
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


a_											=						logging.get_logger(__name__)

a_											=						{
    "studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
    "studio-ousia/luke-large": "https://huggingface.co/studio-ousia/luke-large/resolve/main/config.json",
}






class    UpperCAmelCase_				(	snake_case__					):
 UpperCAmelCase_		    =						"""luke"""





 def __init__(    self ,       lowercase_=5_02_67 ,       lowercase_=50_00_00 ,       lowercase_=7_68 ,       lowercase_=2_56 ,       lowercase_=12 ,       lowercase_=12 ,       lowercase_=30_72 ,       lowercase_="gelu" ,       lowercase_=0.1 ,       lowercase_=0.1 ,       lowercase_=5_12 ,       lowercase_=2 ,       lowercase_=0.02 ,       lowercase_=1E-12 ,       lowercase_=True ,       lowercase_=None ,       lowercase_=1 ,       lowercase_=0 ,       lowercase_=2 ,       **lowercase_ ,       ):
     super().__init__(pad_token_id=lowercase_ ,       bos_token_id=lowercase_ ,       eos_token_id=lowercase_ ,       **lowercase_)

     snake_case_ :    Union[str, Any]     			=						vocab_size
     snake_case_ :    Union[str, Any]     			=						entity_vocab_size
     snake_case_ :    str     			=						hidden_size
     snake_case_ :    Tuple     			=						entity_emb_size
     snake_case_ :    Optional[Any]     			=						num_hidden_layers
     snake_case_ :    Dict     			=						num_attention_heads
     snake_case_ :    List[Any]     			=						hidden_act
     snake_case_ :    int     			=						intermediate_size
     snake_case_ :    Optional[int]     			=						hidden_dropout_prob
     snake_case_ :    Any     			=						attention_probs_dropout_prob
     snake_case_ :    Optional[int]     			=						max_position_embeddings
     snake_case_ :    Optional[Any]     			=						type_vocab_size
     snake_case_ :    List[str]     			=						initializer_range
     snake_case_ :    Dict     			=						layer_norm_eps
     snake_case_ :    int     			=						use_entity_aware_attention
     snake_case_ :    Dict     			=						classifier_dropout






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

import math

def 						UpperCamelCase_     (	__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ):
    """simple docstring"""






    if depth < 0:
        raise ValueError("Depth cannot be less than 0"       )

    if len(__SCREAMING_SNAKE_CASE       ) == 0:
        raise ValueError("Scores cannot be empty"       )

    if depth == height:
        return scores[node_index]

    if is_max:
        return max(
            minimax(depth + 1,		node_index * 2,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ),		minimax(depth + 1,		node_index * 2 + 1,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ),		)

    return min(
        minimax(depth + 1,		node_index * 2,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ),		minimax(depth + 1,		node_index * 2 + 1,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       ),		)

def 						UpperCamelCase_     (	):
    """simple docstring"""






    snake_case_ :    int     			=						[9_0, 2_3, 6, 3_3, 2_1, 6_5, 1_2_3, 3_4_4_2_3]
    snake_case_ :    Union[str, Any]     			=						math.log(len(__SCREAMING_SNAKE_CASE       ),		2       )
    print("Optimal value : ",		end=""       )
    print(minimax(0,		0,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE,		__SCREAMING_SNAKE_CASE       )       )


if __name__ == "__main__":
  import doctest

  doctest.testmod()
  main()




