This repository provides implementations of siamese and triplet neural network architectures along with custom loss functions for contrastive learning. It includes online pair/triplet mining strategies that automatically select hard positive and negative examples within mini-batches to improve embedding quality. The code provides dataset wrappers for MNIST, batch samplers for balanced training, and a unified fit function for training these embedding networks.