def __init__(self,
config_file,
spm_file,
max_seq_length=128,
init_checkpoint=None,
output_dir=None,
gpu_ids=None,
reuse_seq_length=None,
perm_size=None,
mask_alpha=6,
mask_beta=1,
do_lower_case=True,
truncate_method='LIFO'):
raise Exception('We are faced with some problems in XLNetLM. '
'It will soon be fixed in the future.')
super(LMModule, self).__init__(init_checkpoint, output_dir, gpu_ids)
self.batch_size = 64
self.max_seq_length = max_seq_length
self.reuse_seq_length = \
reuse_seq_length if reuse_seq_length else max_seq_length // 2
self.perm_size = \
perm_size if perm_size else max_seq_length // 2
self.truncate_method = truncate_method
self._mems = None
self._mask_alpha = mask_alpha
self._mask_beta = mask_beta
self._num_predict = None
self._id_to_label = None
self.__init_args__ = locals()
self.xlnet_config = get_xlnet_config(config_file)
self.tokenizer = get_sentence_piece_tokenizer(spm_file, do_lower_case)
self._key_to_depths = get_key_to_depths(self.xlnet_config.n_layer)
def __init__(self,
config_file,
spm_file,
max_seq_length=128,
label_size=None,
label_weight=None,
init_checkpoint=None,
output_dir=None,
gpu_ids=None,
do_lower_case=True,
truncate_method='LIFO'):
super(ClassifierModule, self).__init__(init_checkpoint, output_dir,
gpu_ids)
self.batch_size = 0
self.max_seq_length = max_seq_length
self.label_size = label_size
self.label_weight = label_weight
self.truncate_method = truncate_method
self._id_to_label = None
self.__init_args__ = locals()
self.xlnet_config = get_xlnet_config(config_file)
self.tokenizer = get_sentence_piece_tokenizer(spm_file, do_lower_case)
self._key_to_depths = get_key_to_depths(self.xlnet_config.n_layer)