cnn.py 文件源码

def __init__(self, emb_dim=100, window_size=3, init_emb=None,
                 hidden_dim=100, vocab_size=0, splitter=u' ', add_dim=0,
                 PAD_IDX=None):
        """
        Neural network tagger by dos (Santos and Zadrozny, ICML 2014).
        """
        assert window_size % 2 == 1, 'window_size must be odd.'
        dim = emb_dim
        hidden_dim = hidden_dim + add_dim
        self.add_dim = add_dim
        self.hidden_dim = hidden_dim
        super(BaseCNNEncoder, self).__init__(emb=L.EmbedID(vocab_size, emb_dim, ignore_label=-1),
                                             conv=L.Convolution2D(1, hidden_dim, ksize=(window_size, dim),
                                                                  stride=(1, dim), pad=(window_size // 2, 0)))
        self.splitter = splitter
        self.char_level_flag = True if self.splitter is None else False
        self.word_level_flag = not self.char_level_flag
        self.emb_dim = emb_dim
        self.window_size = window_size
        self.dim = dim
        self.PAD_IDX = PAD_IDX
        self.train = True
        # initialize embeddings
        if init_emb is not None:
            self.emb.W = init_emb