Pytorch中的Conv1d和Conv3d | 小王同学

https://a171232886.github.io/2021/11/22/Pytorch%E4%B8%AD%E7%9A%84Conv1d%E5%92%8CConv3d/

Conv1d
torch.nn.Conv1d(in_channels, out_channels, kernel_size, stride=1, padding=0, dilation=1, groups=1, bias=True, padding_mode='zeros')
和Conv2d处理[N,C,H,W]相比，只是处理处理的数据为[N,C,L]，其余相同。

The issue links to a blog post about PyTorch's Conv1d and Conv3d layers. The task is to incorporate this content into the repository's documentation. First, locate the existing documentation structure in the repo (likely under a 'docs' or 'source/_posts' directory for Hexo). Review the linked post's content, then create or update a markdown file that explains Conv1d and Conv3d, comparing them to Conv2d. Ensure the formatting matches the site's style. Done when the new content is added and ready for a pull request.

Vom Indexierungsmodell aus dem Issue-Text verfasst.