lcd.py 文件源码

def linkFeature(self, input_name, conv_name, activation='tanh'):
        print('Am I called')
        filters = self.params.get('filters')
        nb_filter = self.params.get('nb_filter')
        convs = self.layers.get(conv_name)
        assert filters
        assert convs
        features = []
        for fsz, conv in zip(filters, convs):
            conv_output = conv(self.tensors[input_name])
            if type(activation) == type(''):
                act = Activation(
                    activation, name='%s-act-%d' % (input_name, fsz)
                )(conv_output)
            else:
                act = activation(
                    name='%s-advanced-act-%d' % (input_name, fsz)
                )(conv_output)
            maxpool = Lambda(
                lambda x: K.max(x[:,:,:,0], axis=2),
                output_shape=(nb_filter,),
                name='%s-maxpool-%d' % (input_name, fsz)
            )(act)
            features.append(maxpool)
        if len(features) > 1:
            return Merge(mode='concat', name='%s-feature' % input_name)(features)
        else:
            return features[0]