class_docstr: A simple adapter
  converting NiftyNet sampler's output into PyTorch Dataset properties
code: def __getitem__(self, index):
      data = self.sampler(idx=index)
  
      # Transpose to PyTorch format
      image = np.transpose(data["image"], (0, 5, 1, 2, 3, 4))
      label = np.transpose(data["label"], (0, 5, 1, 2, 3, 4))
  
      image = torch.from_numpy(image).float()
      label = torch.from_numpy(label).float()
  
      return image, label
  
imports: import numpy
  import torch
  from torch.utils.data import Dataset
label_desc: Use image node_id 2 for calling the DatasetNiftySampler obj's underlying member method code with example usage: obj.__getitem__(index) and returns: image,  label