



import os
import sys
import unittest


lowerCAmelCase__       = 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
lowerCAmelCase__       = os.path.join(git_repo_path, "src", "transformers")

lowerCAmelCase__       = "\n{0} = None\n"

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


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






class 						__magic_name__    (       unittest.TestCase    ):


 def _UpperCamelCase	(						self		: Union[str, Any]    )    ->      Dict:
   UpperCAmelCase					      =  find_backend("    _import_structure[\"models.albert\"].append(\"AlbertTokenizerFast\")"    )
   self.assertIsNone(_snake_case    )

   UpperCAmelCase					      =  find_backend("    if not is_tokenizers_available():"    )
   self.assertEqual(_snake_case			,						"tokenizers"    )

   UpperCAmelCase					      =  find_backend("    if not is_tensorflow_text_available():"    )
   self.assertEqual(_snake_case			,						"tensorflow_text"    )

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

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

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


 def _UpperCamelCase	(						self		: str    )    ->      str:
   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"			,						_snake_case    )
   self.assertIn("tensorflow_text"			,						_snake_case    )
   self.assertIn("sentencepiece_and_tokenizers"			,						_snake_case    )

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

   UpperCAmelCase					      =  create_dummy_object("function"			,						"\'torch\'"    )
   self.assertEqual(
       _snake_case			,						"\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(_snake_case			,						_snake_case    )


 def _UpperCamelCase	(						self		: List[Any]    )    ->      Any:
   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"]			,						_snake_case    )






def      _lowerCAmelCase(	__A   ,       __A   ,       __A			):
  if n == 0:
    return 1

  elif n % 2 == 1:
    return (binary_exponentiation(__A   ,       n - 1   ,       __A			) * a) % mod

  else:
    UpperCAmelCase					      =  binary_exponentiation(__A   ,       n / 2   ,       __A			)
    return (b * b) % mod


# a prime number
lowerCAmelCase__       = 701

lowerCAmelCase__       = 1000000000
lowerCAmelCase__       = 10

# using binary exponentiation function, O(log(p)):
print((a / b) % p == (a * binary_exponentiation(b, p - 2, p)) % p)





print((a / b) % p == (a * b ** (p - 2)) % p)



