code: def get_outputs(self, merge_multi_context=True):
          
          assert self.binded and self.params_initialized
          return self._modules[-1].get_outputs(merge_multi_context=merge_multi_context)
docs: Gets outputs from a previous forward computation.
  
          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
              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 numpy arrays.