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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 on_backward_end(self, **kwargs):
        "Clip the gradient before the optimizer step."
        if self.clip: nn.utils.clip_grad_norm_(self.learn.model.parameters(), self.clip)