def get_outputs(self, merge_multi_context=True):
        """Gets outputs of the previous forward computation.

        If ``merge_multi_context`` is ``True``, it is like ``[out1, out2]``. Otherwise, it
        is like ``[[out1_dev1, out1_dev2], [out2_dev1, out2_dev2]]``. All the output
        elements are `NDArray`. When `merge_multi_context` is `False`, those `NDArray`
        might live on different devices.

        Parameters
        ----------
        merge_multi_context : bool
            Default is ``True``. In the case when data-parallelism is used, the outputs
            will be collected from multiple devices. A ``True`` value indicate that we
            should merge the collected results so that they look like from a single
            executor.

        Returns
        -------
        list of NDArray or list of list of NDArray
            Output.
        """
        assert self.binded and self.params_initialized
        return self._exec_group.get_outputs(merge_multi_context=merge_multi_context)
Gets outputs of the previous forward computation.

        If ``merge_multi_context`` is ``True``, it is like ``[out1, out2]``. Otherwise, it
        is like ``[[out1_dev1, out1_dev2], [out2_dev1, out2_dev2]]``. All the output
        elements are `NDArray`. When `merge_multi_context` is `False`, those `NDArray`
        might live on different devices.

        Parameters
        ----------
        merge_multi_context : bool
            Default is ``True``. In the case when data-parallelism is used, the outputs
            will be collected from multiple devices. A ``True`` value indicate that we
            should merge the collected results so that they look like from a single
            executor.

        Returns
        -------
        list of NDArray or list of list of NDArray
            Output.