code: def _test_model(self, fn, input_name, input_new, debug=False):
      onnx_model = onnx.load(fn)
      print("onnx loaded")
      from test.models.test_efficientnet import (
          chicken_img,
          car_img,
          preprocess,
          _LABELS,
      )
  
      run_onnx = get_run_onnx(onnx_model)
  
      def run(img):
          inputs = {input_name: preprocess(img, new=input_new)}
          tinygrad_out = list(run_onnx(inputs, debug=debug).values())[
              0
          ].numpy()
          return tinygrad_out.argmax()
  
      cls = run(chicken_img)
      print(cls, _LABELS[cls])
      assert _LABELS[cls] == "hen" or _LABELS[cls] == "cock"
      cls = run(car_img)
      print(cls, _LABELS[cls])
      assert "car" in _LABELS[cls] or _LABELS[cls] == "convertible"
  
file_path: tinygrad/test/models/test_onnx.py
imports: import os
  import time
  import unittest
  import numpy
  import onnx
  from extra.onnx import get_run_onnx
  from tinygrad.tensor import Tensor
  from tinygrad.helpers import CI, fetch, temp
label_desc: Use image node_id 6 for calling the TestOnnxModel obj's underlying member method code with example usage: obj._test_model(fn, input_name, input_new, debug) and returns: tinygrad_out