How to use setup_class method in yandex-tank

Best Python code snippet using yandex-tank

test_kernels.py

Source:test_kernels.py

...14from gptorch.util import TensorType15data_dir = os.path.join(os.path.dirname(__file__), "data", "kernels")16class Kern(object):17    @classmethod18    def setup_class(cls, kernel_type):19        cls.kernel_type = kernel_type20        cls.x1 = TensorType(np.load(os.path.join(data_dir, "x1.npy")))21        cls.x2 = TensorType(np.load(os.path.join(data_dir, "x2.npy")))22        cls.n1, cls.d1 = cls.x1.data.numpy().shape23        cls.n2, cls.d2 = cls.x2.data.numpy().shape24        cls.kern = cls.kernel_type(cls.d1)25        cls.kern_str = cls.kern.__class__.__name__26        cls.kx_expected = np.load(os.path.join(data_dir, "{}_kx.npy".format(27            cls.kern_str)))28        cls.kx2_expected = np.load(os.path.join(data_dir, "{}_kx2.npy".format(29            cls.kern_str)))30        cls.kdiag_expected = np.load(os.path.join(data_dir, 31            "{}_kdiag.npy".format(cls.kern_str)))32    def test_add(self):33        """34        Test kernel addition operator35        """36        k1 = self.kern + self.kern37        k2 = kernels.Sum(self.kern, self.kern)38        k1x = k1.K(self.x1)39        k2x = k2.K(self.x1)40        assert all([x1 == x2 for x1, x2 in zip(k1x.flatten(), k2x.flatten())])41    def test_mul(self):42        """43        Test kernel product operator44        """45        k1 = self.kern * self.kern46        k2 = kernels.Product(self.kern, self.kern)47        k1x = k1.K(self.x1)48        k2x = k2.K(self.x1)49        assert all([x1 == x2 for x1, x2 in zip(k1x.flatten(), k2x.flatten())])50    def test_K(self):51        """52        Inputs are expected to be torch.autograd.Variables of 53        torch.DoubleTensors54        Output is expected to be a torch.autograd.Variable55        """56        kx_actual = self.kern.K(self.x1).data.numpy()57        kx2_actual = self.kern.K(self.x1, self.x2).data.numpy()58        kx2t_actual = self.kern.K(self.x2, self.x1).data.numpy()59        assert np.allclose(self.kx_expected, kx_actual)60        assert np.allclose(self.kx2_expected, kx2_actual)61        # Test symmetric K()62        assert np.allclose(kx_actual.T, kx_actual)63        # Test transpose of cross-kernel:64        assert np.allclose(self.kx2_expected, kx2t_actual.T)65    def test_Kdiag(self):66        kdiag_actual = self.kern.Kdiag(self.x1).data.numpy()67        assert np.allclose(self.kdiag_expected, kdiag_actual)68class Stationary(Kern):69    @classmethod70    def setup_class(cls, kernel_type):71        super(Stationary, cls).setup_class(kernel_type)72        x_shift = 0.3473        cls.x1_shift = cls.x1 + x_shift74        cls.x2_shift = cls.x1 + x_shift75    def test_K(self):76        super().test_K()77        kx_shift_actual = self.kern.K(self.x1_shift).data.numpy()78        assert np.allclose(self.kx_expected, kx_shift_actual)79    def test_Kdiag(self):80        super().test_Kdiag()81        kxdiag_shift_actual = self.kern.Kdiag(self.x1_shift).data.numpy()82        assert np.allclose(self.kdiag_expected, kxdiag_shift_actual)83class ARD(Stationary):84    @classmethod85    def setup_class(cls, kernel_type):86        super(ARD, cls).setup_class(kernel_type)87        cls.ard_length_scales = np.load(os.path.join(data_dir, 88            "ard_length_scales.npy"))89        cls.kern_ard = cls.kernel_type(cls.d1, ARD=True, 90            length_scales=cls.ard_length_scales)91        cls.kx_ard_expected = np.load(os.path.join(data_dir, 92            "{}_kx_ard.npy".format(cls.kern_str)))93        cls.kx2_ard_expected = np.load(os.path.join(data_dir, 94            "{}_kx2_ard.npy".format(cls.kern_str)))95        cls.kdiag_ard_expected = np.load(os.path.join(data_dir,96            "{}_kdiag_ard.npy".format(cls.kern_str)))97    def test_K(self):98        super().test_K()99        kx_ard_actual = self.kern_ard.K(self.x1).data.numpy()100        kx2_ard_actual = self.kern_ard.K(self.x1, self.x2).data.numpy()101        assert np.allclose(self.kx_ard_expected, kx_ard_actual)102        assert np.allclose(self.kx2_ard_expected, kx2_ard_actual)103    def test_Kdiag(self):104        super().test_Kdiag()105        kdiag_ard_actual = self.kern_ard.Kdiag(self.x1).data.numpy()106        assert np.allclose(self.kdiag_ard_expected, kdiag_ard_actual)107class TestWhite(Kern):108    @classmethod109    def setup_class(cls):110        super(TestWhite, cls).setup_class(kernels.White)    111class TestConstant(Kern):112    @classmethod113    def setup_class(cls):114        super(TestConstant, cls).setup_class(kernels.Constant) 115class TestBias(Kern):116    @classmethod117    def setup_class(cls):118        super(TestBias, cls).setup_class(kernels.Bias)119class TestExp(ARD):120    @classmethod121    def setup_class(cls):122        super(TestExp, cls).setup_class(kernels.Exp)123class TestMatern12(ARD):124    @classmethod125    def setup_class(cls):126        super(TestMatern12, cls).setup_class(kernels.Matern12)127class TestMatern32(ARD):128    @classmethod129    def setup_class(cls):130        super().setup_class(kernels.Matern32)131class TestMatern52(ARD):132    @classmethod133    def setup_class(cls):134        super().setup_class(kernels.Matern52)135class TestRbf(ARD):136    @classmethod137    def setup_class(cls):138        super().setup_class(kernels.Rbf)139class TestPeriodic(ARD):140    @classmethod141    def setup_class(cls):142        super().setup_class(kernels.Periodic)143class TestLinear(Kern):144    @classmethod145    def setup_class(cls):...

test_inventory.py

Source:test_inventory.py

...20        with pytest.raises(ValueError):21            object = MobileInventory({'iPhone Model X': -45, 'Xiaomi Model Y': 200, 'Nokia Model Z': 25})22class TestInventoryAddStock():23    @pytest.fixture(scope='module')24    def setup_class(self):25        self.inventory = MobileInventory({'iPhone Model X':100, 'Xiaomi Model Y': 1000, 'Nokia Model Z':25})26        return self.inventory27    def test_add_new_stock_as_dict(self, setup_class):28        setup_class.add_stock({'iPhone Model X':50, 'Xiaomi Model Y': 2000, 'Nokia Model A':10})29        assert setup_class.balance_inventory == {'iPhone Model X':150, 'Xiaomi Model Y': 3000, 'Nokia Model Z':25, 'Nokia Model A':10}30    def test_add_new_stock_as_list(self, setup_class):31        with pytest.raises(TypeError):32            setup_class.add_stock(['iPhone Model X', 'Xiaomi Model Y', 'Nokia Model Z'])33    def test_add_new_stock_with_numeric_keys(self, setup_class):34        with pytest.raises(ValueError):35            setup_class.add_stock({1:'iPhone Model A', 2:'Xiaomi Model B', 3:'Nokia Model C'})36    def test_add_new_stock_with_nonnumeric_values(self, setup_class):37        with pytest.raises(ValueError):38            setup_class.add_stock({'iPhone Model A':'50', 'Xiaomi Model B':'2000', 'Nokia Model C':'25'})39    def test_add_new_stock_with_float_values(self, setup_class):40        with pytest.raises(ValueError):41            setup_class.add_stock({'iPhone Model A':50.5, 'Xiaomi Model B':2000.3, 'Nokia Model C':25})42class TestInventorySellStock():43    @pytest.fixture(scope='module')44    def setup_class(self):45        self.inventory = MobileInventory({'iPhone Model A':50, 'Xiaomi Model B': 2000, 'Nokia Model C':10, 'Sony Model D':1})46        return self.inventory47    def test_sell_stock_as_dict(self, setup_class):48        setup_class.sell_stock({'iPhone Model A':2, 'Xiaomi Model B':20, 'Sony Model D':1})49        assert setup_class.balance_inventory == {'iPhone Model A':48, 'Xiaomi Model B': 1980, 'Nokia Model C':10, 'Sony Model D':0}50    def test_sell_stock_as_list(self, setup_class):51        with pytest.raises(TypeError):52            setup_class.sell_stock(['iPhone Model A', 'Xiaomi Model B', 'Nokia Model C'])53    def test_sell_stock_with_numeric_keys(self, setup_class):54        with pytest.raises(ValueError):55            setup_class.sell_stock({1:'iPhone Model A', 2:'Xiaomi Model B', 3:'Nokia Model C'})56    def test_sell_stock_with_nonnumeric_values(self, setup_class):57        with pytest.raises(ValueError):58            setup_class.sell_stock({'iPhone Model A':'2', 'Xiaomi Model B':'3', 'Nokia Model C':'4'})...

test_setup_flow_example.py

Source:test_setup_flow_example.py

1def setup_module(module):2    module.TestStateFullThing.classcount = 03class TestStateFullThing(object):4    def setup_class(cls):5        cls.classcount += 16    def teardown_class(cls):7        cls.classcount -= 18    def setup_method(self, method):9        self.id = eval(method.__name__[5:])10    def test_42(self):11        assert self.classcount == 112        assert self.id == 4213    def test_23(self):14        assert self.classcount == 115        assert self.id == 2316def teardown_module(module):17    assert module.TestStateFullThing.classcount == 018""" For this example the control flow happens as follows::19    import test_setup_flow_example20    setup_module(test_setup_flow_example)21       setup_class(TestStateFullThing)22           instance = TestStateFullThing()23           setup_method(instance, instance.test_42)24              instance.test_42()25           setup_method(instance, instance.test_23)26              instance.test_23()27       teardown_class(TestStateFullThing)28    teardown_module(test_setup_flow_example)29Note that ``setup_class(TestStateFullThing)`` is called and not30``TestStateFullThing.setup_class()`` which would require you31to insert ``setup_class = classmethod(setup_class)`` to make32your setup function callable....

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