
"""simple docstring"""




import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


_A			:       Tuple   		=       logging.get_logger(__name__)


_A			:       Union[str, Any]   		=       {"""vocab_file""": """vocab.json""", """merges_file""": """merges.txt"""}

_A			:       int   		=       {
    """vocab_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"""
        ),
    },
    """merges_file""": {
        """allenai/longformer-base-4096""": """https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt""",
        """allenai/longformer-large-4096""": (
            """https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-finetuned-triviaqa""": (
            """https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"""
        ),
        """allenai/longformer-base-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
        """allenai/longformer-large-4096-extra.pos.embd.only""": (
            """https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"""
        ),
    },
}

_A			:       str   		=       {
    """allenai/longformer-base-4096""": 40_96,
    """allenai/longformer-large-4096""": 40_96,
    """allenai/longformer-large-4096-finetuned-triviaqa""": 40_96,
    """allenai/longformer-base-4096-extra.pos.embd.only""": 40_96,
    """allenai/longformer-large-4096-extra.pos.embd.only""": 40_96,
}


@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def   __magic_name__	(      ) ->				str:
       lowercase    :				Dict       		=							(
           list(range(ord("!"  )     , ord("~"  ) + 1  )  ) + list(range(ord("¡"  )     , ord("¬"  ) + 1  )  ) + list(range(ord("®"  )     , ord("ÿ"  ) + 1  )  )
       )
       lowercase    :				List[Any]       		=							bs[:]
       lowercase    :				Any       		=							0
       for b in range(2**8  ):
              if b not in bs:
                     bs.append(__snake_case  )
                     cs.append(2**8 + n  )
                     n += 1
       lowercase    :				Optional[Any]       		=							[chr(__snake_case  ) for n in cs]
       return dict(zip(__snake_case     , __snake_case  )  )


def   __magic_name__	(      __snake_case				:       Union[str, Any]  ) ->				Optional[Any]:
       lowercase    :				List[str]       		=							set()
       lowercase    :				Union[str, Any]       		=							word[0]
       for char in word[1:]:
              pairs.add((prev_char, char)  )
              lowercase    :				Optional[int]       		=							char
       return pairs

class 		a__						(      a_						):
   __lowerCAmelCase            =				VOCAB_FILES_NAMES
   __lowerCAmelCase            =				PRETRAINED_VOCAB_FILES_MAP
   __lowerCAmelCase            =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __lowerCAmelCase            =				["""input_ids""", """attention_mask"""]
   def __init__(			self	,    _a	,    _a	,    _a="replace"	,    _a="<s>"	,    _a="</s>"	,    _a="</s>"	,    _a="<s>"	,    _a="<unk>"	,    _a="<pad>"	,    _a="<mask>"	,    _a=False	,    **_a	,    ):
          lowercase    :				Optional[Any]       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else bos_token
          lowercase    :				Dict       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else eos_token
          lowercase    :				Dict       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else sep_token
          lowercase    :				List[str]       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else cls_token
          lowercase    :				Dict       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else unk_token
          lowercase    :				Tuple       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else pad_token

          # Mask token behave like a normal word, i.e. include the space before it
          lowercase    :				str       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else mask_token

          super().__init__(
              errors=_a	,    bos_token=_a	,    eos_token=_a	,    unk_token=_a	,    sep_token=_a	,    cls_token=_a	,    pad_token=_a	,    mask_token=_a	,    add_prefix_space=_a	,    **_a	,    )

          with open(_a	,    encoding="utf-8"				) as vocab_handle:
                 lowercase    :				Optional[int]       		=							json.load(_a				)
          lowercase    :				Optional[Any]       		=							{v: k for k, v in self.encoder.items()}
          lowercase    :				Dict       		=							errors  # how to handle errors in decoding
          lowercase    :				List[str]       		=							bytes_to_unicode()
          lowercase    :				Optional[int]       		=							{v: k for k, v in self.byte_encoder.items()}
          with open(_a	,    encoding="utf-8"				) as merges_handle:
                 lowercase    :				Any       		=							merges_handle.read().split("\n"				)[1:-1]
          lowercase    :				Tuple       		=							[tuple(merge.split()				) for merge in bpe_merges]
          lowercase    :				List[str]       		=							dict(zip(_a	,    range(len(_a				)				)				)				)
          lowercase    :				Tuple       		=							{}
          lowercase    :				Union[str, Any]       		=							add_prefix_space

          # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
          lowercase    :				str       		=							re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"				)
   @property
   def 			__magic_name__			(			self				):
          return len(self.encoder				)
   def 			__magic_name__			(			self				):
          return dict(self.encoder	,    **self.added_tokens_encoder				)
   def 			__magic_name__			(			self	,    _a				):
          if token in self.cache:
                 return self.cache[token]
          lowercase    :				List[Any]       		=							tuple(_a				)
          lowercase    :				List[str]       		=							get_pairs(_a				)

          if not pairs:
                 return token

          while True:
                 lowercase    :				Optional[Any]       		=							min(_a	,    key=lambda _a				: self.bpe_ranks.get(_a	,    float("inf"				)				)				)
                 if bigram not in self.bpe_ranks:
                        break
                 lowercase		,    lowercase    :				Union[str, Any]       		=							bigram
                 lowercase    :				List[Any]       		=							[]
                 lowercase    :				Dict       		=							0
                 while i < len(_a				):
                        try:
                               lowercase    :				Union[str, Any]       		=							word.index(_a	,    _a				)
                        except ValueError:
                               new_word.extend(word[i:]				)
                               break
                        else:
                               new_word.extend(word[i:j]				)
                               lowercase    :				Any       		=							j

                        if word[i] == first and i < len(_a				) - 1 and word[i + 1] == second:
                               new_word.append(first + second				)
                               i += 2
                        else:
                               new_word.append(word[i]				)
                               i += 1
                 lowercase    :				Dict       		=							tuple(_a				)
                 lowercase    :				int       		=							new_word
                 if len(_a				) == 1:
                        break
                 else:
                        lowercase    :				Tuple       		=							get_pairs(_a				)
          lowercase    :				Optional[int]       		=							" ".join(_a				)
          lowercase    :				Union[str, Any]       		=							word
          return word
   def 			__magic_name__			(			self	,    _a				):
          lowercase    :				List[Any]       		=							[]
          for token in re.findall(self.pat	,    _a				):
                 lowercase    :				List[str]       		=							"".join(
                     self.byte_encoder[b] for b in token.encode("utf-8"				)				)  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
                 bpe_tokens.extend(bpe_token for bpe_token in self.bpe(_a				).split(" "				)				)
          return bpe_tokens
   def 			__magic_name__			(			self	,    _a				):
          return self.encoder.get(_a	,    self.encoder.get(self.unk_token				)				)
   def 			__magic_name__			(			self	,    _a				):
          return self.decoder.get(_a				)
   def 			__magic_name__			(			self	,    _a				):
          lowercase    :				Optional[int]       		=							"".join(_a				)
          lowercase    :				Dict       		=							bytearray([self.byte_decoder[c] for c in text]				).decode("utf-8"	,    errors=self.errors				)
          return text
   def 			__magic_name__			(			self	,    _a	,    _a = None				):
          if not os.path.isdir(_a				):
                 logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
                 return
          lowercase    :				List[Any]       		=							os.path.join(
              _a	,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]				)
          lowercase    :				Any       		=							os.path.join(
              _a	,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]				)

          with open(_a	,    "w"	,    encoding="utf-8"				) as f:
                 f.write(json.dumps(self.encoder	,    indent=2	,    sort_keys=_a	,    ensure_ascii=_a				) + "\n"				)

          lowercase    :				List[str]       		=							0
          with open(_a	,    "w"	,    encoding="utf-8"				) as writer:
                 writer.write("#version: 0.2\n"				)
                 for bpe_tokens, token_index in sorted(self.bpe_ranks.items()	,    key=lambda _a				: kv[1]				):
                        if index != token_index:
                               logger.warning(
                                   f"""Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."""
                                   " Please check that the tokenizer is not corrupted!"				)
                               lowercase    :				Dict       		=							token_index
                        writer.write(" ".join(_a				) + "\n"				)
                        index += 1

          return vocab_file, merge_file
   def 			__magic_name__			(			self	,    _a	,    _a = None				):
          if token_ids_a is None:
                 return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          lowercase    :				Any       		=							[self.cls_token_id]
          lowercase    :				Optional[Any]       		=							[self.sep_token_id]
          return cls + token_ids_a + sep + sep + token_ids_a + sep
   def 			__magic_name__			(			self	,    _a	,    _a = None	,    _a = False				):
          if already_has_special_tokens:
                 return super().get_special_tokens_mask(
                     token_ids_a=_a	,    token_ids_a=_a	,    already_has_special_tokens=_a				)

          if token_ids_a is None:
                 return [1] + ([0] * len(_a				)) + [1]
          return [1] + ([0] * len(_a				)) + [1, 1] + ([0] * len(_a				)) + [1]
   def 			__magic_name__			(			self	,    _a	,    _a = None				):
          lowercase    :				str       		=							[self.sep_token_id]
          lowercase    :				List[Any]       		=							[self.cls_token_id]

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

   def 			__magic_name__			(			self	,    _a	,    _a=False	,    **_a				):
          lowercase    :				Any       		=							kwargs.pop("add_prefix_space"	,    self.add_prefix_space				)
          if (is_split_into_words or add_prefix_space) and (len(_a				) > 0 and not text[0].isspace()):
                 lowercase    :				Any       		=							" " + text
          return (text, kwargs)




"""simple docstring"""




import os
import re
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 logging


_A			:       List[str]   		=       logging.get_logger(__name__)

_A			:       List[str]   		=       {"""vocab_file""": """spiece.model"""}

_A			:       List[Any]   		=       {
    """vocab_file""": {
        """google/bigbird-roberta-base""": """https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model""",
        """google/bigbird-roberta-large""": (
            """https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"""
        ),
        """google/bigbird-base-trivia-itc""": (
            """https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"""
        ),
    }
}

_A			:       str   		=       {
    """google/bigbird-roberta-base""": 40_96,
    """google/bigbird-roberta-large""": 40_96,
    """google/bigbird-base-trivia-itc""": 40_96,
}

class 		a__						(      a_						):
   __lowerCAmelCase            =				VOCAB_FILES_NAMES
   __lowerCAmelCase            =				PRETRAINED_VOCAB_FILES_MAP
   __lowerCAmelCase            =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   __lowerCAmelCase            =				["""input_ids""", """attention_mask"""]
   __lowerCAmelCase            =				[]
   def __init__(			self	,    _a	,    _a="<unk>"	,    _a="<s>"	,    _a="</s>"	,    _a="<pad>"	,    _a="[SEP]"	,    _a="[MASK]"	,    _a="[CLS]"	,    _a = None	,    **_a	,    ):
          lowercase    :				Dict       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else bos_token
          lowercase    :				Any       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else eos_token
          lowercase    :				Any       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else unk_token
          lowercase    :				List[Any]       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else pad_token
          lowercase    :				Any       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else cls_token
          lowercase    :				Any       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else sep_token

          # Mask token behave like a normal word, i.e. include the space before it
          lowercase    :				List[Any]       		=							AddedToken(_a	,    lstrip=_a	,    rstrip=_a				) if isinstance(_a	,    _a				) else mask_token

          lowercase    :				Optional[int]       		=							{} if sp_model_kwargs is None else sp_model_kwargs

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

          lowercase    :				Optional[Any]       		=							vocab_file

          lowercase    :				List[str]       		=							spm.SentencePieceProcessor(**self.sp_model_kwargs				)
          self.sp_model.Load(_a				)
   @property
   def 			__magic_name__			(			self				):
          return self.sp_model.get_piece_size()
   def 			__magic_name__			(			self				):
          lowercase    :				str       		=							{self.convert_ids_to_tokens(_a				): i for i in range(self.vocab_size				)}
          vocab.update(self.added_tokens_encoder				)
          return vocab
   def __getstate__(			self				):
          lowercase    :				Union[str, Any]       		=							self.__dict__.copy()
          lowercase    :				Dict       		=							None
          return state
   def __setstate__(			self	,    _a				):
          lowercase    :				str       		=							d

          # for backward compatibility
          if not hasattr(self	,    "sp_model_kwargs"				):
                 lowercase    :				List[str]       		=							{}

          lowercase    :				Any       		=							spm.SentencePieceProcessor(**self.sp_model_kwargs				)
          self.sp_model.Load(self.vocab_file				)
   def 			__magic_name__			(			self	,    _a				):
          return self.sp_model.encode(_a	,    out_type=_a				)
   def 			__magic_name__			(			self	,    _a				):
          return self.sp_model.piece_to_id(_a				)
   def 			__magic_name__			(			self	,    _a				):
          lowercase    :				Union[str, Any]       		=							self.sp_model.IdToPiece(_a				)
          return token
   def 			__magic_name__			(			self	,    _a				):
          lowercase    :				List[Any]       		=							[]
          lowercase    :				List[Any]       		=							""
          lowercase    :				List[Any]       		=							False
          for token in tokens:
                 # make sure that special tokens are not decoded using sentencepiece model
                 if token in self.all_special_tokens:
                        if not prev_is_special:
                               out_string += " "
                        out_string += self.sp_model.decode(_a				) + token
                        lowercase    :				int       		=							True
                        lowercase    :				Union[str, Any]       		=							[]
                 else:
                        current_sub_tokens.append(_a				)
                        lowercase    :				int       		=							False
          out_string += self.sp_model.decode(_a				)
          return out_string.strip()
   def 			__magic_name__			(			self	,    _a	,    _a = False	,    _a = None	,    _a = True	,    **_a	,    ):
          lowercase    :				int       		=							kwargs.pop("use_source_tokenizer"	,    _a				)

          lowercase    :				Union[str, Any]       		=							self.convert_ids_to_tokens(_a	,    skip_special_tokens=_a				)

          # 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    :				Any       		=							[]
          lowercase    :				Dict       		=							[]
          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(_a				)				)
                               lowercase    :				int       		=							[]
                        sub_texts.append(_a				)
                 else:
                        current_sub_text.append(_a				)
          if current_sub_text:
                 sub_texts.append(self.convert_tokens_to_string(_a				)				)

          # Mimic the behavior of the Rust tokenizer:
          # No space before [MASK] and [SEP]
          if spaces_between_special_tokens:
                 lowercase    :				Dict       		=							re.sub(R" (\[(MASK|SEP)\])"	,    R"\1"	,    " ".join(_a				)				)
          else:
                 lowercase    :				Union[str, Any]       		=							"".join(_a				)

          lowercase    :				int       		=							(
              clean_up_tokenization_spaces
              if clean_up_tokenization_spaces is not None
              else self.clean_up_tokenization_spaces
          )
          if clean_up_tokenization_spaces:
                 lowercase    :				Union[str, Any]       		=							self.clean_up_tokenization(_a				)
                 return clean_text
          else:
                 return text
   def 			__magic_name__			(			self	,    _a	,    _a = None				):
          if not os.path.isdir(_a				):
                 logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""				)
                 return
          lowercase    :				List[Any]       		=							os.path.join(
              _a	,    (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]				)

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

          return (out_vocab_file,)
   def 			__magic_name__			(			self	,    _a	,    _a = None				):
          if token_ids_a is None:
                 return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
          lowercase    :				List[str]       		=							[self.cls_token_id]
          lowercase    :				Tuple       		=							[self.sep_token_id]
          return cls + token_ids_a + sep + token_ids_a + sep
   def 			__magic_name__			(			self	,    _a	,    _a = None	,    _a = False				):
          if already_has_special_tokens:
                 return super().get_special_tokens_mask(
                     token_ids_a=_a	,    token_ids_a=_a	,    already_has_special_tokens=_a				)

          if token_ids_a is None:
                 return [1] + ([0] * len(_a				)) + [1]
          return [1] + ([0] * len(_a				)) + [1] + ([0] * len(_a				)) + [1]

   def 			__magic_name__			(			self	,    _a	,    _a = None				):
          lowercase    :				Tuple       		=							[self.sep_token_id]
          lowercase    :				Tuple       		=							[self.cls_token_id]
          if token_ids_a is None:
                 return len(cls + token_ids_a + sep				) * [0]
          return len(cls + token_ids_a + sep				) * [0] + len(token_ids_a + sep				) * [1]


