from collections import OrderedDict
from typing import Mapping

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


__lowerCamelCase :      int										=				logging.get_logger(__name__)

__lowerCamelCase :      Optional[int]										=				{
    """facebook/data2vec-text-base""": """https://huggingface.co/data2vec/resolve/main/config.json""",
}



class 							SCREAMING_SNAKE_CASE__						(    _UpperCamelCase						):





					"""simple docstring"""






					a_     =		'data2vec-text'



					def __init__( self					:  List[str]							,		__A					:  List[Any]=3_0_5_2_2							,		__A					:  int=7_6_8							,		__A					:  Union[str, Any]=1_2							,		__A					:  Optional[Any]=1_2							,		__A					:  Any=3_0_7_2							,		__A					:  Union[str, Any]="gelu"							,		__A					:  Tuple=0.1							,		__A					:  int=0.1							,		__A					:  List[Any]=5_1_2							,		__A					:  Dict=2							,		__A					:  Optional[Any]=0.0_2							,		__A					:  Optional[Any]=1e-1_2							,		__A					:  str=1							,		__A					:  int=0							,		__A					:  List[str]=2							,		__A					:  Union[str, Any]="absolute"							,		__A					:  str=True							,		__A					:  str=None							,		**__A					:  Dict							,		):
						super().__init__(pad_token_id=_UpperCAmelCase							,		bos_token_id=_UpperCAmelCase							,		eos_token_id=_UpperCAmelCase							,		**_UpperCAmelCase	)

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



class 							SCREAMING_SNAKE_CASE__						(    _UpperCamelCase						):





					"""simple docstring"""






					@property
					def 	_lowercase					( self					:  Optional[Any]	):
						if self.task == "multiple-choice":
							snake_case__			:				Optional[int]       =  {0: 'batch', 1: 'choice', 2: 'sequence'}
						else:
							snake_case__			:				str       =  {0: 'batch', 1: 'sequence'}
						return OrderedDict(
						    [
						        ("input_ids", dynamic_axis),
						        ("attention_mask", dynamic_axis),
						    ]	)











import sys

__lowerCamelCase :      List[str]										=				(
    """73167176531330624919225119674426574742355349194934"""
    """96983520312774506326239578318016984801869478851843"""
    """85861560789112949495459501737958331952853208805511"""
    """12540698747158523863050715693290963295227443043557"""
    """66896648950445244523161731856403098711121722383113"""
    """62229893423380308135336276614282806444486645238749"""
    """30358907296290491560440772390713810515859307960866"""
    """70172427121883998797908792274921901699720888093776"""
    """65727333001053367881220235421809751254540594752243"""
    """52584907711670556013604839586446706324415722155397"""
    """53697817977846174064955149290862569321978468622482"""
    """83972241375657056057490261407972968652414535100474"""
    """82166370484403199890008895243450658541227588666881"""
    """16427171479924442928230863465674813919123162824586"""
    """17866458359124566529476545682848912883142607690042"""
    """24219022671055626321111109370544217506941658960408"""
    """07198403850962455444362981230987879927244284909188"""
    """84580156166097919133875499200524063689912560717606"""
    """05886116467109405077541002256983155200055935729725"""
    """71636269561882670428252483600823257530420752963450"""
)







def 					SCREAMING_SNAKE_CASE    (			snake_case_ :							str = N       ):
	snake_case__			:				Any       =  -sys.maxsize - 1
	for i in range(len(snake_case_       ) - 12       ):
		snake_case__			:				Tuple       =  1
		for j in range(13       ):
			product *= int(n[i + j]       )
		if product > largest_product:
			snake_case__			:				Dict       =  product
	return largest_product


if __name__ == "__main__":
	print(f"{solution() = }")



