class_docstr: CINIC-10 dataset [DCA+18]_.
  
  A dataset with the same classes as CIFAR-10, but with downscaled images
  from various matching ImageNet classes added in to increase the size of
  the dataset.
  
  .. [DCA+18] Darlow L.N., Crowley E.J., Antoniou A., and A.J. Storkey
      (2018) CINIC-10 is not ImageNet or CIFAR-10. Report
      EDI-INF-ANC-1802 (arXiv:1810.03505)
class_docstr_tok: ["CINIC-10","dataset","[","DCA+18","]","_",".","A","dataset","with","the","same","classes","as","CIFAR-10",",","but","with","downscaled","images","from","various","matching","ImageNet","classes","added","in","to","increase","the","size","of","the","dataset",".","..","[","DCA+18","]","Darlow","L.N.",",","Crowley","E.J.",",","Antoniou","A.",",","and","A.J",".","Storkey","(","2018",")","CINIC-10","is","not","ImageNet","or","CIFAR-10",".","Report","EDI-INF-ANC-1802","(","arXiv:1810.03505",")"]
docstr_tok: []
code: def get_model(self, arch, pretrained):
      """ """
      if pretrained:
          raise ValueError(
              "CINIC does not support pytorch_pretrained=True"
          )
      return cifar_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 CINIC obj's underlying member method code with example usage: obj.get_model(arch, pretrained) and returns: cifar_models