


"""simple docstring"""





import os
from shutil import copyfile
from typing import Optional, Tuple

from ...file_utils import is_sentencepiece_available
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging


if is_sentencepiece_available():
   from .tokenization_deberta_va import DebertaVaTokenizer
else:
   __UpperCAmelCase    				=      None

__UpperCAmelCase    				=      logging.get_logger(__name__)

__UpperCAmelCase    				=      {"vocab_file": "spm.model", "tokenizer_file": "tokenizer.json"}

__UpperCAmelCase    				=      {
    "vocab_file": {
        "microsoft/deberta-v2-xlarge": "https://huggingface.co/microsoft/deberta-v2-xlarge/resolve/main/spm.model",
        "microsoft/deberta-v2-xxlarge": "https://huggingface.co/microsoft/deberta-v2-xxlarge/resolve/main/spm.model",
        "microsoft/deberta-v2-xlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-v2-xlarge-mnli/resolve/main/spm.model"
        ),
        "microsoft/deberta-v2-xxlarge-mnli": (
            "https://huggingface.co/microsoft/deberta-v2-xxlarge-mnli/resolve/main/spm.model"
        ),
    }
}

__UpperCAmelCase    				=      {
    "microsoft/deberta-v2-xlarge": 512,
    "microsoft/deberta-v2-xxlarge": 512,
    "microsoft/deberta-v2-xlarge-mnli": 512,
    "microsoft/deberta-v2-xxlarge-mnli": 512,
}

__UpperCAmelCase    				=      {
    "microsoft/deberta-v2-xlarge": {"do_lower_case": False},
    "microsoft/deberta-v2-xxlarge": {"do_lower_case": False},
    "microsoft/deberta-v2-xlarge-mnli": {"do_lower_case": False},
    "microsoft/deberta-v2-xxlarge-mnli": {"do_lower_case": False},
}

class  lowercase_  ( a_						):
      __magic_name__     :							Dict          =				VOCAB_FILES_NAMES
      __magic_name__     :							Any          =				PRETRAINED_VOCAB_FILES_MAP
      __magic_name__     :							int          =				PRETRAINED_INIT_CONFIGURATION
      __magic_name__     :							str          =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      __magic_name__     :							List[Any]          =				DebertaVaTokenizer







      def __init__(      self :							List[str]		,  _lowercase :							List[str]=None		,  _lowercase :							str=None		,  _lowercase :							str=False		,  _lowercase :							Tuple=False		,  _lowercase :							str="[CLS]"		,  _lowercase :							Optional[int]="[SEP]"		,  _lowercase :							Dict="[UNK]"		,  _lowercase :							Optional[int]="[SEP]"		,  _lowercase :							Optional[int]="[PAD]"		,  _lowercase :							str="[CLS]"		,  _lowercase :							Optional[int]="[MASK]"		,  **_lowercase :							List[Any]		,  ):
        super().__init__(
            _lowercase		,  tokenizer_file=_lowercase		,  do_lower_case=_lowercase		,  bos_token=_lowercase		,  eos_token=_lowercase		,  unk_token=_lowercase		,  sep_token=_lowercase		,  pad_token=_lowercase		,  cls_token=_lowercase		,  mask_token=_lowercase		,  split_by_punct=_lowercase		,  **_lowercase		,  )

        lowerCAmelCase__    :    List[str]								=					do_lower_case
        lowerCAmelCase__    :    Union[str, Any]								=					split_by_punct
        lowerCAmelCase__    :    Dict								=					vocab_file
        lowerCAmelCase__    :    str								=					False if not self.vocab_file else True







      def 				_lowerCAmelCase       (      self :							Dict		,  _lowercase :							Optional[int]		,  _lowercase :							Dict=None    ):

        if token_ids_a is None:
          return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        lowerCAmelCase__    :    Tuple								=					[self.cls_token_id]
        lowerCAmelCase__    :    Dict								=					[self.sep_token_id]
        return cls + token_ids_a + sep + token_ids_a + sep







      def 				_lowerCAmelCase       (      self :							Tuple		,  _lowercase :							str		,  _lowercase :							Dict=None		,  _lowercase :							str=False    ):

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

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







      def 				_lowerCAmelCase       (      self :							List[str]		,  _lowercase :							Any		,  _lowercase :							Optional[Any]=None    ):
        lowerCAmelCase__    :    Any								=					[self.sep_token_id]
        lowerCAmelCase__    :    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    ) * [0] + len(token_ids_a + sep    ) * [1]







      def 				_lowerCAmelCase       (      self :							List[str]		,  _lowercase :							str		,  _lowercase :							Optional[str] = None    ):
        if not self.can_save_slow_tokenizer:
          raise ValueError(
              "Your fast tokenizer does not have the necessary information to save the vocabulary for a slow "
              "tokenizer."    )

        if not os.path.isdir(_lowercase    ):
          logger.error(f"Vocabulary path ({save_directory}) should be a directory"    )
          return
        lowerCAmelCase__    :    str								=					os.path.join(
            _lowercase		,  (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]    )

        if os.path.abspath(self.vocab_file    ) != os.path.abspath(_lowercase    ):
          copyfile(self.vocab_file		,  _lowercase    )

        return (out_vocab_file,)




"""simple docstring"""





from __future__ import annotations

__UpperCAmelCase    				=      [2, 1, 4, 5, 6, 0, 8, 9, 1, 2, 0, 6, 4, 2, 0, 6, 5, 3, 2, 7]

class  lowercase_  :







      def __init__(      self :							int		,  _lowercase :							int    ):
        lowerCAmelCase__    :    int								=					-1
        lowerCAmelCase__    :    int								=					-1
        lowerCAmelCase__    :    list[int]								=					[-1] * length
        lowerCAmelCase__    :    Node | None								=					None
        lowerCAmelCase__    :    Node | None								=					None







      def __repr__(      self :							List[Any]    ):
        return f"Node(min_value={self.minn} max_value={self.maxx})"





def     lowercase__	(  lowerCamelCase     :  list[int]				)					->     Node | None:
  lowerCAmelCase__    :    Any								=					Node(len(lowerCamelCase				)				)
  lowerCAmelCase__				,		lowerCAmelCase__    :    Any								=					min(lowerCamelCase				), max(lowerCamelCase				)
  # Leaf node case where the node contains only one unique value
  if root.minn == root.maxx:
    return root
  lowerCAmelCase__    :    str								=					(root.minn + root.maxx) // 2

  lowerCAmelCase__    :    list[int]								=					[]
  lowerCAmelCase__    :    list[int]								=					[]

  for index, num in enumerate(lowerCamelCase				):
    if num <= pivot:
      left_arr.append(lowerCamelCase				)
    else:
      right_arr.append(lowerCamelCase				)
    lowerCAmelCase__    :    Optional[Any]								=					len(lowerCamelCase				)
  lowerCAmelCase__    :    List[str]								=					build_tree(lowerCamelCase				)
  lowerCAmelCase__    :    List[Any]								=					build_tree(lowerCamelCase				)
  return root





def     lowercase__	(  lowerCamelCase     :  Node | None				,	lowerCamelCase     :  int				,	lowerCamelCase     :  int				)					->     int:
  if index < 0 or node is None:
    return 0
  # Leaf node cases
  if node.minn == node.maxx:
    return index + 1 if node.minn == num else 0
  lowerCAmelCase__    :    int								=					(node.minn + node.maxx) // 2
  if num <= pivot:
    # go the left subtree and map index to the left subtree
    return rank_till_index(node.left				,	lowerCamelCase				,	node.map_left[index] - 1				)
  else:
    # go to the right subtree and map index to the right subtree
    return rank_till_index(node.right				,	lowerCamelCase				,	index - node.map_left[index]				)





def     lowercase__	(  lowerCamelCase     :  Node | None				,	lowerCamelCase     :  int				,	lowerCamelCase     :  int				,	lowerCamelCase     :  int				)					->     int:
  if start > end:
    return 0
  lowerCAmelCase__    :    int								=					rank_till_index(lowerCamelCase				,	lowerCamelCase				,	lowerCamelCase				)
  lowerCAmelCase__    :    Optional[Any]								=					rank_till_index(lowerCamelCase				,	lowerCamelCase				,	start - 1				)
  return rank_till_end - rank_before_start





def     lowercase__	(  lowerCamelCase     :  Node | None				,	lowerCamelCase     :  int				,	lowerCamelCase     :  int				,	lowerCamelCase     :  int				)					->     int:
  if index > (end - start) or start > end or node is None:
    return -1
  # Leaf node case
  if node.minn == node.maxx:
    return node.minn
  # Number of elements in the left subtree in interval [start, end]
  lowerCAmelCase__    :    List[str]								=					node.map_left[end] - (
      node.map_left[start - 1] if start else 0
  )
  if num_elements_in_left_tree > index:
    return quantile(
        node.left				,	lowerCamelCase				,	(node.map_left[start - 1] if start else 0)				,	node.map_left[end] - 1				,	)
  else:
    return quantile(
        node.right				,	index - num_elements_in_left_tree				,	start - (node.map_left[start - 1] if start else 0)				,	end - node.map_left[end]				,	)





def     lowercase__	(  lowerCamelCase     :  Node | None				,	lowerCamelCase     :  int				,	lowerCamelCase     :  int				,	lowerCamelCase     :  int				,	lowerCamelCase     :  int				)					->     int:
  if (
      start > end
      or node is None
      or start_num > end_num
      or node.minn > end_num
      or node.maxx < start_num
  ):
    return 0
  if start_num <= node.minn and node.maxx <= end_num:
    return end - start + 1
  lowerCAmelCase__    :    List[str]								=					range_counting(
      node.left				,	(node.map_left[start - 1] if start else 0)				,	node.map_left[end] - 1				,	lowerCamelCase				,	lowerCamelCase				,	)
  lowerCAmelCase__    :    List[str]								=					range_counting(
      node.right				,	start - (node.map_left[start - 1] if start else 0)				,	end - node.map_left[end]				,	lowerCamelCase				,	lowerCamelCase				,	)
  return left + right


if __name__ == "__main__":
   import doctest

   doctest.testmod()
