code: def test_mixup_transform_single_label_image_batch_missing_num_classes(
      self,
  ):
      mixup_alpha = 2.0
      mixup_transform = MixupTransform(mixup_alpha, None)
      sample = {
          "input": torch.rand(4, 3, 224, 224, dtype=torch.float32),
          "target": torch.as_tensor([0, 1, 2, 2], dtype=torch.int32),
      }
      with self.assertRaises(Exception):
          mixup_transform(sample)
  
file_path: ClassyVision/test/dataset_transforms_mixup_test.py
imports: import unittest
  import torch
  from classy_vision.dataset.transforms.mixup import MixupTransform
label_desc: Use image node_id 5 for calling the DatasetTransformsMixupTest obj's underlying member method code with example usage: obj.test_mixup_transform_single_label_image_batch_missing_num_classes() without return types