
import unittest
from dataclasses import dataclass

import pytest

from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict

@dataclass
class     a		(_lowerCAmelCase				):




							"""simple docstring"""


							__UpperCAmelCase   :							Optional[Any]					  =  ComputeEnvironment.AMAZON_SAGEMAKER
							__UpperCAmelCase   :							int					  =  True
							__UpperCAmelCase   :							int					  =  "ml.p3.2xlarge"
							__UpperCAmelCase   :							Any					  =  "accelerate_sagemaker_execution_role"
							__UpperCAmelCase   :							Union[str, Any]					  =  "hf-sm"
							__UpperCAmelCase   :							Optional[Any]					  =  "us-east-1"
							__UpperCAmelCase   :							str					  =  1
							__UpperCAmelCase   :							int					  =  "accelerate-sagemaker-1"
							__UpperCAmelCase   :							str					  =  "1.6"
							__UpperCAmelCase   :							str					  =  "4.4"
							__UpperCAmelCase   :							Tuple					  =  "train.py"
							__UpperCAmelCase   :							Optional[int]					  =  [
							    "--model_name_or_path",
							    "bert",
							    "--do_train",
							    "False",
							    "--epochs",
							    "3",
							    "--learning_rate",
							    "5e-5",
							    "--max_steps",
							    "50.5",
							]
							__UpperCAmelCase   :							Union[str, Any]					  =  [
							    "--model_name_or_path",
							    "bert",
							    "--do_train",
							    "--do_test",
							    "False",
							    "--do_predict",
							    "--epochs",
							    "3",
							    "--learning_rate",
							    "5e-5",
							    "--max_steps",
							    "50.5",
							]

class     a		(unittest.TestCase				):




							"""simple docstring"""


							def    __snake_case (							self	:  List[str]    )     ->   Optional[int]:
														# If no defaults are changed, `to_kwargs` returns an empty dict.
														__snake_case		:      Optional[Any]										=       _convert_nargs_to_dict(MockLaunchConfig.success_training_script_args    )
														assert isinstance(converted_args["model_name_or_path"]   ,     lowerCamelCase    )
														assert isinstance(converted_args["do_train"]   ,     lowerCamelCase    )
														assert isinstance(converted_args["epochs"]   ,     lowerCamelCase    )
														assert isinstance(converted_args["learning_rate"]   ,     lowerCamelCase    )
														assert isinstance(converted_args["max_steps"]   ,     lowerCamelCase    )

														with pytest.raises(lowerCamelCase    ):
																					_convert_nargs_to_dict(MockLaunchConfig.fail_training_script_args    )





def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase     ):
							return x if y == 0 else greatest_common_divisor(__lowerCamelCase							,     x % y     )







def     lowerCAmelCase_					( __lowerCamelCase							,     __lowerCamelCase     ):
							return (x * y) // greatest_common_divisor(__lowerCamelCase							,     __lowerCamelCase     )







def     lowerCAmelCase_					( __lowerCamelCase = 2_0     ):
							__snake_case		:      Optional[Any]										=       1
							for i in range(1							,     n + 1     ):
														__snake_case		:      Any										=       lcm(__lowerCamelCase							,     __lowerCamelCase     )
							return g


if __name__ == "__main__":
			print(f'''{solution() = }''')

