



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  __snake_case      (   SCREAMING_SNAKE_CASE):







							'''simple docstring'''






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




class  __snake_case      (   unittest.TestCase):







							'''simple docstring'''






							def _a      (							self		):
											# If no defaults are changed, `to_kwargs` returns an empty dict.
											a__				      =		_convert_nargs_to_dict(MockLaunchConfig.success_training_script_args		)
											assert isinstance(converted_args["""model_name_or_path"""]  ,  a_		)
											assert isinstance(converted_args["""do_train"""]  ,  a_		)
											assert isinstance(converted_args["""epochs"""]  ,  a_		)
											assert isinstance(converted_args["""learning_rate"""]  ,  a_		)
											assert isinstance(converted_args["""max_steps"""]  ,  a_		)

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






from __future__ import annotations

UpperCAmelCase							 =					8.988E9  # units = N * m^s * C^-2

def 			A_      (	__a     :				float ,		__a     :				float ,		__a     :				float ,		__a     :				float		):

				"""simple docstring"""
				a__				      =		abs(chargea * chargea		)

				if (force, chargea, chargea, distance).count(0		) != 1:
								raise ValueError("""One and only one argument must be 0"""		)
				if distance < 0:
								raise ValueError("""Distance cannot be negative"""		)
				if force == 0:
								a__				      =		COULOMBS_CONSTANT * charge_product / (distance**2)
								return {"force": force}
				elif chargea == 0:
								a__				      =		abs(__a		) * (distance**2) / (COULOMBS_CONSTANT * chargea)
								return {"charge1": chargea}
				elif chargea == 0:
								a__				      =		abs(__a		) * (distance**2) / (COULOMBS_CONSTANT * chargea)
								return {"charge2": chargea}
				elif distance == 0:
								a__				      =		(COULOMBS_CONSTANT * charge_product / abs(__a		)) ** 0.5
								return {"distance": distance}
				raise ValueError("""Exactly one argument must be 0"""		)


if __name__ == "__main__":
	import doctest

	doctest.testmod()

