

'''simple docstring'''
# Lint as: python3
import itertools
import os
import re


_snake_case         =  re.compile(r'([A-Z]+)([A-Z][a-z])')
_snake_case         =  re.compile(r'([a-z\d])([A-Z])')

_snake_case         =  re.compile(r'(?<!_)_(?!_)')
_snake_case         =  re.compile(r'(_{2,})')

_snake_case         =  r'^\w+(\.\w+)*$'

_snake_case         =  r'<>:/\|?*'







def  _A		(     snake_case					)      ->     List[str]:
   _lowercase      :				Optional[Any]      					=       _uppercase_uppercase_re.sub(r"\1_\2"		,							snake_case					)
   _lowercase      :				Any      					=       _lowercase_uppercase_re.sub(r"\1_\2"		,							snake_case					)
   return name.lower()







def  _A		(     snake_case					)      ->     Tuple:
   _lowercase      :				Any      					=       _single_underscore_re.split(snake_case					)
   _lowercase      :				Union[str, Any]      					=       [_multiple_underscores_re.split(snake_case					) for n in name]
   return "".join(n.capitalize() for n in itertools.chain.from_iterable(snake_case					) if n != ""					)







def  _A		(     snake_case					)      ->     Dict:
   if os.path.basename(snake_case					) != name:
      raise ValueError(F'''Should be a dataset name, not a path: {name}'''					)
   return camelcase_to_snakecase(snake_case					)







def  _A		(     snake_case		,							snake_case					)      ->     Optional[Any]:
   if os.path.basename(snake_case					) != name:
      raise ValueError(F'''Should be a dataset name, not a path: {name}'''					)
   if not re.match(_split_re		,							snake_case					):
      raise ValueError(F'''Split name should match \'{_split_re}\'\' but got \'{split}\'.'''					)
   return F'''{filename_prefix_for_name(snake_case					)}-{split}'''







def  _A		(     snake_case		,							snake_case		,							snake_case		,							snake_case=None					)      ->     Dict:
   _lowercase      :				List[str]      					=       filename_prefix_for_split(snake_case		,							snake_case					)
   if filetype_suffix:
      prefix += F'''.{filetype_suffix}'''
   _lowercase      :				Dict      					=       os.path.join(snake_case		,							snake_case					)
   return F'''{filepath}*'''







def  _A		(     snake_case		,							snake_case		,							snake_case		,							snake_case=None		,							snake_case=None					)      ->     Optional[int]:
   _lowercase      :				Tuple      					=       filename_prefix_for_split(snake_case		,							snake_case					)
   _lowercase      :				List[str]      					=       os.path.join(snake_case		,							snake_case					)

   if shard_lengths:
      _lowercase      :				List[Any]      					=       len(snake_case					)
      _lowercase      :				List[str]      					=       [F'''{prefix}-{shard_id:05d}-of-{num_shards:05d}''' for shard_id in range(snake_case					)]
      if filetype_suffix:
         _lowercase      :				Any      					=       [filename + F'''.{filetype_suffix}''' for filename in filenames]
      return filenames
   else:
      _lowercase      :				Dict      					=       prefix
      if filetype_suffix:
         filename += F'''.{filetype_suffix}'''
      return [filename]









'''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  )






