model_properties.py 文件源码

def __init__(self, name='clusterer',
                 # model initialization
                 load_weights_from=None, weights_file=None, randomize_weights=False,
                 # network architecture
                 top_layers=3, learnable_layers=3, pooling='maxavg', risk_objective=True,
                 # dropout and learning rates
                 input_dropout=0, dropout=0.0, learning_rate=1e-7):
        assert pooling in ['max', 'avg', 'maxavg']

        self.name = name
        self.path = directories.CLUSTERERS + '/'
        utils.mkdir(self.path)

        self.load_weights_from = load_weights_from
        self.weights_file = weights_file
        self.randomize_weights = randomize_weights
        self.top_layers = top_layers
        self.learnable_layers = learnable_layers
        self.pooling = pooling
        self.risk_objective = risk_objective
        self.input_dropout = input_dropout
        self.dropout = dropout
        self.learning_rate = learning_rate

        self.single_size = 855 if directories.CHINESE else 674
        self.pair_size = 1733 if directories.CHINESE else 1370
        self.static_layers = top_layers - learnable_layers
        if self.static_layers == 0:
            self.anaphoricity_input_size = self.single_size
            self.pair_input_size = self.pair_size
        elif self.static_layers == 1:
            self.anaphoricity_input_size = self.pair_input_size = 1000
        else:
            self.anaphoricity_input_size = self.pair_input_size = 500