def __init__(self, config=None, n_filters=128, rnn_units=64, dropout_p=0.25, with_attention=True, **kwargs): self.n_filters = n_filters self.rnn_units = rnn_units self.dropout_p = dropout_p self.with_attention = with_attention name = 'TextConvLSTM_Attn_' + config.token_level BasicDeepModel.__init__(self, config=config, name=name, **kwargs)
def __init__(self, config=None, rnn_units=30, n_filters=64, filter_size=3, dp=7, dense_units=256, **kwargs): self.rnn_units = rnn_units self.n_filters = n_filters self.filter_size = filter_size self.dp = dp self.dense_units = dense_units name = 'TextDPCNN_' + config.token_level BasicDeepModel.__init__(self, config=config, name=name, **kwargs)
def __init__(self, config=None, rnn_units1=128, rnn_units2=128, **kwargs): self.rnn_units1 = rnn_units1 self.rnn_units2 = rnn_units2 self.sent_maxlen = config.SENT_MAXLEN self.word_maxlen = config.WORD_MAXLEN self.sent_input = Input( shape=(self.sent_maxlen, self.word_maxlen), dtype='int32', name='sentence1') # (, sent_maxlen, word_maxlen) name = 'TextHAN' BasicDeepModel.__init__(self, config=config, name=name, **kwargs)
def __init__(self, config=None, fsizes=(2, 5), n_filters=64, dropout_p=0.25, **kwargs): self.fsizes = fsizes self.n_filters = n_filters self.dropout_p = dropout_p name = 'TextBertCNN' config.bert_flag = True BasicDeepModel.__init__(self, config=config, name=name, **kwargs)
def __init__(self, config=None, n_rnns=None, rnn_units=64, dropout_p=0.5, **kwargs): if n_rnns is None: self.n_rnns = (2, 2) if config.token_level == 'both' else 2 self.rnn_units = rnn_units self.dropout_p = dropout_p name = 'TextGRU_Attn_' + config.token_level BasicDeepModel.__init__(self, config=config, name=name, **kwargs)
def __init__(self, config=None, fsizes=(2, 5), n_filters=64, rnn_units=64, dropout_p=0.25, **kwargs): self.fsizes = fsizes self.n_filters = n_filters # TODO 是否是BasicDeepModel通用?通用的话放在BasicDeepModel那里 self.rnn_units = rnn_units self.dropout_p = dropout_p name = 'TextCNN_BiGRU_' + config.token_level BasicDeepModel.__init__(self, config=config, name=name, **kwargs)
def __init__(self, config=None, rnn_units=30, dropout_p=0.2, n_capsule=10, dim_capsule=16, routings=5, share_weights=True, **kwargs): self.rnn_units = rnn_units self.dropout_p = dropout_p self.n_capsule = n_capsule self.dim_capsule = dim_capsule self.routings = routings self.share_weights = share_weights name = 'TextCapsule_' + config.token_level BasicDeepModel.__init__(self, config=config, name=name, **kwargs)
def __init__(self, config=None, rnn_units=128, dense_units=128, **kwargs): self.rnn_units = rnn_units self.dense_units = dense_units name = 'TextBertGRU' config.bert_flag = True # 唯一与BERT关联的地方 BasicDeepModel.__init__(self, config=config, name=name, **kwargs)
def __init__(self, config=None, rnn_units=64, n_filters=64, **kwargs): self.rnn_units = rnn_units self.n_filters = n_filters name = 'TextRCNN_Attn_' + config.token_level BasicDeepModel.__init__(self, config=config, name=name, **kwargs)