


'''simple docstring'''






from collections import OrderedDict
from typing import Mapping

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


lowercase							=logging.get_logger(__name__)

lowercase							={
    'andreasmadsen/efficient_mlm_m0.40': (
        'https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'
    ),
}






class  __magic_name__							(		lowerCAmelCase    ):
							UpperCAmelCase										="roberta-prelayernorm"






							def __init__(      self  ,							snake_case=5_0_2_6_5  ,							snake_case=7_6_8  ,							snake_case=1_2  ,							snake_case=1_2  ,							snake_case=3_0_7_2  ,							snake_case="gelu"  ,							snake_case=0.1  ,							snake_case=0.1  ,							snake_case=5_1_2  ,							snake_case=2  ,							snake_case=0.02  ,							snake_case=1E-1_2  ,							snake_case=1  ,							snake_case=0  ,							snake_case=2  ,							snake_case="absolute"  ,							snake_case=True  ,							snake_case=None  ,							**snake_case  ,							)						->  Optional[int]:




										'''simple docstring'''
										super().__init__(pad_token_id=snake_case  ,							bos_token_id=snake_case  ,							eos_token_id=snake_case  ,							**snake_case)

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






class  __magic_name__							(		lowerCAmelCase    ):






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




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





'''simple docstring'''






from __future__ import annotations

from random import choice





def lowerCamelCase__      (						__lowerCamelCase	:							Optional[int]							):







   '''simple docstring'''




   return choice(__lowerCamelCase							)





def lowerCamelCase__      (						__lowerCamelCase	:							list[int]	,   __lowerCamelCase	:							int							):







   '''simple docstring'''




   _UpperCAmelCase       :       int							   =random_pivot(__lowerCamelCase							)

   # partition based on pivot
   # linear time
   _UpperCAmelCase       :       str							   =[e for e in lst if e < pivot]
   _UpperCAmelCase       :       Dict							   =[e for e in lst if e > pivot]

   # if we get lucky, pivot might be the element we want.
   # we can easily see this:
   # small (elements smaller than k)
   # + pivot (kth element)
   # + big (elements larger than k)
   if len(__lowerCamelCase							) == k - 1:
      return pivot
   # pivot is in elements bigger than k
   elif len(__lowerCamelCase							) < k - 1:
      return kth_number(__lowerCamelCase	,   k - len(__lowerCamelCase							) - 1							)
   # pivot is in elements smaller than k
   else:
      return kth_number(__lowerCamelCase	,   __lowerCamelCase							)


if __name__ == "__main__":
 import doctest

 doctest.testmod()

