
import os
import sys
import unittest


_UpperCAmelCase      :				List[Any]          = 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
_UpperCAmelCase      :				str          = os.path.join(git_repo_path, "src", "transformers")

_UpperCAmelCase      :				Union[str, Any]          = "\n{0} = None\n"

_UpperCAmelCase      :				List[Any]          = "\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n"


_UpperCAmelCase      :				Optional[int]          = "\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n"


class        lowercase      (	unittest.TestCase     ):



		def __UpperCamelCase				(				self )						->      Tuple:
				"""simple docstring"""
				UpperCamelCase						=  find_backend('    _import_structure["models.albert"].append("AlbertTokenizerFast")' )
				self.assertIsNone(A_ )

				UpperCamelCase						=  find_backend('    if not is_tokenizers_available():' )
				self.assertEqual(A_       ,   'tokenizers' )

				UpperCamelCase						=  find_backend('    if not is_tensorflow_text_available():' )
				self.assertEqual(A_       ,   'tensorflow_text' )

				UpperCamelCase						=  find_backend('    if not (is_sentencepiece_available() and is_tokenizers_available()):' )
				self.assertEqual(A_       ,   'sentencepiece_and_tokenizers' )

				UpperCamelCase						=  find_backend(
				    '    if not (is_sentencepiece_available() and is_tensorflow_text_available()):' )
				self.assertEqual(A_       ,   'sentencepiece_and_tensorflow_text' )

				UpperCamelCase						=  find_backend(
				    '    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):' )
				self.assertEqual(A_       ,   'sentencepiece_and_tokenizers_and_vision' )



		def __UpperCamelCase				(				self )						->      Tuple:
				"""simple docstring"""
				UpperCamelCase						=  read_init()
				# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
				self.assertIn('torch'       ,   A_ )
				self.assertIn('tensorflow_text'       ,   A_ )
				self.assertIn('sentencepiece_and_tokenizers'       ,   A_ )

				# 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 )						->      Optional[int]:
				"""simple docstring"""
				UpperCamelCase						=  create_dummy_object('CONSTANT'       ,   '\'torch\'' )
				self.assertEqual(A_       ,   '\nCONSTANT = None\n' )

				UpperCamelCase						=  create_dummy_object('function'       ,   '\'torch\'' )
				self.assertEqual(
				    A_       ,   '\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n' )

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



		def __UpperCamelCase				(				self )						->      int:
				"""simple docstring"""
				UpperCamelCase						=  '# 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'
				UpperCamelCase						=  create_dummy_files({'torch': ['CONSTANT', 'function', 'FakeClass']} )
				self.assertEqual(dummy_files['torch']       ,   A_ )


def    A (      lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  int(lowercase				)
		if decimal in (0, 1):  # Exit cases for the recursion
				return str(lowercase				)
		UpperCamelCase			,						UpperCamelCase						=  divmod(lowercase					, 2				)
		return binary_recursive(lowercase				) + str(lowercase				)


def    A (      lowercase				)     ->						str:
		'''simple docstring'''

		UpperCamelCase						=  str(lowercase				).strip()
		if not number:
				raise ValueError('No input value was provided'				)
		UpperCamelCase						=  '-' if number.startswith('-'				) else ''
		UpperCamelCase						=  number.lstrip('-'				)
		if not number.isnumeric():
				raise ValueError('Input value is not an integer'				)
		return f'''{negative}0b{binary_recursive(int(lowercase				)				)}'''


if __name__ == "__main__":
					from doctest import testmod

					testmod()
