class_docstr: This class tests for different I/O feature data types for an .mlmodel
  It will cover the following areas to test for:
  - All features must have a valid type
  - Multiarrays must have a valid dataType. Inputs must specify shape. Shape must have >= 0 elements
  - Images must have a valid colorspace. width & height have to be >= 0
  - Dictionaries must have a valid key type
code: def _sklearn_setup(self, model, dtype, data, target):
      model.fit(data, target)
      spec = coremltools.converters.sklearn.convert(
          model, "data", "target"
      ).get_spec()
      return model, spec
  
imports: import unittest
  import numpy
  import PIL.Image
  import coremltools
  from coremltools._deps import _HAS_SKLEARN, MSG_SKLEARN_NOT_FOUND
  from coremltools.models.utils import _is_macos, _macos_version
label_desc: Use image node_id 4 for calling the TestIODataTypes obj's underlying member method code with example usage: obj._sklearn_setup(model, dtype, data, target) and returns: model,  spec