message: Agent: Reset environment and take one step
diff: import gym
  +import numpy as np
  from absl import logging
  from ..flenv import register_gym_env
  @@ -9,5 +10,12 @@ def main(_):
  register_gym_env()
  env = gym.make("FederatedLearning-v0")
  - print("action_space: {}".format(env.action_space))
  - print("observation_space: {}".format(env.observation_space))
  + logging.info("action_space: {}".format(env.action_space))
  + logging.info("observation_space: {}".format(env.observation_space))
  +
  + state = env.reset()
  + logging.info(state)
  +
  + action = np.array([0, 1, 0, 0, 0, 1, 0, 0, 0, 0])
  + state, reward, done, _ = env.step(action)
  + logging.info("s:\n{}\nr: {}\nd: {}".format(state, reward, done))
  