def test_create_more_nodes(self):
from deephyper.search.nas.model.space import AutoKSearchSpace
from deephyper.search.nas.model.space.node import VariableNode
from deephyper.search.nas.model.space.op.op1d import Dense
struct = AutoKSearchSpace((5, ), (1, ), regression=True)
vnode1 = VariableNode()
struct.connect(struct.input_nodes[0], vnode1)
vnode1.add_op(Dense(10))
vnode2 = VariableNode()
vnode2.add_op(Dense(10))
struct.connect(vnode1, vnode2)
struct.set_ops([0, 0])
falias = 'test_auto_keras_search_spaceure'
struct.draw_graphviz(f'{falias}.dot')
model = struct.create_model()
from tensorflow.keras.utils import plot_model
plot_model(model, to_file=f'{falias}.png', show_shapes=True)
def create_search_space(
input_shape=(10, ), output_shape=(7, ), num_layers=10, *args,
**kwargs):
arch = AutoKSearchSpace(input_shape, output_shape, regression=True)
source = prev_input = arch.input_nodes[0]
# look over skip connections within a range of the 3 previous nodes
anchor_points = collections.deque([source], maxlen=3)
for _ in range(num_layers):
vnode = VariableNode()
add_dense_to_(vnode)
arch.connect(prev_input, vnode)
# * Cell output
cell_output = vnode
cmerge = ConstantNode()
cmerge.set_op(AddByProjecting(arch, [cell_output], activation='relu'))
for anchor in anchor_points:
skipco = VariableNode()
skipco.add_op(Tensor([]))
skipco.add_op(Connect(arch, anchor))
arch.connect(skipco, cmerge)
# ! for next iter
prev_input = cmerge
anchor_points.append(prev_input)
return arch
def test_create_search_space(input_shape=(2, ), output_shape=(1, ), **kwargs):
struct = AutoKSearchSpace(input_shape, output_shape, regression=True)
vnode1 = VariableNode()
for _ in range(1, 11):
vnode1.add_op(Operation(layer=tf.keras.layers.Dense(10)))
struct.connect(struct.input_nodes[0], vnode1)
struct.set_ops([0])
struct.create_model()
def create_search_space_old(
input_shape=(2, ), output_shape=(5, ), *args, **kwargs):
ss = AutoKSearchSpace(input_shape, output_shape, regression=True)
prev = ss.input_nodes[0]
for _ in range(3):
cn = ConstantNode(Dense(10, "relu"))
ss.connect(prev, cn)
prev = cn
cn = ConstantNode(Dense(5))
ss.connect(prev, cn)
return ss