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_image_output_rgb(self):
      input_shape = (3, 10, 20)
      input_features = [
          ("data", coremltools.models.datatypes.Array(*input_shape))
      ]
      output_features = [
          ("target", coremltools.models.datatypes.Array(*input_shape))
      ]
      builder = coremltools.models.neural_network.NeuralNetworkBuilder(
          input_features, output_features
      )
      builder.add_elementwise(
          "Identity",
          input_names=["data"],
          output_name="target",
          mode="ADD",
          alpha=0.0,
      )
      spec = builder.spec
      output = spec.description.output[0]
      output.type.imageType.colorSpace = coremltools.proto.FeatureTypes_pb2.ImageFeatureType.ColorSpace.Value(
          "RGB"
      )
      output.type.imageType.height = input_shape[1]
      output.type.imageType.width = input_shape[2]
  
      coreml_model = coremltools.models.MLModel(spec)
      input_data = np.floor(np.random.rand(*input_shape) * 255)
  
      coreml_out = coreml_model.predict({"data": input_data})["target"]
      self.assertEqual(PIL.Image.Image, type(coreml_out))
      self.assertEqual("RGBA", coreml_out.mode)
      np.testing.assert_equal(
          np.uint8(input_data),
          np.array(coreml_out).transpose(2, 0, 1)[:3, :],
      )
  
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 12 for calling the TestIODataTypes obj's underlying member method code with example usage: obj.test_image_output_rgb() without return types