




from collections import OrderedDict
from typing import Mapping

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


__lowerCAmelCase	:       Optional[int]     =	logging.get_logger(__name__)

__lowerCAmelCase	:       List[Any]     =	{
    'facebook/data2vec-text-base': 'https://huggingface.co/data2vec/resolve/main/config.json',
}




class 					snake_case__							(_UpperCamelCase     ):
				"""simple docstring"""



				SCREAMING_SNAKE_CASE_ :							str											=      """data2vec-text"""





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



				@property
				def 							__UpperCAmelCase							(   self       :  Optional[Any]							)      ->  Mapping[str, Mapping[int, str]]:
							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     __magic_name__       (				A	:      list     ):






			'''simple docstring'''







			for i in range(len(A     ) - 1,						0,						-1     ):
						a					=    False

						for j in range(A,						0,						-1     ):
									if unsorted[j] < unsorted[j - 1]:
												a					,	a					=    unsorted[j - 1], unsorted[j]
												a					=    True

						for j in range(A     ):
									if unsorted[j] > unsorted[j + 1]:
												a					,	a					=    unsorted[j + 1], unsorted[j]
												a					=    True

						if not swapped:
									break
			return unsorted


if __name__ == "__main__":
		import doctest

		doctest.testmod()
		__lowerCAmelCase	:       Tuple     =	input('Enter numbers separated by a comma:\n').strip()
		__lowerCAmelCase	:       List[Any]     =	[int(item) for item in user_input.split(',')]
		print(F'''{cocktail_shaker_sort(unsorted) = }''')






