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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 allreduce_grads(self):
 """For each parameter, reduce the gradients from different contexts. Should be called after `autograd.backward()`, outside of `record()` scope, and before `trainer.update()`. For normal parameter updates, `step()` should be used, which internally calls `allreduce_grads()` and then `update()`. However, if you need to get the reduced gradients to perform certain transformation, such as in gradient clipping, then you may want to manually call `allreduce_grads()` and `update()` separately. """

        if not self._kv_initialized:
            self._init_kvstore()
        if self._params_to_init:
            self._init_params()
        assert not (self._kvstore and self._update_on_kvstore), \
                'allreduce_grads() when parameters are updated on kvstore ' \
                'is not supported. Try setting `update_on_kvstore` ' \
                'to False when creating trainer.'

        self._allreduce_grads()