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 reset(self, mask=None):
      if mask is None:
          mask = np.zeros(self.num_envs)
      obs = [
          env.reset() if not m else o
          for m, env, o in zip(mask, self.envs, self.last_obs)
      ]
      self.last_obs = obs
      return obs
  
file_path: chainerrl/chainerrl/envs/serial_vector_env.py
imports: import numpy
  import chainerrl
label_desc: Use image node_id 3 for calling the SerialVectorEnv obj's underlying member method code with example usage: obj.reset(mask) and returns: obs