def test_istrained_with_load(self):
old_backend = Backend()
dataset = datasets.load_iris()
old_backend.load(dataset)
old_backend.fit()
new_backend = Backend()
self.assertTrue(new_backend.istrained(read=True))
def test_predict_when_trained(self):
backend = Backend()
dataset = datasets.load_iris()
backend.load(dataset)
backend.fit()
sample = dataset["data"][:10]
predictions = backend.predict(sample)
self.assertEqual(len(predictions), 10)
def test_istrained_without_load(self):
backend = Backend()
dataset = datasets.load_iris()
self.assertFalse(backend.istrained())
backend.load(dataset)
self.assertFalse(backend.istrained())
backend.fit()
self.assertTrue(backend.istrained())
def test_fit_when_loaded(self):
backend = Backend()
dataset = datasets.load_iris()
backend.load(dataset)
self.assertTrue(backend.fit())
def test_fit_when_not_loaded(self):
backend = Backend()
with self.assertRaises(RuntimeError):
backend.fit()