




"""simple docstring"""



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

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE    =	logging.get_logger(__name__)

SCREAMING_SNAKE_CASE    =	"▁"

SCREAMING_SNAKE_CASE    =	{"vocab_file": "prophetnet.tokenizer"}

SCREAMING_SNAKE_CASE    =	{
    "vocab_file": {
        "microsoft/xprophetnet-large-wiki100-cased": (
            "https://huggingface.co/microsoft/xprophetnet-large-wiki100-cased/resolve/main/prophetnet.tokenizer"
        ),
    }
}

SCREAMING_SNAKE_CASE    =	{
    "microsoft/xprophetnet-large-wiki100-cased": {"do_lower_case": False},
}

SCREAMING_SNAKE_CASE    =	{
    "microsoft/xprophetnet-large-wiki100-cased": 512,
}







def   _SCREAMING_SNAKE_CASE       (							lowercase_						)						->		List[Any]:
 A__	=    collections.OrderedDict()
 with open(lowercase_      ,			"r"      ,			encoding="utf-8"						) as reader:
  A__	=    reader.readlines()
 for index, token in enumerate(lowercase_						):
  A__	=    token.rstrip("\n"						)
  A__	=    index
 return vocab






class      UpperCAmelCase_  (						A_							):
    lowercase__						 =				VOCAB_FILES_NAMES
    lowercase__						 =				PRETRAINED_VOCAB_FILES_MAP
    lowercase__						 =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    lowercase__						 =				['''input_ids''', '''attention_mask''']




    def __init__(   self						:	str     ,			snake_case_						:	str     ,			snake_case_						:	str="[SEP]"     ,			snake_case_						:	str="[SEP]"     ,			snake_case_						:	str="[SEP]"     ,			snake_case_						:	Union[str, Any]="[UNK]"     ,			snake_case_						:	int="[PAD]"     ,			snake_case_						:	List[Any]="[CLS]"     ,			snake_case_						:	Optional[Any]="[MASK]"     ,			snake_case_						:	Optional[Dict[str, Any]] = None     ,			**snake_case_						:	Dict     ,			)				->							None:




     '''simple docstring'''

     A__	=    {} if sp_model_kwargs is None else sp_model_kwargs

     super().__init__(
         bos_token=snake_case_     ,			eos_token=snake_case_     ,			sep_token=snake_case_     ,			unk_token=snake_case_     ,			pad_token=snake_case_     ,			cls_token=snake_case_     ,			mask_token=snake_case_     ,			sp_model_kwargs=self.sp_model_kwargs     ,			**snake_case_     ,			)

     try:
      import sentencepiece as spm
     except ImportError:
      logger.warning(
          "You need to install SentencePiece to use XLMRobertaTokenizer: https://github.com/google/sentencepiece"
          " pip install sentencepiece"				)
      raise

     A__	=    spm.SentencePieceProcessor(**self.sp_model_kwargs				)
     self.sp_model.Load(str(snake_case_				)				)
     A__	=    vocab_file

     # Original fairseq vocab and spm vocab must be "aligned":
     # Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
     # -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
     # fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
     # spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

     # put special tokens and [unused] tokens into the vocab
     A__	=    {"[PAD]": 0, "[CLS]": 1, "[SEP]": 2, "[UNK]": 3, "[MASK]": 4}

     for i in range(10				):
      A__	=    F"""[unused{i}]"""
      A__	=    5 + i

     # The first "real" token "," has position 15 in the embedding vocab and position 3 in the spm vocab
     A__	=    12
     A__	=    {v: k for k, v in self.fairseq_tokens_to_ids.items()}
     for k in self.fairseq_tokens_to_ids.keys():
      self.unique_no_split_tokens.append(snake_case_				)




    def __getstate__(   self						:	List[str]				)				->							Union[str, Any]:




     '''simple docstring'''

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




    def __setstate__(   self						:	Any     ,			snake_case_						:	List[str]				)				->							List[str]:




     '''simple docstring'''

     A__	=    d
     try:
      import sentencepiece as spm
     except ImportError:
      logger.warning(
          "You need to install SentencePiece to use XLMRobertaTokenizer: https://github.com/google/sentencepiece"
          " pip install sentencepiece"				)
      raise

     # 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 							__magic_name__							(   self						:	Tuple     ,			snake_case_						:	List[int]     ,			snake_case_						:	Optional[List[int]] = None     ,			snake_case_						:	bool = False				)				->							List[int]:




     '''simple docstring'''

     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 None:
      return ([0] * len(snake_case_				)) + [1]
     return ([0] * len(snake_case_				)) + [1] + ([0] * len(snake_case_				)) + [1]




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




     '''simple docstring'''

     A__	=    [self.sep_token_id]

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




    @property
    def 							__magic_name__							(   self						:	List[Any]				)				->							Optional[Any]:




     '''simple docstring'''

     return len(self.sp_model				) + self.fairseq_offset




    def 							__magic_name__							(   self						:	str				)				->							int:




     '''simple docstring'''

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




    def 							__magic_name__							(   self						:	Union[str, Any]     ,			snake_case_						:	str				)				->							str:




     '''simple docstring'''

     return self.sp_model.encode(snake_case_     ,			out_type=snake_case_				)




    def 							__magic_name__							(   self						:	Optional[int]     ,			snake_case_						:	List[Any]				)				->							str:




     '''simple docstring'''

     if token in self.fairseq_tokens_to_ids:
      return self.fairseq_tokens_to_ids[token]
     A__	=    self.sp_model.PieceToId(snake_case_				)

     # Need to return unknown token if the SP model returned 0
     return spm_id + self.fairseq_offset if spm_id else self.unk_token_id




    def 							__magic_name__							(   self						:	str     ,			snake_case_						:	Union[str, Any]				)				->							Tuple:




     '''simple docstring'''

     if index in self.fairseq_ids_to_tokens:
      return self.fairseq_ids_to_tokens[index]
     return self.sp_model.IdToPiece(index - self.fairseq_offset				)




    def 							__magic_name__							(   self						:	str     ,			snake_case_						:	int				)				->							List[Any]:




     '''simple docstring'''

     A__	=    "".join(snake_case_				).replace(snake_case_     ,			" "				).strip()
     return out_string




    def 							__magic_name__							(   self						:	Optional[Any]     ,			snake_case_						:	str     ,			snake_case_						:	Optional[str] = None				)				->							Tuple[str]:




     '''simple docstring'''

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

     return (out_vocab_file,)




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




     '''simple docstring'''

     if token_ids_a is None:
      return token_ids_a + [self.sep_token_id]
     A__	=    [self.sep_token_id]
     return token_ids_a + sep + token_ids_a + sep











"""simple docstring"""



SCREAMING_SNAKE_CASE    =	[
    999,
    800,
    799,
    600,
    599,
    500,
    400,
    399,
    377,
    355,
    333,
    311,
    288,
    266,
    244,
    222,
    200,
    199,
    177,
    155,
    133,
    111,
    88,
    66,
    44,
    22,
    0,
]

SCREAMING_SNAKE_CASE    =	[
    999,
    976,
    952,
    928,
    905,
    882,
    858,
    857,
    810,
    762,
    715,
    714,
    572,
    429,
    428,
    286,
    285,
    238,
    190,
    143,
    142,
    118,
    95,
    71,
    47,
    24,
    0,
]

SCREAMING_SNAKE_CASE    =	[
    999,
    988,
    977,
    966,
    955,
    944,
    933,
    922,
    911,
    900,
    899,
    879,
    859,
    840,
    820,
    800,
    799,
    766,
    733,
    700,
    699,
    650,
    600,
    599,
    500,
    499,
    400,
    399,
    350,
    300,
    299,
    266,
    233,
    200,
    199,
    179,
    159,
    140,
    120,
    100,
    99,
    88,
    77,
    66,
    55,
    44,
    33,
    22,
    11,
    0,
]

SCREAMING_SNAKE_CASE    =	[
    999,
    995,
    992,
    989,
    985,
    981,
    978,
    975,
    971,
    967,
    964,
    961,
    957,
    956,
    951,
    947,
    942,
    937,
    933,
    928,
    923,
    919,
    914,
    913,
    908,
    903,
    897,
    892,
    887,
    881,
    876,
    871,
    870,
    864,
    858,
    852,
    846,
    840,
    834,
    828,
    827,
    820,
    813,
    806,
    799,
    792,
    785,
    784,
    777,
    770,
    763,
    756,
    749,
    742,
    741,
    733,
    724,
    716,
    707,
    699,
    698,
    688,
    677,
    666,
    656,
    655,
    645,
    634,
    623,
    613,
    612,
    598,
    584,
    570,
    569,
    555,
    541,
    527,
    526,
    505,
    484,
    483,
    462,
    440,
    439,
    396,
    395,
    352,
    351,
    308,
    307,
    264,
    263,
    220,
    219,
    176,
    132,
    88,
    44,
    0,
]

SCREAMING_SNAKE_CASE    =	[
    999,
    997,
    995,
    992,
    990,
    988,
    986,
    984,
    981,
    979,
    977,
    975,
    972,
    970,
    968,
    966,
    964,
    961,
    959,
    957,
    956,
    954,
    951,
    949,
    946,
    944,
    941,
    939,
    936,
    934,
    931,
    929,
    926,
    924,
    921,
    919,
    916,
    914,
    913,
    910,
    907,
    905,
    902,
    899,
    896,
    893,
    891,
    888,
    885,
    882,
    879,
    877,
    874,
    871,
    870,
    867,
    864,
    861,
    858,
    855,
    852,
    849,
    846,
    843,
    840,
    837,
    834,
    831,
    828,
    827,
    824,
    821,
    817,
    814,
    811,
    808,
    804,
    801,
    798,
    795,
    791,
    788,
    785,
    784,
    780,
    777,
    774,
    770,
    766,
    763,
    760,
    756,
    752,
    749,
    746,
    742,
    741,
    737,
    733,
    730,
    726,
    722,
    718,
    714,
    710,
    707,
    703,
    699,
    698,
    694,
    690,
    685,
    681,
    677,
    673,
    669,
    664,
    660,
    656,
    655,
    650,
    646,
    641,
    636,
    632,
    627,
    622,
    618,
    613,
    612,
    607,
    602,
    596,
    591,
    586,
    580,
    575,
    570,
    569,
    563,
    557,
    551,
    545,
    539,
    533,
    527,
    526,
    519,
    512,
    505,
    498,
    491,
    484,
    483,
    474,
    466,
    457,
    449,
    440,
    439,
    428,
    418,
    407,
    396,
    395,
    381,
    366,
    352,
    351,
    330,
    308,
    307,
    286,
    264,
    263,
    242,
    220,
    219,
    176,
    175,
    132,
    131,
    88,
    44,
    0,
]

SCREAMING_SNAKE_CASE    =	[
    999,
    991,
    982,
    974,
    966,
    958,
    950,
    941,
    933,
    925,
    916,
    908,
    900,
    899,
    874,
    850,
    825,
    800,
    799,
    700,
    600,
    500,
    400,
    300,
    200,
    100,
    0,
]

SCREAMING_SNAKE_CASE    =	[
    999,
    992,
    985,
    978,
    971,
    964,
    957,
    949,
    942,
    935,
    928,
    921,
    914,
    907,
    900,
    899,
    879,
    859,
    840,
    820,
    800,
    799,
    766,
    733,
    700,
    699,
    650,
    600,
    599,
    500,
    499,
    400,
    399,
    300,
    299,
    200,
    199,
    100,
    99,
    0,
]

SCREAMING_SNAKE_CASE    =	[
    999,
    996,
    992,
    989,
    985,
    982,
    979,
    975,
    972,
    968,
    965,
    961,
    958,
    955,
    951,
    948,
    944,
    941,
    938,
    934,
    931,
    927,
    924,
    920,
    917,
    914,
    910,
    907,
    903,
    900,
    899,
    891,
    884,
    876,
    869,
    861,
    853,
    846,
    838,
    830,
    823,
    815,
    808,
    800,
    799,
    788,
    777,
    766,
    755,
    744,
    733,
    722,
    711,
    700,
    699,
    688,
    677,
    666,
    655,
    644,
    633,
    622,
    611,
    600,
    599,
    585,
    571,
    557,
    542,
    528,
    514,
    500,
    499,
    485,
    471,
    457,
    442,
    428,
    414,
    400,
    399,
    379,
    359,
    340,
    320,
    300,
    299,
    279,
    259,
    240,
    220,
    200,
    199,
    166,
    133,
    100,
    99,
    66,
    33,
    0,
]





