
"""simple docstring"""

from __future__ import annotations

SCREAMING_SNAKE_CASE_            =    [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
SCREAMING_SNAKE_CASE_            =    [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]




def      lowercase__    (       lowerCAmelCase					:       list[float]			)			->   list[float]:






    """simple docstring"""




    UpperCAmelCase          =       []
    UpperCAmelCase          =       len(lowerCAmelCase			)

    for i in range(lowerCAmelCase			):
        UpperCAmelCase          =       -1
        for j in range(i + 1			,					lowerCAmelCase			):
            if arr[i] < arr[j]:
                UpperCAmelCase          =       arr[j]
                break
        result.append(lowerCAmelCase			)
    return result




def      lowercase__    (       lowerCAmelCase					:       list[float]			)			->   list[float]:






    """simple docstring"""




    UpperCAmelCase          =       []
    for i, outer in enumerate(lowerCAmelCase			):
        UpperCAmelCase          =       -1
        for inner in arr[i + 1 :]:
            if outer < inner:
                UpperCAmelCase          =       inner
                break
        result.append(lowerCAmelCase			)
    return result




def      lowercase__    (       lowerCAmelCase					:       list[float]			)			->   list[float]:






    """simple docstring"""




    UpperCAmelCase          =       len(lowerCAmelCase			)
    UpperCAmelCase          =       []
    UpperCAmelCase          =       [-1] * arr_size

    for index in reversed(range(lowerCAmelCase			)			):
        if stack:
            while stack[-1] <= arr[index]:
                stack.pop()
                if not stack:
                    break
        if stack:
            UpperCAmelCase          =       stack[-1]
        stack.append(arr[index]			)
    return result


if __name__ == "__main__":
   from doctest import testmod
   from timeit import timeit

   testmod()
   print(next_greatest_element_slow(arr))
   print(next_greatest_element_fast(arr))
   print(next_greatest_element(arr))

   SCREAMING_SNAKE_CASE_            =    (
       '''from __main__ import arr, next_greatest_element_slow, '''
       '''next_greatest_element_fast, next_greatest_element'''
   )
   print(
       '''next_greatest_element_slow():''',
       timeit('''next_greatest_element_slow(arr)''', setup=setup),
   )
   print(
       '''next_greatest_element_fast():''',
       timeit('''next_greatest_element_fast(arr)''', setup=setup),
   )
   print(
       '''     next_greatest_element():''',
       timeit('''next_greatest_element(arr)''', setup=setup),
   )





"""simple docstring"""

from collections import OrderedDict
from typing import Mapping

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


SCREAMING_SNAKE_CASE_            =    logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_            =    {
    '''kssteven/ibert-roberta-base''': '''https://huggingface.co/kssteven/ibert-roberta-base/resolve/main/config.json''',
    '''kssteven/ibert-roberta-large''': '''https://huggingface.co/kssteven/ibert-roberta-large/resolve/main/config.json''',
    '''kssteven/ibert-roberta-large-mnli''': (
        '''https://huggingface.co/kssteven/ibert-roberta-large-mnli/resolve/main/config.json'''
    ),
}
class   _UpperCAmelCase				(		SCREAMING_SNAKE_CASE_				):
      __SCREAMING_SNAKE_CASE :				Tuple				   =						"ibert"




      def __init__(				self ,							lowercase_=3_0_5_2_2 ,							lowercase_=7_6_8 ,							lowercase_=1_2 ,							lowercase_=1_2 ,							lowercase_=3_0_7_2 ,							lowercase_="gelu" ,							lowercase_=0.1 ,							lowercase_=0.1 ,							lowercase_=5_1_2 ,							lowercase_=2 ,							lowercase_=0.0_2 ,							lowercase_=1E-12 ,							lowercase_=1 ,							lowercase_=0 ,							lowercase_=2 ,							lowercase_="absolute" ,							lowercase_=False ,							lowercase_="none" ,							**lowercase_ ,							)    ->       Optional[int]:
          super().__init__(pad_token_id=lowercase_ ,							bos_token_id=lowercase_ ,							eos_token_id=lowercase_ ,							**lowercase_				)

          UpperCAmelCase          =       vocab_size
          UpperCAmelCase          =       hidden_size
          UpperCAmelCase          =       num_hidden_layers
          UpperCAmelCase          =       num_attention_heads
          UpperCAmelCase          =       hidden_act
          UpperCAmelCase          =       intermediate_size
          UpperCAmelCase          =       hidden_dropout_prob
          UpperCAmelCase          =       attention_probs_dropout_prob
          UpperCAmelCase          =       max_position_embeddings
          UpperCAmelCase          =       type_vocab_size
          UpperCAmelCase          =       initializer_range
          UpperCAmelCase          =       layer_norm_eps
          UpperCAmelCase          =       position_embedding_type
          UpperCAmelCase          =       quant_mode
          UpperCAmelCase          =       force_dequant

class   _UpperCAmelCase				(		SCREAMING_SNAKE_CASE_				):




      @property
      def      a_   (				self				)    ->       Mapping[str, Mapping[int, str]]:
          if self.task == "multiple-choice":
              UpperCAmelCase          =       {0: 'batch', 1: 'choice', 2: 'sequence'}
          else:
              UpperCAmelCase          =       {0: 'batch', 1: 'sequence'}
          return OrderedDict(
              [
                  ('input_ids', dynamic_axis),
                  ('attention_mask', dynamic_axis),
              ]				)



