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)