


lowerCAmelCase__  :List[Any]   			=							2_5_6
# Modulus to hash a string
lowerCAmelCase__  :List[str]   			=							1_0_0_0_0_0_3

def        lowerCAmelCase__ (			a__:		Tuple			,  a__:		Optional[int]       )  ->		bool:


							'''simple docstring'''





							_UpperCAmelCase 		=			len(_SCREAMING_SNAKE_CASE       )
							_UpperCAmelCase 		=			len(_SCREAMING_SNAKE_CASE       )
							if p_len > t_len:
														return False

							_UpperCAmelCase 		=			0
							_UpperCAmelCase 		=			0
							_UpperCAmelCase 		=			1

							# Calculating the hash of pattern and substring of text
							for i in range(_SCREAMING_SNAKE_CASE       ):
														_UpperCAmelCase 		=			(ord(pattern[i]       ) + p_hash * alphabet_size) % modulus
														_UpperCAmelCase 		=			(ord(text[i]       ) + text_hash * alphabet_size) % modulus
														if i == p_len - 1:
																					continue
														_UpperCAmelCase 		=			(modulus_power * alphabet_size) % modulus

							for i in range(0			,  t_len - p_len + 1       ):
														if text_hash == p_hash and text[i : i + p_len] == pattern:
																					return True
														if i == t_len - p_len:
																					continue
														# Calculate the https://en.wikipedia.org/wiki/Rolling_hash
														_UpperCAmelCase 		=			(
														    (text_hash - ord(text[i]       ) * modulus_power) * alphabet_size
														    + ord(text[i + p_len]       )
														) % modulus
							return False

def        lowerCAmelCase__ (			)  ->		None:


							'''simple docstring'''





							_UpperCAmelCase 		=			'abc1abc12'
							_UpperCAmelCase 		=			'alskfjaldsabc1abc1abc12k23adsfabcabc'
							_UpperCAmelCase 		=			'alskfjaldsk23adsfabcabc'
							assert rabin_karp(_SCREAMING_SNAKE_CASE			,  _SCREAMING_SNAKE_CASE       ) and not rabin_karp(_SCREAMING_SNAKE_CASE			,  _SCREAMING_SNAKE_CASE       )

							# Test 2)
							_UpperCAmelCase 		=			'ABABX'
							_UpperCAmelCase 		=			'ABABZABABYABABX'
							assert rabin_karp(_SCREAMING_SNAKE_CASE			,  _SCREAMING_SNAKE_CASE       )

							# Test 3)
							_UpperCAmelCase 		=			'AAAB'
							_UpperCAmelCase 		=			'ABAAAAAB'
							assert rabin_karp(_SCREAMING_SNAKE_CASE			,  _SCREAMING_SNAKE_CASE       )

							# Test 4)
							_UpperCAmelCase 		=			'abcdabcy'
							_UpperCAmelCase 		=			'abcxabcdabxabcdabcdabcy'
							assert rabin_karp(_SCREAMING_SNAKE_CASE			,  _SCREAMING_SNAKE_CASE       )

							# Test 5)
							_UpperCAmelCase 		=			'Lü'
							_UpperCAmelCase 		=			'Lüsai'
							assert rabin_karp(_SCREAMING_SNAKE_CASE			,  _SCREAMING_SNAKE_CASE       )
							_UpperCAmelCase 		=			'Lue'
							assert not rabin_karp(_SCREAMING_SNAKE_CASE			,  _SCREAMING_SNAKE_CASE       )
							print('Success.'       )


if __name__ == "__main__":
		test_rabin_karp()

"""simple docstring"""
from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


lowercase__					       =	logging.get_logger(__name__)

lowercase__					       =	{
    'andreasmadsen/efficient_mlm_m0.40': (
        'https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'
    ),
}




class    __snake_case       (     __lowerCAmelCase				):
      a__        =		"""roberta-prelayernorm"""



      def __init__(						self    ,			lowercase=5_02_65    ,			lowercase=7_68    ,			lowercase=12    ,			lowercase=12    ,			lowercase=30_72    ,			lowercase="gelu"    ,			lowercase=0.1    ,			lowercase=0.1    ,			lowercase=5_12    ,			lowercase=2    ,			lowercase=0.02    ,			lowercase=1e-12    ,			lowercase=1    ,			lowercase=0    ,			lowercase=2    ,			lowercase="absolute"    ,			lowercase=True    ,			lowercase=None    ,			**lowercase    ,			)	->			Any:





        '''simple docstring'''





        super().__init__(pad_token_id=lowercase    ,			bos_token_id=lowercase    ,			eos_token_id=lowercase    ,			**lowercase)

        a__:     Union[str, Any]										=	vocab_size
        a__:     str										=	hidden_size
        a__:     Tuple										=	num_hidden_layers
        a__:     List[str]										=	num_attention_heads
        a__:     Dict										=	hidden_act
        a__:     int										=	intermediate_size
        a__:     Tuple										=	hidden_dropout_prob
        a__:     str										=	attention_probs_dropout_prob
        a__:     Tuple										=	max_position_embeddings
        a__:     Tuple										=	type_vocab_size
        a__:     Optional[Any]										=	initializer_range
        a__:     Tuple										=	layer_norm_eps
        a__:     Optional[int]										=	position_embedding_type
        a__:     Any										=	use_cache
        a__:     Dict										=	classifier_dropout







class    __snake_case       (     __lowerCAmelCase				):



      @property
      def   lowerCamelCase_   (						self)	->			Mapping[str, Mapping[int, str]]:





        '''simple docstring'''





        if self.task == "multiple-choice":
          a__:     str										=	{0: 'batch', 1: 'choice', 2: 'sequence'}
        else:
          a__:     Union[str, Any]										=	{0: 'batch', 1: 'sequence'}
        return OrderedDict(
            [
                ('input_ids', dynamic_axis),
                ('attention_mask', dynamic_axis),
            ])


