class_docstr: Test dataset for validating registry functions
class_docstr_tok: ["Test","dataset","for","validating","registry","functions"]
code: def __init__(
      self,
      split,
      batchsize_per_replica,
      shuffle,
      transform,
      num_samples,
      clips_per_video,
      samples,
  ):
      self.samples = samples
      input_tensors = [sample["input"] for sample in samples]
      target_tensors = [sample["target"] for sample in samples]
      dataset = ListDataset(
          input_tensors, target_tensors, loader=lambda x: x
      )
      super(TestVideoDataset, self).__init__(
          dataset,
          split,
          batchsize_per_replica,
          shuffle,
          transform,
          num_samples,
          clips_per_video,
      )
  
imports: import unittest
  import torch
  from classy_vision.dataset import build_dataset, register_dataset
  from classy_vision.dataset.classy_video_dataset import ClassyVideoDataset, MaxLengthClipSampler
  from classy_vision.dataset.core import ListDataset
  from classy_vision.dataset.transforms.util_video import build_video_field_transform_default
  from torch.utils.data import Sampler
label_desc: Use image node_id 1 to create a new TestVideoDataset object from inherited base classes: ClassyVideoDataset with example: obj = TestVideoDataset(split, batchsize_per_replica, shuffle, transform, num_samples, clips_per_video, samples)