

'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments







def  _A		(     )      ->     List[str]:
   _lowercase      :				int      					=       HfArgumentParser(snake_case					)
   _lowercase      :				Dict      					=       parser.parse_args_into_dataclasses()[0]
   _lowercase      :				Tuple      					=       TensorFlowBenchmark(args=snake_case					)
   try:
      _lowercase      :				List[Any]      					=       parser.parse_args_into_dataclasses()[0]
   except ValueError as e:
      _lowercase      :				List[str]      					=       "Arg --no_{0} is no longer used, please use --no-{0} instead."
      _lowercase      :				List[str]      					=       " ".join(str(snake_case					).split(" "					)[:-1]					)
      _lowercase      :				Optional[Any]      					=       ""
      _lowercase      :				int      					=       eval(str(snake_case					).split(" "					)[-1]					)
      _lowercase      :				List[str]      					=       []
      for arg in depreciated_args:
         # arg[2:] removes '--'
         if arg[2:] in TensorFlowBenchmark.deprecated_args:
            # arg[5:] removes '--no_'
            full_error_msg += arg_error_msg.format(arg[5:]					)
         else:
            wrong_args.append(snake_case					)
      if len(snake_case					) > 0:
         _lowercase      :				Union[str, Any]      					=       full_error_msg + begin_error_msg + str(snake_case					)
      raise ValueError(snake_case					)
   benchmark.run()


if __name__ == "__main__":
    main()









'''simple docstring'''
import os
import sys
import unittest


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

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

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


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


class        a__  (							unittest.TestCase  ):


   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Optional[int]      					=       find_backend("    _import_structure[\"models.albert\"].append(\"AlbertTokenizerFast\")"  )
      self.assertIsNone(_UpperCamelCase  )

      _lowercase      :				Dict      					=       find_backend("    if not is_tokenizers_available():"  )
      self.assertEqual(_UpperCamelCase      ,    "tokenizers"  )

      _lowercase      :				str      					=       find_backend("    if not is_tensorflow_text_available():"  )
      self.assertEqual(_UpperCamelCase      ,    "tensorflow_text"  )

      _lowercase      :				Optional[Any]      					=       find_backend("    if not (is_sentencepiece_available() and is_tokenizers_available()):"  )
      self.assertEqual(_UpperCamelCase      ,    "sentencepiece_and_tokenizers"  )

      _lowercase      :				List[str]      					=       find_backend(
          "    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"  )
      self.assertEqual(_UpperCamelCase      ,    "sentencepiece_and_tensorflow_text"  )

      _lowercase      :				Optional[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 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				List[Any]      					=       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 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				int      					=       create_dummy_object("CONSTANT"      ,    "'torch'"  )
      self.assertEqual(_UpperCamelCase      ,    "\nCONSTANT = None\n"  )

      _lowercase      :				Optional[Any]      					=       create_dummy_object("function"      ,    "'torch'"  )
      self.assertEqual(
          _UpperCamelCase      ,    "\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"  )

      _lowercase      :				Union[str, Any]      					=       "\nclass FakeClass(metaclass=DummyObject):\n    _backends = 'torch'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, 'torch')\n"
      _lowercase      :				List[str]      					=       create_dummy_object("FakeClass"      ,    "'torch'"  )
      self.assertEqual(_UpperCamelCase      ,    _UpperCamelCase  )






   def 						_lowerCamelCase       (			self  ):





      """simple docstring"""





      _lowercase      :				Optional[int]      					=       "# 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"
      _lowercase      :				str      					=       create_dummy_files({"torch": ["CONSTANT", "function", "FakeClass"]}  )
      self.assertEqual(dummy_files["torch"]      ,    _UpperCamelCase  )






