


import os

import pytest
from attr import dataclass


_A		       =						'us-east-1'  # defaults region






@dataclass
class     UpperCAmelCase__       :



    """simple docstring"""






    UpperCAmelCase__						:		str
    UpperCAmelCase__						:		List[str]      =  'arn:aws:iam::558105141721:role/sagemaker_execution_role'
    UpperCAmelCase__						:		Optional[int]      =  {
        'task_name': 'mnli',
        'per_device_train_batch_size': 1_6,
        'per_device_eval_batch_size': 1_6,
        'do_train': True,
        'do_eval': True,
        'do_predict': True,
        'output_dir': '/opt/ml/model',
        'overwrite_output_dir': True,
        'max_steps': 5_0_0,
        'save_steps': 5_5_0_0,
    }
    UpperCAmelCase__						:		Any      =  {**hyperparameters, 'max_steps': 1_0_0_0}






    @property
    def _a					(			self    )  ->       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 _a					(			self    )  ->       str:
         return f'{self.framework}-transfromers-test'






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






    @property
    def _a					(			self    )  ->       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 						_UpperCAmelCase				(			SCREAMING_SNAKE_CASE__			:					Optional[int]				):
     __UpperCamelCase    							=SageMakerTestEnvironment(framework=request.cls.framework				)







from __future__ import annotations




def 				a						(							snake_case__:					list[int]						,   snake_case__:					int						,   snake_case__:					int						,   snake_case__:					int					):


				'''simple docstring'''
				if (direction == 1 and array[indexa] > array[indexa]) or (
				    direction == 0 and array[indexa] < array[indexa]
				):
								lowercase_  ,	lowercase_       =					array[indexa], array[indexa]




def 				a						(							snake_case__:					list[int]						,   snake_case__:					int						,   snake_case__:					int						,   snake_case__:					int					):


				'''simple docstring'''
				if length > 1:
								lowercase_       =					int(length / 2					)
								for i in range(snake_case__						,   low + middle					):
												comp_and_swap(snake_case__						,   snake_case__						,   i + middle						,   snake_case__					)
								bitonic_merge(snake_case__						,   snake_case__						,   snake_case__						,   snake_case__					)
								bitonic_merge(snake_case__						,   low + middle						,   snake_case__						,   snake_case__					)




def 				a						(							snake_case__:					list[int]						,   snake_case__:					int						,   snake_case__:					int						,   snake_case__:					int					):


				'''simple docstring'''
				if length > 1:
								lowercase_       =					int(length / 2					)
								bitonic_sort(snake_case__						,   snake_case__						,   snake_case__						,   1					)
								bitonic_sort(snake_case__						,   low + middle						,   snake_case__						,   0					)
								bitonic_merge(snake_case__						,   snake_case__						,   snake_case__						,   snake_case__					)


if __name__ == "__main__":
						__a  			=					input('Enter numbers separated by a comma:\n').strip()
						__a  			=					[int(item.strip()) for item in user_input.split(',')]

						bitonic_sort(unsorted, 0, len(unsorted), 1)
						print('\nSorted array in ascending order is: ', end='')
						print(*unsorted, sep=', ')

						bitonic_merge(unsorted, 0, len(unsorted), 0)
						print('Sorted array in descending order is: ', end='')
						print(*unsorted, sep=', ')




