class_docstr: Component to perform the perceptual evaluation with the networks pretrained on RadImagenet (pretrained by Mei, et
  al. "RadImageNet: An Open Radiologic Deep Learning Research Dataset for Effective Transfer Learning"). This class
  uses torch Hub to download the networks from "Warvito/radimagenet-models".
  
  Args:
      net: {``"radimagenet_resnet50"``}
          Specifies the network architecture to use. Defaults to ``"radimagenet_resnet50"``.
      verbose: if false, mute messages from torch Hub load function.
code: def __init__(
      self, net: str = "radimagenet_resnet50", verbose: bool = False
  ) -> None:
      super().__init__()
      self.model = torch.hub.load(
          "Warvito/radimagenet-models", model=net, verbose=verbose
      )
      self.eval()
  
      for param in self.parameters():
          param.requires_grad = False
  
imports: from __future__ import annotations
  import warnings
  import torch
  import torch.nn
  from monai.utils import optional_import
  from monai.utils.enums import StrEnum
label_desc: Use image node_id 1 to create a new RadImageNetPerceptualSimilarity object from inherited base classes: nn with example: obj = RadImageNetPerceptualSimilarity(net, verbose)