How to use test_activation method in Slash

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test_af.py

Source:test_af.py

...21    def test_init(self):22        function = self._getTargetClass()()23        assert function(-1) == 024        assert function(0) == 125    def test_activation(self):26        function = self._getTargetClass()(1, 5)27        assert function(0) == 028        assert function(1) == 529    def test_activationVector(self):30        from numpy import array31        function = self._getTargetClass()()32        result = function(array([-1, 0, 1])) == array([0, 1, 1])33        assert result.all()34    def test_derivative(self):35        function = self._getTargetClass()()36        assert function.derivative(2) == 137    def test_derivativeVector(self):38        from numpy import array39        function = self._getTargetClass()()40        result = function.derivative(array([1, 2, 3, 4])) == array([1, 1, 1, 1])41        assert result.all()42class Test_Linear(unittest.TestCase):43    def _getTargetClass(self):44        from peach.nn.af import Linear45        return Linear46    def test_alias(self):47        from peach.nn.af import Identity48        assert Identity == self._getTargetClass()49    def test_activation(self):50        from numpy import array51        function = self._getTargetClass()()52        result = function(3) == array([3.])53        assert result.all()54    def test_activationVector(self):55        from numpy import array56        function = self._getTargetClass()()57        result = function(array([-1, 0, 1])) == array([-1, 0, 1])58        assert result.all()59    def test_derivative(self):60        function = self._getTargetClass()()61        assert function.derivative(5) == 162    def test_derivativeVector(self):63        from numpy import array64        function = self._getTargetClass()()65        result = function.derivative(array([1, 2, 3, 4])) == array([1, 1, 1, 1])66        assert result.all()67class Test_Ramp(unittest.TestCase):68    def _getTargetClass(self):69        from peach.nn.af import Ramp70        return Ramp71    def test_activation(self):72        function = self._getTargetClass()((-1, -1), (1, 1))73        assert function(-2) == -174        assert function(0.5) == 0.575        assert function(2) == 176    def test_activationVector(self):77        from numpy import array78        function = self._getTargetClass()((-1, -1), (1, 1))79        result = function(array([-2, 0, 2])) == array([-1, 0, 1])80        assert result.all()81    def test_derivative(self):82        function = self._getTargetClass()()83        assert function.derivative(-1) == 084        assert function.derivative(0.1) == 185        assert function.derivative(1) == 086    def test_derivativeVector(self):87        from numpy import array88        function = self._getTargetClass()()89        result = function.derivative(array([-1, 0.1, 1])) == array([0, 1, 0])90        assert result.all()91class Test_Sigmoid(unittest.TestCase):92    def _getTargetClass(self):93        from peach.nn.af import Sigmoid94        return Sigmoid95    def test_alias(self):96        from peach.nn.af import Logistic97        assert Logistic == self._getTargetClass()98    def test_activation(self):99        function = self._getTargetClass()()100        assert function(0) == 0.5101        self.assertAlmostEquals(function(-1), 0.268941421)102        self.assertAlmostEquals(function(1), 0.731058578)103    def test_activationVector(self):104        from numpy import array105        function = self._getTargetClass()()106        result = function(array([0, 0])) == array([0.5, 0.5])107        assert result.all()108    def test_derivative(self):109        function = self._getTargetClass()()110        assert function.derivative(0) == 0.25111        self.assertAlmostEquals(function.derivative(-1), 0.196611933)112        self.assertAlmostEquals(function.derivative(1), 0.196611933)113    def test_derivativeVector(self):114        from numpy import array115        function = self._getTargetClass()()116        result = function.derivative(array([0, 0])) == array([0.25, 0.25])117        assert result.all()118class Test_Signum(unittest.TestCase):119    def _getTargetClass(self):120        from peach.nn.af import Signum121        return Signum122    def test_activation(self):123        function = self._getTargetClass()()124        assert function(0) == 0125        assert function(-2) == -1126        assert function(2) == 1127    def test_activationVector(self):128        from numpy import array129        function = self._getTargetClass()()130        result = function(array([-2, -1, 0, 1, 2])) == array([-1, -1, 0, 1, 1])131        assert result.all()132    def test_derivative(self):133        function = self._getTargetClass()()134        assert function.derivative(2) == 1135    def test_derivativeVector(self):136        from numpy import array137        function = self._getTargetClass()()138        result = function.derivative(array([1, 2, 3, 4])) == array([1, 1, 1, 1])139        assert result.all()140class Test_ArcTan(unittest.TestCase):141    def _getTargetClass(self):142        from peach.nn.af import ArcTan143        return ArcTan144    def test_activation(self):145        function = self._getTargetClass()()146        assert function(-1) == -0.25147        assert function(0) == 0148        assert function(1) == 0.25149    def test_activationVector(self):150        from numpy import array151        function = self._getTargetClass()()152        result = function(array([-1, 0, 1])) == array([-0.25, 0, 0.25])153        assert result.all()154    def test_derivative(self):155        function = self._getTargetClass()()156        self.assertAlmostEquals(function.derivative(-1), 0.15915494309189)157        self.assertAlmostEquals(function.derivative(0), 0.31830988618379)158        self.assertAlmostEquals(function.derivative(1), 0.15915494309189)159    def test_derivativeVector(self):160        from numpy import array161        function = self._getTargetClass()()162        result = function.derivative(array([-1, 0, 1]))163        self.assertAlmostEquals(result[0], 0.15915494309189)164        self.assertAlmostEquals(result[1], 0.31830988618379)165        self.assertAlmostEquals(result[2], 0.15915494309189)166class Test_TanH(unittest.TestCase):167    def _getTargetClass(self):168        from peach.nn.af import TanH169        return TanH170    def test_activation(self):171        function = self._getTargetClass()()172        assert function(0) == 0173        self.assertAlmostEquals(function(1), 0.7615941559)174        self.assertAlmostEquals(function(-1), -0.7615941559)175    def test_activationVector(self):176        from numpy import array177        function = self._getTargetClass()()178        result = function(array([0, 0])) == array([0, 0])179        assert result.all()180    def test_derivative(self):181        function = self._getTargetClass()()182        assert function.derivative(0) == 1183        self.assertAlmostEquals(function.derivative(1), 0.41997434161)184        self.assertAlmostEquals(function.derivative(-1), 0.41997434161)...

test.py

Source:test.py

1from unittest import TestCase2from hamcrest import assert_that, equal_to3from pytest_reference_formatter.formatter import handling_references4class TestFormatter(TestCase):5    def test_single_reference_can_be_formatted(self):6        """ when user input has one parameter """7        single_reference_input = \8            ['paessler.license.tests.admin_testcases.test_activation.DeactivateSystemIDScenario.'9             'test_deactivating_systemid_creates_sales_comment']10        single_reference_input_with_django_sites_and_py = \11            ['django-sites.paessler.license.tests.admin_testcases.test_activation.py.DeactivateSystemIDScenario.'12             'test_deactivating_systemid_creates_sales_comment']13        single_reference_expected_output = \14            ['django-sites/paessler/license/tests/admin_testcases/test_activation.py::'15             'DeactivateSystemIDScenario::test_deactivating_systemid_creates_sales_comment']16        assert_that(handling_references(single_reference_input),17                    equal_to(single_reference_expected_output), 'identifier')18        assert_that(handling_references(single_reference_input_with_django_sites_and_py),19                    equal_to(single_reference_expected_output), 'identifier')20    def test_multiple_reference_can_be_formatted(self):21        """ when user input has more than one parameter """22        multiple_reference_input = \23            ['paessler.license.tests.admin_testcases.test_activation.DeactivateSystemIDScenario.'24             'test_deactivating_systemid_creates_sales_comment',25             'django-sites.paessler.license.tests.admin_testcases.test_activation.'26             'ChangeExpirationOfSystemIDGrantScenario.'27             'test_changing_expiration_for_systemid_creates_sales_comment']28        multiple_reference_expected_output = \29            ['django-sites/paessler/license/tests/admin_testcases/test_activation.py::'30             'DeactivateSystemIDScenario::'31             'test_deactivating_systemid_creates_sales_comment',32             'django-sites/paessler/license/tests/admin_testcases/test_activation.py::'33             'ChangeExpirationOfSystemIDGrantScenario::'34             'test_changing_expiration_for_systemid_creates_sales_comment']...

activations.py

Source:activations.py

1import numpy as np2class sigmoid():3    """4    An object that allows for easy access to all activation functions needed for5    sigmoid activation.6    Methods:7        forward : gives the result of a sigmoid avtivation8        derviative : gives the result for backpropagation with sigmoid activation9    """10    def forward(self, inputs):11        return 1 / (1 + np.exp(-inputs))12    13    def derivative(self, inputs):14        return np.exp(-inputs) / np.square(1 + np.exp(-inputs))15if __name__ == "__main__":16    """17    If this file is being run individually test the implementation of neural net classes.18    """19    test_inputs = np.array([[2], [1]])20    test_activation = sigmoid()21    print("Sigmoid Foward Results:", test_activation.forward(test_inputs))22    print("Sigmoid Backwards Results:", test_activation.derivative(test_inputs))...

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