





from math import asin, atan, cos, radians, sin, sqrt, tan

a__:      Tuple									=		6_37_81_37.0
a__:      Optional[Any]									=		6_35_67_52.31_42_45
a__:      int									=		6_378_137


def 	UpperCamelCase__(       UpperCamelCase__			:       float ,     UpperCamelCase__			:       float ,     UpperCamelCase__			:       float ,     UpperCamelCase__			:       float  )->float:
       A__											=						(AXIS_A - AXIS_B) / AXIS_A
       A__											=						atan((1 - flattening) * tan(radians(UpperCamelCase__  )  )  )
       A__											=						atan((1 - flattening) * tan(radians(UpperCamelCase__  )  )  )
       A__											=						radians(UpperCamelCase__  )
       A__											=						radians(UpperCamelCase__  )
       # Equation
       A__											=						sin((phi_a - phi_a) / 2  )
       A__											=						sin((lambda_a - lambda_a) / 2  )
       # Square both values
       sin_sq_phi *= sin_sq_phi
       sin_sq_lambda *= sin_sq_lambda
       A__											=						sqrt(sin_sq_phi + (cos(UpperCamelCase__  ) * cos(UpperCamelCase__  ) * sin_sq_lambda)  )
       return 2 * RADIUS * asin(UpperCamelCase__  )


if __name__ == "__main__":
       import doctest

       doctest.testmod()












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__:      Union[str, Any]									=		logging.get_logger(__name__)

a__:      Union[str, Any]									=		{'vocab_file': 'spiece.model'}

a__:      Tuple									=		{
    '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__:      Any									=		{
    'google/bigbird-roberta-base': 4_096,
    'google/bigbird-roberta-large': 4_096,
    'google/bigbird-base-trivia-itc': 4_096,
}




class     SCREAMING_SNAKE_CASE__ (						UpperCamelCase__      ):
 __SCREAMING_SNAKE_CASE							       =	VOCAB_FILES_NAMES
 __SCREAMING_SNAKE_CASE							       =	PRETRAINED_VOCAB_FILES_MAP
 __SCREAMING_SNAKE_CASE							       =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __SCREAMING_SNAKE_CASE							       =	['''input_ids''', '''attention_mask''']
 __SCREAMING_SNAKE_CASE							       =	[]



 def __init__(							self,__lowerCamelCase,__lowerCamelCase="<unk>",__lowerCamelCase="<s>",__lowerCamelCase="</s>",__lowerCamelCase="<pad>",__lowerCamelCase="[SEP]",__lowerCamelCase="[MASK]",__lowerCamelCase="[CLS]",__lowerCamelCase = None,**__lowerCamelCase,):
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else bos_token
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else eos_token
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else unk_token
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else pad_token
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else cls_token
        A__											=						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
        A__											=						AddedToken(__lowerCamelCase,lstrip=__lowerCamelCase,rstrip=__lowerCamelCase ) if isinstance(__lowerCamelCase,__lowerCamelCase ) else mask_token

        A__											=						{} if sp_model_kwargs is None else sp_model_kwargs

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

        A__											=						vocab_file

        A__											=						spm.SentencePieceProcessor(**self.sp_model_kwargs )
        self.sp_model.Load(__lowerCamelCase )



 @property
 def 				UpperCamelCase			(							self ):
        return self.sp_model.get_piece_size()



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



 def __getstate__(							self ):
        A__											=						self.__dict__.copy()
        A__											=						None
        return state



 def __setstate__(							self,__lowerCamelCase ):
        A__											=						d

        # 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 				UpperCamelCase			(							self,__lowerCamelCase ):
        return self.sp_model.encode(__lowerCamelCase,out_type=__lowerCamelCase )



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        return self.sp_model.piece_to_id(__lowerCamelCase )



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        A__											=						self.sp_model.IdToPiece(__lowerCamelCase )
        return token



 def 				UpperCamelCase			(							self,__lowerCamelCase ):
        A__											=						[]
        A__											=						''''''
        A__											=						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(__lowerCamelCase ) + token
                      A__											=						True
                      A__											=						[]
               else:
                      current_sub_tokens.append(__lowerCamelCase )
                      A__											=						False
        out_string += self.sp_model.decode(__lowerCamelCase )
        return out_string.strip()



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = False,__lowerCamelCase = None,__lowerCamelCase = True,**__lowerCamelCase,):
        A__											=						kwargs.pop('''use_source_tokenizer''',__lowerCamelCase )

        A__											=						self.convert_ids_to_tokens(__lowerCamelCase,skip_special_tokens=__lowerCamelCase )

        # 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
        A__											=						[]
        A__											=						[]
        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(__lowerCamelCase ) )
                             A__											=						[]
                      sub_texts.append(__lowerCamelCase )
               else:
                      current_sub_text.append(__lowerCamelCase )
        if current_sub_text:
               sub_texts.append(self.convert_tokens_to_string(__lowerCamelCase ) )

        # Mimic the behavior of the Rust tokenizer:
        # No space before [MASK] and [SEP]
        if spaces_between_special_tokens:
               A__											=						re.sub(r''' (\[(MASK|SEP)\])''',r'''\1''',''' '''.join(__lowerCamelCase ) )
        else:
               A__											=						''''''.join(__lowerCamelCase )

        A__											=						(
            clean_up_tokenization_spaces
            if clean_up_tokenization_spaces is not None
            else self.clean_up_tokenization_spaces
        )
        if clean_up_tokenization_spaces:
               A__											=						self.clean_up_tokenization(__lowerCamelCase )
               return clean_text
        else:
               return text



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None ):
        if not os.path.isdir(__lowerCamelCase ):
               logger.error(f"Vocabulary path ({save_directory}) should be a directory" )
               return
        A__											=						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 ) and os.path.isfile(self.vocab_file ):
               copyfile(self.vocab_file,__lowerCamelCase )
        elif not os.path.isfile(self.vocab_file ):
               with open(__lowerCamelCase,'''wb''' ) as fi:
                      A__											=						self.sp_model.serialized_model_proto()
                      fi.write(__lowerCamelCase )

        return (out_vocab_file,)



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None ):
        if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
        A__											=						[self.cls_token_id]
        A__											=						[self.sep_token_id]
        return cls + token_ids_a + sep + token_ids_a + sep



 def 				UpperCamelCase			(							self,__lowerCamelCase,__lowerCamelCase = None,__lowerCamelCase = False ):
        if already_has_special_tokens:
               return super().get_special_tokens_mask(
                   token_ids_a=__lowerCamelCase,token_ids_a=__lowerCamelCase,already_has_special_tokens=__lowerCamelCase )

        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,__lowerCamelCase,__lowerCamelCase = None ):
        A__											=						[self.sep_token_id]
        A__											=						[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]





