def test_train_labels_no_labels(self): layer_sizes = [5, 20, 10] d = DBN(layer_sizes, 2) data = [[1, 1, 1, 1, 1], [1, 1, 1, 1, 1]] labels = [] with self.assertRaises(ValueError): d.train_labels(data, labels, 1, 1)
def test_get_topology_constructs(self): layer_sizes = [144, 50, 50, 2000] number_labels = 1 d = DBN(layer_sizes, number_labels) layer_sizes.append(number_labels) self.assertListEqual(d.get_topology(), layer_sizes)
def test_rbms_list_setup_correct(self): layer_sizes = [144, 50, 50, 2000] d = DBN(layer_sizes, 1) self.assertEquals(len(d._rbms), d.number_layers)
def test_number_inputs_setup_correct(self): layer_sizes = [144, 50, 50, 2000] d = DBN(layer_sizes, 1) self.assertEquals(d.number_inputs, 144)
def test_empty_config_constructor(self): layer_sizes = [] with self.assertRaises(IndexError): d = DBN(layer_sizes, 1)
def test_classify_wrong_shape(self): layer_sizes = [5, 20, 10] d = DBN(layer_sizes, 2) data = [[1, 1, 1, 1]] with self.assertRaises(ValueError): probs = d.classify(data)
def test_dbn_constructor(self): layer_sizes = [10, 20] d = DBN(layer_sizes, 1)
def test_pre_train_negative_batch(self): layer_sizes = [5, 20, 10] d = DBN(layer_sizes, 10) data = [[1, 1, 1, 1, 1], [1, 1, 1, 1, 1]] with self.assertRaises(ValueError): d.pre_train(data, 1, -1)
def test_classify(self): layer_sizes = [5, 20, 10] d = DBN(layer_sizes, 2) data = [[1, 1, 1, 1, 1]] probs = d.classify(data)
def test_train_labels(self): layer_sizes = [5, 20, 10] d = DBN(layer_sizes, 2) data = [[1, 1, 1, 1, 1], [1, 1, 1, 1, 1]] labels = [[1, 0], [0, 1]] d.train_labels(data, labels, 1, 1)
def test_pre_train_wrong_data_size(self): layer_sizes = [5, 20] d = DBN(layer_sizes, 10) data = [[1, 1, 1, 1, 1, 1, 1]] with self.assertRaises(ValueError): d.pre_train(data, 1, 1)
def test_pre_train_correct_data_size(self): layer_sizes = [5, 20, 10] d = DBN(layer_sizes, 10) data = [[1, 1, 1, 1, 1], [1, 1, 1, 1, 1]] d.pre_train(data, 1, 1)
def test_one_layer_constructor(self): layer_sizes = [10] d = DBN(layer_sizes, 1)
def test_negative_dimension_constructor(self): layer_sizes = [-10, 500] with self.assertRaises(ValueError): d = DBN(layer_sizes, 1)