code: def load_data(
      self,
      files: List[PATH_TYPE],
      targets: List[Any],
      clip_sampler: Union[str, "ClipSampler"] = "random",
      clip_duration: float = 2,
      clip_sampler_kwargs: Dict[str, Any] = None,
      video_sampler: Type[Sampler] = torch.utils.data.RandomSampler,
      decode_audio: bool = False,
      decoder: str = "pyav",
      target_formatter: Optional[TargetFormatter] = None,
  ) -> "LabeledVideoDataset":
      dataset = LabeledVideoDataset(
          LabeledVideoPaths(list(zip(files, targets))),
          _make_clip_sampler(
              clip_sampler, clip_duration, clip_sampler_kwargs
          ),
          video_sampler=video_sampler,
          decode_audio=decode_audio,
          decoder=decoder,
      )
      if not self.predicting:
          self.load_target_metadata(
              [
                  sample[1]
                  for sample in dataset._labeled_videos._paths_and_labels
              ],
              target_formatter=target_formatter,
          )
      return dataset
  
imports: import os
  from typing import Any, Callable, Collection, Dict, List, Optional, Type, Union
  import pandas
  import torch
  from torch.utils.data import Sampler
  from flash.core.data.io.classification_input import ClassificationInputMixin
  from flash.core.data.io.input import DataKeys, Input, IterableInput
  from flash.core.data.utilities.classification import MultiBinaryTargetFormatter, TargetFormatter, _is_list_like
  from flash.core.data.utilities.data_frame import resolve_files, resolve_targets
  from flash.core.data.utilities.loading import load_data_frame
  from flash.core.data.utilities.paths import PATH_TYPE, list_valid_files, make_dataset
  from flash.core.integrations.fiftyone.utils import FiftyOneLabelUtilities
  from flash.core.utilities.imports import _FIFTYONE_AVAILABLE, _PYTORCHVIDEO_AVAILABLE, lazy_import, requires
label_desc: Use image node_id 1 for calling the VideoClassificationInput obj's underlying member method code with example usage: obj.load_data(files, targets, clip_sampler, clip_duration, clip_sampler_kwargs, video_sampler, decode_audio, decoder, target_formatter) and returns: dataset