Exemple #1
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    def step(self, model_states: StatesModel,
             env_states: StatesEnv) -> StatesEnv:
        """
        Set the environment to the target states by applying the specified \
        actions an arbitrary number of time steps.

        The state transitions will be calculated in parallel.

        Args:
            model_states: :class:`StatesModel` representing the data to be used \
                         to act on the environment.
            env_states: :class:`StatesEnv` representing the data to be set in \
                        the environment.

        Returns:
            :class:`StatesEnv` containing the information that describes the \
            new state of the Environment.

        """
        split_env_states = [
            env.step.remote(model_states=ms, env_states=es)
            for env, ms, es in zip(
                self.envs,
                model_states.split_states(self.n_workers),
                env_states.split_states(self.n_workers),
            )
        ]
        env_states = ray.get(split_env_states)
        new_env_states: StatesEnv = StatesEnv.merge_states(env_states)
        return new_env_states
Exemple #2
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    def step(self, model_states: StatesModel,
             env_states: StatesEnv) -> StatesEnv:
        """
        Forward a batch of actions to the wrapped environments.

        Args:
          model_states: States representing the data to be used to act on the environment.
          env_states: States representing the data to be set in the environment.

        Returns:
          Batch of observations, rewards, and done flags.

        """
        split_states = self._make_transitions(model_states=model_states,
                                              env_states=env_states)
        states: StatesEnv = StatesEnv.merge_states(split_states)
        return states