generator.py 文件源码

def create_trainable_model(self,sequences, pred_length, proxy_layer=None, need_noise_dropout=False, stddev=5.,sample_stddev=None):
        from keras.layers import Input, GaussianNoise
        from keras.models import Model

        from pp_layer import HawkesLayer

        if self.sequence_weights is None:
            sys.stderr.write(str({
                'error info':'unpretrained generator',
            }) + '\n')
            sys.stderr.flush()

        x = Input(batch_shape=(1,1), dtype='int32')
        hawkes_layer = HawkesLayer(sequences,pred_length,sequence_weights=self.sequence_weights,proxy_layer=proxy_layer,sample_stddev=sample_stddev)
        y = hawkes_layer(x)
        if need_noise_dropout == True:
            y = GaussianNoise(stddev)(y)

        model = Model(inputs=[x], outputs=[y], name='hawkes_output')

        self.model = model
        self.hawkes_layer = hawkes_layer
        return model