def test_LayerTypes(self): X = numpy.zeros((8,12)) for l in ['autoencoder', 'denoising']: ae = AE(layers=[L("Sigmoid", type=l, units=4)]) y = ae.fit_transform(X) assert_equals(type(y), numpy.ndarray) assert_equals(y.shape, (8, 4))
def test_LayerTypes(self): X = numpy.zeros((8, 12)) for l in ['autoencoder', 'denoising']: ae = AE(layers=[L("Sigmoid", type=l, units=4)]) y = ae.fit_transform(X) assert_equals(type(y), numpy.ndarray) assert_equals(y.shape, (8, 4))
def test_CostFunctions(self): X = numpy.zeros((8,12)) for t in ['msre', 'mbce']: ae = AE(layers=[L("Sigmoid", units=4, cost=t)], n_iter=1) y = ae.fit_transform(X) assert_equals(type(y), numpy.ndarray) assert_equals(y.shape, (8, 4))
def test_CostFunctions(self): X = numpy.zeros((8, 12)) for t in ['msre', 'mbce']: ae = AE(layers=[L("Sigmoid", units=4, cost=t)], n_iter=1) y = ae.fit_transform(X) assert_equals(type(y), numpy.ndarray) assert_equals(y.shape, (8, 4))