code: def test_mixup_transform_single_label_multi_modal_batch(self):
      mixup_alpha = 2.0
      num_classes = 3
      mixup_transform = MixupTransform(mixup_alpha, num_classes)
      sample = {
          "input": {
              "video": torch.rand(
                  4, 3, 4, 224, 224, dtype=torch.float32
              ),
              "audio": torch.rand(4, 1, 40, 100, dtype=torch.float32),
          },
          "target": torch.as_tensor([0, 1, 2, 2], dtype=torch.int32),
      }
      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 7 for calling the DatasetTransformsMixupTest obj's underlying member method code with example usage: obj.test_mixup_transform_single_label_multi_modal_batch() without return types