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 test_support_vector_classifier(self):
      for dtype in self.number_data_type.keys():
          scikit_model = SVC(kernel="rbf", gamma=1.2, C=1)
          data = self.scikit_data["data"].astype(dtype)
          target = (
              self.scikit_data["target"].astype(dtype)
              > self.scikit_data["target"].astype(dtype).mean()
          )
          scikit_model, spec = self._sklearn_setup(
              scikit_model, dtype, data, target
          )
          coreml_model = create_model(spec)
          for idx in range(0, 10):
              test_data = data[idx].reshape(1, -1)
              try:
                  self.assertEqual(
                      scikit_model.predict(test_data)[0],
                      bool(
                          int(
                              coreml_model.predict({"data": test_data})[
                                  "target"
                              ]
                          )
                      ),
                      msg="{} != {} for Dtype: {}".format(
                          scikit_model.predict(test_data)[0],
                          bool(
                              int(
                                  coreml_model.predict(
                                      {"data": test_data}
                                  )["target"]
                              )
                          ),
                          dtype,
                      ),
                  )
              except RuntimeError:
                  print("{} not supported. ".format(dtype))
  
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 9 for calling the TestIODataTypes obj's underlying member method code with example usage: obj.test_support_vector_classifier() without return types