code: def __init__(
      self,
      dataset,
      labels,
      multi_class,
      num_classes=None,
      label_indices=None,
      add_to_input=True,
  ):
      super().__init__(dataset)
  
      self.label_indices = label_indices
      self.labels = labels
      self.multi_class = multi_class
      self.add_to_input = add_to_input
      if num_classes is None and multi_class:
          assert self.label_indices is not None
          num_classes = len(self.label_indices)
  
      self.num_classes = num_classes
  
imports: import torch
  from fairseq.data import BaseWrapperDataset, data_utils
label_desc: Use image node_id 1 to create a new AddClassTargetDataset object from inherited base classes: BaseWrapperDataset with example: obj = AddClassTargetDataset(dataset, labels, multi_class, num_classes, label_indices, add_to_input)