



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


_lowercase: Tuple      			=		logging.get_logger(__name__)

_lowercase: Dict      			=		{"vocab_file": "spiece.model"}

_lowercase: str      			=		{
    "vocab_file": {
        "xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model",
        "xlnet-large-cased": "https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model",
    }
}

_lowercase: List[Any]      			=		{
    "xlnet-base-cased": None,
    "xlnet-large-cased": None,
}

# Segments (not really needed)
_lowercase: Dict      			=		0
_lowercase: str      			=		1
_lowercase: Optional[Any]      			=		2
_lowercase: Dict      			=		3
_lowercase: Union[str, Any]      			=		4



class 	_lowercase							(   lowerCAmelCase	):





	"""simple docstring"""
	__A							=							VOCAB_FILES_NAMES
	__A							=							PRETRAINED_VOCAB_FILES_MAP
	__A							=							PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	__A							=							"left"




	def __init__(self		,       lowerCamelCase_		,       lowerCamelCase_=False		,       lowerCamelCase_=True		,       lowerCamelCase_=False		,       lowerCamelCase_="<s>"		,       lowerCamelCase_="</s>"		,       lowerCamelCase_="<unk>"		,       lowerCamelCase_="<sep>"		,       lowerCamelCase_="<pad>"		,       lowerCamelCase_="<cls>"		,       lowerCamelCase_="<mask>"		,       lowerCamelCase_=["<eop>", "<eod>"]		,       lowerCamelCase_ = None		,       **lowerCamelCase_		,       ):
						"""simple docstring"""

						a					     =   AddedToken(lowerCamelCase_		,       lstrip=lowerCamelCase_		,       rstrip=lowerCamelCase_		) if isinstance(lowerCamelCase_		,       lowerCamelCase_		) else mask_token

						a					     =   {} if sp_model_kwargs is None else sp_model_kwargs

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

						a					     =   3

						a					     =   do_lower_case
						a					     =   remove_space
						a					     =   keep_accents
						a					     =   vocab_file

						a					     =   spm.SentencePieceProcessor(**self.sp_model_kwargs		)
						self.sp_model.Load(lowerCamelCase_		)




	@property
	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						return len(self.sp_model		)




	def      UpperCamelCase_       (self		):
						"""simple docstring"""

						a					     =   {self.convert_ids_to_tokens(lowerCamelCase_		): i for i in range(self.vocab_size		)}
						vocab.update(self.added_tokens_encoder		)
						return vocab




	def __getstate__(self		):
						"""simple docstring"""

						a					     =   self.__dict__.copy()
						a					     =   None
						return state




	def __setstate__(self		,       lowerCamelCase_		):
						"""simple docstring"""

						a					     =   d

						# for backward compatibility
						if not hasattr(self		,       "sp_model_kwargs"		):
											a					     =   {}

						a					     =   spm.SentencePieceProcessor(**self.sp_model_kwargs		)
						self.sp_model.Load(self.vocab_file		)




	def      UpperCamelCase_       (self		,       lowerCamelCase_		):
						"""simple docstring"""

						if self.remove_space:
											a					     =   " ".join(inputs.strip().split()		)
						else:
											a					     =   inputs
						a					     =   outputs.replace("``"		,       "\""		).replace("''"		,       "\""		)

						if not self.keep_accents:
											a					     =   unicodedata.normalize("NFKD"		,       lowerCamelCase_		)
											a					     =   "".join([c for c in outputs if not unicodedata.combining(lowerCamelCase_		)]		)
						if self.do_lower_case:
											a					     =   outputs.lower()

						return outputs




	def      UpperCamelCase_       (self		,       lowerCamelCase_		):
						"""simple docstring"""

						a					     =   self.preprocess_text(lowerCamelCase_		)
						a					     =   self.sp_model.encode(lowerCamelCase_		,       out_type=lowerCamelCase_		)
						a					     =   []
						for piece in pieces:
											if len(lowerCamelCase_		) > 1 and piece[-1] == str(","		) and piece[-2].isdigit():
																a					     =   self.sp_model.EncodeAsPieces(piece[:-1].replace(lowerCamelCase_		,       ""		)		)
																if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																					if len(cur_pieces[0]		) == 1:
																										a					     =   cur_pieces[1:]
																					else:
																										a					     =   cur_pieces[0][1:]
																cur_pieces.append(piece[-1]		)
																new_pieces.extend(lowerCamelCase_		)
											else:
																new_pieces.append(lowerCamelCase_		)

						return new_pieces




	def      UpperCamelCase_       (self		,       lowerCamelCase_		):
						"""simple docstring"""

						return self.sp_model.PieceToId(lowerCamelCase_		)




	def      UpperCamelCase_       (self		,       lowerCamelCase_		):
						"""simple docstring"""

						return self.sp_model.IdToPiece(lowerCamelCase_		)




	def      UpperCamelCase_       (self		,       lowerCamelCase_		):
						"""simple docstring"""

						a					     =   "".join(lowerCamelCase_		).replace(lowerCamelCase_		,       " "		).strip()
						return out_string




	def      UpperCamelCase_       (self		,       lowerCamelCase_		,       lowerCamelCase_ = False		,       lowerCamelCase_ = None		,       lowerCamelCase_ = True		,       **lowerCamelCase_		,       ):
						"""simple docstring"""

						a					     =   kwargs.pop("use_source_tokenizer"		,       lowerCamelCase_		)

						a					     =   self.convert_ids_to_tokens(lowerCamelCase_		,       skip_special_tokens=lowerCamelCase_		)

						# To avoid mixing byte-level and unicode for byte-level BPT
						# we need to build string separately for added tokens and byte-level tokens
						# cf. https://github.com/huggingface/transformers/issues/1133
						a					     =   []
						a					     =   []
						for token in filtered_tokens:
											if skip_special_tokens and token in self.all_special_ids:
																continue
											if token in self.added_tokens_encoder:
																if current_sub_text:
																					sub_texts.append(self.convert_tokens_to_string(lowerCamelCase_		)		)
																					a					     =   []
																sub_texts.append(lowerCamelCase_		)
											else:
																current_sub_text.append(lowerCamelCase_		)
						if current_sub_text:
											sub_texts.append(self.convert_tokens_to_string(lowerCamelCase_		)		)

						# Mimic the behavior of the Rust tokenizer:
						# By default, there are no spaces between special tokens
						a					     =   "".join(lowerCamelCase_		)

						a					     =   (
						    clean_up_tokenization_spaces
						    if clean_up_tokenization_spaces is not None
						    else self.clean_up_tokenization_spaces
						)
						if clean_up_tokenization_spaces:
											a					     =   self.clean_up_tokenization(lowerCamelCase_		)
											return clean_text
						else:
											return text




	def      UpperCamelCase_       (self		,       lowerCamelCase_		,       lowerCamelCase_ = None		):
						"""simple docstring"""

						a					     =   [self.sep_token_id]
						a					     =   [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      UpperCamelCase_       (self		,       lowerCamelCase_		,       lowerCamelCase_ = None		,       lowerCamelCase_ = False		):
						"""simple docstring"""

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

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




	def      UpperCamelCase_       (self		,       lowerCamelCase_		,       lowerCamelCase_ = None		):
						"""simple docstring"""

						a					     =   [self.sep_token_id]
						a					     =   [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      UpperCamelCase_       (self		,       lowerCamelCase_		,       lowerCamelCase_ = None		):
						"""simple docstring"""

						if not os.path.isdir(lowerCamelCase_		):
											logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''		)
											return
						a					     =   os.path.join(
						    lowerCamelCase_		,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]		)

						if os.path.abspath(self.vocab_file		) != os.path.abspath(lowerCamelCase_		) and os.path.isfile(self.vocab_file		):
											copyfile(self.vocab_file		,       lowerCamelCase_		)
						elif not os.path.isfile(self.vocab_file		):
											with open(lowerCamelCase_		,       "wb"		) as fi:
																a					     =   self.sp_model.serialized_model_proto()
																fi.write(lowerCamelCase_		)

						return (out_vocab_file,)





_lowercase: Dict      			=		[
    (1000, "M"),
    (900, "CM"),
    (500, "D"),
    (400, "CD"),
    (100, "C"),
    (90, "XC"),
    (50, "L"),
    (40, "XL"),
    (10, "X"),
    (9, "IX"),
    (5, "V"),
    (4, "IV"),
    (1, "I"),
]






def     a(      A       :    str       )		->       int:
					"""simple docstring"""





					a					     =   {"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1000}
					a					     =   0
					a					     =   0
					while place < len(A       ):
										if (place + 1 < len(A       )) and (vals[roman[place]] < vals[roman[place + 1]]):
															total += vals[roman[place + 1]] - vals[roman[place]]
															place += 2
										else:
															total += vals[roman[place]]
															place += 1
					return total






def     a(      A       :    int       )		->       str:
					"""simple docstring"""





					a					     =   []
					for arabic, roman in ROMAN:
										((a)     ,				(a))					     =   divmod(A ,     A       )
										result.append(roman * factor       )
										if number == 0:
															break
					return "".join(A       )


if __name__ == "__main__":
				import doctest

				doctest.testmod()
