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.

Scritto dal modello di indicizzazione a partire dal testo della issue.