




import argparse
import os
import re


# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
__lowerCAmelCase						:							Optional[int]			     =						'src/transformers'

# Matches is_xxx_available()
__lowerCAmelCase						:							List[str]			     =						re.compile(r'is\_([a-z_]*)_available()')
# Matches from xxx import bla
__lowerCAmelCase						:							List[Any]			     =						re.compile(r'\s+from\s+\S*\s+import\s+([^\(\s].*)\n')
__lowerCAmelCase						:							Optional[Any]			     =						re.compile(r'^\s+if\s+not\s+\(?is\_[a-z_]*\_available\(\)')


__lowerCAmelCase						:							int			     =						'\n{0} = None\n'

__lowerCAmelCase						:							Optional[int]			     =						'\nclass {0}(metaclass=DummyObject):\n    _backends = {1}\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, {1})\n'


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




def      __magic_name__							(					A						:   int  ):






			'''simple docstring'''







			if _re_test_backend.search(A__  ) is None:
						return None
			a       =     [b[0] for b in _re_backend.findall(A__  )]
			backends.sort()
			return "_and_".join(A__  )




def      __magic_name__							(					):






			'''simple docstring'''







			with open(os.path.join(A__,    "__init__.py"  ),    "r",    encoding="utf-8",    newline="\n"  ) as f:
						a       =     f.readlines()

			# Get to the point we do the actual imports for type checking
			a       =     0
			while not lines[line_index].startswith("if TYPE_CHECKING"  ):
						line_index += 1

			a       =     {}
			# Go through the end of the file
			while line_index < len(A__  ):
						# If the line is an if is_backend_available, we grab all objects associated.
						a       =     find_backend(lines[line_index]  )
						if backend is not None:
									while not lines[line_index].startswith("    else:"  ):
												line_index += 1
									line_index += 1

									a       =     []
									# Until we unindent, add backend objects to the list
									while len(lines[line_index]  ) <= 1 or lines[line_index].startswith(" " * 8  ):
												a       =     lines[line_index]
												a       =     _re_single_line_import.search(A__  )
												if single_line_import_search is not None:
															objects.extend(single_line_import_search.groups()[0].split(", "  )  )
												elif line.startswith(" " * 12  ):
															objects.append(line[12:-2]  )
												line_index += 1

									a       =     objects
						else:
									line_index += 1

			return backend_specific_objects




def      __magic_name__							(					A						:   str,    A						:   Optional[int]  ):






			'''simple docstring'''







			if name.isupper():
						return DUMMY_CONSTANT.format(A__  )
			elif name.islower():
						return DUMMY_FUNCTION.format(A__,    A__  )
			else:
						return DUMMY_CLASS.format(A__,    A__  )




def      __magic_name__							(					A						:   Dict=None  ):






			'''simple docstring'''







			if backend_specific_objects is None:
						a       =     read_init()
			# For special correspondence backend to module name as used in the function requires_modulename
			a       =     {}

			for backend, objects in backend_specific_objects.items():
						a       =     "[" + ", ".join(F"""\"{b}\"""" for b in backend.split("_and_"  )  ) + "]"
						a       =     "# This file is autogenerated by the command `make fix-copies`, do not edit.\n"
						dummy_file += "from ..utils import DummyObject, requires_backends\n\n"
						dummy_file += "\n".join([create_dummy_object(A__,    A__  ) for o in objects]  )
						a       =     dummy_file

			return dummy_files




def      __magic_name__							(					A						:   Optional[int]=False  ):






			'''simple docstring'''







			a       =     create_dummy_files()
			# For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
			a       =     {"torch": "pt"}

			# Locate actual dummy modules and read their content.
			a       =     os.path.join(A__,    "utils"  )
			a       =     {
			    backend: os.path.join(A__,    F"""dummy_{short_names.get(A__,    A__  )}_objects.py"""  )
			    for backend in dummy_files.keys()
			}

			a       =     {}
			for backend, file_path in dummy_file_paths.items():
						if os.path.isfile(A__  ):
									with open(A__,    "r",    encoding="utf-8",    newline="\n"  ) as f:
												a       =     f.read()
						else:
									a       =     ""

			for backend in dummy_files.keys():
						if dummy_files[backend] != actual_dummies[backend]:
									if overwrite:
												print(
												    F"""Updating transformers.utils.dummy_{short_names.get(A__,    A__  )}_objects.py as the main """
												    "__init__ has new objects."  )
												with open(dummy_file_paths[backend],    "w",    encoding="utf-8",    newline="\n"  ) as f:
															f.write(dummy_files[backend]  )
									else:
												raise ValueError(
												    "The main __init__ has objects that are not present in "
												    F"""transformers.utils.dummy_{short_names.get(A__,    A__  )}_objects.py. Run `make fix-copies` """
												    "to fix this."  )


if __name__ == "__main__":
		__lowerCAmelCase						:							str			     =						argparse.ArgumentParser()
		parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
		__lowerCAmelCase						:							Optional[Any]			     =						parser.parse_args()

		check_dummies(args.fix_and_overwrite)










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


_snake_case				=			{
    "configuration_nystromformer": ["NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "NystromformerConfig"],
}

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _snake_case				=			[
          "NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
          "NystromformerForMaskedLM",
          "NystromformerForMultipleChoice",
          "NystromformerForQuestionAnswering",
          "NystromformerForSequenceClassification",
          "NystromformerForTokenClassification",
          "NystromformerLayer",
          "NystromformerModel",
          "NystromformerPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_nystromformer import NYSTROMFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, NystromformerConfig

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_nystromformer import (
                NYSTROMFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
                NystromformerForMaskedLM,
                NystromformerForMultipleChoice,
                NystromformerForQuestionAnswering,
                NystromformerForSequenceClassification,
                NystromformerForTokenClassification,
                NystromformerLayer,
                NystromformerModel,
                NystromformerPreTrainedModel,
            )


else:
      import sys

      _snake_case				=			_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



