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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 step(self, loss, optimizer, scheduler, update=True):
 """ Performs one step of the optimizer. :param loss: value of loss function :param optimizer: optimizer :param update: if True executes weight update """

        loss.backward()
        if update:
            if self.grad_clip != float('inf'):
                clip_grad_norm_(self.model.parameters(), self.grad_clip)
            scheduler.step()
            optimizer.step()
            self.model.zero_grad()