Example #1
0
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()
Example #2
0
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
Example #3
0
    def test_create_one_vnode(self):
        from deephyper.search.nas.model.space import AutoKSearchSpace
        struct = AutoKSearchSpace((5, ), (1, ), regression=True)

        from deephyper.search.nas.model.space.node import VariableNode
        vnode = VariableNode()

        struct.connect(struct.input_nodes[0], vnode)

        from deephyper.search.nas.model.space.op.op1d import Dense
        vnode.add_op(Dense(10))

        struct.set_ops([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)
Example #4
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    def test_create_multiple_inputs(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, ), (5, )], (1, ), regression=True)

        struct.set_ops([])

        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)
Example #5
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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
Example #6
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 def test_create(self):
     from deephyper.search.nas.model.space import AutoKSearchSpace
     AutoKSearchSpace((5, ), (1, ), regression=True)