Greetings to the PyTorch community! Here is a quick update on PyTorch docs.
In November 2023, we successfully conducted a PyTorch Docathon, a community event where PyTorch community members gathered together to improve PyTorch documentation and tutorials. This event saw a global participation of contributors who dedicated their time and effort to enhance our docs. We extend our sincere gratitude to everyone involved.
A key accomplishment of the Docathon was the comprehensive work carried out on docstrings. Our community contributors meticulously reviewed and improved the docstrings based on the provided tasks.
In addition to that, we’ve added three new tutorials that showcase real-world applications of PyTorch. We are particularly proud that two of these tutorials were contributed by PyTorch ecosystem partners.
Here is the new tutorials for you to explore:
- Whole Slide Image Classification Using PyTorch and TIAToolbox —This tutorial demonstrates how to classify Whole Slide Images (WSIs) using PyTorch deep learning models with TIAToolbox, which are images of human tissue samples used by pathologists and researchers to study diseases like cancer at the microscopic level.
- Semi-Supervised Learning using USB built upon PyTorch – This tutorial introduces USB, a flexible and modular semi-supervised learning framework based on PyTorch, demonstrating its ease of use in training a FreeMatch/SoftMatch model on CIFAR-10 using pre-trained ViT and its adaptability to various algorithms and imbalanced datasets.
- Deploying a PyTorch Stable Diffusion model as a Vertex AI Endpoint – This tutorial provides a step-by-step guide on how to streamline the deployment of a PyTorch Stable Diffusion model (v1.5) using Vertex AI, a fully-managed machine learning platform, by creating a custom TorchServe handler, uploading model artifacts to Google Cloud Storage, creating a Vertex AI model with the model artifacts and a prebuilt PyTorch container image, and finally deploying the model onto an endpoint.
We’re planning more community events this year, so stay tuned!
The PyTorch Team