
"""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_					:						Tuple				= logging.get_logger(__name__)

UpperCamelCase_					:						Dict				= {'vocab_file': 'spiece.model'}

UpperCamelCase_					:						Dict				= {
    '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_					:						Optional[Any]				= {
    'xlnet-base-cased': None,
    'xlnet-large-cased': None,
}

# Segments (not really needed)
UpperCamelCase_					:						List[str]				= 0
UpperCamelCase_					:						Tuple				= 1
UpperCamelCase_					:						Dict				= 2
UpperCamelCase_					:						Optional[Any]				= 3
UpperCamelCase_					:						List[Any]				= 4






class __lowerCAmelCase				(					UpperCamelCase_      ):




			"""simple docstring"""







			snake_case	      =				VOCAB_FILES_NAMES
			snake_case	      =				PRETRAINED_VOCAB_FILES_MAP
			snake_case	      =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			snake_case	      =				"left"




			def __init__(				self						:					Union[str, Any]       ,   _snake_case						:					Union[str, Any]       ,   _snake_case						:					Any=False       ,   _snake_case						:					str=True       ,   _snake_case						:					List[Any]=False       ,   _snake_case						:					str="<s>"       ,   _snake_case						:					Optional[int]="</s>"       ,   _snake_case						:					Optional[Any]="<unk>"       ,   _snake_case						:					Optional[int]="<sep>"       ,   _snake_case						:					List[str]="<pad>"       ,   _snake_case						:					Tuple="<cls>"       ,   _snake_case						:					Union[str, Any]="<mask>"       ,   _snake_case						:					List[Any]=["<eop>", "<eod>"]       ,   _snake_case						:					Optional[Dict[str, Any]] = None       ,   **_snake_case						:					List[str]       ,   )      -> Optional[int]:







								"""simple docstring"""
								A_				 =						AddedToken(UpperCamelCase__       ,   lstrip=UpperCamelCase__       ,   rstrip=UpperCamelCase__	) if isinstance(UpperCamelCase__       ,   UpperCamelCase__	) else mask_token

								A_				 =						{} 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__       ,   )

								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(UpperCamelCase__	)




			@property
			def      lowerCamelCase__     (				self						:					str	)      -> Dict:







								"""simple docstring"""
								return len(self.sp_model	)




			def      lowerCamelCase__     (				self						:					List[Any]	)      -> Any:







								"""simple docstring"""
								A_				 =						{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[str]	)      -> Tuple:







								"""simple docstring"""
								A_				 =						self.__dict__.copy()
								A_				 =						None
								return state




			def __setstate__(				self						:					Optional[int]       ,   _snake_case						:					Optional[Any]	)      -> Tuple:







								"""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      lowerCamelCase__     (				self						:					Tuple       ,   _snake_case						:					List[str]	)      -> Any:







								"""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"       ,   UpperCamelCase__	)
													A_				 =						''''''.join([c for c in outputs if not unicodedata.combining(UpperCamelCase__	)]	)
								if self.do_lower_case:
													A_				 =						outputs.lower()

								return outputs




			def      lowerCamelCase__     (				self						:					Any       ,   _snake_case						:					str	)      -> Optional[int]:







								"""simple docstring"""
								A_				 =						self.preprocess_text(UpperCamelCase__	)
								A_				 =						self.sp_model.encode(UpperCamelCase__       ,   out_type=UpperCamelCase__	)
								A_				 =						[]
								for piece in pieces:
													if len(UpperCamelCase__	) > 1 and piece[-1] == str(","	) and piece[-2].isdigit():
																		A_				 =						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:
																												A_				 =						cur_pieces[1:]
																							else:
																												A_				 =						cur_pieces[0][1:]
																		cur_pieces.append(piece[-1]	)
																		new_pieces.extend(UpperCamelCase__	)
													else:
																		new_pieces.append(UpperCamelCase__	)

								return new_pieces




			def      lowerCamelCase__     (				self						:					Any       ,   _snake_case						:					List[str]	)      -> Any:







								"""simple docstring"""
								return self.sp_model.PieceToId(UpperCamelCase__	)




			def      lowerCamelCase__     (				self						:					Any       ,   _snake_case						:					List[Any]	)      -> int:







								"""simple docstring"""
								return self.sp_model.IdToPiece(UpperCamelCase__	)




			def      lowerCamelCase__     (				self						:					List[str]       ,   _snake_case						:					Optional[Any]	)      -> Dict:







								"""simple docstring"""
								A_				 =						''''''.join(UpperCamelCase__	).replace(UpperCamelCase__       ,   " "	).strip()
								return out_string




			def      lowerCamelCase__     (				self						:					Optional[int]       ,   _snake_case						:					List[int]       ,   _snake_case						:					bool = False       ,   _snake_case						:					bool = None       ,   _snake_case						:					bool = True       ,   **_snake_case						:					Optional[int]       ,   )      -> Optional[Any]:







								"""simple docstring"""
								A_				 =						kwargs.pop("use_source_tokenizer"       ,   UpperCamelCase__	)

								A_				 =						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
								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(UpperCamelCase__	)	)
																							A_				 =						[]
																		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
								A_				 =						''''''.join(UpperCamelCase__	)

								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(UpperCamelCase__	)
													return clean_text
								else:
													return text




			def      lowerCamelCase__     (				self						:					List[str]       ,   _snake_case						:					List[int]       ,   _snake_case						:					Optional[List[int]] = None	)      -> str:







								"""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      lowerCamelCase__     (				self						:					List[str]       ,   _snake_case						:					List[int]       ,   _snake_case						:					Optional[List[int]] = None       ,   _snake_case						:					bool = False	)      -> List[str]:







								"""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						:					Optional[Any]       ,   _snake_case						:					List[int]       ,   _snake_case						:					Optional[List[int]] = None	)      -> Union[str, Any]:







								"""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      lowerCamelCase__     (				self						:					List[Any]       ,   _snake_case						:					str       ,   _snake_case						:					Optional[str] = None	)      -> Any:







								"""simple docstring"""





								if not os.path.isdir(UpperCamelCase__	):
													logger.error(F'Vocabulary path ({save_directory}) should be a directory'	)
													return
								A_				 =						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:
																		A_				 =						self.sp_model.serialized_model_proto()
																		fi.write(UpperCamelCase__	)

								return (out_vocab_file,)






"""simple docstring"""





def 							A_     (__a				,   __a				,   __a				):

					'''simple docstring'''





					A_				 =						len(__a				)
					A_				 =						[[0] * n for i in range(__a				)]
					for i in range(__a				):
										A_				 =						y_points[i]

					for i in range(2				,   __a				):
										for j in range(__a				,   __a				):
															A_				 =						(
															    (xa - x_points[j - i + 1]) * q[j][i - 1]
															    - (xa - x_points[j]) * q[j - 1][i - 1]
															) / (x_points[j] - x_points[j - i + 1])

					return [q[n - 1][n - 1], q]


if __name__ == "__main__":
		import doctest

		doctest.testmod()




