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 number_data_type(self):
      return dict(
          int8=np.int8,
          int16=np.int16,
          int32=np.int32,
          uint8=np.uint8,
          uint16=np.uint16,
          uint32=np.uint32,
          float=np.float32,
          double=np.double,
      )
  
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 3 for calling the TestIODataTypes obj's underlying member method code with example usage: obj.number_data_type() and returns: dict