





import os

import pytest
from attr import dataclass


_snake_case  :    Any						    =  'us-east-1'  # defaults region



@dataclass
class 				_UpperCAmelCase    :

  """simple docstring"""


  a_        = 42
  a_        = """arn:aws:iam::558105141721:role/sagemaker_execution_role"""
  a_        = {
      """task_name""": """mnli""",
      """per_device_train_batch_size""": 16,
      """per_device_eval_batch_size""": 16,
      """do_train""": True,
      """do_eval""": True,
      """do_predict""": True,
      """output_dir""": """/opt/ml/model""",
      """overwrite_output_dir""": True,
      """max_steps""": 5_00,
      """save_steps""": 55_00,
  }
  a_        = {**hyperparameters, """max_steps""": 10_00}






  @property
  def 				lowercase		(				self :		Dict     )							->						str:
     if self.framework == "pytorch":
        return [
            {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
            {"Name": "eval_accuracy", "Regex": r"eval_accuracy.*=\D*(.*?)$"},
            {"Name": "eval_loss", "Regex": r"eval_loss.*=\D*(.*?)$"},
        ]
     else:
        return [
            {"Name": "train_runtime", "Regex": r"train_runtime.*=\D*(.*?)$"},
            {"Name": "eval_accuracy", "Regex": r"loss.*=\D*(.*?)]?$"},
            {"Name": "eval_loss", "Regex": r"sparse_categorical_accuracy.*=\D*(.*?)]?$"},
        ]






  @property
  def 				lowercase		(				self :		List[str]     )							->						str:
     return f"""{self.framework}-transfromers-test"""






  @property
  def 				lowercase		(				self :		int     )							->						str:
     return f"""./tests/sagemaker/scripts/{self.framework}"""






  @property
  def 				lowercase		(				self :		List[str]     )							->						str:
     if self.framework == "pytorch":
        return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-pytorch-training:1.7.1-transformers4.6.1-gpu-py36-cu110-ubuntu18.04"
     else:
        return "763104351884.dkr.ecr.us-east-1.amazonaws.com/huggingface-tensorflow-training:2.4.1-transformers4.6.1-gpu-py37-cu110-ubuntu18.04"





@pytest.fixture(scope='class'	)
def   a_    ( lowerCAmelCase_      :			int	):
   __lowerCAmelCase								=	SageMakerTestEnvironment(framework=request.cls.framework	)








from __future__ import annotations

import math

def   a_    ( lowerCAmelCase_      :			int,	lowerCAmelCase_      :			int,	lowerCAmelCase_      :			bool,	lowerCAmelCase_      :			list[int],	lowerCAmelCase_      :			float	):

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

   if len(lowerCAmelCase_	) == 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,	lowerCAmelCase_,	lowerCAmelCase_,	lowerCAmelCase_	),	minimax(depth + 1,	node_index * 2 + 1,	lowerCAmelCase_,	lowerCAmelCase_,	lowerCAmelCase_	),	)

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

def   a_    ( ):
   __lowerCAmelCase								=	[90, 23, 6, 33, 21, 65, 123, 3_4423]
   __lowerCAmelCase								=	math.log(len(lowerCAmelCase_	),	2	)
   print('Optimal value : ',	end=''	)
   print(minimax(0,	0,	lowerCAmelCase_,	lowerCAmelCase_,	lowerCAmelCase_	)	)


if __name__ == "__main__":
     import doctest

     doctest.testmod()
     main()

