class_docstr: Video dataset for EpicKitchen-55 Dataset
  <https://epic-kitchens.github.io/2019/>
  
  This dataset handles the loading, decoding, and configurable clip
  sampling for the videos.
class_docstr_tok: ["Video","dataset","for","EpicKitchen-55","Dataset","<","https",":","\/\/epic-kitchens.github.io\/2019\/",">","This","dataset","handles","the","loading",",","decoding",",","and","configurable","clip","sampling","for","the","videos","."]
docstr: Samples a video clip associated to the given index.
  
  Args:
      index (int): index for the video clip.
  
  Returns:
      A video clip with the following format if transform is None:
          {{
              'video_id': <str>,
              'video': <video_tensor>,
              'audio': <audio_tensor>,
              'actions': <df[ActionData]>,
              'start_time': <float>,
              'stop_time': <float>
          }}
      Otherwise, the transform defines the clip output.
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code: def __getitem__(self, index) -> Dict[str, Any]:
      """
      Samples a video clip associated to the given index.
  
      Args:
          index (int): index for the video clip.
  
      Returns:
          A video clip with the following format if transform is None:
              {{
                  'video_id': <str>,
                  'video': <video_tensor>,
                  'audio': <audio_tensor>,
                  'actions': <df[ActionData]>,
                  'start_time': <float>,
                  'stop_time': <float>
              }}
          Otherwise, the transform defines the clip output.
      """
      clip = self._clips[index]
      video = self._videos[clip.video_id]
  
      if isinstance(video, FrameVideo):
          clip_dict = video.get_clip(
              clip.start_time, clip.stop_time, self._frame_filter
          )
      else:
          clip_dict = video.get_clip(clip.start_time, clip.stop_time)
  
      clip_data = {
          "video_id": clip.video_id,
          **clip_dict,
          "actions": self._actions[clip.video_id],
          "start_time": clip.start_time,
          "stop_time": clip.stop_time,
      }
  
      if self._transform:
          clip_data = self._transform(clip_data)
  
      return clip_data
  
file_path: pytorchvideo/pytorchvideo/data/epic_kitchen/epic_kitchen_dataset.py
imports: import ast
  from dataclasses import dataclass, fields
  from typing import Any, Callable, Dict, List, Optional
  import torch
  from pytorchvideo.data.dataset_manifest_utils import EncodedVideoInfo, get_seconds_from_hms_time, VideoClipInfo, VideoDataset, VideoDatasetType, VideoFrameInfo, VideoInfo
  from pytorchvideo.data.frame_video import FrameVideo
  from pytorchvideo.data.utils import DataclassFieldCaster, load_dataclass_dict_from_csv
  from pytorchvideo.data.video import Video
label_desc: Use image node_id 2 for calling the EpicKitchenDataset obj's underlying member method code with example usage: obj.__getitem__(index) and returns: clip_data