class_docstr: RestrictedImagenet Dataset [TSE+19]_
  
  A subset of ImageNet with the following labels:
  
  * Dog (classes 151-268)
  * Cat (classes 281-285)
  * Frog (classes 30-32)
  * Turtle (classes 33-37)
  * Bird (classes 80-100)
  * Monkey (classes 365-382)
  * Fish (classes 389-397)
  * Crab (classes 118-121)
  * Insect (classes 300-319)
  
  To initialize, just provide the path to the full ImageNet dataset
  (no special formatting required).
  
  .. [TSE+19] Tsipras, D., Santurkar, S., Engstrom, L., Turner, A., &
      Madry, A. (2019). Robustness May Be at Odds with Accuracy. ICLR
      2019.
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docstr_tok: []
code: def get_model(self, arch, pretrained):
      """ """
      if pretrained:
          raise ValueError("Dataset doesn't support pytorch_pretrained")
      return imagenet_models.__dict__[arch](
          num_classes=self.num_classes
      )
  
imports: import pathlib
  import torch
  import torch.utils.data
  from .None import imagenet_models, cifar_models
  from torchvision import transforms, datasets
  from .tools import constants
  from .tools import openimgs_helpers
  from .None import data_augmentation
  from .None import loaders
  from .tools.helpers import get_label_mapping
label_desc: Use image node_id 2 for calling the RestrictedImageNet obj's underlying member method code with example usage: obj.get_model(arch, pretrained) and returns: imagenet_models