def __init__(
self,
network: Union[tf.keras.layers.Layer, tf.keras.Model],
start_n_top: int,
end_n_top: int,
dropout_rate: float,
span_labeling_activation: tf.keras.initializers.
Initializer = 'tanh',
initializer: tf.keras.initializers.Initializer = 'glorot_uniform',
**kwargs):
super().__init__(**kwargs)
self._config = {
'network': network,
'start_n_top': start_n_top,
'end_n_top': end_n_top,
'dropout_rate': dropout_rate,
'span_labeling_activation': span_labeling_activation,
'initializer': initializer,
}
self._network = network
self._initializer = initializer
self._start_n_top = start_n_top
self._end_n_top = end_n_top
self._dropout_rate = dropout_rate
self._activation = span_labeling_activation
self.span_labeling = networks.XLNetSpanLabeling(
input_width=network.get_config()['inner_size'],
start_n_top=self._start_n_top,
end_n_top=self._end_n_top,
activation=self._activation,
dropout_rate=self._dropout_rate,
initializer=self._initializer)
def __init__(
self,
network: Union[tf.keras.layers.Layer, tf.keras.Model],
start_n_top: int = 5,
end_n_top: int = 5,
dropout_rate: float = 0.1,
span_labeling_activation: tf.keras.initializers.
Initializer = 'tanh',
initializer: tf.keras.initializers.Initializer = 'glorot_uniform',
**kwargs):
super().__init__(**kwargs)
self._config = {
'network': network,
'start_n_top': start_n_top,
'end_n_top': end_n_top,
'dropout_rate': dropout_rate,
'span_labeling_activation': span_labeling_activation,
'initializer': initializer,
}
network_config = network.get_config()
try:
input_width = network_config['inner_size']
self._xlnet_base = True
except KeyError:
# BertEncoder uses 'intermediate_size' due to legacy naming.
input_width = network_config['intermediate_size']
self._xlnet_base = False
self._network = network
self._initializer = initializer
self._start_n_top = start_n_top
self._end_n_top = end_n_top
self._dropout_rate = dropout_rate
self._activation = span_labeling_activation
self.span_labeling = networks.XLNetSpanLabeling(
input_width=input_width,
start_n_top=self._start_n_top,
end_n_top=self._end_n_top,
activation=self._activation,
dropout_rate=self._dropout_rate,
initializer=self._initializer)
