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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
       from .tokenization_big_bird import BigBirdTokenizer
else:
       __SCREAMING_SNAKE_CASE								=None

__SCREAMING_SNAKE_CASE								=logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE								={"vocab_file": "spiece.model", "tokenizer_file": "tokenizer.json"}

__SCREAMING_SNAKE_CASE								={
    "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"
        ),
    },
    "tokenizer_file": {
        "google/bigbird-roberta-base": (
            "https://huggingface.co/google/bigbird-roberta-base/resolve/main/tokenizer.json"
        ),
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/tokenizer.json"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/tokenizer.json"
        ),
    },
}

__SCREAMING_SNAKE_CASE								={
    "google/bigbird-roberta-base": 4096,
    "google/bigbird-roberta-large": 4096,
    "google/bigbird-base-trivia-itc": 4096,
}


__SCREAMING_SNAKE_CASE								="▁"







class  UpperCamelCase	(    lowercase_						):
   lowercase							=						VOCAB_FILES_NAMES
   lowercase							=						PRETRAINED_VOCAB_FILES_MAP
   lowercase							=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
   lowercase							=						BigBirdTokenizer
   lowercase							=						['input_ids', 'attention_mask']
   lowercase							=						[]
   def __init__(    self  ,__UpperCamelCase=None  ,__UpperCamelCase=None  ,__UpperCamelCase="<unk>"  ,__UpperCamelCase="<s>"  ,__UpperCamelCase="</s>"  ,__UpperCamelCase="<pad>"  ,__UpperCamelCase="[SEP]"  ,__UpperCamelCase="[MASK]"  ,__UpperCamelCase="[CLS]"  ,**__UpperCamelCase  ,)			->   Optional[Any]:


        '''simple docstring'''


        lowercase_			:       Any									=			AddedToken(lowerCamelCase_  ,lstrip=lowerCamelCase_  ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_  ,lowerCamelCase_    ) else bos_token
        lowercase_			:       Dict									=			AddedToken(lowerCamelCase_  ,lstrip=lowerCamelCase_  ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_  ,lowerCamelCase_    ) else eos_token
        lowercase_			:       Optional[Any]									=			AddedToken(lowerCamelCase_  ,lstrip=lowerCamelCase_  ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_  ,lowerCamelCase_    ) else unk_token
        lowercase_			:       int									=			AddedToken(lowerCamelCase_  ,lstrip=lowerCamelCase_  ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_  ,lowerCamelCase_    ) else pad_token
        lowercase_			:       Any									=			AddedToken(lowerCamelCase_  ,lstrip=lowerCamelCase_  ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_  ,lowerCamelCase_    ) else cls_token
        lowercase_			:       Any									=			AddedToken(lowerCamelCase_  ,lstrip=lowerCamelCase_  ,rstrip=lowerCamelCase_    ) if isinstance(lowerCamelCase_  ,lowerCamelCase_    ) else sep_token

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

        super().__init__(
            lowerCamelCase_  ,tokenizer_file=lowerCamelCase_  ,bos_token=lowerCamelCase_  ,eos_token=lowerCamelCase_  ,unk_token=lowerCamelCase_  ,sep_token=lowerCamelCase_  ,pad_token=lowerCamelCase_  ,cls_token=lowerCamelCase_  ,mask_token=lowerCamelCase_  ,**lowerCamelCase_  ,)

        lowercase_			:       List[Any]									=			vocab_file
        lowercase_			:       Optional[Any]									=			False if not self.vocab_file else True
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = None    )			->   Tuple:


        '''simple docstring'''


        lowercase_			:       Optional[Any]									=			[self.sep_token_id]
        lowercase_			:       int									=			[self.cls_token_id]
        if token_ids_a is None:
             return cls + token_ids_a + sep
        return cls + token_ids_a + sep + token_ids_a + sep
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = None  ,__UpperCamelCase = False    )			->   Optional[Any]:


        '''simple docstring'''


        if already_has_special_tokens:
             if token_ids_a is not None:
                  raise ValueError(
                      'You should not supply a second sequence if the provided sequence of '
                      'ids is already formatted with special tokens for the model.'    )
             return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

        if token_ids_a is None:
             return [1] + ([0] * len(lowerCamelCase_    )) + [1]
        return [1] + ([0] * len(lowerCamelCase_    )) + [1] + ([0] * len(lowerCamelCase_    )) + [1]
   def     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = None    )			->   List[str]:


        '''simple docstring'''


        lowercase_			:       Any									=			[self.sep_token_id]
        lowercase_			:       Optional[int]									=			[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     _UpperCAmelCase     (    self  ,__UpperCamelCase  ,__UpperCamelCase = None    )			->   Union[str, Any]:


        '''simple docstring'''


        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(lowerCamelCase_    ):
             logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''    )
             return
        lowercase_			:       Tuple									=			os.path.join(
            lowerCamelCase_  ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']    )

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

        return (out_vocab_file,)


"""simple docstring"""







from random import randint, random



def     lowercase__( __SCREAMING_SNAKE_CASE							:  int  ,    __SCREAMING_SNAKE_CASE							:  int  ,    __SCREAMING_SNAKE_CASE							:  int  ,    __SCREAMING_SNAKE_CASE							:  bool = False  ,    __SCREAMING_SNAKE_CASE							:  bool = False  ,    __SCREAMING_SNAKE_CASE							:  int = 5  ,    ):
     lowercase_			:       Union[str, Any]									=			[[-1] * number_of_cells]  # Create a highway without any car
     lowercase_			:       str									=			0
     lowercase_			:       List[Any]									=			max(__SCREAMING_SNAKE_CASE  ,    0   )
     while i < number_of_cells:
          lowercase_			:       Union[str, Any]									=			(
              randint(0  ,    __SCREAMING_SNAKE_CASE   ) if random_speed else initial_speed
          )  # Place the cars
          i += (
              randint(1  ,    max_speed * 2   ) if random_frequency else frequency
          )  # Arbitrary number, may need tuning
     return highway



def     lowercase__( __SCREAMING_SNAKE_CASE							:  list  ,    __SCREAMING_SNAKE_CASE							:  int   ):
     lowercase_			:       Union[str, Any]									=			0
     lowercase_			:       Dict									=			highway_now[car_index + 1 :]
     for cell in range(len(__SCREAMING_SNAKE_CASE   )   ):  # May need a better name for this
          if cells[cell] != -1:  # If the cell is not empty then
               return distance  # we have the distance we wanted
          distance += 1
     # Here if the car is near the end of the highway
     return distance + get_distance(__SCREAMING_SNAKE_CASE  ,    -1   )



def     lowercase__( __SCREAMING_SNAKE_CASE							:  list  ,    __SCREAMING_SNAKE_CASE							:  float  ,    __SCREAMING_SNAKE_CASE							:  int   ):
     lowercase_			:       List[Any]									=			len(__SCREAMING_SNAKE_CASE   )
     # Beforce calculations, the highway is empty
     lowercase_			:       Dict									=			[-1] * number_of_cells

     for car_index in range(__SCREAMING_SNAKE_CASE   ):
          if highway_now[car_index] != -1:
               # Add 1 to the current speed of the car and cap the speed
               lowercase_			:       Any									=			min(highway_now[car_index] + 1  ,    __SCREAMING_SNAKE_CASE   )
               # Number of empty cell before the next car
               lowercase_			:       List[Any]									=			get_distance(__SCREAMING_SNAKE_CASE  ,    __SCREAMING_SNAKE_CASE   ) - 1
               # We can't have the car causing an accident
               lowercase_			:       Dict									=			min(next_highway[car_index]  ,    __SCREAMING_SNAKE_CASE   )
               if random() < probability:
                    # Randomly, a driver will slow down
                    lowercase_			:       Optional[Any]									=			max(next_highway[car_index] - 1  ,    0   )
     return next_highway



def     lowercase__( __SCREAMING_SNAKE_CASE							:  list  ,    __SCREAMING_SNAKE_CASE							:  int  ,    __SCREAMING_SNAKE_CASE							:  float  ,    __SCREAMING_SNAKE_CASE							:  int   ):
     lowercase_			:       Union[str, Any]									=			len(highway[0]   )

     for i in range(__SCREAMING_SNAKE_CASE   ):
          lowercase_			:       Optional[Any]									=			update(highway[i]  ,    __SCREAMING_SNAKE_CASE  ,    __SCREAMING_SNAKE_CASE   )
          lowercase_			:       List[str]									=			[-1] * number_of_cells

          for car_index in range(__SCREAMING_SNAKE_CASE   ):
               lowercase_			:       Optional[Any]									=			next_speeds_calculated[car_index]
               if speed != -1:
                    # Change the position based on the speed (with % to create the loop)
                    lowercase_			:       Any									=			(car_index + speed) % number_of_cells
                    # Commit the change of position
                    lowercase_			:       Optional[Any]									=			speed
          highway.append(__SCREAMING_SNAKE_CASE   )

     return highway


if __name__ == "__main__":
       import doctest

       doctest.testmod()

