from collections import OrderedDict
from typing import Mapping

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


_lowercase							:      int      							=logging.get_logger(__name__)

_lowercase							:      Dict      							={
    '''junnyu/roformer_chinese_small''': '''https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json''',
    '''junnyu/roformer_chinese_base''': '''https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json''',
    '''junnyu/roformer_chinese_char_small''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json'''
    ),
    '''junnyu/roformer_chinese_char_base''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_discriminator''': (
        '''https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_generator''': (
        '''https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json'''
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}



class  SCREAMING_SNAKE_CASE_ (					lowerCAmelCase_			):
  '''simple docstring'''


  lowercase		:     int            =				"""roformer"""







  def __init__(				self    :					Optional[int]      ,	SCREAMING_SNAKE_CASE__    :					Dict=5_00_00      ,	SCREAMING_SNAKE_CASE__    :					Any=None      ,	SCREAMING_SNAKE_CASE__    :					int=7_68      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]=12      ,	SCREAMING_SNAKE_CASE__    :					Union[str, Any]=12      ,	SCREAMING_SNAKE_CASE__    :					Tuple=30_72      ,	SCREAMING_SNAKE_CASE__    :					Any="gelu"      ,	SCREAMING_SNAKE_CASE__    :					List[Any]=0.1      ,	SCREAMING_SNAKE_CASE__    :					Union[str, Any]=0.1      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]=15_36      ,	SCREAMING_SNAKE_CASE__    :					Optional[Any]=2      ,	SCREAMING_SNAKE_CASE__    :					Union[str, Any]=0.0_2      ,	SCREAMING_SNAKE_CASE__    :					Union[str, Any]=1e-12      ,	SCREAMING_SNAKE_CASE__    :					List[Any]=0      ,	SCREAMING_SNAKE_CASE__    :					List[Any]=False      ,	SCREAMING_SNAKE_CASE__    :					Tuple=True      ,	**SCREAMING_SNAKE_CASE__    :					int      ,	)    ->				Tuple:
         super().__init__(pad_token_id=SCREAMING_SNAKE_CASE__      ,	**SCREAMING_SNAKE_CASE__     )

         A						:     List[Any]         =vocab_size
         A						:     Any         =hidden_size if embedding_size is None else embedding_size
         A						:     Dict         =hidden_size
         A						:     List[Any]         =num_hidden_layers
         A						:     Tuple         =num_attention_heads
         A						:     Union[str, Any]         =hidden_act
         A						:     List[Any]         =intermediate_size
         A						:     Optional[Any]         =hidden_dropout_prob
         A						:     List[str]         =attention_probs_dropout_prob
         A						:     str         =max_position_embeddings
         A						:     Optional[int]         =type_vocab_size
         A						:     Optional[Any]         =initializer_range
         A						:     Tuple         =layer_norm_eps
         A						:     Optional[int]         =rotary_value
         A						:     int         =use_cache







class  SCREAMING_SNAKE_CASE_ (					lowerCAmelCase_			):
  '''simple docstring'''


  @property
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Any     )    ->				List[str]:

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







def A__  (			lowercase:     int					)				->		int:
       if not isinstance(lowercase,		lowercase					) or number < 0:
              raise ValueError('Input must be a non-negative integer'					)

       A						:     Any         =0
       while number:
              # This way we arrive at next set bit (next 1) instead of looping
              # through each bit and checking for 1s hence the
              # loop won't run 32 times it will only run the number of `1` times
              number &= number - 1
              count += 1
       return count


if __name__ == "__main__":
    import doctest

    doctest.testmod()






