
from collections import OrderedDict
from typing import Mapping

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


lowerCAmelCase_           = logging.get_logger(__name__)

lowerCAmelCase_           = {
    'facebook/xmod-base': 'https://huggingface.co/facebook/xmod-base/resolve/main/config.json',
    'facebook/xmod-large-prenorm': 'https://huggingface.co/facebook/xmod-large-prenorm/resolve/main/config.json',
    'facebook/xmod-base-13-125k': 'https://huggingface.co/facebook/xmod-base-13-125k/resolve/main/config.json',
    'facebook/xmod-base-30-125k': 'https://huggingface.co/facebook/xmod-base-30-125k/resolve/main/config.json',
    'facebook/xmod-base-30-195k': 'https://huggingface.co/facebook/xmod-base-30-195k/resolve/main/config.json',
    'facebook/xmod-base-60-125k': 'https://huggingface.co/facebook/xmod-base-60-125k/resolve/main/config.json',
    'facebook/xmod-base-60-265k': 'https://huggingface.co/facebook/xmod-base-60-265k/resolve/main/config.json',
    'facebook/xmod-base-75-125k': 'https://huggingface.co/facebook/xmod-base-75-125k/resolve/main/config.json',
    'facebook/xmod-base-75-269k': 'https://huggingface.co/facebook/xmod-base-75-269k/resolve/main/config.json',
}
class      UpperCamelCase (				snake_case__ ):







		"""simple docstring"""



		snake_case    =   "xmod"
		def __init__(  self		:       Optional[int]						,_SCREAMING_SNAKE_CASE		:       str=3_0_5_2_2						,_SCREAMING_SNAKE_CASE		:       str=7_6_8						,_SCREAMING_SNAKE_CASE		:       List[Any]=1_2						,_SCREAMING_SNAKE_CASE		:       str=1_2						,_SCREAMING_SNAKE_CASE		:       Any=3_0_7_2						,_SCREAMING_SNAKE_CASE		:       List[Any]="gelu"						,_SCREAMING_SNAKE_CASE		:       int=0.1						,_SCREAMING_SNAKE_CASE		:       List[Any]=0.1						,_SCREAMING_SNAKE_CASE		:       List[str]=5_1_2						,_SCREAMING_SNAKE_CASE		:       List[str]=2						,_SCREAMING_SNAKE_CASE		:       List[Any]=0.02						,_SCREAMING_SNAKE_CASE		:       Dict=1E-12						,_SCREAMING_SNAKE_CASE		:       int=1						,_SCREAMING_SNAKE_CASE		:       Union[str, Any]=0						,_SCREAMING_SNAKE_CASE		:       Dict=2						,_SCREAMING_SNAKE_CASE		:       Optional[Any]="absolute"						,_SCREAMING_SNAKE_CASE		:       List[Any]=True						,_SCREAMING_SNAKE_CASE		:       Union[str, Any]=None						,_SCREAMING_SNAKE_CASE		:       List[Any]=False						,_SCREAMING_SNAKE_CASE		:       List[str]=2						,_SCREAMING_SNAKE_CASE		:       Any=False						,_SCREAMING_SNAKE_CASE		:       Any=True						,_SCREAMING_SNAKE_CASE		:       Tuple=True						,_SCREAMING_SNAKE_CASE		:       Optional[Any]=("en_XX",)						,_SCREAMING_SNAKE_CASE		:       int=None						,**_SCREAMING_SNAKE_CASE		:       Any						,)    ->   List[str]:


						'''simple docstring'''
						super().__init__(pad_token_id=_SCREAMING_SNAKE_CASE						,bos_token_id=_SCREAMING_SNAKE_CASE						,eos_token_id=_SCREAMING_SNAKE_CASE						,**_SCREAMING_SNAKE_CASE		)

						A	 =      vocab_size
						A	 =      hidden_size
						A	 =      num_hidden_layers
						A	 =      num_attention_heads
						A	 =      hidden_act
						A	 =      intermediate_size
						A	 =      hidden_dropout_prob
						A	 =      attention_probs_dropout_prob
						A	 =      max_position_embeddings
						A	 =      type_vocab_size
						A	 =      initializer_range
						A	 =      layer_norm_eps
						A	 =      position_embedding_type
						A	 =      use_cache
						A	 =      classifier_dropout
						A	 =      pre_norm
						A	 =      adapter_reduction_factor
						A	 =      adapter_layer_norm
						A	 =      adapter_reuse_layer_norm
						A	 =      ln_before_adapter
						A	 =      list(_SCREAMING_SNAKE_CASE		)
						A	 =      default_language


class      UpperCamelCase (				snake_case__ ):







		"""simple docstring"""



		@property
		def       A(  self		:       Optional[Any]		)    ->   Mapping[str, Mapping[int, str]]:


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













from itertools import permutations







def      snake_case		(							UpperCAmelCase	:       tuple   ):
				if num[3] % 2 != 0:
								return False

				if (num[2] + num[3] + num[4]) % 3 != 0:
								return False

				if num[5] % 5 != 0:
								return False

				A	 =      [7, 11, 13, 17]
				for i, test in enumerate(UpperCAmelCase   ):
								if (num[i + 4] * 1_00 + num[i + 5] * 10 + num[i + 6]) % test != 0:
												return False
				return True







def      snake_case		(							UpperCAmelCase	:       int = 10   ):
				return sum(
				    int(''.join(map(UpperCAmelCase,						UpperCAmelCase   )   )   )
				    for num in permutations(range(UpperCAmelCase   )   )
				    if is_substring_divisible(UpperCAmelCase   )   )


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





