class_docstr: An instance of PyTorch VisionData the represents the COCO128 dataset.
  
  Parameters
  ----------
  root : str
      Path to the root directory of the dataset.
  name : str
      Name of the dataset.
  train : bool
      if `True` train dataset, otherwise test dataset
  transform : Callable, optional
      A function/transforms that takes in an image and a label and returns the
      transformed versions of both.
      E.g, ``transforms.Rotate``
  target_transform : Callable, optional
      A function/transform that takes in the target and transforms it.
  transforms : Callable, optional
      A function/transform that takes in an PIL image and returns a transformed version.
      E.g, transforms.RandomCrop
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docstr: Download coco128 and returns the root path and folder name.
docstr_tok: ["Download","coco128","and","returns","the","root","path","and","folder","name","."]
code: def download_coco128(
      cls, root: t.Union[str, Path]
  ) -> t.Tuple[Path, str]:
      """Download coco128 and returns the root path and folder name."""
      return download_coco128(root)
  
imports: import logging
  import typing
  import warnings
  import zipfile
  from io import BytesIO
  from pathlib import Path
  from urllib.request import urlopen
  import albumentations
  import numpy
  import torch
  from PIL import Image
  from torch.utils.data import DataLoader
  from typing_extensions import Literal
  from deepchecks.vision.datasets.assets.coco_detection.static_predictions_yolo import coco_detections_static_predictions_dict
  from deepchecks.vision.datasets.detection.coco_utils import COCO_DIR, LABEL_MAP, download_coco128, get_image_and_label
  from deepchecks.vision.utils.test_utils import get_data_loader_sequential, hash_image
  from deepchecks.vision.vision_data import BatchOutputFormat, VisionData
label_desc: Use image node_id 4 for calling the CocoDataset obj's underlying member method code with example usage: obj.download_coco128(cls, root) and returns: download_coco128