




import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer


_snake_case            = logging.get_logger(__name__)

_snake_case            = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}

_snake_case            = {
    """vocab_file""": {
        """yjernite/retribert-base-uncased""": (
            """https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt"""
        ),
    },
    """tokenizer_file""": {
        """yjernite/retribert-base-uncased""": (
            """https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json"""
        ),
    },
}

_snake_case            = {
    """yjernite/retribert-base-uncased""": 512,
}


_snake_case            = {
    """yjernite/retribert-base-uncased""": {"""do_lower_case""": True},
}







class 		lowercase							(     _lowerCAmelCase	):
     _a											=		VOCAB_FILES_NAMES
     _a											=		PRETRAINED_VOCAB_FILES_MAP
     _a											=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _a											=		PRETRAINED_INIT_CONFIGURATION
     _a											=		RetriBertTokenizer
     _a											=		['input_ids', 'attention_mask']

     def __init__(						self	,  _a=None	,  _a=None	,  _a=True	,  _a="[UNK]"	,  _a="[SEP]"	,  _a="[PAD]"	,  _a="[CLS]"	,  _a="[MASK]"	,  _a=True	,  _a=None	,  **_a	,  )		->							List[Any]:
           super().__init__(
               _lowerCAmelCase	,  tokenizer_file=_lowerCAmelCase	,  do_lower_case=_lowerCAmelCase	,  unk_token=_lowerCAmelCase	,  sep_token=_lowerCAmelCase	,  pad_token=_lowerCAmelCase	,  cls_token=_lowerCAmelCase	,  mask_token=_lowerCAmelCase	,  tokenize_chinese_chars=_lowerCAmelCase	,  strip_accents=_lowerCAmelCase	,  **_lowerCAmelCase	,  )

           _A							:  Any    =		json.loads(self.backend_tokenizer.normalizer.__getstate__()       )
           if (
               normalizer_state.get("""lowercase"""	,  _lowerCAmelCase       ) != do_lower_case
               or normalizer_state.get("""strip_accents"""	,  _lowerCAmelCase       ) != strip_accents
               or normalizer_state.get("""handle_chinese_chars"""	,  _lowerCAmelCase       ) != tokenize_chinese_chars
           ):
                 _A							:  Optional[int]    =		getattr(_lowerCAmelCase	,  normalizer_state.pop("""type"""       )       )
                 _A							:  Tuple    =		do_lower_case
                 _A							:  Tuple    =		strip_accents
                 _A							:  str    =		tokenize_chinese_chars
                 _A							:  int    =		normalizer_class(**_lowerCAmelCase       )

           _A							:  Optional[Any]    =		do_lower_case

     def       a__			(						self	,  _a	,  _a=None       )		->							Optional[int]:
           _A							:  List[Any]    =		[self.cls_token_id] + token_ids_a + [self.sep_token_id]

           if token_ids_a:
                 output += token_ids_a + [self.sep_token_id]

           return output

     def       a__			(						self	,  _a	,  _a = None       )		->							List[int]:
           _A							:  Dict    =		[self.sep_token_id]
           _A							:  Union[str, 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       a__			(						self	,  _a	,  _a = None       )		->							Tuple[str]:
           _A							:  List[str]    =		self._tokenizer.model.save(_lowerCAmelCase	,  name=_lowerCAmelCase       )
           return tuple(_lowerCAmelCase       )










from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean







def        lowerCAmelCase_			(  snake_case_  ):

      # A local function to see if a dot lands in the circle.
      def is_in_circle(snake_case_,snake_case_  ) -> bool:
            _A							:  List[str]    =		sqrt((x**2) + (y**2)  )
            # Our circle has a radius of 1, so a distance
            # greater than 1 would land outside the circle.
            return distance_from_centre <= 1

      # The proportion of guesses that landed in the circle
      _A							:  Optional[int]    =		mean(
          int(is_in_circle(uniform(-1.0,1.0  ),uniform(-1.0,1.0  )  )  )
          for _ in range(snake_case_  )  )
      # The ratio of the area for circle to square is pi/4.
      _A							:  List[str]    =		proportion * 4
      print(f'''The estimated value of pi is {pi_estimate}'''  )
      print(f'''The numpy value of pi is {pi}'''  )
      print(f'''The total error is {abs(pi - pi_estimate  )}'''  )







def        lowerCAmelCase_			(  snake_case_,snake_case_,snake_case_ = 0.0,snake_case_ = 1.0,):
      return mean(
          function_to_integrate(uniform(snake_case_,snake_case_  )  ) for _ in range(snake_case_  )  ) * (max_value - min_value)







def        lowerCAmelCase_			(  snake_case_,snake_case_ = 0.0,snake_case_ = 1.0  ):

      def identity_function(snake_case_  ) -> float:
            return x

      _A							:  Any    =		area_under_curve_estimator(
          snake_case_,snake_case_,snake_case_,snake_case_  )
      _A							:  Tuple    =		(max_value * max_value - min_value * min_value) / 2

      print("""******************"""  )
      print(f'''Estimating area under y=x where x varies from {min_value} to {max_value}'''  )
      print(f'''Estimated value is {estimated_value}'''  )
      print(f'''Expected value is {expected_value}'''  )
      print(f'''Total error is {abs(estimated_value - expected_value  )}'''  )
      print("""******************"""  )







def        lowerCAmelCase_			(  snake_case_  ):

      def function_to_integrate(snake_case_  ) -> float:
            return sqrt(4.0 - x * x  )

      _A							:  Optional[int]    =		area_under_curve_estimator(
          snake_case_,snake_case_,0.0,2.0  )

      print("""******************"""  )
      print("""Estimating pi using area_under_curve_estimator"""  )
      print(f'''Estimated value is {estimated_value}'''  )
      print(f'''Expected value is {pi}'''  )
      print(f'''Total error is {abs(estimated_value - pi  )}'''  )
      print("""******************"""  )


if __name__ == "__main__":
  import doctest

  doctest.testmod()

