


import importlib.metadata
import sys

from transformers.testing_utils import TestCasePlus
from transformers.utils.versions import require_version, require_version_core


snake_case_  :	Dict							  =							importlib.metadata.version('''numpy''')
snake_case_  :	Any							  =							'''.'''.join([str(x) for x in sys.version_info[:3]])

class   A__							(						UpperCamelCase__     ):




						def 							__UpperCamelCase (				self    :					Optional[int]     )							->   Union[str, Any]:


										"""simple docstring"""





										require_version_core('''numpy<1000.4.5'''     )
										require_version_core('''numpy<1000.4'''     )
										require_version_core('''numpy<1000'''     )

										# le
										require_version_core('''numpy<=1000.4.5'''     )
										require_version_core(f"numpy<={numpy_ver}"     )

										# eq
										require_version_core(f"numpy=={numpy_ver}"     )

										# ne
										require_version_core('''numpy!=1000.4.5'''     )

										# ge
										require_version_core('''numpy>=1.0'''     )
										require_version_core('''numpy>=1.0.0'''     )
										require_version_core(f"numpy>={numpy_ver}"     )

										# gt
										require_version_core('''numpy>1.0.0'''     )

										# mix
										require_version_core('''numpy>1.0.0,<1000'''     )

										# requirement w/o version
										require_version_core('''numpy'''     )

										# unmet requirements due to version conflict
										for req in ["numpy==1.0.0", "numpy>=1000.0.0", f"numpy<{numpy_ver}"]:
														try:
																		require_version_core(_a     )
														except ImportError as e:
																		self.assertIn(f"{req} is required" ,			str(_a     )     )
																		self.assertIn('''but found''' ,			str(_a     )     )

        # unmet requirements due to missing module
										for req in ["numpipypie>1", "numpipypie2"]:
														try:
																		require_version_core(_a     )
														except importlib.metadata.PackageNotFoundError as e:
																		self.assertIn(f"The '{req}' distribution was not found and is required by this application" ,			str(_a     )     )
																		self.assertIn('''Try: pip install transformers -U''' ,			str(_a     )     )

        # bogus requirements formats:
        # 1. whole thing
										for req in ["numpy??1.0.0", "numpy1.0.0"]:
														try:
																		require_version_core(_a     )
														except ValueError as e:
																		self.assertIn('''requirement needs to be in the pip package format''' ,			str(_a     )     )
        # 2. only operators
										for req in ["numpy=1.0.0", "numpy == 1.00", "numpy<>1.0.0", "numpy><1.00", "numpy>>1.0.0"]:
														try:
																		require_version_core(_a     )
														except ValueError as e:
																		self.assertIn('''need one of ''' ,			str(_a     )     )




						def 							__UpperCamelCase (				self    :					Any     )							->   Any:


										"""simple docstring"""





										require_version('''python>=3.6.0'''     )

										# not matching requirements
										for req in ["python>9.9.9", "python<3.0.0"]:
														try:
																		require_version_core(_a     )
														except ImportError as e:
																		self.assertIn(f"{req} is required" ,			str(_a     )     )
																		self.assertIn(f"but found python=={python_ver}" ,			str(_a     )     )



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     )