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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 evaluate(self, data_loader):
 """ Sets model in eval mode, disables gradients, preallocates memory and runs validation on data provided by data_loader. :param data_loader: data loader """

        torch.set_grad_enabled(False)
        self.model.eval()
        torch.cuda.empty_cache()
        self.preallocate(data_loader, training=False)
        output = self.feed_data(data_loader, training=False)
        self.model.zero_grad()
        torch.cuda.empty_cache()
        return output