





from collections import OrderedDict
from typing import Mapping

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


A       :   str					= logging.get_logger(__name__)

A       :   int					= {
    '''facebook/data2vec-text-base''': '''https://huggingface.co/data2vec/resolve/main/config.json''',
}


class     A     (SCREAMING_SNAKE_CASE       ):
			'''simple docstring'''




			__lowerCamelCase      :			int							     =       '''data2vec-text'''






			def __init__(     self  :       List[Any]				,      __lowerCAmelCase  :       List[Any]=3_05_22				,      __lowerCAmelCase  :       int=7_68				,      __lowerCAmelCase  :       int=12				,      __lowerCAmelCase  :       List[Any]=12				,      __lowerCAmelCase  :       str=30_72				,      __lowerCAmelCase  :       List[str]="gelu"				,      __lowerCAmelCase  :       Dict=0.1				,      __lowerCAmelCase  :       int=0.1				,      __lowerCAmelCase  :       List[str]=5_12				,      __lowerCAmelCase  :       Optional[Any]=2				,      __lowerCAmelCase  :       Optional[int]=0.0_2				,      __lowerCAmelCase  :       Tuple=1e-12				,      __lowerCAmelCase  :       List[Any]=1				,      __lowerCAmelCase  :       str=0				,      __lowerCAmelCase  :       List[Any]=2				,      __lowerCAmelCase  :       Optional[Any]="absolute"				,      __lowerCAmelCase  :       Union[str, Any]=True				,      __lowerCAmelCase  :       str=None				,      **__lowerCAmelCase  :       List[Any]				,      )      ->      List[str]:







					"""simple docstring"""






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

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


class     A     (SCREAMING_SNAKE_CASE       ):
			'''simple docstring'''




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







					"""simple docstring"""






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










def   __lowerCamelCase   (				__a  :int       ,	__a  :int       )						->							Optional[Any]:






		"""simple docstring"""

		if b == 0:
				return 1
		if (b % 2) == 0:
				return actual_power(__a       ,	int(b / 2       )       ) * actual_power(__a       ,	int(b / 2       )       )
		else:
				return a * actual_power(__a       ,	int(b / 2       )       ) * actual_power(__a       ,	int(b / 2       )       )







def   __lowerCamelCase   (				__a  :int       ,	__a  :int       )						->							float:






		"""simple docstring"""

		if b < 0:
				return 1 / actual_power(__a       ,	__a       )
		return actual_power(__a       ,	__a       )


if __name__ == "__main__":
					print(power(-2, -3))



