def test_predict_1_returns_correct_shape(self): layer = Layer(1) for i in range(functions_in_layer): classifier = NodeClassifier('extra node' + str(i)) X = np.random.randn(samples_count, feature_count) y = np.random.randint(0, high=2, size=samples_count) classifier.fit(X, y) layer.nodes.append(classifier) x_transformed = layer.predict(X) self.assertEqual(x_transformed.shape, (samples_count, functions_in_layer))
def test_predict_0_returns_same(self): layer = Layer(0, NodeClassifier('test layer')) X = np.random.randn(3, 3) X2 = layer.predict(X) self.assertEqual(X.__hash__, X2.__hash__)