



"""simple docstring"""







def       _lowerCamelCase				(							UpperCAmelCase_ :       Optional[Any]     )	-> Dict:






	"""simple docstring"""





	A__											=					[]
	A__											=					set({"(", "[", "{"}     )
	A__											=					set({")", "]", "}"}     )
	A__											=					{"{": "}", "[": "]", "(": ")"}

	for i in range(len(UpperCAmelCase_     )     ):
		if s[i] in open_brackets:
			stack.append(s[i]     )

		elif s[i] in closed_brackets and (
		    len(UpperCAmelCase_     ) == 0 or (len(UpperCAmelCase_     ) > 0 and open_to_closed[stack.pop()] != s[i])
		):
			return False

	return len(UpperCAmelCase_     ) == 0

def       _lowerCamelCase				(							)	-> str:






	"""simple docstring"""





	A__											=					input("Enter sequence of brackets: "     )
	if is_balanced(UpperCAmelCase_     ):
		print(UpperCAmelCase_,	"is balanced"     )
	else:
		print(UpperCAmelCase_,	"is not balanced"     )


if __name__ == "__main__":
			main()











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        SCREAMING_SNAKE_CASE__					(		UpperCamelCase__ ):
 __SCREAMING_SNAKE_CASE							=      ComputeEnvironment.AMAZON_SAGEMAKER
 __SCREAMING_SNAKE_CASE							=      True
 __SCREAMING_SNAKE_CASE							=      '''ml.p3.2xlarge'''
 __SCREAMING_SNAKE_CASE							=      '''accelerate_sagemaker_execution_role'''
 __SCREAMING_SNAKE_CASE							=      '''hf-sm'''
 __SCREAMING_SNAKE_CASE							=      '''us-east-1'''
 __SCREAMING_SNAKE_CASE							=      1
 __SCREAMING_SNAKE_CASE							=      '''accelerate-sagemaker-1'''
 __SCREAMING_SNAKE_CASE							=      '''1.6'''
 __SCREAMING_SNAKE_CASE							=      '''4.4'''
 __SCREAMING_SNAKE_CASE							=      '''train.py'''
 __SCREAMING_SNAKE_CASE							=      [
     '''--model_name_or_path''',
     '''bert''',
     '''--do_train''',
     '''False''',
     '''--epochs''',
     '''3''',
     '''--learning_rate''',
     '''5e-5''',
     '''--max_steps''',
     '''50.5''',
 ]
 __SCREAMING_SNAKE_CASE							=      [
     '''--model_name_or_path''',
     '''bert''',
     '''--do_train''',
     '''--do_test''',
     '''False''',
     '''--do_predict''',
     '''--epochs''',
     '''3''',
     '''--learning_rate''',
     '''5e-5''',
     '''--max_steps''',
     '''50.5''',
 ]




class        SCREAMING_SNAKE_CASE__					(		unittest.TestCase ):



 def 							UpperCamelCase     (				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'''],__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					)





