Avalanche
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Avalanche - v0.2.0
Avalanche - v0.2.0
  • Avalanche: an End-to-End Library for Continual Learning
  • 📌Getting Started
    • Introduction
    • Current Release
    • How to Install
    • Learn Avalanche in 5 Minutes
  • 📙From Zero to Hero Tutorial
    • Introduction
    • Models
    • Benchmarks
    • Training
    • Evaluation
    • Loggers
    • Putting All Together
    • Extending Avalanche
    • Contribute to Avalanche
  • How-Tos
    • AvalancheDataset
      • Preamble: PyTorch Datasets
      • Creating AvalancheDatasets
      • Advanced Transformations
    • Dataloaders, Buffers, and Replay
  • 📝Examples
    • Models
    • Benchmarks
    • Training
    • Evaluation
    • Loggers
  • 💻Code Documentation
    • Avalanche API
  • How to Contribute
    • Guidelines
  • ❓Questions and Issues
    • Ask Your Question
    • Add Your Issue
    • Request a Feature
    • Give Feedback
    • FAQ
  • 👪About Us
    • The People
    • Join Us!
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  1. How-Tos

AvalancheDataset

Dealing with AvalancheDatasets

PreviousContribute to AvalancheNextPreamble: PyTorch Datasets

Last updated 2 years ago

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The AvalancheDataset is an implementation of the PyTorch Dataset class that comes with many useful out-of-the-box functionalities. For most users, the AvalancheDataset can be used as a plain PyTorch Dataset that will return x, y, t elements. However, the AvalancheDataset is much more powerful than a simple PyTorch Dataset.

A serie of Mini How-Tos will guide you through the functionalities of the AvalancheDataset and its subclasses:

Brefore jumping to the actual Mini How-Tos, we recommend having a look at the basic notions of Dataset and DataLoader by reading the .

Preamble: PyTorch Datasets
Creating AvalancheDatasets
Advanced Transformations
Preamble page