code: def __init__(self, size, n_classes, length, n_channels):
      self.length = length
  
      if not isinstance(size, list) and not isinstance(size, tuple):
          size = (size, size)
  
      self.imgs = torch.randn(length, n_channels, *size)
      self.labels = torch.randint(0, n_classes, (length,))
  
imports: import torch
  from torch.utils.data import Dataset
label_desc: Use image node_id 1 to create a new MockVisionDataset object from inherited base classes: Dataset with example: obj = MockVisionDataset(size, n_classes, length, n_channels)