Python check_valid_datatype Examples

Example #1

File: testAbstractDatatype.py Project: welkinland/keras-pandas

 def test_no_output_support(self):
     datatype = AbstractDatatype()
     self.assertTrue(check_valid_datatype(datatype))
     self.assertEqual(2, len(datatype.input_nub_generator('test', 'test')))
     self.assertRaises(ValueError, datatype.output_nub_generator, 'test',
                       'test')
     self.assertRaises(ValueError, datatype.output_suggested_loss)
     self.assertRaises(ValueError, datatype._check_output_support)

Example #2

File: testAbstractDatatype.py Project: welkinland/keras-pandas

 def test_output_support(self):
     datatype = AbstractDatatype()
     datatype.supports_output = True
     self.assertTrue(check_valid_datatype(datatype))
     self.assertEqual(2, len(datatype.input_nub_generator('test', 'test')))
     self.assertEqual(None, datatype.output_nub_generator('test', 'test'))
     self.assertEqual(None, datatype.output_suggested_loss())
     self.assertTrue(datatype._check_output_support())

Example #3

File: testCategorical.py Project: jordanosborn/tf2-keras-pandas

 def test_datatype_signature(self):
     datatype = Categorical()
     lib.check_valid_datatype(datatype)
     self.assertTrue(datatype.supports_output)

Example #4

    def test_datatype_signature(self):
        # Create datatype
        datatype = Boolean()

        # Check valid datatype
        lib.check_valid_datatype(datatype)

Example #5

File: testTimeSeries.py Project: welkinland/keras-pandas

    def test_datatype_signature(self):
        # Create datatype
        datatype = TimeSeries()

        # Check valid datatype
        lib.check_valid_datatype(datatype)