Pytorch中的Relu对梯度的影响 | 小王同学

https://a171232886.github.io/2021/12/29/pytorch%E4%B8%AD%E7%9A%84Relu%E5%AF%B9%E6%A2%AF%E5%BA%A6%E7%9A%84%E5%BD%B1%E5%93%8D/

Relu层
卷积层和全连接层这种有可训练参数的，可以求梯度。Relu层怎么办？
先说结论：Relu(x)，若x<=0，x的梯度为0，若x>0，梯度为x。

The issue links to a blog post about how ReLU affects gradients in PyTorch. To address this, first read the linked post to understand the context. Then, check the repository's structure to see if there's a section for tutorials or explanations about neural network layers. The task likely involves adding or clarifying content about ReLU's gradient behavior within the site's documentation or blog posts.

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