






"""simple docstring"""







def       _lowerCAmelCase       (      lowerCAmelCase	,      lowerCAmelCase = False		):







    '''simple docstring'''

    if not isinstance(lowerCAmelCase	,      lowerCAmelCase		):
        UpperCAmelCase	    =			F'''Expected string as input, found {type(lowerCAmelCase		)}'''
        raise ValueError(lowerCAmelCase		)
    if not isinstance(lowerCAmelCase	,      lowerCAmelCase		):
        UpperCAmelCase	    =			F'''Expected boolean as use_pascal parameter, found {type(lowerCAmelCase		)}'''
        raise ValueError(lowerCAmelCase		)

    UpperCAmelCase	    =			input_str.split("""_"""		)

    UpperCAmelCase	    =			0 if use_pascal else 1

    UpperCAmelCase	    =			words[start_index:]

    UpperCAmelCase	    =			[word[0].upper() + word[1:] for word in words_to_capitalize]

    UpperCAmelCase	    =			"""""" if use_pascal else words[0]

    return "".join([initial_word, *capitalized_words]		)


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

 testmod()








"""simple docstring"""







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_	:    List[Any]            =      {
    '''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   UpperCamelCase_ (       a_  ):
  _A       :					int				=	'xlm-roberta-xl'



  def __init__(      self ,		snake_case__=25_08_80 ,		snake_case__=25_60 ,		snake_case__=36 ,		snake_case__=32 ,		snake_case__=1_02_40 ,		snake_case__="gelu" ,		snake_case__=0.1 ,		snake_case__=0.1 ,		snake_case__=5_14 ,		snake_case__=1 ,		snake_case__=0.02 ,		snake_case__=1e-05 ,		snake_case__=1 ,		snake_case__=0 ,		snake_case__=2 ,		snake_case__="absolute" ,		snake_case__=True ,		snake_case__=None ,		**snake_case__ ,		)			->			Union[str, Any]:



         """simple docstring"""





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





class   UpperCamelCase_ (       a_  ):



  @property
  def 		UpperCamelCase_				(      self				)			->			Mapping[str, Mapping[int, str]]:



         """simple docstring"""





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