a07c82b9886d1d3fd58908c6109c4d2096760824,pyannote/audio/labeling/models.py,LSTMSequenceLabeling,design_model,#LSTMSequenceLabeling#Any#,260

Before Change

        model.compile(optimizer=self.optimizer,
                      loss="categorical_crossentropy",
                      metrics=["accuracy"])

        return model

After Change

                               dropout_U=0.0)(x)

                if self.bidirectional:
                    backward = LSTM(name="backward_{i:d}".format(i=i),
                                    go_backwards=True,
                                    output_dim=output_dim,
                                    return_sequences=True,
                                    activation="tanh",
                                    dropout_W=0.0,
                                    dropout_U=0.0)(x)

        // concatenate forward and backward
        if self.bidirectional:
            // FIXME -- check value of concat_axis=1
            x = merge([forward, backward], mode="concat", concat_axis=2)
        else:
            x = forward

        // stack dense layers
        for i, output_dim in enumerate(self.dense):
            x = TimeDistributed(Dense(output_dim,
                                      activation="tanh",
                                      name="dense_{i:d}".format(i=i)))(x)

        // one dimension per class
        outputs = TimeDistributed(Dense(self.output_dim, activation="softmax"))(x)

        return Model(input=inputs, output=outputs)

Instances