code: def test_tutorial():
      from coremltools.converters.mil import Builder as mb
  
      @mb.program(
          input_specs=[
              mb.TensorSpec(shape=(1, 100, 100, 3)),
          ]
      )
      def prog(x):
          x = mb.relu(x=x, name="relu")
          x = mb.transpose(x=x, perm=[0, 3, 1, 2], name="transpose")
          x = mb.reduce_mean(
              x=x, axes=[2, 3], keep_dims=False, name="reduce"
          )
          x = mb.log(x=x, name="log")
          y = mb.add(x=1, y=2)
          return x
  
      print("prog:\n", prog)
  
      # Convert and verify
      from coremltools.converters.mil.converter import _convert
      from coremltools import models
  
      proto = _convert(prog, convert_from="mil")
  
      model = models.MLModel(proto)
  
      # running predict() is only supported on macOS
      if ct.utils._is_macos():
          prediction = model.predict(
              {
                  "x": np.random.rand(1, 100, 100, 3).astype(
                      np.float32
                  ),
              }
          )
          assert len(prediction) == 1
  
imports: from os import getcwd, chdir
  from shutil import rmtree
  from os.path import exists
  from tempfile import mkdtemp
  import pytest
  import numpy
  import coremltools
  import os
  from coremltools._deps import _HAS_TF_1, _HAS_TF_2, _HAS_TORCH, MSG_TF1_NOT_FOUND, MSG_TF2_NOT_FOUND, MSG_TORCH_NOT_FOUND
label_desc: Use image node_id 1 for calling the TestMILExamples obj's underlying member method code with example usage: obj.test_tutorial() and returns: x