
"""simple docstring"""

import os
import sys
import unittest


_A						=			os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
_A						=			os.path.join(git_repo_path, 'src', 'transformers')

_A						=			'\n{0} = None\n'

_A						=			'\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n'


_A						=			'\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n'






class 	_lowercase       (    unittest.TestCase		):




	def       _UpperCamelCase   (			self )		->							Optional[Any]:
			lowerCamelCase					:      str          =   find_backend('    _import_structure["models.albert"].append("AlbertTokenizerFast")' )
			self.assertIsNone(UpperCAmelCase_ )

			lowerCamelCase					:      Optional[Any]          =   find_backend('    if not is_tokenizers_available():' )
			self.assertEqual(UpperCAmelCase_		,			'tokenizers' )

			lowerCamelCase					:      Dict          =   find_backend('    if not is_tensorflow_text_available():' )
			self.assertEqual(UpperCAmelCase_		,			'tensorflow_text' )

			lowerCamelCase					:      List[Any]          =   find_backend('    if not (is_sentencepiece_available() and is_tokenizers_available()):' )
			self.assertEqual(UpperCAmelCase_		,			'sentencepiece_and_tokenizers' )

			lowerCamelCase					:      Optional[int]          =   find_backend(
			    '    if not (is_sentencepiece_available() and is_tensorflow_text_available()):' )
			self.assertEqual(UpperCAmelCase_		,			'sentencepiece_and_tensorflow_text' )

			lowerCamelCase					:      Union[str, Any]          =   find_backend(
			    '    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):' )
			self.assertEqual(UpperCAmelCase_		,			'sentencepiece_and_tokenizers_and_vision' )




	def       _UpperCamelCase   (			self )		->							int:
			lowerCamelCase					:      List[str]          =   read_init()
			# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
			self.assertIn('torch'		,			UpperCAmelCase_ )
			self.assertIn('tensorflow_text'		,			UpperCAmelCase_ )
			self.assertIn('sentencepiece_and_tokenizers'		,			UpperCAmelCase_ )

			# Likewise, we can't assert on the exact content of a key
			self.assertIn('BertModel'		,			objects['torch'] )
			self.assertIn('TFBertModel'		,			objects['tf'] )
			self.assertIn('FlaxBertModel'		,			objects['flax'] )
			self.assertIn('BertModel'		,			objects['torch'] )
			self.assertIn('TFBertTokenizer'		,			objects['tensorflow_text'] )
			self.assertIn('convert_slow_tokenizer'		,			objects['sentencepiece_and_tokenizers'] )




	def       _UpperCamelCase   (			self )		->							List[str]:
			lowerCamelCase					:      Any          =   create_dummy_object('CONSTANT'		,			'\'torch\'' )
			self.assertEqual(UpperCAmelCase_		,			'\nCONSTANT = None\n' )

			lowerCamelCase					:      Optional[int]          =   create_dummy_object('function'		,			'\'torch\'' )
			self.assertEqual(
			    UpperCAmelCase_		,			'\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n' )

			lowerCamelCase					:      int          =   '\nclass FakeClass(metaclass=DummyObject):\n    _backends = \'torch\'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, \'torch\')\n'
			lowerCamelCase					:      str          =   create_dummy_object('FakeClass'		,			'\'torch\'' )
			self.assertEqual(UpperCAmelCase_		,			UpperCAmelCase_ )




	def       _UpperCamelCase   (			self )		->							Tuple:
			lowerCamelCase					:      Optional[Any]          =   '# This file is autogenerated by the command `make fix-copies`, do not edit.\nfrom ..utils import DummyObject, requires_backends\n\n\nCONSTANT = None\n\n\ndef function(*args, **kwargs):\n    requires_backends(function, ["torch"])\n\n\nclass FakeClass(metaclass=DummyObject):\n    _backends = ["torch"]\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, ["torch"])\n'
			lowerCamelCase					:      Dict          =   create_dummy_files({'torch': ['CONSTANT', 'function', 'FakeClass']} )
			self.assertEqual(dummy_files['torch']		,			UpperCAmelCase_ )








"""simple docstring"""

def 		UpperCAmelCase (		a_ = 1000      ):





		'''simple docstring'''


		lowerCamelCase					:      Dict          =   2**power
		lowerCamelCase					:      List[str]          =   str(a_      )
		lowerCamelCase					:      Dict          =   list(a_      )
		lowerCamelCase					:      Optional[Any]          =   0

		for i in list_num:
				sum_of_num += int(a_      )

		return sum_of_num


if __name__ == "__main__":
					_A						=			int(input('Enter the power of 2: ').strip())
					print('2 ^ ', power, ' = ', 2**power)
					_A						=			solution(power)
					print('Sum of the digits is: ', result)






