code: def main():
      model = models.mobilenet_v2(
          weights=models.MobileNet_V2_Weights.IMAGENET1K_V1
      )
      model.eval()
      example = torch.rand(1, 3, 224, 224)
      model = torch.jit.trace(model, example)
      compile_spec = mobilenetv2_spec()
      mlmodel = torch._C._jit_to_backend("coreml", model, compile_spec)
      print(mlmodel._c._get_method("forward").graph)
      mlmodel._save_for_lite_interpreter("../models/model_coreml.ptl")
      torch.jit.save(mlmodel, "../models/model_coreml.pt")
  
imports: import torch
  from torch.backends._coreml.preprocess import CompileSpec, CoreMLComputeUnit, TensorSpec
  from torchvision import models
label_desc: Use image node_id 2 for calling a global function with example usage: main() without return types