code: def se_resnet34(num_classes):
      """Constructs a ResNet-34 model.
  
      Args:
          pretrained (bool): If True, returns a model pre-trained on ImageNet
      """
      model = ResNet(
          SEBasicBlock, [3, 4, 6, 3], num_classes=num_classes
      )
      model.avgpool = nn.AdaptiveAvgPool2d(1)
      return model
  
imports: import numpy
  import torch
  from torch import nn
  from torch.autograd import Variable
  from torchvision.models import ResNet
  from pytorch2keras.converter import pytorch_to_keras
label_desc: Use image node_id 3 for calling a global function with example usage: se_resnet34(num_classes) and returns: model