TorchCross

Easy-to-use PyTorch library for cross-domain learning, few-shot learning and meta-learning.

What is TorchCross?

TorchCross is a PyTorch library for cross-domain learning, few-shot learning and meta-learning. It provides convenient utilities for creating cross-domain learning or few-shot learning experiments.

Package Overview

• torchcross: The main package, containing the core functionality of the library.
• torchcross.data: Contains the CrossDomainDataset and FewShotDataset classes, which wrap TaskSource instances to produce batches for cross-domain learning or tasks for few-shot learning experiments.
• torchcross.data.task: Contains the Task and TaskDescription classes, which represent a task in a few-shot learning scenario and a task's metadata, respectively.
• torchcross.cd contains functions to create heads, losses and metrics for cross-domain learning experiments.

This library is still in beta. The API is potentially subject to change. Any feedback is welcome.

Installation

The library can be installed via pip:

pip install torchcross

Examples

See the examples directory.