This repository offers a curated collection of PyTorch code examples for deep learning researchers, focusing on concise, under-30-line implementations of common models. It serves as a practical supplement to official PyTorch documentation, enabling rapid learning and experimentation with various deep learning architectures.

How It Works

The tutorial is structured into sections covering PyTorch basics, intermediate concepts like CNNs and RNNs, and advanced topics such as GANs and VAEs. Each example demonstrates core functionalities with minimal code, promoting understanding of fundamental PyTorch operations and model building blocks.

Quick Start & Requirements

• Primary install / run command: git clone https://github.com/yunjey/pytorch-tutorial.git followed by cd pytorch-tutorial/tutorials/PATH_TO_PROJECT and python main.py.
• Prerequisites: Python 2.7 or 3.5+, PyTorch 0.4.0+.

Highlighted Details

• Covers a wide range of deep learning models from basic regression to advanced GANs and VAEs.
• Emphasizes code brevity, with most models implemented in under 30 lines.
• Includes utilities like TensorBoard integration for PyTorch.

Maintenance & Community

This repository appears to be a personal project by yunjey, with no explicit mention of active maintenance, community channels, or notable contributors in the provided README.

Licensing & Compatibility

The README does not specify a license. Compatibility for commercial use or closed-source linking is not addressed.

Limitations & Caveats

The project relies on an older version of PyTorch (0.4.0+), which may not be compatible with current PyTorch features or best practices. The lack of explicit licensing and community support could pose adoption risks.