code: def get_model(name):
      __dict__ = globals()
  
      if name in models.__dict__:
          fn = models.__dict__[name]
      elif name in [
          "resnet18_QAT_8b",
          "resnet18_QAT_6b",
          "resnet18_QAT_5b",
          "resnet18_QAT_4b",
      ]:
          fn = __dict__[name]
      else:
          raise RuntimeError("Unknown model name {}".format(name))
  
      return fn(num_classes=10)
  
imports: import os
  from pathlib import Path
  import brevitas.nn
  import torch
  import torch.nn
  from pact import PACTReLU
  from torchvision import datasets, models
  from torchvision.transforms import Compose, Normalize, Pad, RandomCrop, RandomHorizontalFlip, ToTensor
label_desc: Use image node_id 2 for calling a global function with example usage: get_model(name) and returns: fn