v1.0.0

🎂 Exactly 1 year after the first release of Easy FSL, we have one more year of experience in Few-Shot Learning research. We capitalize on this experience to make Easy FSL easier, cleaner, smarter.

No more episodic training logic inside Few-Shot Learning methods: you can train them however you want.
And more content! 4 additional methods; several ResNet architecture as they're often used in FSL research; and 4 ready-to-use datasets.

🗞️ What's New

• Few-Shot Learning methods
  • Finetune
  • Transductive Finetuning
  • BD-CSPN
  • Transductive Information Maximization
• Pre-designed ResNet architecutres for Few-Shot Learning
• Most common few-shot classification datasets
  • _tiered_ImageNet
  • _mini_ImageNet
  • CU-Birds
  • Danish Fungi (not common but new, and really great)
  • And also an abstract class FewShotDataset to ease your developement or novel or modified datasets
• Example notebooks to perform both episodic training and classical training for your Few-Shot Learning methods
• Support Python 3.9

🔩 What's Changed

• AbstractMetaLearner is renamed FewShotClassifier. All the episodic training logic has been removed from this class and moved to the example notebook episodic_training.ipynb
• FewShotClassifier now supports non-cuda devices
• FewShotClassifier can now be initialized with a backbone on GPU
• Relation module in RelationNetworks can now be parameterized
• Same for embedding modules in Matching Networks
• Same for image preprocessing in pre-designed datasets like EasySet
• EasySet now only collects image files

Full Changelog: v0.2.2...v1.0.0