Machine Learning de ponta a ponta
Joshua Stapleton
Machine Learning Engineer
unittest
import unittest class TestModelInference(unittest.TestCase): def setUp(self): self.model = fitted_model self.X_test = X_test def test_prediction_output_shape(self): y_pred = self.model.predict(self.X_test) self.assertEqual(y_pred.shape[0], self.X_test.shape[0]) if __name__ == '__main__': unittest.main()
import unittest
class TestModelInference(unittest.TestCase):
def setUp(self): self.model = fitted_model self.X_test = X_test
def test_prediction_output_shape(self): y_pred = self.model.predict(self.X_test) self.assertEqual(y_pred.shape[0], self.X_test.shape[0])
if __name__ == '__main__': unittest.main()
def test_input_values(self): print("Running test_input_values test case") # Get inputs (each row in testing set) for input in X_test: for value in input: # if value is cholestrol, for example: self.assertIn(value, [0, 500])
Introdução a Testes em Python
Boas práticas
Benefícios do TDD
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