假设你正在训练一个网络，参数为 [4.5, 2.5, 1.2, 0.6]，学习率为 0.2，梯度为 [-1, 9, 2, 5]。更新一个梯度下降步长后，网络的参数等于多少？ Suppose that you are training a network with parameters [4.5, 2.5, 1.2, 0.6], a learning rate of 0.2, and a gradient of [-1, 9, 2, 5]. After one update step of gradient descent, what would your network's parameters be equal to?单项选择题

A

[4.7, 0.7, 0.8, -0.4]

B

[4.6, 1.6, 1, 0.1]

C

[1.8, 7.1, 6.2, 2.4]

D

[4.4, 8.9, 7.2, 1.2]

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