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
class_docstr_tok: ["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_regressor(self):
      for dtype in self.number_data_type.keys():
          scikit_model = SVR(kernel="rbf")
          data = self.scikit_data["data"].astype(dtype)
          target = self.scikit_data["target"].astype(dtype)
          scikit_model, spec = self._sklearn_setup(
              scikit_model, dtype, data, target
          )
          test_data = data[0].reshape(1, -1)
          coreml_model = create_model(spec)
          try:
              self.assertEqual(
                  scikit_model.predict(test_data)[0],
                  coreml_model.predict({"data": test_data})["target"],
                  msg="{} != {} for Dtype: {}".format(
                      scikit_model.predict(test_data)[0],
                      coreml_model.predict({"data": test_data})[
                          "target"
                      ],
                      dtype,
                  ),
              )
          except RuntimeError:
              print("{} not supported. ".format(dtype))
  
imports: import coremltools
  from coremltools._deps import _HAS_KERAS2_TF, MSG_KERAS2_NOT_FOUND, _HAS_SKLEARN, MSG_SKLEARN_NOT_FOUND
  from coremltools.models.utils import _macos_version, _is_macos
  import unittest
  import numpy
  import pytest
  import PIL.Image
label_desc: Use image node_id 10 for calling the TestIODataTypes obj's underlying member method code with example usage: obj.test_support_vector_regressor() without return types