def test_backprop(self):
layer = Loss('binary_crossentropy', self.pre_activation)
layer.forwardprop(self.X, self.y)
got = layer.backprop(self.X, self.y)
expected = np.array([[-0.121425], [-0.129134], [0.024423],
[-0.141438]])
np.testing.assert_array_almost_equal(got, expected)
def test_backprop(self):
layer = Loss('categorical_crossentropy', self.pre_activation)
layer.forwardprop(self.X, self.Y)
got = layer.backprop(self.X, self.Y)
expected = np.array([[-0.16763847, 0.05107491, 0.11656356],
[0.01975598, -0.22650574, 0.20674977],
[0.00873619, 0.04923977, -0.05797596],
[-0.20473984, 0.07537936, 0.12936047]])
np.testing.assert_array_almost_equal(got, expected)
def test_forwardprop(self):
layer = Loss('categorical_crossentropy')
got = layer.forwardprop(self.X, self.Y)
expected = 2.370872
np.testing.assert_almost_equal(got, expected, decimal=6)
def test_forwardprop(self):
layer = Loss('binary_crossentropy', self.pre_activation)
got = layer.forwardprop(self.X, self.y)
expected = 0.582168
np.testing.assert_almost_equal(got, expected, decimal=6)
def test_forwardprop(self):
layer = Loss('mse')
got = layer.forwardprop(self.X, self.y)
expected = 41.889377
np.testing.assert_almost_equal(got, expected, decimal=6)