code: def create_resnet(layers):
      if layers == 34:
          return resnet34(pretrained=True), 512
      elif layers == 50:
          return resnet50(pretrained=True), 2048
      elif layers == 101:
          return resnet101(pretrained=True), 2048
      elif layers == 152:
          return resnet152(pretrained=True), 2048
      else:
          raise NotImplementedError(
              "only 34, 50, 101, 152 version of Resnet are implemented"
          )
  
imports: from torch import nn
  from torch.nn import functional
  import torch
  from torchvision import models
  from torchvision.models import resnet34, resnet101, resnet50, resnet152
  import torchvision
label_desc: Use image node_id 2 for calling a global function with example usage: create_resnet(layers) and returns: resnet34,  int, resnet50,  int, resnet101,  int, resnet152,  int