def test_disable_domain(capsys, logging_config):
log = Logger()
log.set_enabled('spam', False)
assert log._enabled_keys['spam'] == False
log.spam('eggs')
out, err = capsys.readouterr()
assert out == ''
assert err == ''
class TicTacToeSim(Simulator):
def __init__(self, brain, iteration_limit=0):
super(TicTacToeSim, self).__init__(brain, 'TicTacToeSimulator')
self._env = TicTacToeGame()
def episode_finish(self):
log.info("Episode {} reward: {}".format(self.episode_count,
self.episode_reward))
def episode_start(self, config):
observation = self._env.reset()
return {'image': observation}
def simulate(self, action):
observation, reward, done = self._env.advance(action)
return {'image': observation}, reward, done
if __name__ == "__main__":
config = Config(sys.argv)
brain = Brain(config)
sim = TicTacToeSim(brain)
# If predicting print the board
if sim.predict:
log.set_enabled('game')
while sim.run():
continue
import sys
import gym
from bonsai_ai import Brain, Config, Predictor
from bonsai_ai.logger import Logger
log = Logger()
log.set_enabled("info")
def _state(observation):
""" Converts gym observation into Inkling state dictionary """
state = {
'position': observation[0],
'velocity': observation[1],
'angle': observation[2],
'rotation': observation[3]
}
return state
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__':
