code: def test_create_single_input_column(self):
      sf_session_id = [
          max(self.data[self.session_id]),
          min(self.data[self.session_id]),
      ]
      input_data = tc.SFrame(
          {
              self.features[0]: [3.14, -3.14],
              self.target: ["foo", "bar"],
              self.session_id: sf_session_id,
          }
      )
      model = tc.activity_classifier.create(
          input_data,
          features=["X1-r"],
          target=self.target,
          session_id=self.session_id,
          prediction_window=self.prediction_window,
      )
      filename = tempfile.NamedTemporaryFile(suffix=".mlmodel").name
      model.export_coreml(filename)
  
      # Load the model back from the CoreML model file
      import coremltools
  
      coreml_model = coremltools.models.MLModel(filename)
      self.check_prediction_match(model, coreml_model)
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import unittest
  import turicreate
  import random
  import tempfile
  import math
  import numpy
  from numbers import Number
  from .None import util
  import pytest
  from turicreate.toolkits._internal_utils import _mac_ver
  from turicreate.toolkits._main import ToolkitError
  import uuid
label_desc: Use image node_id 5 for calling the ActivityClassifierTest obj's underlying member method code with example usage: obj.test_create_single_input_column() without return types