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使用 nn.Sequential 快速构建模型

无需自定义类即可串联各层

使用 nn.Sequential 快速构建模型 是 CoddyKit 上的免费 Deep Learning Academy 课时。这是第 3 节课，共 4 节。你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。这是 Deep Learning Academy 学习路径的一部分，你的进度在网页和 CoddyKit 应用中同步。 Deep Learning Academy 课程共包含 4 节课。

本课时的部分内容尚未翻译，以英文显示。

A Shortcut for Simple Nets

When data flows straight through layers in order, nn.Sequential lets you skip writing a full custom class.

List Your Layers in Order

You pass the layers as arguments, and Sequential runs them one after another. The order you list them is the order they execute.

model = nn.Sequential(
    nn.Linear(4, 16),
    nn.ReLU(),
    nn.Linear(16, 3))

Activations Go Inside Too

Activations are modules as well, so drop nn.ReLU() right between your linear layers in the list.

Call It Like Any Model

A Sequential model is still an nn.Module, so you run it with model(x) exactly like a custom class.

output = model(input_tensor)

No forward to Write

Sequential supplies the forward pass for you, feeding the output of each layer into the next automatically.

Perfect for Linear Pipelines

It shines when there are no branches or skips, just a clean chain from input to output.

Add Names With OrderedDict

Pass an OrderedDict to give each layer a readable name, which makes printing the model much clearer.

from collections import OrderedDict
nn.Sequential(OrderedDict(fc1=nn.Linear(4,8)))

Index Into the Layers

You can reach any layer by position, since Sequential acts like a list. This helps you inspect or tweak one part.

first_layer = model[0]

When to Switch Back

Need an if-branch, a skip connection, or reused layers? Then go back to a custom nn.Module instead.

Nest for Structure

You can even put a Sequential inside another to group related layers into a tidy block.

Readable at a Glance

For straightforward models, Sequential is shorter and easier to scan. Less code means fewer bugs. ✨

Quick Check

Think about the kind of model that fits nn.Sequential best.

Recap

Use nn.Sequential to chain layers in order without writing forward. Reach for a custom class only when you need branches or skips. 🎯

常见问题解答

「使用 nn.Sequential 快速构建模型」课时是免费的吗？

是的 — 「使用 nn.Sequential 快速构建模型」的完整文本可在网页上免费阅读。要进行交互式练习（内置代码编辑器和全天候 AI 导师）并解锁 Deep Learning Academy 课程的其余内容，请升级到 CoddyKit PRO。 Deep Learning Academy 课程共包含 4 节课。

「使用 nn.Sequential 快速构建模型」这节课中我会学到什么？

无需自定义类即可串联各层你通过在浏览器中直接运行的动手代码来练习 Deep Learning Academy，全天候 AI 导师会在你学习这节课的过程中回答你的问题。

学习 Deep Learning Academy 需要有经验吗？

无需任何先前经验。CoddyKit 上的 Deep Learning Academy 课程适合初学者到高级学习者，你可以从这里开始或从头开始，按照自己的节奏学习。这是第 3 节课，共 4 节。

「使用 nn.Sequential 快速构建模型」课时需要多长时间？

大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动，所以你能稳步进步，并在网页和应用中从离开的地方继续。

我能在这节 Deep Learning Academy 课中编写并运行代码吗？

能。每节 Deep Learning Academy 课都包含内置代码编辑器，你可以在浏览器中直接编写并运行真实代码，并获得即时 AI 反馈 — 无需本地设置。

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