Tags: sicara/easy-few-shot-learning
Tags
Release v0.2.2 => v1.0.0 * Rename AbstractMetaLearner to FewShotClassifier * Remove episodic training logic from few-shot classifiers * Make FewShotClassifier support backbones on CUDA at initialization * Add 4 new methods: Finetune, Transductive Finetuning, TIM and BD-CSPN * Add SOTA ResNets for Few-Shot Learning * Make modules parameterizable in Relation Networks and Matching Networks * Add abstract class FewShotDataset for all few-shot datasets * Make transforms parameterizable in EasySet * Add format restrictions in EasySet * Add TieredImageNet and CUB constructors using EasySet * Add Danish Fungi dataset * Add MiniImageNet * Add notebooks for episodic training and classical training * Add Python 3.9 support
Small fixes in EasySet and AbstractMetaLearner * Fix best validation accuracy update * Sort data instances for each class in EasySet * Move switch to train mode inside fit_on_task() * Add citation file * Make AbstractMetaLearner.fit() return average loss * Add EasySet.number_of_classes() * Fix python version in CI linter * Fix linter version * Bump version: 0.2.1 → 0.2.2
PreviousNext