def test_builder_with_validation(self): builder = KNearestNeighborsClassifierBuilder( input_name='input', output_name='output', number_of_dimensions=10, default_class_label='defaultLabel', k=3, weighting_scheme='inverse_distance', index_type='kd_tree', leaf_size=50) builder.author = 'CoreML Team' builder.license = 'MIT' builder.description = 'test_builder_with_validation' # Save the updated spec coreml_model = MLModel(builder.spec) coreml_model_path = '/tmp/__test_builder_with_validation.mlmodel' coreml_model.save(coreml_model_path) self.assertTrue(os.path.isfile(coreml_model_path)) try: stdout, stderr, return_code = self._compile_mlmodel( coreml_model_path) self.assertEqual(return_code, 0) finally: self._delete_mlmodel_and_mlmodelc(coreml_model_path)
def test_can_init_and_save_model_from_builder_with_updated_spec(self): builder = KNearestNeighborsClassifierBuilder( input_name="input", output_name="output", number_of_dimensions=10, default_class_label="defaultLabel", k=3, weighting_scheme="inverse_distance", index_type="kd_tree", leaf_size=50, ) builder.author = "CoreML Team" builder.license = "MIT" builder.description = "test_builder_with_validation" # Save the updated spec coreml_model = MLModel(builder.spec) self.assertIsNotNone(coreml_model) coreml_model_path = "/tmp/__test_builder_with_validation.mlmodel" try: coreml_model.save(coreml_model_path) self.assertTrue(os.path.isfile(coreml_model_path)) finally: self._delete_mlmodel_and_mlmodelc(coreml_model_path)