





from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403






def 		lowerCAmelCase  (	UpperCamelCase__   :   str       ,			UpperCamelCase__   :   complex       ,			UpperCamelCase__   :   str = "x"       ,			UpperCamelCase__   :   float = 10**-10       ,			UpperCamelCase__   :   int = 1       ,			)      ->    complex:

						"""simple docstring"""





						__SCREAMING_SNAKE_CASE:				List[str]           =   symbols(UpperCamelCase__					)
						__SCREAMING_SNAKE_CASE:				List[Any]           =   lambdify(UpperCamelCase__       ,			UpperCamelCase__					)
						__SCREAMING_SNAKE_CASE:				Dict           =   lambdify(UpperCamelCase__       ,			diff(UpperCamelCase__       ,			UpperCamelCase__					)					)

						__SCREAMING_SNAKE_CASE:				int           =   starting_point

						while True:
												if diff_function(UpperCamelCase__					) != 0:
																		__SCREAMING_SNAKE_CASE:				str           =   prev_guess - multiplicity * func(UpperCamelCase__					) / diff_function(
																		    UpperCamelCase__					)
												else:
																		raise ZeroDivisionError('''Could not find root'''					) from None

												# Precision is checked by comparing the difference of consecutive guesses
												if abs(next_guess - prev_guess					) < precision:
																		return next_guess

												__SCREAMING_SNAKE_CASE:				Optional[Any]           =   next_guess


# Let's Execute
if __name__ == "__main__":
							# Find root of trigonometric function
							# Find value of pi
							print(f'''The root of sin(x) = 0 is {newton_raphson('sin(x)', 2)}''')

							# Find root of polynomial
							# Find fourth Root of 5
							print(f'''The root of x**4 - 5 = 0 is {newton_raphson('x**4 -5', 0.4 +5j)}''')

							# Find value of e
							print(
							    """The root of log(y) - 1 = 0 is """,
							    f'''{newton_raphson('log(y) - 1', 2, variable='y')}''',
							)

							# Exponential Roots
							print(
							    """The root of exp(x) - 1 = 0 is""",
							    f'''{newton_raphson('exp(x) - 1', 10, precision=0.0_0_5)}''',
							)

							# Find root of cos(x)
							print(f'''The root of cos(x) = 0 is {newton_raphson('cos(x)', 0)}''')










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






				def 			snake_case_    (  self					):

										"""simple docstring"""




										__SCREAMING_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					)



