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)