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 seed(self, seeds):
      for env, seed in zip(self.envs, seeds):
          env.seed(seed)
  
file_path: chainerrl/chainerrl/envs/serial_vector_env.py
imports: import numpy
  import chainerrl
label_desc: Use image node_id 4 for calling the SerialVectorEnv obj's underlying member method code with example usage: obj.seed(seeds) without return types