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)
