = Predictor(brain, 'cartpole_simulator')
predictor._ioloop = IOLoop.current()
return predictor
def _action(action):
""" Converts Inkling action into a gym action """
return action['command']
def _log_state_and_action(state, action):
log.info("The BRAIN received the following state: {}".format(state))
log.info("The BRAIN returned the following action: {}".format(action))
if __name__ == '__main__':
# Set up predictor
config = Config(sys.argv)
brain = Brain(config)
predictor = Predictor(brain, 'cartpole_simulator')
# Set up cartpole simulator
episode_count = 10
env = gym.make('CartPole-v0')
# Reset, get state, exchange state for action, and then step the sim
observation = env.reset()
state = _state(observation)
action = _action(predictor.get_action(state))
_log_state_and_action(state, action)
observation, reward, done, info = env.step(action)
env.render()
# Loop until episode_count is reached
while episode_count:
def predictor_with_train_config(train_config):
brain = Brain(train_config)
predictor = Predictor(brain, 'cartpole_simulator')
return predictor
def predictor_with_train_config(train_config):
requests.patch("http://127.0.0.1:9000/cartpole")
brain = Brain(train_config)
predictor = Predictor(brain, 'cartpole_simulator')
return predictor
def predictor(predict_config):
brain = Brain(predict_config)
predictor = Predictor(brain, 'cartpole_simulator')
return predictor