Exemplo n.º 1
0
    def test_unmasked_constrained_viterbi_tags(self):
        # TODO: using BILUO tag scheme instead of BIO.
        #       So that, transition from tags to end can be tested.

        raw_constraints = np.array([
            #     O     B-X    I-X    B-Y    I-Y  start   end
            [     1,     1,     0,     1,     0,    0,     1],  # O
            [     1,     1,     1,     1,     0,    0,     1],  # B-X
            [     1,     1,     1,     1,     0,    0,     1],  # I-X
            [     1,     1,     0,     1,     1,    0,     1],  # B-Y
            [     1,     1,     0,     1,     1,    0,     1],  # I-Y
            [     1,     1,     0,     1,     0,    0,     0],  # start
            [     0,     0,     0,     0,     0,    0,     0],  # end
        ])

        constraints = np.argwhere(raw_constraints > 0).tolist()

        # transitions = np.array([
        #     #     O     B-X    I-X    B-Y    I-Y
        #     [    0.1,   0.2,   0.3,   0.4,   0.5],  # O
        #     [    0.8,   0.3,   0.1,   0.7,   0.9],  # B-X
        #     [   -0.3,   2.1,  -5.6,   3.4,   4.0],  # I-X
        #     [    0.2,   0.4,   0.6,  -0.3,  -0.4],  # B-Y
        #     [    1.0,   1.0,   1.0,   1.0,   1.0]   # I-Y
        # ])

        transitions = np.ones([5, 5])

        # transitions_from_start = np.array(
        #     #     O     B-X    I-X    B-Y    I-Y
        #     [    0.1,   0.2,   0.3,   0.4,   0.6]  # start
        # )

        transitions_from_start = np.ones(5)

        # transitions_to_end = np.array(
        #     [
        #     #    end
        #         -0.1,  # O
        #         -0.2,  # B-X
        #          0.3,  # I-X
        #         -0.4,  # B-Y
        #         -0.4   # I-Y
        #     ]
        # )

        transitions_to_end = np.ones(5)

        logits = np.array([
            [
            # constraint transition from start to tags
            #     O     B-X    I-X    B-Y    I-Y
                [ 0.,    .1,   1.,     0.,   0.],
                [ 0.,    0.,   1.,     0.,   0.],
                [ 0.,    0.,   1.,     0.,   0.]
            ],
            [
            # constraint transition from tags to tags
            #     O     B-X    I-X    B-Y    I-Y
                [ 0.,    1.,   0.,     0.,   0.],
                [ 0.,    0.,   .1,     1.,   0.],
                [ 0.,    0.,   1.,     0.,   0.]
            ]
        ])

        crf = CRF(
            units=5,
            use_kernel=False,  # disable kernel transform
            chain_initializer=initializers.Constant(transitions),
            use_boundary=True,
            # left_boundary_initializer=initializers.Constant(transitions_from_start),
            # right_boundary_initializer=initializers.Constant(transitions_to_end),
            transition_constraint=constraints,
            name="crf_layer"
        )
        crf.left_boundary = crf.add_weight(
            shape=(5,),
            name="left_boundary",
            initializer=initializers.Constant(self.transitions_from_start),
        )
        crf.right_boundary = crf.add_weight(
            shape=(5,),
            name="right_boundary",
            initializer=initializers.Constant(self.transitions_to_end),
        )

        crf_loss_instance = ConditionalRandomFieldLoss()

        model = Sequential()
        model.add(layers.Input(shape=(3, 5)))
        model.add(crf)
        model.compile('adam', loss={"crf_layer": crf_loss_instance})

        for layer in model.layers:
            print(layer.get_config())
            print(dict(zip(layer.weights, layer.get_weights())))

        # Get just the tags from each tuple of (tags, score).
        viterbi_tags = model.predict(logits)

        # Now the tags should respect the constraints
        expected_tags = [
            [1, 2, 2],  # B-X  I-X  I-X
            [1, 2, 2]   # B-X  I-X  I-X
        ]

        # if constrain not work it should be:
        # [
        #     [2, 4, 3],
        #     [2, 3, 0]
        # ]

        # test assert
        np.testing.assert_equal(viterbi_tags, expected_tags)
Exemplo n.º 2
0
    def test_constrained_viterbi_tags(self):
        constraints = {(0, 0), (0, 1),
                       (1, 1), (1, 2),
                       (2, 2), (2, 3),
                       (3, 3), (3, 4),
                       (4, 4), (4, 0)}

        # Add the transitions to the end tag
        # and from the start tag.
        for i in range(5):
            constraints.add((5, i))
            constraints.add((i, 6))

        mask = np.array([
                [1, 1, 1],
                [1, 1, 0]
        ])

        crf = CRF(
            units=5,
            use_kernel=False,  # disable kernel transform
            chain_initializer=initializers.Constant(self.transitions),
            use_boundary=True,
            # left_boundary_initializer=initializers.Constant(self.transitions_from_start),
            # right_boundary_initializer=initializers.Constant(self.transitions_to_end),
            transition_constraint=constraints,
            name="crf_layer"
        )
        crf.left_boundary = crf.add_weight(
            shape=(5,),
            name="left_boundary",
            initializer=initializers.Constant(self.transitions_from_start),
        )
        crf.right_boundary = crf.add_weight(
            shape=(5,),
            name="right_boundary",
            initializer=initializers.Constant(self.transitions_to_end),
        )


        crf_loss_instance = ConditionalRandomFieldLoss()

        model = Sequential()
        model.add(layers.Input(shape=(3, 5)))
        model.add(MockMasking(mask_shape=(2, 3), mask_value=mask))
        model.add(crf)
        model.compile('adam', loss={"crf_layer": crf_loss_instance})

        for layer in model.layers:
            print(layer.get_config())
            print(dict(zip(layer.weights, layer.get_weights())))

        # Get just the tags from each tuple of (tags, score).
        viterbi_tags = model.predict(self.logits)

        # Now the tags should respect the constraints
        expected_tags = [
            [2, 3, 3],
            [2, 3, 0]
        ]

        # if constrain not work it should be:
        # [
        #     [2, 4, 3],
        #     [2, 3, 0]
        # ]

        # test assert
        np.testing.assert_equal(viterbi_tags, expected_tags)