nn.BatchNorm2d requires_grad
时间: 2024-04-05 08:13:21 浏览: 34
nn.BatchNorm2d的requires_grad属性决定了在训练过程中是否对该层的参数进行梯度更新。如果requires_grad为True,则该层的参数将参与梯度计算和反向传播,并进行参数更新。如果requires_grad为False,则该层的参数将被固定,不参与梯度计算和参数更新。
引用中提到了nn.BatchNorm2D是PaddlePaddle库中实现二维批量归一化操作的类,但对于requires_grad属性的具体说明并未提及。
引用中展示了如何在模型只在一块GPU上跑时通过改变param的requires_grad属性来控制参数更新。
引用中给出了torch.nn.BatchNorm2d类的构造函数,但对requires_grad属性的具体说明也没有提及。
因此,根据提供的引用内容,无法确定nn.BatchNorm2d的requires_grad属性的具体取值。<span class="em">1</span><span class="em">2</span><span class="em">3</span>
#### 引用[.reference_title]
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