





"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


a		:				int  			=    logging.get_logger(__name__)

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


class  __UpperCamelCase       (		a__		):
							lowerCamelCase     :      Tuple         ='data2vec-text'






							def __init__(     self   ,      lowerCAmelCase__=3_0522   ,      lowerCAmelCase__=768   ,      lowerCAmelCase__=12   ,      lowerCAmelCase__=12   ,      lowerCAmelCase__=3072   ,      lowerCAmelCase__="gelu"   ,      lowerCAmelCase__=0.1   ,      lowerCAmelCase__=0.1   ,      lowerCAmelCase__=512   ,      lowerCAmelCase__=2   ,      lowerCAmelCase__=0.02   ,      lowerCAmelCase__=1E-12   ,      lowerCAmelCase__=1   ,      lowerCAmelCase__=0   ,      lowerCAmelCase__=2   ,      lowerCAmelCase__="absolute"   ,      lowerCAmelCase__=True   ,      lowerCAmelCase__=None   ,      **lowerCAmelCase__   ,      )			->				str:
								super().__init__(pad_token_id=UpperCAmelCase__   ,      bos_token_id=UpperCAmelCase__   ,      eos_token_id=UpperCAmelCase__   ,      **UpperCAmelCase__   )

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


class  __UpperCamelCase       (		a__		):






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









"""simple docstring"""




import baseaa






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					str      )				->bytes:






	'''simple docstring'''






	return baseaa.aaaencode(string.encode("utf-8"      )      )






def    _SCREAMING_SNAKE_CASE	(			_lowercase		:					bytes      )				->str:






	'''simple docstring'''






	return baseaa.aaadecode(_lowercase      ).decode("utf-8"      )


if __name__ == "__main__":
		import doctest

		doctest.testmod()


