code: def resnet32(pretrained=False, **kwargs):
      if pretrained:
          raise NotImplementedError
      # change n=3 for ResNet-20, and n=9 for ResNet-56
      n = 5
      model = ResNet(BasicBlock, [n, n, n], **kwargs)
      return model
  
file_path: avalanche/avalanche/models/resnet32.py
imports: import torch.nn
label_desc: Use image node_id 2 for calling a global function with example usage: resnet32(pretrained) and returns: model