The train and validation datasets will be created using the TFDatasetMultiShotMemorySampler object. This creates a sampler that loads datasets from TensorFlow Datasets and yields batches containing a target number of classes and a target number of examples per class. Additionally, we can restrict the sampler to only yield the subset of classes defined in class_list, enabling us to train on a subset of the classes and then test how the embedding generalizes to the unseen classes. This can be useful when working on few-shot learning problems.