class TestModelHubAPIModelReturnsOneLabelList(unittest.TestCase):
def setUp(self):
model = ModelReturnsOneLabelList()
self.this_dir = os.path.dirname(os.path.realpath(__file__))
# load config version 2 with only one output specified
contrib_src_dir = os.path.join(self.this_dir, "mockmodels", "contrib_src_mi")
self.api = ModelHubAPI(model, contrib_src_dir)
def tearDown(self):
pass
def test_predict_returns_expected_mock_prediction(self):
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_si/sample_data/testimage_ramp_4x2.png")
self.assertEqual(0.3, result["output"][0]["prediction"][0]["probability"])
self.assertEqual("class_1", result["output"][0]["prediction"][1]["label"])
self.assertEqual(0.7, result["output"][0]["prediction"][1]["probability"])
self.assertEqual("class_0", result["output"][0]["prediction"][0]["label"])
def test_predict_returns_correct_output_format(self):
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_si/sample_data/testimage_ramp_4x2.png")
self.assertIsInstance(result["output"], list)
self.assertIsInstance(result["output"][0]["prediction"], list)
self.assertIsInstance(result["output"][0]["prediction"][0], dict)
self.assertIsInstance(result["output"][0]["prediction"][1], dict)
def setUp(self):
model = Model()
self.this_dir = os.path.dirname(os.path.realpath(__file__))
contrib_src_dir = os.path.join(self.this_dir, "mockmodels", "contrib_src_si")
self.api = ModelHubAPI(model, contrib_src_dir)
self.setup_self_temp_output_dir()
self.api.output_folder = self.temp_output_dir
def setUp(self):
self.this_dir = os.path.dirname(os.path.realpath(__file__))
self.contrib_src_dir = os.path.join(self.this_dir, "mockmodels", "contrib_src_mi")
self.setup_self_temp_work_dir()
self.setup_self_temp_output_dir()
self.setup_self_test_client(ModelNeedsTwoInputs(), self.contrib_src_dir)
self.client.api = ModelHubAPI(ModelNeedsTwoInputs(), self.contrib_src_dir)
self.client.api.get_config = self.monkeyconfig()
class TestModelHubAPIModelReturnsOneNumpyArray(unittest.TestCase):
def setUp(self):
model = ModelReturnsOneNumpyArray()
self.this_dir = os.path.dirname(os.path.realpath(__file__))
contrib_src_dir = os.path.join(self.this_dir, "mockmodels", "contrib_src_si")
self.api = ModelHubAPI(model, contrib_src_dir)
def tearDown(self):
pass
def test_predict_returns_expected_mock_prediction_list(self):
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_si/sample_data/testimage_ramp_4x2.png", numpyToFile=False)
self.assertListEqual([[0,1,1,0],[0,2,2,0]], result["output"][0]["prediction"])
def test_predict_returns_correct_output_format(self):
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_si/sample_data/testimage_ramp_4x2.png", numpyToFile=False)
self.assertIsInstance(result["output"], list)
self.assertIsInstance(result["output"][0]["prediction"], list)
class TestModelHUBAPIMultiInput(unittest.TestCase):
def setUp(self):
model = ModelNeedsTwoInputs()
self.this_dir = os.path.dirname(os.path.realpath(__file__))
contrib_src_dir = os.path.join(self.this_dir, "mockmodels", "contrib_src_mi")
self.api = ModelHubAPI(model, contrib_src_dir)
def tearDown(self):
pass
def test_predict_accepts_and_processes_valid_json(self):
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_mi/sample_data/valid_input_list.json")
self.assertEqual(result["output"][0]["prediction"][0], True)
def test_predict_accepts_and_processes_valid_dict(self):
with open(self.this_dir + "/mockmodels/contrib_src_mi/sample_data/valid_input_list.json", "r") as f:
input_dict = json.load(f)
result = self.api.predict(input_dict)
self.assertEqual(result["output"][0]["prediction"][0], True)
def test_predict_rejects_invalid_file(self):
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_si/sample_data/testimage_ramp_4x2.png")
self.assertIn("error", result)
class TestModelHubAPIUtitilyFunctions(unittest.TestCase):
def setUp(self):
model = ModelReturnsOneLabelList()
self.this_dir = os.path.dirname(os.path.realpath(__file__))
# load config version 2 with only one output specified
contrib_src_dir = os.path.join(self.this_dir, "mockmodels", "contrib_src_mi")
self.api = ModelHubAPI(model, contrib_src_dir)
def tearDown(self):
pass
def test_json_write_fails_for_invalid_path(self):
result = self.api._write_json({"some":"key"}, "this/does/not/exist/johndoe.json")
self.assertIn("error", result)
import os from modelhubapi import ModelHubAPI from inference import Model model = ModelHubAPI(Model(), os.path.dirname(os.path.realpath(__file__)))
def setUp(self):
model = ModelNeedsTwoInputs()
self.this_dir = os.path.dirname(os.path.realpath(__file__))
contrib_src_dir = os.path.join(self.this_dir, "mockmodels", "contrib_src_mi")
self.api = ModelHubAPI(model, contrib_src_dir)
def setUp(self):
model = ModelReturnsListOfOneLabelList()
self.this_dir = os.path.dirname(os.path.realpath(__file__))
contrib_src_dir = os.path.join(self.this_dir, "mockmodels", "contrib_src_si")
self.api = ModelHubAPI(model, contrib_src_dir)
def setUp(self):
model = ModelReturnsOneLabelList()
self.this_dir = os.path.dirname(os.path.realpath(__file__))
# load config version 2 with only one output specified
contrib_src_dir = os.path.join(self.this_dir, "mockmodels", "contrib_src_mi")
self.api = ModelHubAPI(model, contrib_src_dir)
class TestModelHubAPI(TestAPIBase):
def setUp(self):
model = Model()
self.this_dir = os.path.dirname(os.path.realpath(__file__))
contrib_src_dir = os.path.join(self.this_dir, "mockmodels", "contrib_src_si")
self.api = ModelHubAPI(model, contrib_src_dir)
self.setup_self_temp_output_dir()
self.api.output_folder = self.temp_output_dir
def tearDown(self):
shutil.rmtree(self.temp_output_dir, ignore_errors=True)
pass
def test_get_config_returns_no_error(self):
config = self.api.get_config()
self.assertNotIn("error", config)
def test_get_config_returns_correct_dict(self):
config = self.api.get_config()
self.assert_config_contains_correct_dict(config)
def test_get_legal_returns_expected_keys(self):
legal = self.api.get_legal()
self.assert_legal_contains_expected_keys(legal)
def test_get_legal_returns_expected_mock_values(self):
legal = self.api.get_legal()
self.assert_legal_contains_expected_mock_values(legal)
def test_get_model_io_returns_expected_mock_values(self):
model_io = self.api.get_model_io()
self.assert_model_io_contains_expected_mock_values(model_io)
def test_get_samples_returns_path_to_mock_samples(self):
samples = self.api.get_samples()
self.assertEqual(self.this_dir + "/mockmodels/contrib_src_si/sample_data", samples["folder"])
samples["files"].sort()
self.assertListEqual(["testimage_ramp_4x2.jpg",
"testimage_ramp_4x2.png"],
samples["files"])
def test_predict_returns_expected_mock_prediction_list(self):
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_si/sample_data/testimage_ramp_4x2.png", numpyToFile=False)
self.assert_predict_contains_expected_mock_prediction(result, expectList=True)
def test_predict_returns_expected_mock_prediction_url(self):
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_si/sample_data/testimage_ramp_4x2.png", numpyToFile=True)
self.assert_predict_contains_expected_mock_prediction(result)
def test_predict_returns_expected_mock_meta_info(self):
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_si/sample_data/testimage_ramp_4x2.png")
self.assert_predict_contains_expected_mock_meta_info(result)
def test_predict_returns_correct_output_format(self):
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_si/sample_data/testimage_ramp_4x2.png", numpyToFile=False)
self.assertIsInstance(result["output"], list)
self.assertIsInstance(result["output"][0]["prediction"], list)
self.assertIsInstance(result["output"][0]["prediction"][0], dict)
self.assertIsInstance(result["output"][0]["prediction"][1], dict)
self.assertIsInstance(result["output"][1]["prediction"], list)
def test_predict_output_types_match_config(self):
model_io = self.api.get_model_io()
result = self.api.predict(self.this_dir + "/mockmodels/contrib_src_si/sample_data/testimage_ramp_4x2.png")
self.assertEqual(len(model_io["output"]), len(result["output"]))
for i in range(len(model_io["output"])):
self.assertEqual(model_io["output"][i]["type"], result["output"][i]["type"])