# yunjey/pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

Repository: https://github.com/yunjey/pytorch-tutorial
Canonical: https://ross.abutalabs.com/products/pytorch-tutorial
Language: Python
License: MIT
License Family: permissive
Topics: deep-learning, pytorch-tutorial, neural-networks, pytorch
Last push: 2023-08-15T10:17:50+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3463, "days_push": 1114, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 32462, forks 8222 (observed 2026-08-28T04:11:57.567755+00:00)

## What it is
A collection of concise PyTorch tutorial code for deep learning researchers, covering basics through advanced models like GANs, VAEs, and image captioning. Most models are implemented in under 30 lines of code with runnable examples.

## Use cases
- learn pytorch from scratch
- understand how to implement a CNN in pytorch
- example code for training a GAN
- build a simple RNN language model
- learn variational autoencoder implementation
- pytorch tutorial for deep learning researchers
- see minimal neural network code examples

## When to choose
- you want short, readable reference implementations of classic deep learning models
- you are a researcher transitioning to PyTorch from another framework
- you prefer learning by reading minimal runnable code

## When to avoid
- you need production-ready or actively maintained model code
- you want tutorials covering the latest PyTorch APIs or transformers
- you need guided lessons with explanations rather than code

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: deep-learning, machine-learning
- domain: deep-learning, machine-learning, tutorials
- platform: python, cross-platform
- tags: pytorch, neural-networks, tutorial-code, gan, cnn, rnn, autoencoder

## Member repositories
- yunjey/pytorch-tutorial (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:11:57.567755+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:52:06.261048+00:00, confidence not recorded.
  - readme: https://github.com/yunjey/pytorch-tutorial (fetched 2026-08-28T04:11:57.567755+00:00, sha e61c09a8db03)
- Data as of 2026-08-30T08:39:29.467469+00:00.