class_docstr: VectorEnv where each env is run sequentially.
  
  The purpose of this VectorEnv is to help debugging. For speed, you should
  use MultiprocessVectorEnv if possible.
  
  Args:
      env_fns (list of gym.Env): List of gym.Env.
code: def step(self, actions):
      results = [env.step(a) for env, a in zip(self.envs, actions)]
      self.last_obs, rews, dones, infos = zip(*results)
      return self.last_obs, rews, dones, infos
  
file_path: chainerrl/chainerrl/envs/serial_vector_env.py
imports: import numpy
  import chainerrl
label_desc: Use image node_id 2 for calling the SerialVectorEnv obj's underlying member method code with example usage: obj.step(actions) and returns: self,  rews,  dones,  infos