






"""simple docstring"""

import os
import sys
import unittest


lowercase    			=       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
lowercase    			=       os.path.join(git_repo_path, '''src''', '''transformers''')

lowercase    			=       '''
{0} = None
'''

lowercase    			=       '''
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
'''


lowercase    			=       '''
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
'''

class 						A_							(      unittest.TestCase  ):







				def     _snake_case					(							self							:						List[str]	)				->					Optional[int]:
										__magic_name__            =     find_backend("    _import_structure[\"models.albert\"].append(\"AlbertTokenizerFast\")"	)
										self.assertIsNone(__lowerCamelCase	)

										__magic_name__            =     find_backend("    if not is_tokenizers_available():"	)
										self.assertEqual(__lowerCamelCase						,    "tokenizers"	)

										__magic_name__            =     find_backend("    if not is_tensorflow_text_available():"	)
										self.assertEqual(__lowerCamelCase						,    "tensorflow_text"	)

										__magic_name__            =     find_backend("    if not (is_sentencepiece_available() and is_tokenizers_available()):"	)
										self.assertEqual(__lowerCamelCase						,    "sentencepiece_and_tokenizers"	)

										__magic_name__            =     find_backend(
										    "    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"	)
										self.assertEqual(__lowerCamelCase						,    "sentencepiece_and_tensorflow_text"	)

										__magic_name__            =     find_backend(
										    "    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):"	)
										self.assertEqual(__lowerCamelCase						,    "sentencepiece_and_tokenizers_and_vision"	)







				def     _snake_case					(							self							:						Optional[int]	)				->					List[Any]:
										__magic_name__            =     read_init()
										# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
										self.assertIn("torch"						,    __lowerCamelCase	)
										self.assertIn("tensorflow_text"						,    __lowerCamelCase	)
										self.assertIn("sentencepiece_and_tokenizers"						,    __lowerCamelCase	)

										# 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     _snake_case					(							self							:						Optional[int]	)				->					Optional[Any]:
										__magic_name__            =     create_dummy_object("CONSTANT"						,    "'torch'"	)
										self.assertEqual(__lowerCamelCase						,    "\nCONSTANT = None\n"	)

										__magic_name__            =     create_dummy_object("function"						,    "'torch'"	)
										self.assertEqual(
										    __lowerCamelCase						,    "\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"	)

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







				def     _snake_case					(							self							:						Tuple	)				->					List[Any]:
										__magic_name__            =     "# 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"
										__magic_name__            =     create_dummy_files({"torch": ["CONSTANT", "function", "FakeClass"]}	)
										self.assertEqual(dummy_files["torch"]						,    __lowerCamelCase	)











"""simple docstring"""

def _lowerCAmelCase	(  __lowerCamelCase:str   ):

						'''simple docstring'''






						return "".join(chr(ord(__lowerCamelCase   ) - 3_2   ) if "a" <= char <= "z" else char for char in word   )


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

			testmod()



