


"""simple docstring"""


import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer


__lowerCamelCase   :Any						     =		logging.get_logger(__name__)

__lowerCamelCase   :Any						     =		{'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

__lowerCamelCase   :List[Any]						     =		{
    'vocab_file': {
        'distilbert-base-uncased': 'https://huggingface.co/distilbert-base-uncased/resolve/main/vocab.txt',
        'distilbert-base-uncased-distilled-squad': (
            'https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/vocab.txt'
        ),
        'distilbert-base-cased': 'https://huggingface.co/distilbert-base-cased/resolve/main/vocab.txt',
        'distilbert-base-cased-distilled-squad': (
            'https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/vocab.txt'
        ),
        'distilbert-base-german-cased': 'https://huggingface.co/distilbert-base-german-cased/resolve/main/vocab.txt',
        'distilbert-base-multilingual-cased': (
            'https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'distilbert-base-uncased': 'https://huggingface.co/distilbert-base-uncased/resolve/main/tokenizer.json',
        'distilbert-base-uncased-distilled-squad': (
            'https://huggingface.co/distilbert-base-uncased-distilled-squad/resolve/main/tokenizer.json'
        ),
        'distilbert-base-cased': 'https://huggingface.co/distilbert-base-cased/resolve/main/tokenizer.json',
        'distilbert-base-cased-distilled-squad': (
            'https://huggingface.co/distilbert-base-cased-distilled-squad/resolve/main/tokenizer.json'
        ),
        'distilbert-base-german-cased': (
            'https://huggingface.co/distilbert-base-german-cased/resolve/main/tokenizer.json'
        ),
        'distilbert-base-multilingual-cased': (
            'https://huggingface.co/distilbert-base-multilingual-cased/resolve/main/tokenizer.json'
        ),
    },
}

__lowerCamelCase   :Dict						     =		{
    'distilbert-base-uncased': 512,
    'distilbert-base-uncased-distilled-squad': 512,
    'distilbert-base-cased': 512,
    'distilbert-base-cased-distilled-squad': 512,
    'distilbert-base-german-cased': 512,
    'distilbert-base-multilingual-cased': 512,
}


__lowerCamelCase   :Optional[Any]						     =		{
    'distilbert-base-uncased': {'do_lower_case': True},
    'distilbert-base-uncased-distilled-squad': {'do_lower_case': True},
    'distilbert-base-cased': {'do_lower_case': False},
    'distilbert-base-cased-distilled-squad': {'do_lower_case': False},
    'distilbert-base-german-cased': {'do_lower_case': False},
    'distilbert-base-multilingual-cased': {'do_lower_case': False},
}


class       A__						(    snake_case_):


     """simple docstring"""
     snake_case__						:       str				    =VOCAB_FILES_NAMES
     snake_case__						:       Optional[int]				    =PRETRAINED_VOCAB_FILES_MAP
     snake_case__						:       List[Any]				    =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     snake_case__						:       Union[str, Any]				    =PRETRAINED_INIT_CONFIGURATION
     snake_case__						:       Any				    =['''input_ids''', '''attention_mask''']
     snake_case__						:       List[str]				    =DistilBertTokenizer

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

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

           lowerCamelCase       :       Optional[Any]   =						do_lower_case

     def 		a__    (						self:    Any  ,		__a:    List[str]  ,		__a:    Dict=None						)->     Optional[Any]:
           lowerCamelCase       :       Optional[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:    Dict  ,		__a:    List[int]  ,		__a:    Optional[List[int]] = None						)->     int:
           lowerCamelCase       :       List[Any]   =						[self.sep_token_id]
           lowerCamelCase       :       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 		a__    (						self:    Optional[int]  ,		__a:    str  ,		__a:    Optional[str] = None						)->     str:
           lowerCamelCase       :       int   =						self._tokenizer.model.save(lowercase__  ,		name=lowercase__						)
           return tuple(lowercase__						)










'''simple docstring'''


import math
import random



def  _SCREAMING_SNAKE_CASE     (      UpperCamelCase__    :					float ,    UpperCamelCase__    :					bool = False				):




     """simple docstring"""


     if deriv:
          return value * (1 - value)
     return 1 / (1 + math.exp(-value				))


# Initial Value
lowerCAmelCase_      :  Optional[Any]				     =  0.02



def  _SCREAMING_SNAKE_CASE     (      UpperCamelCase__    :					int ,    UpperCamelCase__    :					int				):




     """simple docstring"""


     a_     :							Tuple     						=  float(2 * (random.randint(1 ,    100				)) - 1				)

     for _ in range(UpperCamelCase__				):
          # Forward propagation
          a_     :							Dict     						=  sigmoid_function(INITIAL_VALUE * weight				)
          # How much did we miss?
          a_     :							Dict     						=  (expected / 100) - layer_a
          # Error delta
          a_     :							Optional[Any]     						=  layer_1_error * sigmoid_function(UpperCamelCase__ ,    UpperCamelCase__				)
          # Update weight
          weight += INITIAL_VALUE * layer_1_delta

     return layer_a * 100


if __name__ == "__main__":
 import doctest

 doctest.testmod()

 lowerCAmelCase_      :  str				     =  int(input('Expected value: '))
 lowerCAmelCase_      :  str				     =  int(input('Number of propagations: '))
 print(forward_propagation(expected, number_propagations))
