def __init__(self,
scope_name,
size,
param_attr=None,
bias_attr=None,
is_reverse=False,
gate_activation='sigmoid',
candidate_activation='tanh',
h_0=None,
origin_mode=False,
init_size = None):
super(DynamicGRU, self).__init__(scope_name)
self.gru_unit = GRUUnit(
self.full_name(),
size * 3,
param_attr=param_attr,
bias_attr=bias_attr,
activation=candidate_activation,
gate_activation=gate_activation,
origin_mode=origin_mode)
self.size = size
self.h_0 = h_0
self.is_reverse = is_reverse
def __init__(self, decoder_size, num_classes):
super(GRUDecoderWithAttention, self).__init__()
self.simple_attention = SimpleAttention(decoder_size)
self.fc_1_layer = Linear(
Config.encoder_size * 2, decoder_size * 3, bias_attr=False)
self.fc_2_layer = Linear(
decoder_size, decoder_size * 3, bias_attr=False)
self.gru_unit = GRUUnit(
size=decoder_size * 3, param_attr=None, bias_attr=None)
self.out_layer = Linear(
decoder_size, num_classes + 2, bias_attr=None, act='softmax')
self.decoder_size = decoder_size
def __init__(self, scope_name, decoder_size, num_classes):
super(GRUDecoderWithAttention, self).__init__(scope_name)
self.simple_attention = SimpleAttention(self.full_name(), decoder_size)
self.fc_1_layer = FC(self.full_name(),
size=decoder_size * 3,
bias_attr=False)
self.fc_2_layer = FC(self.full_name(),
size=decoder_size * 3,
bias_attr=False)
self.gru_unit = GRUUnit(
self.full_name(),
size=decoder_size * 3,
param_attr=None,
bias_attr=None)
self.out_layer = FC(self.full_name(),
size=num_classes + 2,
bias_attr=None,
act='softmax')
self.decoder_size = decoder_size
def __init__(self, name_scope, size):
super(DynamicGRU, self).__init__(name_scope)
self.gru_unit = GRUUnit(self.full_name(), size * 3)