from collections import OrderedDict
from typing import Mapping

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


__lowerCamelCase    :				Optional[int]							     =	logging.get_logger(__name__)

__lowerCamelCase    :				str							     =	{
    '''facebook/xlm-roberta-xl''': '''https://huggingface.co/facebook/xlm-roberta-xl/resolve/main/config.json''',
    '''facebook/xlm-roberta-xxl''': '''https://huggingface.co/facebook/xlm-roberta-xxl/resolve/main/config.json''',
    # See all XLM-RoBERTa-XL models at https://huggingface.co/models?filter=xlm-roberta-xl
}







class __snake_case       (		SCREAMING_SNAKE_CASE__	):
   lowerCAmelCase_														=							"xlm-roberta-xl"




   def __init__(					self    :       Optional[Any] ,			_lowercase    :       List[str]=25_08_80 ,			_lowercase    :       Any=25_60 ,			_lowercase    :       Union[str, Any]=36 ,			_lowercase    :       str=32 ,			_lowercase    :       Tuple=1_02_40 ,			_lowercase    :       str="gelu" ,			_lowercase    :       str=0.1 ,			_lowercase    :       List[str]=0.1 ,			_lowercase    :       int=5_14 ,			_lowercase    :       str=1 ,			_lowercase    :       Union[str, Any]=0.02 ,			_lowercase    :       List[str]=1E-05 ,			_lowercase    :       int=1 ,			_lowercase    :       Optional[int]=0 ,			_lowercase    :       str=2 ,			_lowercase    :       int="absolute" ,			_lowercase    :       Any=True ,			_lowercase    :       Dict=None ,			**_lowercase    :       Any ,			):



     """simple docstring"""






     super().__init__(pad_token_id=_lowercase ,			bos_token_id=_lowercase ,			eos_token_id=_lowercase ,			**_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   vocab_size
     SCREAMING_SNAKE_CASE__    							=   hidden_size
     SCREAMING_SNAKE_CASE__    							=   num_hidden_layers
     SCREAMING_SNAKE_CASE__    							=   num_attention_heads
     SCREAMING_SNAKE_CASE__    							=   hidden_act
     SCREAMING_SNAKE_CASE__    							=   intermediate_size
     SCREAMING_SNAKE_CASE__    							=   hidden_dropout_prob
     SCREAMING_SNAKE_CASE__    							=   attention_probs_dropout_prob
     SCREAMING_SNAKE_CASE__    							=   max_position_embeddings
     SCREAMING_SNAKE_CASE__    							=   type_vocab_size
     SCREAMING_SNAKE_CASE__    							=   initializer_range
     SCREAMING_SNAKE_CASE__    							=   layer_norm_eps
     SCREAMING_SNAKE_CASE__    							=   position_embedding_type
     SCREAMING_SNAKE_CASE__    							=   use_cache
     SCREAMING_SNAKE_CASE__    							=   classifier_dropout







class __snake_case       (		SCREAMING_SNAKE_CASE__	):




   @property
   def 			__a		(					self    :       Union[str, Any]   ):



     """simple docstring"""






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

def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: int			)							->      int:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__    							=   [1]

  SCREAMING_SNAKE_CASE__							,  SCREAMING_SNAKE_CASE__							,  SCREAMING_SNAKE_CASE__    							=   0, 0, 0
  SCREAMING_SNAKE_CASE__    							=   ugly_nums[ia] * 2
  SCREAMING_SNAKE_CASE__    							=   ugly_nums[ia] * 3
  SCREAMING_SNAKE_CASE__    							=   ugly_nums[ia] * 5

  for _ in range(1				,  __UpperCamelCase			):
    SCREAMING_SNAKE_CASE__    							=   min(__UpperCamelCase				,  __UpperCamelCase				,  __UpperCamelCase			)
    ugly_nums.append(__UpperCamelCase			)
    if next_num == next_a:
      ia += 1
      SCREAMING_SNAKE_CASE__    							=   ugly_nums[ia] * 2
    if next_num == next_a:
      ia += 1
      SCREAMING_SNAKE_CASE__    							=   ugly_nums[ia] * 3
    if next_num == next_a:
      ia += 1
      SCREAMING_SNAKE_CASE__    							=   ugly_nums[ia] * 5
  return ugly_nums[-1]


if __name__ == "__main__":
   from doctest import testmod

   testmod(verbose=True)
   print(F"""{ugly_numbers(200) = }""")
