class_docstr: Suppress the transformations of a dataset.
  
  This will act on the transformation fields.
  
  Note: there are no ways to suppress hard coded transformations
  or transformations held in fields with custom names.
class_docstr_tok: ["Suppress","the","transformations","of","a","dataset",".","This","will","act","on","the","transformation","fields",".","Note",":","there","are","no","ways","to","suppress","hard","coded","transformations","or","transformations","held","in","fields","with","custom","names","."]
code: def __init__(self, dataset):
      self.dataset = dataset
      self._held_out_transforms = dict()
  
imports: from dataclasses import dataclass
  from pathlib import Path
  from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Optional, Union
  from collections import OrderedDict
  import warnings
  import numpy
  import torch
  from torch.utils.data.sampler import Sampler
  from avalanche.benchmarks.scenarios.generic_scenario import CLScenario
  from avalanche.benchmarks.utils.data import AvalancheDataset
  from avalanche.benchmarks.utils.dataset_traversal_utils import flat_datasets_from_benchmark, single_flat_dataset
  from avalanche.benchmarks.utils.utils import concat_datasets
label_desc: Use image node_id 1 to create a new _SuppressTransformations object  with example: obj = _SuppressTransformations(dataset)