lcd.py 文件源码

def doubleFeature(self, pos, neg, conv_name, activation='tanh'):
        name = '%s+%s' % (pos, neg)
        filters = self.params['filters']
        nb_filter = self.params['nb_filter']
        convs = self.layers[conv_name]
        features = []
        pos = self.tensors[pos]
        neg = self.tensors[neg]
        for fsz, conv in zip(filters, convs):
            sum = Merge(
                mode='sum',
            )([conv(pos), conv(neg)])
            if type(activation) == type(''):
                act = Activation(
                    activation, name='%s-act-%d' % ('+'.join(input_names), fsz)
                )(sum)
            else:
                act = activation(
                    name='%s-advanced-act-%d' % (name, fsz)
                )(sum)
            maxpool = Lambda(
                lambda x: K.max(x, axis=1),
                output_shape=(nb_filter,),
                name='%s-maxpool-%d' % (name, fsz)
            )(act)
            print('maxpool', maxpool._keras_shape)
            features.append(maxpool)
        if len(features) > 1:
            return Merge(
                mode='concat', 
                name='%s-feature' % name,
            )(features)
        else:
            return features[0]