Pytorch How And When To Use Module Sequential Modulelist And Moduledict: Organize PyTorch models

Understand the project

Practical overview

Use it as a code reference when learning how to refactor a PyTorch model into clearer, reusable components.

PyTorch learners who want to structure neural-network code into reusable components.
Developers comparing explicit custom modules with sequential layer blocks.

Build a CNN classifier from a custom nn.Module.
Group ordered layers into nn.Sequential blocks.
Extract a repeated convolution, batch-normalization and ReLU pattern into a reusable helper.

Before you choose

The repository is public on GitHub.

The README says the examples were updated for PyTorch 1.5.
Although the title names ModuleList and ModuleDict, the available README material chiefly demonstrates Module and Sequential.

Check current requirements in the official documentation. Source-based guidance does not mean OpenViST has run or independently tested this project.

Source-based practical guide

Organize a CNN classifier by grouping layers into Sequential blocks and reusing a convolution-block helper.

PyTorch with the torch.nn module, as used in the tutorial.
A CNN input with the dimensions expected by the example’s linear layer: 64 × 28 × 28 features after the convolutional blocks.

Subclass nn.Module and define the classifier’s constructor and forward method.
Create a helper that returns an nn.Sequential containing a convolution, batch normalization, and ReLU.
Use the helper to define convolutional blocks, and use nn.Sequential for the decoder layers.
In forward, pass the input through the blocks, flatten it, and pass it through the decoder.

A classifier organized around reusable convolutional blocks and a Sequential decoder, following the tutorial’s example.

The example is updated for PyTorch 1.5; compatibility with other versions is not established here.
The linear decoder dimensions assume the feature size shown in the example.
The available tutorial text does not document model training or evaluation.

Evidence and transparency

Source record details

Source availability: Active
Sources checked: 17 October 2026
Original website title: FrancescoSaverioZuppichini/Pytorch-how-and-when-to-use-Module-Sequential-ModuleList-and-ModuleDict · Official homepage title · retained in its source language