'Gets outputs of the previous forward computation.
If `merge_multi_context` is ``True``, it is like ``[out1, out2]``. Otherwise,
it returns out put of form ``[[out1_dev1, out1_dev2], [out2_dev1, out2_dev2]]``.
All the output elements have type `NDArray`. When `merge_multi_context` is ``False``,
those `NDArray` instances might live on different devices.
Parameters
merge_multi_context : bool
Defaults to ``True``. In the case when data-parallelism is used, the outputs
will be collected from multiple devices. A ``True`` value indicates 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
Examples
>>> # An example of getting forward output.
>>> print mod.get_outputs()[0].asnumpy()
[[ 0.09999977  0.10000153  0.10000716  0.10000195  0.09999853  0.09999743
0.10000272  0.10000113  0.09999088  0.09999888]]'

def get_outputs(self, merge_multi_context=True):

    raise NotImplementedError()
