

'''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_						     =					logging.get_logger(__name__)

UpperCamelCase_						     =					{"""vocab_file""": """spiece.model"""}

UpperCamelCase_						     =					{
    """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""",
    }
}

UpperCamelCase_						     =					{
    """xlnet-base-cased""": None,
    """xlnet-large-cased""": None,
}

# Segments (not really needed)
UpperCamelCase_						     =					0
UpperCamelCase_						     =					1
UpperCamelCase_						     =					2
UpperCamelCase_						     =					3
UpperCamelCase_						     =					4





class 		__SCREAMING_SNAKE_CASE       ( lowercase__			):
				lowerCamelCase_							=						VOCAB_FILES_NAMES
				lowerCamelCase_							=						PRETRAINED_VOCAB_FILES_MAP
				lowerCamelCase_							=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				lowerCamelCase_							=						'left'







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

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

										super().__init__(
										    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__		,				additional_special_tokens=UpperCAmelCase__		,				sp_model_kwargs=self.sp_model_kwargs		,				**UpperCAmelCase__		,				)

										lowercase   :       Optional[Any]								=3

										lowercase   :       int								=do_lower_case
										lowercase   :       Tuple								=remove_space
										lowercase   :       List[Any]								=keep_accents
										lowercase   :       Tuple								=vocab_file

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







				@property
				def    lowerCamelCase_  (					self    :		Tuple      ):
										'''simple docstring'''
										return len(self.sp_model      )







				def    lowerCamelCase_  (					self    :		Optional[Any]      ):
										'''simple docstring'''
										lowercase   :       List[Any]								={self.convert_ids_to_tokens(UpperCAmelCase__      ): i for i in range(self.vocab_size      )}
										vocab.update(self.added_tokens_encoder      )
										return vocab







				def __getstate__(					self    :		List[Any]      ):
										'''simple docstring'''
										lowercase   :       int								=self.__dict__.copy()
										lowercase   :       List[Any]								=None
										return state







				def __setstate__(					self    :		Any		,				UpperCAmelCase__    :		List[str]      ):
										'''simple docstring'''
										lowercase   :       int								=d

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

										lowercase   :       Union[str, Any]								=spm.SentencePieceProcessor(**self.sp_model_kwargs      )
										self.sp_model.Load(self.vocab_file      )







				def    lowerCamelCase_  (					self    :		str		,				UpperCAmelCase__    :		Optional[Any]      ):
										'''simple docstring'''
										if self.remove_space:
																lowercase   :       str								=''' '''.join(inputs.strip().split()      )
										else:
																lowercase   :       int								=inputs
										lowercase   :       List[Any]								=outputs.replace('''``'''		,				'''"'''      ).replace('''\'\''''		,				'''"'''      )

										if not self.keep_accents:
																lowercase   :       Any								=unicodedata.normalize('''NFKD'''		,				UpperCAmelCase__      )
																lowercase   :       int								=''''''.join([c for c in outputs if not unicodedata.combining(UpperCAmelCase__      )]      )
										if self.do_lower_case:
																lowercase   :       int								=outputs.lower()

										return outputs







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

										return new_pieces







				def    lowerCamelCase_  (					self    :		List[Any]		,				UpperCAmelCase__    :		Optional[int]      ):
										'''simple docstring'''
										return self.sp_model.PieceToId(UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Tuple		,				UpperCAmelCase__    :		Dict      ):
										'''simple docstring'''
										return self.sp_model.IdToPiece(UpperCAmelCase__      )







				def    lowerCamelCase_  (					self    :		Union[str, Any]		,				UpperCAmelCase__    :		str      ):
										'''simple docstring'''
										lowercase   :       str								=''''''.join(UpperCAmelCase__      ).replace(UpperCAmelCase__		,				''' '''      ).strip()
										return out_string







				def    lowerCamelCase_  (					self    :		Optional[Any]		,				UpperCAmelCase__    :		List[int]		,				UpperCAmelCase__    :		bool = False		,				UpperCAmelCase__    :		bool = None		,				UpperCAmelCase__    :		bool = True		,				**UpperCAmelCase__    :		Union[str, Any]		,				):
										'''simple docstring'''
										lowercase   :       Optional[int]								=kwargs.pop('''use_source_tokenizer'''		,				UpperCAmelCase__      )

										lowercase   :       Any								=self.convert_ids_to_tokens(UpperCAmelCase__		,				skip_special_tokens=UpperCAmelCase__      )

										# 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
										lowercase   :       Dict								=[]
										lowercase   :       Optional[Any]								=[]
										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(UpperCAmelCase__      )      )
																												lowercase   :       List[Any]								=[]
																						sub_texts.append(UpperCAmelCase__      )
																else:
																						current_sub_text.append(UpperCAmelCase__      )
										if current_sub_text:
																sub_texts.append(self.convert_tokens_to_string(UpperCAmelCase__      )      )

										# Mimic the behavior of the Rust tokenizer:
										# By default, there are no spaces between special tokens
										lowercase   :       Any								=''''''.join(UpperCAmelCase__      )

										lowercase   :       str								=(
										    clean_up_tokenization_spaces
										    if clean_up_tokenization_spaces is not None
										    else self.clean_up_tokenization_spaces
										)
										if clean_up_tokenization_spaces:
																lowercase   :       str								=self.clean_up_tokenization(UpperCAmelCase__      )
																return clean_text
										else:
																return text







				def    lowerCamelCase_  (					self    :		str		,				UpperCAmelCase__    :		List[int]		,				UpperCAmelCase__    :		Optional[List[int]] = None      ):
										'''simple docstring'''
										lowercase   :       Dict								=[self.sep_token_id]
										lowercase   :       Union[str, Any]								=[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    lowerCamelCase_  (					self    :		str		,				UpperCAmelCase__    :		List[int]		,				UpperCAmelCase__    :		Optional[List[int]] = None		,				UpperCAmelCase__    :		bool = False      ):
										'''simple docstring'''

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

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







				def    lowerCamelCase_  (					self    :		Union[str, Any]		,				UpperCAmelCase__    :		List[int]		,				UpperCAmelCase__    :		Optional[List[int]] = None      ):
										'''simple docstring'''
										lowercase   :       Optional[Any]								=[self.sep_token_id]
										lowercase   :       Tuple								=[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    lowerCamelCase_  (					self    :		Any		,				UpperCAmelCase__    :		str		,				UpperCAmelCase__    :		Optional[str] = None      ):
										'''simple docstring'''
										if not os.path.isdir(UpperCAmelCase__      ):
																logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
																return
										lowercase   :       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__      ) and os.path.isfile(self.vocab_file      ):
																copyfile(self.vocab_file		,				UpperCAmelCase__      )
										elif not os.path.isfile(self.vocab_file      ):
																with open(UpperCAmelCase__		,				'''wb'''      ) as fi:
																						lowercase   :       Optional[int]								=self.sp_model.serialized_model_proto()
																						fi.write(UpperCAmelCase__      )

										return (out_vocab_file,)








'''simple docstring'''





from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments






def 							_lowerCAmelCase (      )							->     List[Any]:
						lowercase   :       Tuple								=HfArgumentParser(__magic_name__	)
						lowercase   :       Union[str, Any]								=parser.parse_args_into_dataclasses()[0]
						lowercase   :       Any								=TensorFlowBenchmark(args=__magic_name__	)
						try:
												lowercase   :       List[Any]								=parser.parse_args_into_dataclasses()[0]
						except ValueError as e:
												lowercase   :       List[Any]								='''Arg --no_{0} is no longer used, please use --no-{0} instead.'''
												lowercase   :       Any								=''' '''.join(str(__magic_name__	).split(''' '''	)[:-1]	)
												lowercase   :       Optional[Any]								=''''''
												lowercase   :       List[str]								=eval(str(__magic_name__	).split(''' '''	)[-1]	)
												lowercase   :       Optional[Any]								=[]
												for arg in depreciated_args:
																		# arg[2:] removes '--'
																		if arg[2:] in TensorFlowBenchmark.deprecated_args:
																								# arg[5:] removes '--no_'
																								full_error_msg += arg_error_msg.format(arg[5:]	)
																		else:
																								wrong_args.append(__magic_name__	)
												if len(__magic_name__	) > 0:
																		lowercase   :       int								=full_error_msg + begin_error_msg + str(__magic_name__	)
												raise ValueError(__magic_name__	)
						benchmark.run()


if __name__ == "__main__":
							main()





