code: def __init__(
      self,
      root,
      meta_train=False,
      meta_val=False,
      meta_test=False,
      meta_split=None,
      transform=None,
      class_augmentations=None,
      download=False,
      normalize=True,
  ):
      super(PlantsShapeClassDataset, self).__init__(
          meta_train=meta_train,
          meta_val=meta_val,
          meta_test=meta_test,
          meta_split=meta_split,
          class_augmentations=class_augmentations,
      )
  
      self.root = os.path.join(os.path.expanduser(root), self.folder)
      self.transform = transform
  
      self.split_filename = os.path.join(
          self.root, self.filename.format(self.meta_split)
      )
      self.split_filename_labels = os.path.join(
          self.root, self.filename_labels.format(self.meta_split)
      )
      self.split_filename_mean_std = os.path.join(
          self.root, self.filename_mean_std
      )
  
      self._data_file = None
      self._data = None
      self._labels = None
      self._mean_std = None
  
      if download:
          self.download(normalize)
  
      if not self._check_integrity():
          raise RuntimeError("PlantsShape integrity check failed")
      self._num_classes = len(self.labels)
  
imports: import numpy
  import os
  import json
  import h5py
  from tqdm import tqdm
  from torchmeta.utils.data import Dataset, ClassDataset, CombinationMetaDataset
  from torchmeta.datasets.utils import get_asset
label_desc: Use image node_id 1 to create a new PlantsShapeClassDataset object from inherited base classes: ClassDataset with example: obj = PlantsShapeClassDataset(root, meta_train, meta_val, meta_test, meta_split, transform, class_augmentations, download, normalize)