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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def _verify_same_spaces(self):
 """Verifies that all the envs have the same observation and action space."""


    # Pre-conditions: self._envs is initialized.

    if self._envs is None:
      raise ValueError("Environments not initialized.")

    if not isinstance(self._envs, list):
      tf.logging.warning("Not checking observation and action space "
                         "compatibility across envs, since there is just one.")
      return

    # NOTE: We compare string representations of observation_space and
    # action_space because compositional classes like space.Tuple don't return
    # true on object comparison.

    if not all(
        str(env.observation_space) == str(self.observation_space)
        for env in self._envs):
      err_str = ("All environments should have the same observation space, but "
                 "don't.")
      tf.logging.error(err_str)
      # Log all observation spaces.
      for i, env in enumerate(self._envs):
        tf.logging.error("Env[%d] has observation space [%s]", i,
                         env.observation_space)
      raise ValueError(err_str)

    if not all(
        str(env.action_space) == str(self.action_space) for env in self._envs):
      err_str = "All environments should have the same action space, but don't."
      tf.logging.error(err_str)
      # Log all action spaces.
      for i, env in enumerate(self._envs):
        tf.logging.error("Env[%d] has action space [%s]", i, env.action_space)
      raise ValueError(err_str)