


'''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_		:   Union[str, Any]							   =		logging.get_logger(__name__)

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

UpperCAmelCase_		:   List[Any]							   =		{
    '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_		:   Dict							   =		0
UpperCAmelCase_		:   Dict							   =		1
UpperCAmelCase_		:   str							   =		2
UpperCAmelCase_		:   str							   =		3
UpperCAmelCase_		:   int							   =		4





class     lowercase__  (						_snake_case					):





							'''simple docstring'''


							A_							:      Union[str, Any]      	=  VOCAB_FILES_NAMES
							A_							:      List[str]      	=  PRETRAINED_VOCAB_FILES_MAP
							A_							:      Union[str, Any]      	=  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							A_							:      str      	=  """left"""






							def __init__(    self    ,					__snake_case    ,					__snake_case=False    ,					__snake_case=True    ,					__snake_case=False    ,					__snake_case="<s>"    ,					__snake_case="</s>"    ,					__snake_case="<unk>"    ,					__snake_case="<sep>"    ,					__snake_case="<pad>"    ,					__snake_case="<cls>"    ,					__snake_case="<mask>"    ,					__snake_case=["<eop>", "<eod>"]    ,					__snake_case = None    ,					**__snake_case    ,					):
											# Mask token behave like a normal word, i.e. include the space before it
											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      AddedToken(__snake_case    ,					lstrip=__snake_case    ,					rstrip=__snake_case  ) if isinstance(__snake_case    ,					__snake_case  ) else mask_token

											_SCREAMING_SNAKE_CASE :       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    ,					)

											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      3

											_SCREAMING_SNAKE_CASE :       Dict     		=      do_lower_case
											_SCREAMING_SNAKE_CASE :       Tuple     		=      remove_space
											_SCREAMING_SNAKE_CASE :       List[str]     		=      keep_accents
											_SCREAMING_SNAKE_CASE :       int     		=      vocab_file

											_SCREAMING_SNAKE_CASE :       str     		=      spm.SentencePieceProcessor(**self.sp_model_kwargs  )
											self.sp_model.Load(__snake_case  )






							@property
							def UpperCAmelCase_	(    self  ):
											return len(self.sp_model  )






							def UpperCAmelCase_	(    self  ):
											_SCREAMING_SNAKE_CASE :       Optional[int]     		=      {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  ):
											_SCREAMING_SNAKE_CASE :       str     		=      self.__dict__.copy()
											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      None
											return state






							def __setstate__(    self    ,					__snake_case  ):
											_SCREAMING_SNAKE_CASE :       List[Any]     		=      d

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

											_SCREAMING_SNAKE_CASE :       Tuple     		=      spm.SentencePieceProcessor(**self.sp_model_kwargs  )
											self.sp_model.Load(self.vocab_file  )






							def UpperCAmelCase_	(    self    ,					__snake_case  ):
											if self.remove_space:
															_SCREAMING_SNAKE_CASE :       int     		=      """ """.join(inputs.strip().split()  )
											else:
															_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      inputs
											_SCREAMING_SNAKE_CASE :       List[Any]     		=      outputs.replace("""``"""    ,					"""\""""  ).replace("""''"""    ,					"""\""""  )

											if not self.keep_accents:
															_SCREAMING_SNAKE_CASE :       Any     		=      unicodedata.normalize("""NFKD"""    ,					__snake_case  )
															_SCREAMING_SNAKE_CASE :       Tuple     		=      """""".join([c for c in outputs if not unicodedata.combining(__snake_case  )]  )
											if self.do_lower_case:
															_SCREAMING_SNAKE_CASE :       Dict     		=      outputs.lower()

											return outputs






							def UpperCAmelCase_	(    self    ,					__snake_case  ):
											_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      self.preprocess_text(__snake_case  )
											_SCREAMING_SNAKE_CASE :       str     		=      self.sp_model.encode(__snake_case    ,					out_type=__snake_case  )
											_SCREAMING_SNAKE_CASE :       Optional[Any]     		=      []
											for piece in pieces:
															if len(__snake_case  ) > 1 and piece[-1] == str(""","""  ) and piece[-2].isdigit():
																			_SCREAMING_SNAKE_CASE :       Any     		=      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:
																											_SCREAMING_SNAKE_CASE :       Dict     		=      cur_pieces[1:]
																							else:
																											_SCREAMING_SNAKE_CASE :       int     		=      cur_pieces[0][1:]
																			cur_pieces.append(piece[-1]  )
																			new_pieces.extend(__snake_case  )
															else:
																			new_pieces.append(__snake_case  )

											return new_pieces






							def UpperCAmelCase_	(    self    ,					__snake_case  ):
											return self.sp_model.PieceToId(__snake_case  )






							def UpperCAmelCase_	(    self    ,					__snake_case  ):
											return self.sp_model.IdToPiece(__snake_case  )






							def UpperCAmelCase_	(    self    ,					__snake_case  ):
											_SCREAMING_SNAKE_CASE :       Optional[int]     		=      """""".join(__snake_case  ).replace(__snake_case    ,					""" """  ).strip()
											return out_string






							def UpperCAmelCase_	(    self    ,					__snake_case    ,					__snake_case = False    ,					__snake_case = None    ,					__snake_case = True    ,					**__snake_case    ,					):
											_SCREAMING_SNAKE_CASE :       List[str]     		=      kwargs.pop("""use_source_tokenizer"""    ,					__snake_case  )

											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      self.convert_ids_to_tokens(__snake_case    ,					skip_special_tokens=__snake_case  )

											# 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
											_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      []
											_SCREAMING_SNAKE_CASE :       str     		=      []
											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(__snake_case  )  )
																							_SCREAMING_SNAKE_CASE :       List[Any]     		=      []
																			sub_texts.append(__snake_case  )
															else:
																			current_sub_text.append(__snake_case  )
											if current_sub_text:
															sub_texts.append(self.convert_tokens_to_string(__snake_case  )  )

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

											_SCREAMING_SNAKE_CASE :       str     		=      (
											    clean_up_tokenization_spaces
											    if clean_up_tokenization_spaces is not None
											    else self.clean_up_tokenization_spaces
											)
											if clean_up_tokenization_spaces:
															_SCREAMING_SNAKE_CASE :       Any     		=      self.clean_up_tokenization(__snake_case  )
															return clean_text
											else:
															return text






							def UpperCAmelCase_	(    self    ,					__snake_case    ,					__snake_case = None  ):
											_SCREAMING_SNAKE_CASE :       str     		=      [self.sep_token_id]
											_SCREAMING_SNAKE_CASE :       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 UpperCAmelCase_	(    self    ,					__snake_case    ,					__snake_case = None    ,					__snake_case = False  ):

											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 UpperCAmelCase_	(    self    ,					__snake_case    ,					__snake_case = None  ):
											_SCREAMING_SNAKE_CASE :       str     		=      [self.sep_token_id]
											_SCREAMING_SNAKE_CASE :       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 UpperCAmelCase_	(    self    ,					__snake_case    ,					__snake_case = None  ):
											if not os.path.isdir(__snake_case  ):
															logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""  )
															return
											_SCREAMING_SNAKE_CASE :       int     		=      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:
																			_SCREAMING_SNAKE_CASE :       int     		=      self.sp_model.serialized_model_proto()
																			fi.write(__snake_case  )

											return (out_vocab_file,)








'''simple docstring'''


from __future__ import annotations

import os
from typing import Any

import requests

UpperCAmelCase_		:   List[Any]							   =		'https://api.github.com'

# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
UpperCAmelCase_		:   Optional[Any]							   =		BASE_URL + '/user'

# https://github.com/settings/tokens
UpperCAmelCase_		:   str							   =		os.environ.get('USER_TOKEN', '')







def 			snake_case_   (  SCREAMING_SNAKE_CASE__     ):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE :       Union[str, Any]     		=      {
				    """Authorization""": f"""token {auth_token}""",
				    """Accept""": """application/vnd.github.v3+json""",
				}
				return requests.get(SCREAMING_SNAKE_CASE__							,      headers=SCREAMING_SNAKE_CASE__     ).json()


if __name__ == "__main__":  # pragma: no cover
				if USER_TOKEN:
								for key, value in fetch_github_info(USER_TOKEN).items():
												print(F"{key}: {value}")
				else:
								raise ValueError('\'USER_TOKEN\' field cannot be empty.')




