Avalanche
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Avalanche - v0.6.0
Avalanche - v0.6.0
  • 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
      • avalanche-datasets
      • avalanche-transformations
    • Dataloaders, Buffers, and Replay
    • Save and load checkpoints
  • 📝Examples
    • Models
    • Benchmarks
    • Training
    • Evaluation
    • Loggers
  • 💻Code Documentation
    • Avalanche API
  • How to Contribute
    • Guidelines
  • ❓Questions and Issues
    • Ask Your Question
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    • FAQ
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  1. Examples

Evaluation

Protocols and Metrics Code Examples

PreviousTrainingNextLoggers

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Avalanche offers significant support for defining your own eveluation protocol (classic or custom metrics, when and on what to test). You can find examples related to the benchmarks here:

  • : this is a simple example on how to use the Evaluation Plugin (the evaluation controller object)

  • : how to use metrics as standalone objects.

  • : this example shows how to produce confusion matrix during training and evaluation.

  • : this is a simple example on how to use the Dataset inspection plugins.

  • : example usage of the mean_score helper to show the scores of the true class, averaged by new and old classes.

  • : this is a simple example on how to use the Evaluation Plugin with metrics returning values for different tasks.

📝
Eval Plugin
Standalone Metrics
Confusion Matrix
Dataset Inspection
Mean Score
Task Metrics