def to_skip_connection_model(model):
"""Return skip_connected model
Args:
model: the model from which we get skip_connected model
Returns:
The skip_connected model
"""
graph = Graph(model)
weighted_layers = list(filter(lambda x: is_conv_layer(x), model.layers))
index_a = randint(0, len(weighted_layers) - 1)
index_b = randint(0, len(weighted_layers) - 1)
if index_a > index_b:
index_a, index_b = index_b, index_a
a = weighted_layers[index_a]
b = weighted_layers[index_b]
if a.input.shape == b.output.shape:
return graph.to_add_skip_model(a, b)
elif random() < 0.5:
return graph.to_add_skip_model(a, b)
else:
return graph.to_concat_skip_model(a, b)
def test_legal_graph():
graph = Graph(get_pooling_model(), False)
graph.to_add_skip_model(2, 6)
assert legal_graph(graph)
graph.to_add_skip_model(2, 6)
assert not legal_graph(graph)