


from typing import List

from tokenizers import NormalizedString, PreTokenizedString, normalizers
class      UpperCAmelCase_ :

			'''simple docstring'''




			def __init__(		self						,    __A			):






					"""simple docstring"""





					lowerCamelCase			: Optional[int]   =    vocab
					lowerCamelCase			: Union[str, Any]   =    normalizers.BertNormalizer(
					    clean_text=SCREAMING_SNAKE_CASE_						,    handle_chinese_chars=SCREAMING_SNAKE_CASE_						,    strip_accents=SCREAMING_SNAKE_CASE_						,    lowercase=SCREAMING_SNAKE_CASE_						,    )
					try:
							import rjieba
					except ImportError:
							raise ImportError(
							    "You need to install rjieba to use RoFormerTokenizer. "
							    "See https://pypi.org/project/rjieba/ for installation."			)
					lowerCamelCase			: str   =    rjieba






			def _snake_case   (		self						,    __A						,    __A			):






					"""simple docstring"""





					lowerCamelCase			: Any   =    []

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






					"""simple docstring"""





					pretok.split(self.jieba_split			)







from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_snake_case					=					{
    '''configuration_rwkv''': ['''RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''RwkvConfig''', '''RwkvOnnxConfig'''],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _snake_case					=					[
       '''RWKV_PRETRAINED_MODEL_ARCHIVE_LIST''',
       '''RwkvForCausalLM''',
       '''RwkvModel''',
       '''RwkvPreTrainedModel''',
   ]


if TYPE_CHECKING:
   from .configuration_rwkv import RWKV_PRETRAINED_CONFIG_ARCHIVE_MAP, RwkvConfig, RwkvOnnxConfig

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_rwkv import (
          RWKV_PRETRAINED_MODEL_ARCHIVE_LIST,
          RwkvForCausalLM,
          RwkvModel,
          RwkvPreTrainedModel,
      )
else:
   import sys

   _snake_case					=					_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)



