


'''simple docstring'''
from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


UpperCamelCase__          = {
    'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
    'susnato/ernie-m-large_pytorch': 'https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json',
}




class      lowerCamelCase_  (      _SCREAMING_SNAKE_CASE ):
      lowerCAmelCase__							=	"""ernie_m"""
      lowerCAmelCase__							=	{"dropout": "classifier_dropout", "num_classes": "num_labels"}






      def __init__(   self							:       Dict		,		_A							:       Dict = 250_002		,		_A							:       int = 768		,		_A							:       str = 12		,		_A							:       Union[str, Any] = 12		,		_A							:       Dict = 3_072		,		_A							:       Optional[Any] = "gelu"		,		_A							:       Tuple = 0.1		,		_A							:       Optional[int] = 0.1		,		_A							:       List[Any] = 514		,		_A							:       Optional[int] = 0.0_2		,		_A							:       int = 1		,		_A							:       int = 1e-05		,		_A							:       str=None		,		_A							:       Any=False		,		_A							:       Tuple=0.0		,		**_A							:       Union[str, Any]		,		):


          '''simple docstring'''


          super().__init__(pad_token_id=__snake_case		,		**__snake_case					)
          UpperCAmelCase__     :						int						=							vocab_size
          UpperCAmelCase__     :						Dict						=							hidden_size
          UpperCAmelCase__     :						Optional[Any]						=							num_hidden_layers
          UpperCAmelCase__     :						Union[str, Any]						=							num_attention_heads
          UpperCAmelCase__     :						Any						=							intermediate_size
          UpperCAmelCase__     :						List[Any]						=							hidden_act
          UpperCAmelCase__     :						Any						=							hidden_dropout_prob
          UpperCAmelCase__     :						int						=							attention_probs_dropout_prob
          UpperCAmelCase__     :						Union[str, Any]						=							max_position_embeddings
          UpperCAmelCase__     :						str						=							initializer_range
          UpperCAmelCase__     :						Dict						=							layer_norm_eps
          UpperCAmelCase__     :						Dict						=							classifier_dropout
          UpperCAmelCase__     :						Dict						=							is_decoder
          UpperCAmelCase__     :						Optional[int]						=							act_dropout







from __future__ import annotations

def      UpperCAmelCase_    (    _UpperCAmelCase							:list[float]  ,						_UpperCAmelCase							:list[float]				)	->				float:
     '''simple docstring'''


     A_          =       sorted(numsa + numsa				)
     A_   ,    A_          =       divmod(len(_UpperCAmelCase				)  ,						2				)
     if mod == 1:
          return all_numbers[div]
     else:
          return (all_numbers[div] + all_numbers[div - 1]) / 2


if __name__ == "__main__":
      import doctest

      doctest.testmod()
      a__      :     Optional[Any]         =		[float(x) for x in input('Enter the elements of first array: ').split()]
      a__      :     int         =		[float(x) for x in input('Enter the elements of second array: ').split()]
      print(f'''The median of two arrays is: {median_of_two_arrays(array_a, array_a)}''')



