def test_long_transform(): graph = DefaultClassifierGenerator(10, (32, 32, 3)).generate() history = [('to_wider_model', 1, 256), ('to_conv_deeper_model', 1, 3), ('to_concat_skip_model', 6, 11)] for args in history: getattr(graph, args[0])(*list(args[1:])) graph.produce_model() assert legal_graph(graph)
def test_long_transform(): graph = CnnGenerator(10, (32, 32, 3)).generate() history = [('to_wider_model', 1, 256), ('to_conv_deeper_model', 1, 3), ('to_concat_skip_model', 5, 9)] for args in history: getattr(graph, args[0])(*list(args[1:])) graph.produce_model() assert legal_graph(graph)
def test_wider_dense(): graph = CnnGenerator(10, (32, 32, 3)).generate() graph.produce_model().set_weight_to_graph() history = [('to_wider_model', 14, 64)] for args in history: getattr(graph, args[0])(*list(args[1:])) graph.produce_model() assert legal_graph(graph)
def test_wider_dense(): graph = CnnGenerator(10, (32, 32, 3)).generate() graph.produce_model().set_weight_to_graph() history = [('to_wider_model', 14, 64)] for args in history: getattr(graph, args[0])(*list(args[1:])) graph.produce_model() assert legal_graph(graph)