
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/data2vec-text-base''': '''https://huggingface.co/data2vec/resolve/main/config.json''',
}






class     UpperCAmelCase						(		A_					):
   A__   :						int			=	'''data2vec-text'''



   def __init__(self						:   List[Any]       ,		snake_case__						:   List[Any]=3_05_22       ,		snake_case__						:   int=7_68       ,		snake_case__						:   int=12       ,		snake_case__						:   List[Any]=12       ,		snake_case__						:   str=30_72       ,		snake_case__						:   List[str]="gelu"       ,		snake_case__						:   Dict=0.1       ,		snake_case__						:   int=0.1       ,		snake_case__						:   List[str]=5_12       ,		snake_case__						:   Optional[Any]=2       ,		snake_case__						:   Optional[int]=0.02       ,		snake_case__						:   Tuple=1e-12       ,		snake_case__						:   List[Any]=1       ,		snake_case__						:   str=0       ,		snake_case__						:   List[Any]=2       ,		snake_case__						:   Optional[Any]="absolute"       ,		snake_case__						:   Union[str, Any]=True       ,		snake_case__						:   str=None       ,		**snake_case__						:   List[Any]       ,		)						->      List[str]:


          '''simple docstring'''


          super().__init__(pad_token_id=__lowerCAmelCase       ,		bos_token_id=__lowerCAmelCase       ,		eos_token_id=__lowerCAmelCase       ,		**__lowerCAmelCase					)

          snake_case			:  Optional[Any]     							= vocab_size
          snake_case			:  str     							= hidden_size
          snake_case			:  Union[str, Any]     							= num_hidden_layers
          snake_case			:  str     							= num_attention_heads
          snake_case			:  List[Any]     							= hidden_act
          snake_case			:  Optional[Any]     							= intermediate_size
          snake_case			:  int     							= hidden_dropout_prob
          snake_case			:  str     							= attention_probs_dropout_prob
          snake_case			:  int     							= max_position_embeddings
          snake_case			:  Dict     							= type_vocab_size
          snake_case			:  int     							= initializer_range
          snake_case			:  Union[str, Any]     							= layer_norm_eps
          snake_case			:  Any     							= position_embedding_type
          snake_case			:  Optional[int]     							= use_cache
          snake_case			:  List[str]     							= classifier_dropout






class     UpperCAmelCase						(		A_					):



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


          '''simple docstring'''


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












def   __lowerCamelCase   (				__a  :str       )						->							bool:






		"""simple docstring"""

		A__     =  0
		for ch in input_str:
				A__     =  ord(__a       )
				A__     =  pow(2       ,	__a       )

				# If we already turned on bit for current character's unicode
				if bitmap >> ch_unicode & 1 == 1:
						return False
				bitmap |= ch_bit_index_on
		return True


if __name__ == "__main__":
					import doctest

					doctest.testmod()



