

'''simple docstring'''
import os

import pytest
from attr import dataclass


lowerCamelCase					: int   					=	"us-east-1"  # defaults region







@dataclass
class 				A__       :
  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 		A    (						self :      int					)      ->       str:





       '''simple docstring'''






       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 		A    (						self :      Optional[Any]					)      ->       int:





       '''simple docstring'''






       return f"{self.framework}-transfromers-test"





  @property
  def 		A    (						self :      Optional[Any]					)      ->       int:





       '''simple docstring'''






       return f"./tests/sagemaker/scripts/{self.framework}"





  @property
  def 		A    (						self :      List[Any]					)      ->       int:





       '''simple docstring'''






       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 			_lowerCAmelCase   (		_UpperCamelCase		:	Optional[int]							) ->     Dict:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE				       =SageMakerTestEnvironment(framework=request.cls.framework							)







from collections.abc import Callable





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE							,     _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




    _A     =							a
    _A     =							b
    if function(_SCREAMING_SNAKE_CASE				) == 0:  # one of the a or b is a root for the function
        return a
    elif function(_SCREAMING_SNAKE_CASE				) == 0:
        return b
    elif (
        function(_SCREAMING_SNAKE_CASE				) * function(_SCREAMING_SNAKE_CASE				) > 0
    ):  # if none of these are root and they are both positive or negative,
        # then this algorithm can't find the root
        raise ValueError('could not find root in given interval.'				)
    else:
        _A     =							start + (end - start) / 2.0
        while abs(start - mid				) > 10**-7:  # until precisely equals to 10^-7
            if function(_SCREAMING_SNAKE_CASE				) == 0:
                return mid
            elif function(_SCREAMING_SNAKE_CASE				) * function(_SCREAMING_SNAKE_CASE				) < 0:
                _A     =							mid
            else:
                _A     =							mid
            _A     =							start + (end - start) / 2.0
        return mid





def 				__lowerCAmelCase(       _SCREAMING_SNAKE_CASE				)							-> float:




    """simple docstring"""




    return x**3 - 2 * x - 5


if __name__ == "__main__":
 print(bisection(f, 1, 1_000))

 import doctest

 doctest.testmod()





