class_docstr: Dummy Classification Dataset for CI/CD testing
  
  Args:
      opts: command-line arguments
code: def __init__(self, opts, *args, **kwargs) -> None:
      super().__init__()
  
      self.n_classes = 1000
      setattr(opts, "model.classification.n_classes", self.n_classes)
      setattr(
          opts,
          "dataset.collate_fn_name_train",
          "image_classification_data_collate_fn",
      )
      setattr(
          opts,
          "dataset.collate_fn_name_val",
          "image_classification_data_collate_fn",
      )
      setattr(
          opts,
          "dataset.collate_fn_name_test",
          "image_classification_data_collate_fn",
      )
  
imports: from typing import Dict, Tuple
  import torch
  import torch.utils.data
label_desc: Use image node_id 1 to create a new DummyClassificationDataset object from inherited base classes: data with example: obj = DummyClassificationDataset(opts)