model.eval() with torch.no_grad(): predicted = model(test_inputs) r2_score = 1 - (torch.sum((predicted - test_labels) ** 2) / torch.sum((test_labels - torch.mean(test_labels)) ** 2)) print("R2 Score: {:.2f}".format(r2_score.item())) 在这个例子中,我们使用torch.mean计算...
model.eval() with torch.no_grad(): predicted = model(test_inputs) r2_score = 1 - (torch.sum((predicted - test_labels) ** 2) / torch.sum((test_labels - torch.mean(test_labels)) ** 2)) print("R2 Score: {:.2f}".format(r2_score.item())) 在这个例子中,我们使用torch.mean计算...