



'''simple docstring'''






import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging


UpperCamelCase__:   int								=			logging.get_logger(__name__)

UpperCamelCase__:   Tuple								=			{"vocab_file": "spiece.model"}

UpperCamelCase__:   List[Any]								=			{
    "vocab_file": {
        "TsinghuaAI/CPM-Generate": "https://huggingface.co/TsinghuaAI/CPM-Generate/resolve/main/spiece.model",
    }
}

class 				SCREAMING_SNAKE_CASE(							A__			):







	"""simple docstring"""






	def __init__(						self			:     Dict		,			__snake_case			:     Optional[Any]		,			__snake_case			:     Optional[Any]=False		,			__snake_case			:     str=True		,			__snake_case			:     List[Any]=False		,			__snake_case			:     Union[str, Any]="<s>"		,			__snake_case			:     Tuple="</s>"		,			__snake_case			:     str="<unk>"		,			__snake_case			:     int="<sep>"		,			__snake_case			:     str="<pad>"		,			__snake_case			:     Optional[int]="<cls>"		,			__snake_case			:     Dict="<mask>"		,			__snake_case			:     str=["<eop>", "<eod>"]		,			__snake_case			:     Optional[Dict[str, Any]] = None		,			**__snake_case			:     Any		,			)			->		None:
								UpperCAmelCase :       Any 							=		AddedToken(__snake_case		,			lstrip=__snake_case		,			rstrip=__snake_case		) if isinstance(__snake_case		,			__snake_case		) else mask_token

								UpperCAmelCase :       Tuple 							=		{} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    do_lower_case=__snake_case		,			remove_space=__snake_case		,			keep_accents=__snake_case		,			bos_token=__snake_case		,			eos_token=__snake_case		,			unk_token=__snake_case		,			sep_token=__snake_case		,			pad_token=__snake_case		,			cls_token=__snake_case		,			mask_token=__snake_case		,			additional_special_tokens=__snake_case		,			sp_model_kwargs=self.sp_model_kwargs		,			**__snake_case		,			)

								UpperCAmelCase :       Union[str, Any] 							=		3

								UpperCAmelCase :       str 							=		do_lower_case
								UpperCAmelCase :       Optional[Any] 							=		remove_space
								UpperCAmelCase :       str 							=		keep_accents
								UpperCAmelCase :       Optional[Any] 							=		vocab_file

								UpperCAmelCase :       List[Any] 							=		spm.SentencePieceProcessor(**self.sp_model_kwargs		)
								self.sp_model.Load(__snake_case		)

								try:
															import jieba
								except ModuleNotFoundError as error:
															raise error.__class__(
															    '''You need to install jieba to use CpmTokenizer or CpmTokenizerFast. '''
															    '''See https://pypi.org/project/jieba/ for installation.'''		)
								UpperCAmelCase :       List[str] 							=		jieba
								UpperCAmelCase :       Any 							=		str.maketrans(''' \n'''		,			'''\u2582\u2583'''		)







	@property
	# Copied from transformers.models.xlnet.tokenization_xlnet.XLNetTokenizer.vocab_size
	def      A	(						self			:     Tuple		)			->		Dict:
								return len(self.sp_model		)







	def      A	(						self			:     Tuple		)			->		int:
								UpperCAmelCase :       Dict 							=		{self.convert_ids_to_tokens(__snake_case		): i for i in range(self.vocab_size		)}
								vocab.update(self.added_tokens_encoder		)
								return vocab







	def __getstate__(						self			:     Optional[int]		)			->		Any:
								UpperCAmelCase :       int 							=		self.__dict__.copy()
								UpperCAmelCase :       Optional[Any] 							=		None
								return state







	def __setstate__(						self			:     Any		,			__snake_case			:     Union[str, Any]		)			->		Optional[Any]:
								UpperCAmelCase :       List[str] 							=		d

								# for backward compatibility
								if not hasattr(self		,			'''sp_model_kwargs'''		):
															UpperCAmelCase :       Dict 							=		{}

								UpperCAmelCase :       Optional[Any] 							=		spm.SentencePieceProcessor(**self.sp_model_kwargs		)
								self.sp_model.Load(self.vocab_file		)







	def      A	(						self			:     int		,			__snake_case			:     int		)			->		Tuple:
								if self.remove_space:
															UpperCAmelCase :       Dict 							=		''' '''.join(inputs.strip().split()		)
								else:
															UpperCAmelCase :       Any 							=		inputs
								UpperCAmelCase :       List[str] 							=		outputs.replace('''``'''		,			'''"'''		).replace('''\'\''''		,			'''"'''		)

								if not self.keep_accents:
															UpperCAmelCase :       int 							=		unicodedata.normalize('''NFKD'''		,			__snake_case		)
															UpperCAmelCase :       List[str] 							=		''''''.join([c for c in outputs if not unicodedata.combining(__snake_case		)]		)
								if self.do_lower_case:
															UpperCAmelCase :       Union[str, Any] 							=		outputs.lower()

								return outputs







	def      A	(						self			:     Any		,			__snake_case			:     str		)			->		List[str]:
								UpperCAmelCase :       Dict 							=		self.preprocess_text(__snake_case		)
								UpperCAmelCase :       Union[str, Any] 							=		self.sp_model.encode(__snake_case		,			out_type=__snake_case		)
								UpperCAmelCase :       List[Any] 							=		[]
								for piece in pieces:
															if len(__snake_case		) > 1 and piece[-1] == str(''','''		) and piece[-2].isdigit():
																						UpperCAmelCase :       List[str] 							=		self.sp_model.EncodeAsPieces(piece[:-1].replace(__snake_case		,			''''''		)		)
																						if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																													if len(cur_pieces[0]		) == 1:
																																				UpperCAmelCase :       Union[str, Any] 							=		cur_pieces[1:]
																													else:
																																				UpperCAmelCase :       Dict 							=		cur_pieces[0][1:]
																						cur_pieces.append(piece[-1]		)
																						new_pieces.extend(__snake_case		)
															else:
																						new_pieces.append(__snake_case		)

								return new_pieces







	def      A	(						self			:     Dict		,			__snake_case			:     Tuple		)			->		List[Any]:
								return self.sp_model.PieceToId(__snake_case		)







	def      A	(						self			:     Any		,			__snake_case			:     str		)			->		List[Any]:
								return self.sp_model.IdToPiece(__snake_case		)







	def      A	(						self			:     str		,			__snake_case			:     Tuple		)			->		Dict:
								UpperCAmelCase :       List[Any] 							=		''''''.join(__snake_case		).replace(__snake_case		,			''' '''		).strip()
								return out_string







	def      A	(						self			:     Union[str, Any]		,			__snake_case			:     List[int]		,			__snake_case			:     Optional[List[int]] = None		)			->		List[int]:
								UpperCAmelCase :       Dict 							=		[self.sep_token_id]
								UpperCAmelCase :       int 							=		[self.cls_token_id]
								if token_ids_a is None:
															return token_ids_a + sep + cls
								return token_ids_a + sep + token_ids_a + sep + cls







	def      A	(						self			:     Union[str, Any]		,			__snake_case			:     List[int]		,			__snake_case			:     Optional[List[int]] = None		,			__snake_case			:     bool = False		)			->		List[int]:

								if already_has_special_tokens:
															return super().get_special_tokens_mask(
															    token_ids_a=__snake_case		,			token_ids_a=__snake_case		,			already_has_special_tokens=__snake_case		)

								if token_ids_a is not None:
															return ([0] * len(__snake_case		)) + [1] + ([0] * len(__snake_case		)) + [1, 1]
								return ([0] * len(__snake_case		)) + [1, 1]







	def      A	(						self			:     Any		,			__snake_case			:     List[int]		,			__snake_case			:     Optional[List[int]] = None		)			->		List[int]:
								UpperCAmelCase :       Any 							=		[self.sep_token_id]
								UpperCAmelCase :       Union[str, Any] 							=		[2]

								if token_ids_a is None:
															return len(token_ids_a + sep		) * [0] + cls_segment_id
								return len(token_ids_a + sep		) * [0] + len(token_ids_a + sep		) * [1] + cls_segment_id







	def      A	(						self			:     Tuple		,			__snake_case			:     str		,			__snake_case			:     Optional[str] = None		)			->		Tuple[str]:
								if not os.path.isdir(__snake_case		):
															logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""		)
															return
								UpperCAmelCase :       Any 							=		os.path.join(
								    __snake_case		,			(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']		)

								if os.path.abspath(self.vocab_file		) != os.path.abspath(__snake_case		) and os.path.isfile(self.vocab_file		):
															copyfile(self.vocab_file		,			__snake_case		)
								elif not os.path.isfile(self.vocab_file		):
															with open(__snake_case		,			'''wb'''		) as fi:
																						UpperCAmelCase :       Optional[Any] 							=		self.sp_model.serialized_model_proto()
																						fi.write(__snake_case		)

								return (out_vocab_file,)







	def      A	(						self			:     Optional[Any]		,			*__snake_case			:     Any		,			**__snake_case			:     Optional[Any]		)			->		int:
								UpperCAmelCase :       Any 							=		super()._decode(*__snake_case		,			**__snake_case		)
								UpperCAmelCase :       Any 							=		text.replace(''' '''		,			''''''		).replace('''\u2582'''		,			''' '''		).replace('''\u2583'''		,			'''\n'''		)
								return text








"""simple docstring"""


import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
			from .tokenization_rembert import RemBertTokenizer
else:
			__A						   =			None

__A						   =			logging.get_logger(__name__)
__A						   =			{"vocab_file": "sentencepiece.model", "tokenizer_file": "tokenizer.json"}

__A						   =			{
    "vocab_file": {
        "google/rembert": "https://huggingface.co/google/rembert/resolve/main/sentencepiece.model",
    },
    "tokenizer_file": {
        "google/rembert": "https://huggingface.co/google/rembert/resolve/main/tokenizer.json",
    },
}

__A						   =			{
    "google/rembert": 256,
}

__A						   =			"▁"





class     snake_case	(				__snake_case  ):
				SCREAMING_SNAKE_CASE_   :      Tuple         =  VOCAB_FILES_NAMES
				SCREAMING_SNAKE_CASE_   :      Any         =  PRETRAINED_VOCAB_FILES_MAP
				SCREAMING_SNAKE_CASE_   :      Tuple         =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				SCREAMING_SNAKE_CASE_   :      Dict         =  RemBertTokenizer

				def __init__(	self							:				Tuple     ,  UpperCamelCase__							:				Dict=None     ,  UpperCamelCase__							:				List[Any]=None     ,  UpperCamelCase__							:				str=True     ,  UpperCamelCase__							:				Optional[int]=True     ,  UpperCamelCase__							:				Optional[Any]=False     ,  UpperCamelCase__							:				int="[CLS]"     ,  UpperCamelCase__							:				Optional[Any]="[SEP]"     ,  UpperCamelCase__							:				List[str]="<unk>"     ,  UpperCamelCase__							:				Dict="[SEP]"     ,  UpperCamelCase__							:				int="<pad>"     ,  UpperCamelCase__							:				Any="[CLS]"     ,  UpperCamelCase__							:				str="[MASK]"     ,  **UpperCamelCase__							:				Optional[Any]     ,  )->   List[Any]:



						'''simple docstring'''


						__lowerCAmelCase:       int          =			AddedToken(UpperCamelCase__     ,  lstrip=UpperCamelCase__     ,  rstrip=UpperCamelCase__) if isinstance(UpperCamelCase__     ,  UpperCamelCase__) else mask_token

						super().__init__(
						    UpperCamelCase__     ,  tokenizer_file=UpperCamelCase__     ,  do_lower_case=UpperCamelCase__     ,  remove_space=UpperCamelCase__     ,  keep_accents=UpperCamelCase__     ,  bos_token=UpperCamelCase__     ,  eos_token=UpperCamelCase__     ,  unk_token=UpperCamelCase__     ,  sep_token=UpperCamelCase__     ,  pad_token=UpperCamelCase__     ,  cls_token=UpperCamelCase__     ,  mask_token=UpperCamelCase__     ,  **UpperCamelCase__     ,  )

						__lowerCAmelCase:       Optional[int]          =			do_lower_case
						__lowerCAmelCase:       int          =			remove_space
						__lowerCAmelCase:       int          =			keep_accents
						__lowerCAmelCase:       str          =			vocab_file
						__lowerCAmelCase:       Tuple          =			False if not self.vocab_file else True

				def 							lowercase_     (	self							:				Any     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   List[int]:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[int]          =			[self.sep_token_id]
						__lowerCAmelCase:       Any          =			[self.cls_token_id]
						if token_ids_a is None:
								return cls + token_ids_a + sep
						return cls + token_ids_a + sep + token_ids_a + sep

				def 							lowercase_     (	self							:				Optional[Any]     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None     ,  UpperCamelCase__							:				bool = False)->   List[int]:



						'''simple docstring'''


						if already_has_special_tokens:
								if token_ids_a is not None:
										raise ValueError(
										    "You should not supply a second sequence if the provided sequence of "
										    "ids is already formatted with special tokens for the model.")
								return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

						if token_ids_a is not None:
								return [1] + ([0] * len(UpperCamelCase__)) + [1] + ([0] * len(UpperCamelCase__)) + [1]
						return [1] + ([0] * len(UpperCamelCase__)) + [1]

				def 							lowercase_     (	self							:				Tuple     ,  UpperCamelCase__							:				List[int]     ,  UpperCamelCase__							:				Optional[List[int]] = None)->   List[int]:



						'''simple docstring'''


						__lowerCAmelCase:       Optional[int]          =			[self.sep_token_id]
						__lowerCAmelCase:       Dict          =			[self.cls_token_id]

						if token_ids_a is None:
								return len(cls + token_ids_a + sep) * [0]
						return len(cls + token_ids_a + sep) * [0] + len(token_ids_a + sep) * [1]




				def 							lowercase_     (	self							:				Union[str, Any]     ,  UpperCamelCase__							:				str     ,  UpperCamelCase__							:				Optional[str] = None)->   Tuple[str]:



						'''simple docstring'''


						if not os.path.isdir(UpperCamelCase__):
								logger.error("Vocabulary path ({}) should be a directory".format(UpperCamelCase__))
								return
						__lowerCAmelCase:       Optional[Any]          =			os.path.join(
						    UpperCamelCase__     ,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"])

						if os.path.abspath(self.vocab_file) != os.path.abspath(UpperCamelCase__):
								copyfile(self.vocab_file     ,  UpperCamelCase__)

						return (out_vocab_file,)


