


from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available, is_torch_available


snake_case_  :	str							  =							{'''configuration_bert_generation''': ['''BertGenerationConfig''']}

try:
							if not is_sentencepiece_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							snake_case_  :	Tuple							  =							['''BertGenerationTokenizer''']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							snake_case_  :	Tuple							  =							[
							    '''BertGenerationDecoder''',
							    '''BertGenerationEncoder''',
							    '''BertGenerationPreTrainedModel''',
							    '''load_tf_weights_in_bert_generation''',
							]


if TYPE_CHECKING:
							from .configuration_bert_generation import BertGenerationConfig

							try:
														if not is_sentencepiece_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_bert_generation import BertGenerationTokenizer

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_bert_generation import (
														    BertGenerationDecoder,
														    BertGenerationEncoder,
														    BertGenerationPreTrainedModel,
														    load_tf_weights_in_bert_generation,
														)

else:
							import sys

							snake_case_  :	Union[str, Any]							  =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers

class   A__							:




						def __init__(				self    :					List[Any] ,			_a    :					List[Any]     )							->   None:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE	     =vocab
										_SCREAMING_SNAKE_CASE	     =normalizers.BertNormalizer(
										    clean_text=_a ,			handle_chinese_chars=_a ,			strip_accents=_a ,			lowercase=_a ,			)
										try:
														import rjieba
										except ImportError:
														raise ImportError(
														    '''You need to install rjieba to use RoFormerTokenizer. '''
														    '''See https://pypi.org/project/rjieba/ for installation.'''     )
										_SCREAMING_SNAKE_CASE	     =rjieba




						def 							__UpperCamelCase (				self    :					List[Any] ,			_a    :					int ,			_a    :					NormalizedString     )							->   List[NormalizedString]:


										"""simple docstring"""





										_SCREAMING_SNAKE_CASE	     =[]

										# this code slice normalized_string is too slow (6s) but test_alignement_methods can pass
										for token, start, end in self.jieba.tokenize(str(_a     ) ,			hmm=_a     ):
														if token in self.vocab:
																		splits.append(normalized_string[start:end]     )
														else:
																		_SCREAMING_SNAKE_CASE	     =self.normalizers.normalize_str(_a     ).split()
																		for token in token_list:
																						if token:
																										_SCREAMING_SNAKE_CASE	     =start + len(_a     )
																										splits.append(normalized_string[start:end]     )
																										_SCREAMING_SNAKE_CASE	     =end

        # this code test_alignement_methods can't pass but fast (300ms)
        # for token in self.jieba.cut(str(normalized_string), False):
        #     if token in self.vocab:
        #         splits.append(NormalizedString(token))
        #     else:
        #         token_list = self.normalizers.normalize_str(token).split()
        #         for token in token_list:
        #             if token:
        #                 splits.append(NormalizedString(token))

										return splits




						def 							__UpperCamelCase (				self    :					List[Any] ,			_a    :					PreTokenizedString     )							->   int:


										"""simple docstring"""





										pretok.split(self.jieba_split     )