

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


SCREAMING_SNAKE_CASE		:str						=     {
    """configuration_megatron_bert""": ["""MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MegatronBertConfig"""],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE		:List[Any]						=     [
     """MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST""",
     """MegatronBertForCausalLM""",
     """MegatronBertForMaskedLM""",
     """MegatronBertForMultipleChoice""",
     """MegatronBertForNextSentencePrediction""",
     """MegatronBertForPreTraining""",
     """MegatronBertForQuestionAnswering""",
     """MegatronBertForSequenceClassification""",
     """MegatronBertForTokenClassification""",
     """MegatronBertModel""",
     """MegatronBertPreTrainedModel""",
 ]

if TYPE_CHECKING:
 from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_megatron_bert import (
      MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
      MegatronBertForCausalLM,
      MegatronBertForMaskedLM,
      MegatronBertForMultipleChoice,
      MegatronBertForNextSentencePrediction,
      MegatronBertForPreTraining,
      MegatronBertForQuestionAnswering,
      MegatronBertForSequenceClassification,
      MegatronBertForTokenClassification,
      MegatronBertModel,
      MegatronBertPreTrainedModel,
  )

else:
 import sys

 SCREAMING_SNAKE_CASE		:Tuple						=     _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



from __future__ import annotations

import math




def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			,						SCREAMING_SNAKE_CASE_			)->						int:



    """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 			lowerCAmelCase(      )->						None:



    """simple docstring"""






    UpperCamelCase_			  =						[9_0, 2_3, 6, 3_3, 2_1, 6_5, 1_2_3, 3_4_4_2_3]
    UpperCamelCase_			  =						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()
