01b8f6eef41c36f12019adfc23ace2a100d77610,maml_rl/envs/sync_vector_env.py,SyncVectorEnv,__init__,#SyncVectorEnv#,6

Before Change

        self.observation_space = observation_space
        self.action_space = action_space

        self._dones = np.zeros((self.num_envs,), dtype=np.bool_)

    def seed(self, seeds=None):
        if seeds is None:

After Change

                                            action_space=action_space,
                                            **kwargs)
        for env in self.envs:
            if not hasattr(env.unwrapped, "reset_task"):
                raise ValueError("The environment provided is not a "
                                 "meta-learning environment. It does not have "
                                 "the method `reset_task` implemented.")

    def reset_task(self, task):
        for env in self.envs:
            env.unwrapped.reset_task(task)

Instances