class_docstr: ## Dataset
  
  This loads the training dataset and resize it to the give image size.
class_docstr_tok: ["#","#","Dataset","This","loads","the","training","dataset","and","resize","it","to","the","give","image","size","."]
docstr: Number of images
docstr_tok: ["Number","of","images"]
code: def __len__(self):
      """Number of images"""
      return len(self.paths)
  
imports: import math
  from pathlib import Path
  from typing import Iterator, Tuple
  import torch
  import torch.utils.data
  import torchvision
  from PIL import Image
  from labml import tracker, lab, monit, experiment
  from labml.configs import BaseConfigs
  from labml_helpers.device import DeviceConfigs
  from labml_helpers.train_valid import ModeState, hook_model_outputs
  from labml_nn.gan.stylegan import Discriminator, Generator, MappingNetwork, GradientPenalty, PathLengthPenalty
  from labml_nn.gan.wasserstein import DiscriminatorLoss, GeneratorLoss
  from labml_nn.utils import cycle_dataloader
label_desc: Use image node_id 2 for calling the Dataset obj's underlying member method code with example usage: obj.__len__() and returns: len