





'''simple docstring'''






import itertools





def      lowercase  (  lowerCAmelCase :						int):



				"""simple docstring"""


				return (
				    int(''''''.join(combination[0:2])) * int(''''''.join(combination[2:5]))
				    == int(''''''.join(combination[5:9]))
				) or (
				    int(''''''.join(combination[0])) * int(''''''.join(combination[1:5]))
				    == int(''''''.join(combination[5:9]))
				)





def      lowercase  (  ):



				"""simple docstring"""


				return sum(
				    {
				        int(''''''.join(pandigital[5:9]))
				        for pandigital in itertools.permutations('''123456789''')
				        if is_combination_valid(a_)
				    })


if __name__ == "__main__":
	print(solution())



from collections import OrderedDict
from typing import Mapping

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


A__							=				logging.get_logger(__name__)

A__							=				{
    "nghuyong/ernie-1.0-base-zh": "https://huggingface.co/nghuyong/ernie-1.0-base-zh/resolve/main/config.json",
    "nghuyong/ernie-2.0-base-en": "https://huggingface.co/nghuyong/ernie-2.0-base-en/resolve/main/config.json",
    "nghuyong/ernie-2.0-large-en": "https://huggingface.co/nghuyong/ernie-2.0-large-en/resolve/main/config.json",
    "nghuyong/ernie-3.0-base-zh": "https://huggingface.co/nghuyong/ernie-3.0-base-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-medium-zh": "https://huggingface.co/nghuyong/ernie-3.0-medium-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-mini-zh": "https://huggingface.co/nghuyong/ernie-3.0-mini-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-micro-zh": "https://huggingface.co/nghuyong/ernie-3.0-micro-zh/resolve/main/config.json",
    "nghuyong/ernie-3.0-nano-zh": "https://huggingface.co/nghuyong/ernie-3.0-nano-zh/resolve/main/config.json",
    "nghuyong/ernie-gram-zh": "https://huggingface.co/nghuyong/ernie-gram-zh/resolve/main/config.json",
    "nghuyong/ernie-health-zh": "https://huggingface.co/nghuyong/ernie-health-zh/resolve/main/config.json",
}

class 					__UpperCamelCase					(       SCREAMING_SNAKE_CASE      ):
	_lowercase	: Dict												=	"ernie"







	def __init__( self:			List[Any]	,			__UpperCamelCase:			Dict=3_05_22	,			__UpperCamelCase:			str=7_68	,			__UpperCamelCase:			Tuple=12	,			__UpperCamelCase:			int=12	,			__UpperCamelCase:			Optional[Any]=30_72	,			__UpperCamelCase:			str="gelu"	,			__UpperCamelCase:			Any=0.1	,			__UpperCamelCase:			int=0.1	,			__UpperCamelCase:			int=5_12	,			__UpperCamelCase:			Any=2	,			__UpperCamelCase:			Tuple=3	,			__UpperCamelCase:			Any=False	,			__UpperCamelCase:			Optional[int]=0.02	,			__UpperCamelCase:			List[Any]=1E-12	,			__UpperCamelCase:			Union[str, Any]=0	,			__UpperCamelCase:			Tuple="absolute"	,			__UpperCamelCase:			Union[str, Any]=True	,			__UpperCamelCase:			Optional[Any]=None	,			**__UpperCamelCase:			List[Any]	,			):

						'''simple docstring'''





						super().__init__(pad_token_id=__UpperCamelCase	,			**__UpperCamelCase   )

						__magic_name__				=     vocab_size
						__magic_name__				=     hidden_size
						__magic_name__				=     num_hidden_layers
						__magic_name__				=     num_attention_heads
						__magic_name__				=     hidden_act
						__magic_name__				=     intermediate_size
						__magic_name__				=     hidden_dropout_prob
						__magic_name__				=     attention_probs_dropout_prob
						__magic_name__				=     max_position_embeddings
						__magic_name__				=     type_vocab_size
						__magic_name__				=     task_type_vocab_size
						__magic_name__				=     use_task_id
						__magic_name__				=     initializer_range
						__magic_name__				=     layer_norm_eps
						__magic_name__				=     position_embedding_type
						__magic_name__				=     use_cache
						__magic_name__				=     classifier_dropout




class 					__UpperCamelCase					(       SCREAMING_SNAKE_CASE      ):







	@property
	def 						_SCREAMING_SNAKE_CASE				( self:			Tuple   ):

						'''simple docstring'''





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




