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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def get_input_grads(self, merge_multi_context=True):
 """Get the gradients with respect to the inputs of the module. 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 indicate that we should merge the collected results so that they look like from a single executor. Returns ------- If `merge_multi_context` is ``True``, it is like ``[grad1, grad2]``. Otherwise, it is like ``[[grad1_dev1, grad1_dev2], [grad2_dev1, grad2_dev2]]``. All the output elements are `NDArray`. """

        assert self.inputs_need_grad
        if merge_multi_context:
            return _merge_multi_context(self.input_grad_arrays, self.data_layouts)
        return self.input_grad_arrays