





from collections import OrderedDict
from typing import Mapping

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


snake_case 				=       logging.get_logger(__name__)

snake_case 				=       {
    """xlm-roberta-base""": """https://huggingface.co/xlm-roberta-base/resolve/main/config.json""",
    """xlm-roberta-large""": """https://huggingface.co/xlm-roberta-large/resolve/main/config.json""",
    """xlm-roberta-large-finetuned-conll02-dutch""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll02-dutch/resolve/main/config.json"""
    ),
    """xlm-roberta-large-finetuned-conll02-spanish""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll02-spanish/resolve/main/config.json"""
    ),
    """xlm-roberta-large-finetuned-conll03-english""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll03-english/resolve/main/config.json"""
    ),
    """xlm-roberta-large-finetuned-conll03-german""": (
        """https://huggingface.co/xlm-roberta-large-finetuned-conll03-german/resolve/main/config.json"""
    ),
}





class 				A_				(      UpperCAmelCase	):







       """simple docstring"""





       SCREAMING_SNAKE_CASE_      : List[str]      =  '''xlm-roberta'''







       def __init__(    self	:	Union[str, Any]						,__A	:	Dict=3_0522						,__A	:	Union[str, Any]=768						,__A	:	Dict=12						,__A	:	Union[str, Any]=12						,__A	:	List[str]=3072						,__A	:	Dict="gelu"						,__A	:	List[Any]=0.1						,__A	:	Optional[int]=0.1						,__A	:	Any=512						,__A	:	int=2						,__A	:	str=0.02						,__A	:	List[Any]=1e-12						,__A	:	Optional[Any]=1						,__A	:	List[Any]=0						,__A	:	List[Any]=2						,__A	:	Tuple="absolute"						,__A	:	str=True						,__A	:	Tuple=None						,**__A	:	int						,)						->					List[str]:
         super().__init__(pad_token_id=__A						,bos_token_id=__A						,eos_token_id=__A						,**__A  )

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





class 				A_				(      UpperCAmelCase	):







       """simple docstring"""





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






from itertools import count

def 							SCREAMING_SNAKE_CASE__       (  snake_case__  :int = 50     )      ->						int:
  _lowercase							= [1] * min_block_length

  for n in count(snake_case__     ):
    fill_count_functions.append(1     )

    for block_length in range(snake_case__			,							n + 1     ):
      for block_start in range(n - block_length     ):
        fill_count_functions[n] += fill_count_functions[
            n - block_start - block_length - 1
        ]

      fill_count_functions[n] += 1

    if fill_count_functions[n] > 100_0000:
      break

  return n


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