

import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roberta import RobertaTokenizer


lowerCAmelCase__       = logging.get_logger(__name__)

lowerCAmelCase__       = {"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

lowerCAmelCase__       = {
    "vocab_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/vocab.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/vocab.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/vocab.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/vocab.json",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/vocab.json",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/merges.txt",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/merges.txt",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/merges.txt",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/merges.txt",
        "roberta-base-openai-detector": "https://huggingface.co/roberta-base-openai-detector/resolve/main/merges.txt",
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/merges.txt"
        ),
    },
    "tokenizer_file": {
        "roberta-base": "https://huggingface.co/roberta-base/resolve/main/tokenizer.json",
        "roberta-large": "https://huggingface.co/roberta-large/resolve/main/tokenizer.json",
        "roberta-large-mnli": "https://huggingface.co/roberta-large-mnli/resolve/main/tokenizer.json",
        "distilroberta-base": "https://huggingface.co/distilroberta-base/resolve/main/tokenizer.json",
        "roberta-base-openai-detector": (
            "https://huggingface.co/roberta-base-openai-detector/resolve/main/tokenizer.json"
        ),
        "roberta-large-openai-detector": (
            "https://huggingface.co/roberta-large-openai-detector/resolve/main/tokenizer.json"
        ),
    },
}

lowerCAmelCase__       = {
    "roberta-base": 512,
    "roberta-large": 512,
    "roberta-large-mnli": 512,
    "distilroberta-base": 512,
    "roberta-base-openai-detector": 512,
    "roberta-large-openai-detector": 512,
}






class 						__magic_name__    (       _snake_case    ):
 UpperCAmelCase							    =						VOCAB_FILES_NAMES
 UpperCAmelCase							    =						PRETRAINED_VOCAB_FILES_MAP
 UpperCAmelCase							    =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 UpperCAmelCase							    =						["""input_ids""", """attention_mask"""]
 UpperCAmelCase							    =						RobertaTokenizer


 def __init__(						self		: Dict			,						lowerCAmelCase__		: List[Any]=None			,						lowerCAmelCase__		: List[Any]=None			,						lowerCAmelCase__		: Optional[Any]=None			,						lowerCAmelCase__		: List[str]="replace"			,						lowerCAmelCase__		: List[Any]="<s>"			,						lowerCAmelCase__		: str="</s>"			,						lowerCAmelCase__		: Optional[int]="</s>"			,						lowerCAmelCase__		: Dict="<s>"			,						lowerCAmelCase__		: Tuple="<unk>"			,						lowerCAmelCase__		: List[Any]="<pad>"			,						lowerCAmelCase__		: Any="<mask>"			,						lowerCAmelCase__		: Optional[Any]=False			,						lowerCAmelCase__		: Union[str, Any]=True			,						**lowerCAmelCase__		: Tuple			,						)    ->      Tuple:
   super().__init__(
       lowerCAmelCase__			,						lowerCAmelCase__			,						tokenizer_file=lowerCAmelCase__			,						errors=lowerCAmelCase__			,						bos_token=lowerCAmelCase__			,						eos_token=lowerCAmelCase__			,						sep_token=lowerCAmelCase__			,						cls_token=lowerCAmelCase__			,						unk_token=lowerCAmelCase__			,						pad_token=lowerCAmelCase__			,						mask_token=lowerCAmelCase__			,						add_prefix_space=lowerCAmelCase__			,						trim_offsets=lowerCAmelCase__			,						**lowerCAmelCase__			,						)

   UpperCAmelCase					      =  json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()    )
   if pre_tok_state.get("add_prefix_space"			,						lowerCAmelCase__    ) != add_prefix_space:
     UpperCAmelCase					      =  getattr(lowerCAmelCase__			,						pre_tok_state.pop("type"    )    )
     UpperCAmelCase					      =  add_prefix_space
     UpperCAmelCase					      =  pre_tok_class(**lowerCAmelCase__    )

   UpperCAmelCase					      =  add_prefix_space

   UpperCAmelCase					      =  "post_processor"
   UpperCAmelCase					      =  getattr(self.backend_tokenizer			,						lowerCAmelCase__			,						lowerCAmelCase__    )
   if tokenizer_component_instance:
     UpperCAmelCase					      =  json.loads(tokenizer_component_instance.__getstate__()    )

     # The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
     if "sep" in state:
       UpperCAmelCase					      =  tuple(state["sep"]    )
     if "cls" in state:
       UpperCAmelCase					      =  tuple(state["cls"]    )

     UpperCAmelCase					      =  False

     if state.get("add_prefix_space"			,						lowerCAmelCase__    ) != add_prefix_space:
       UpperCAmelCase					      =  add_prefix_space
       UpperCAmelCase					      =  True

     if state.get("trim_offsets"			,						lowerCAmelCase__    ) != trim_offsets:
       UpperCAmelCase					      =  trim_offsets
       UpperCAmelCase					      =  True

     if changes_to_apply:
       UpperCAmelCase					      =  getattr(lowerCAmelCase__			,						state.pop("type"    )    )
       UpperCAmelCase					      =  component_class(**lowerCAmelCase__    )
       setattr(self.backend_tokenizer			,						lowerCAmelCase__			,						lowerCAmelCase__    )


 @property
 def _UpperCamelCase	(						self		: str    )    ->      str:
   if self._mask_token is None:
     if self.verbose:
       logger.error("Using mask_token, but it is not set yet."    )
     return None
   return str(self._mask_token    )


 @mask_token.setter
 def _UpperCamelCase	(						self		: Optional[Any]			,						lowerCAmelCase__		: Union[str, Any]    )    ->      int:
   UpperCAmelCase					      =  AddedToken(lowerCAmelCase__			,						lstrip=lowerCAmelCase__			,						rstrip=lowerCAmelCase__    ) if isinstance(lowerCAmelCase__			,						lowerCAmelCase__    ) else value
   UpperCAmelCase					      =  value


 def _UpperCamelCase	(						self		: Tuple			,						*lowerCAmelCase__		: List[Any]			,						**lowerCAmelCase__		: List[Any]    )    ->      BatchEncoding:
   UpperCAmelCase					      =  kwargs.get("is_split_into_words"			,						lowerCAmelCase__    )
   assert self.add_prefix_space or not is_split_into_words, (
       f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
       "to use it with pretokenized inputs."
   )

   return super()._batch_encode_plus(*lowerCAmelCase__			,						**lowerCAmelCase__    )


 def _UpperCamelCase	(						self		: Optional[Any]			,						*lowerCAmelCase__		: Dict			,						**lowerCAmelCase__		: str    )    ->      BatchEncoding:
   UpperCAmelCase					      =  kwargs.get("is_split_into_words"			,						lowerCAmelCase__    )

   assert self.add_prefix_space or not is_split_into_words, (
       f"You need to instantiate {self.__class__.__name__} with add_prefix_space=True "
       "to use it with pretokenized inputs."
   )

   return super()._encode_plus(*lowerCAmelCase__			,						**lowerCAmelCase__    )


 def _UpperCamelCase	(						self		: Optional[int]			,						lowerCAmelCase__		: str			,						lowerCAmelCase__		: Optional[str] = None    )    ->      Tuple[str]:
   UpperCAmelCase					      =  self._tokenizer.model.save(lowerCAmelCase__			,						name=lowerCAmelCase__    )
   return tuple(lowerCAmelCase__    )


 def _UpperCamelCase	(						self		: Optional[Any]			,						lowerCAmelCase__		: Optional[int]			,						lowerCAmelCase__		: Union[str, Any]=None    )    ->      List[Any]:
   UpperCAmelCase					      =  [self.bos_token_id] + token_ids_a + [self.eos_token_id]
   if token_ids_a is None:
     return output

   return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]


 def _UpperCamelCase	(						self		: List[str]			,						lowerCAmelCase__		: List[int]			,						lowerCAmelCase__		: Optional[List[int]] = None    )    ->      List[int]:
   UpperCAmelCase					      =  [self.sep_token_id]
   UpperCAmelCase					      =  [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      _lowerCAmelCase(	__A   ,       __A			):
  return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def      _lowerCAmelCase(	__A   ,       __A=0			):
  return sorted(__A   ,       key=lambda __A			: x[column]			)
def      _lowerCAmelCase(	__A   ,       __A   ,       __A=float("inf"			)			):

  for i in range(points_counts - 1			):
    for j in range(i + 1   ,       __A			):
      UpperCAmelCase					      =  euclidean_distance_sqr(points[i]   ,       points[j]			)
      if current_dis < min_dis:
        UpperCAmelCase					      =  current_dis
  return min_dis
def      _lowerCAmelCase(	__A   ,       __A   ,       __A=float("inf"			)			):

  for i in range(min(6   ,       points_counts - 1			)   ,       __A			):
    for j in range(max(0   ,       i - 6			)   ,       __A			):
      UpperCAmelCase					      =  euclidean_distance_sqr(points[i]   ,       points[j]			)
      if current_dis < min_dis:
        UpperCAmelCase					      =  current_dis
  return min_dis
def      _lowerCAmelCase(	__A   ,       __A   ,       __A			):

  # base case
  if points_counts <= 3:
    return dis_between_closest_pair(__A   ,       __A			)

  # recursion
  UpperCAmelCase					      =  points_counts // 2
  UpperCAmelCase					      =  closest_pair_of_points_sqr(
      __A   ,       points_sorted_on_y[:mid]   ,       __A			)
  UpperCAmelCase					      =  closest_pair_of_points_sqr(
      __A   ,       points_sorted_on_y[mid:]   ,       points_counts - mid			)
  UpperCAmelCase					      =  min(__A   ,       __A			)
  UpperCAmelCase					      =  []
  for point in points_sorted_on_x:
    if abs(point[0] - points_sorted_on_x[mid][0]			) < closest_pair_dis:
      cross_strip.append(__A			)

  UpperCAmelCase					      =  dis_between_closest_in_strip(
      __A   ,       len(__A			)   ,       __A			)
  return min(__A   ,       __A			)
def      _lowerCAmelCase(	__A   ,       __A			):
  UpperCAmelCase					      =  column_based_sort(__A   ,       column=0			)
  UpperCAmelCase					      =  column_based_sort(__A   ,       column=1			)
  return (
      closest_pair_of_points_sqr(
          __A   ,       __A   ,       __A			)
  ) ** 0.5


if __name__ == "__main__":
      lowerCAmelCase__       = [(2, 3), (12, 30), (40, 50), (5, 1), (12, 10), (3, 4)]
      print("Distance:", closest_pair_of_points(points, len(points)))



