






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
a 			=							'src/transformers'

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


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

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


a 			=							'\ndef {0}(*args, **kwargs):\n    requires_backends({0}, {1})\n'
def    a__    (	A       ):
   if _re_test_backend.search(A       ) is None:
      return None
   lowercase__    :						int       =			[b[0] for b in _re_backend.findall(A       )]
   backends.sort()
   return "_and_".join(A       )
def    a__    (	):
   with open(os.path.join(A		,					"""__init__.py"""       )		,					"""r"""		,					encoding="""utf-8"""		,					newline="""\n"""       ) as f:
      lowercase__    :						str       =			f.readlines()

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

   lowercase__    :						int       =			{}
   # 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.
      lowercase__    :						Any       =			find_backend(lines[line_index]       )
      if backend is not None:
         while not lines[line_index].startswith("""    else:"""       ):
            line_index += 1
         line_index += 1

         lowercase__    :						Optional[int]       =			[]
         # Until we unindent, add backend objects to the list
         while len(lines[line_index]       ) <= 1 or lines[line_index].startswith(""" """ * 8       ):
            lowercase__    :						Tuple       =			lines[line_index]
            lowercase__    :						Dict       =			_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

         lowercase__    :						Any       =			objects
      else:
         line_index += 1

   return backend_specific_objects
def    a__    (	A		,					A       ):
   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    a__    (	A=None       ):
   if backend_specific_objects is None:
      lowercase__    :						List[str]       =			read_init()
   # For special correspondence backend to module name as used in the function requires_modulename
   lowercase__    :						List[Any]       =			{}

   for backend, objects in backend_specific_objects.items():
      lowercase__    :						List[str]       =			"""[""" + """, """.join(F'''"{b}"''' for b in backend.split("""_and_"""       )       ) + """]"""
      lowercase__    :						Dict       =			"""# 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]       )
      lowercase__    :						List[Any]       =			dummy_file

   return dummy_files
def    a__    (	A=False       ):
   lowercase__    :						List[Any]       =			create_dummy_files()
   # For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
   lowercase__    :						Optional[int]       =			{"""torch""": """pt"""}

   # Locate actual dummy modules and read their content.
   lowercase__    :						Union[str, Any]       =			os.path.join(A		,					"""utils"""       )
   lowercase__    :						List[str]       =			{
       backend: os.path.join(A		,					F'''dummy_{short_names.get(A		,					A       )}_objects.py'''       )
       for backend in dummy_files.keys()
   }

   lowercase__    :						List[Any]       =			{}
   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:
            lowercase__    :						List[Any]       =			f.read()
      else:
         lowercase__    :						str       =			""""""

   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__":
 a 			=							argparse.ArgumentParser()
 parser.add_argument('--fix_and_overwrite', action='store_true', help='Whether to fix inconsistencies.')
 a 			=							parser.parse_args()

 check_dummies(args.fix_and_overwrite)










import enum
import inspect
from typing import Iterable, List, Optional, Tuple, Union
class 							__snake_case(       enum.Enum   ):
 lowercase			:							List[str]		   =		'''timm'''
 lowercase			:							Any		   =		'''transformers'''
def    a__    (	A		,					A		,					A       ):
   if stage_names is None:
      raise ValueError("""Stage_names must be set for transformers backbones"""       )

   if out_features is not None:
      if not isinstance(A		,					(list,)       ):
         raise ValueError(F'''out_features must be a list {type(A       )}'''       )
      if any(feat not in stage_names for feat in out_features       ):
         raise ValueError(F'''out_features must be a subset of stage_names: {stage_names} got {out_features}'''       )

   if out_indices is not None:
      if not isinstance(A		,					(list, tuple)       ):
         raise ValueError(F'''out_indices must be a list or tuple, got {type(A       )}'''       )
      if any(idx >= len(A       ) for idx in out_indices       ):
         raise ValueError("""out_indices must be valid indices for stage_names {stage_names}, got {out_indices}"""       )

   if out_features is not None and out_indices is not None:
      if len(A       ) != len(A       ):
         raise ValueError("""out_features and out_indices should have the same length if both are set"""       )
      if out_features != [stage_names[idx] for idx in out_indices]:
         raise ValueError("""out_features and out_indices should correspond to the same stages if both are set"""       )
def    a__    (	A		,					A		,					A		,					):
   if out_indices is None and out_features is None:
      lowercase__    :						int       =			[len(A       ) - 1]
      lowercase__    :						Dict       =			[stage_names[-1]]
   elif out_indices is None and out_features is not None:
      lowercase__    :						Any       =			[stage_names.index(A       ) for layer in out_features]
   elif out_features is None and out_indices is not None:
      lowercase__    :						List[str]       =			[stage_names[idx] for idx in out_indices]
   return out_features, out_indices
def    a__    (	A		,					A		,					A		,					):
   verify_out_features_out_indices(out_features=A		,					out_indices=A		,					stage_names=A       )
   lowercase__  ,       lowercase__    :						Dict       =			_align_output_features_output_indices(
       out_features=A		,					out_indices=A		,					stage_names=A       )
   # Verify that the aligned out_features and out_indices are valid
   verify_out_features_out_indices(out_features=A		,					out_indices=A		,					stage_names=A       )
   return output_features, output_indices
class 							__snake_case:
 lowercase			:							Optional[BackboneType]		   =		None



 def     UpperCAmelCase     (						self : Dict			,		UpperCAmelCase__ : int						):

    """simple docstring"""






    if getattr(self			,		"""_backbone"""			,		UpperCAmelCase__						) is None:
       raise ValueError("""self._backbone must be set before calling _init_timm_backbone"""						)

    # These will diagree with the defaults for the transformers models e.g. for resnet50
    # the transformer model has out_features = ['stem', 'stage1', 'stage2', 'stage3', 'stage4']
    # the timm model has out_features = ['act', 'layer1', 'layer2', 'layer3', 'layer4']
    lowercase__    :						List[str]       =			[stage["""module"""] for stage in self._backbone.feature_info.info]
    lowercase__    :						int       =			[stage["""num_chs"""] for stage in self._backbone.feature_info.info]
    lowercase__    :						Optional[int]       =			self._backbone.feature_info.out_indices
    lowercase__    :						Optional[Any]       =			self._backbone.feature_info.module_name()

    # We verify the out indices and out features are valid
    verify_out_features_out_indices(
        out_features=UpperCAmelCase__			,		out_indices=UpperCAmelCase__			,		stage_names=self.stage_names						)
    lowercase__  ,       lowercase__    :						int       =			out_features, out_indices



 def     UpperCAmelCase     (						self : Optional[Any]			,		UpperCAmelCase__ : str						):

    """simple docstring"""






    lowercase__    :						List[str]       =			getattr(UpperCAmelCase__			,		"""stage_names"""						)
    lowercase__    :						Union[str, Any]       =			getattr(UpperCAmelCase__			,		"""out_features"""			,		UpperCAmelCase__						)
    lowercase__    :						List[str]       =			getattr(UpperCAmelCase__			,		"""out_indices"""			,		UpperCAmelCase__						)

    lowercase__    :						Tuple       =			stage_names
    lowercase__  ,       lowercase__    :						List[str]       =			get_aligned_output_features_output_indices(
        out_features=UpperCAmelCase__			,		out_indices=UpperCAmelCase__			,		stage_names=UpperCAmelCase__						)
    # Number of channels for each stage. This is set in the transformer backbone model init
    lowercase__    :						Optional[int]       =			None



 def     UpperCAmelCase     (						self : Tuple			,		UpperCAmelCase__ : Optional[Any]						):

    """simple docstring"""






    lowercase__    :						List[Any]       =			config

    lowercase__    :						Optional[Any]       =			getattr(UpperCAmelCase__			,		"""use_timm_backbone"""			,		UpperCAmelCase__						)
    lowercase__    :						Optional[int]       =			BackboneType.TIMM if self.use_timm_backbone else BackboneType.TRANSFORMERS

    if self.backbone_type == BackboneType.TIMM:
       self._init_timm_backbone(UpperCAmelCase__						)
    elif self.backbone_type == BackboneType.TRANSFORMERS:
       self._init_transformers_backbone(UpperCAmelCase__						)
    else:
       raise ValueError(f'''backbone_type {self.backbone_type} not supported.'''						)



 @property
 def     UpperCAmelCase     (						self : int						):

    """simple docstring"""






    return self._out_features



 @out_features.setter
 def     UpperCAmelCase     (						self : Dict			,		UpperCAmelCase__ : List[str]						):

    """simple docstring"""






    lowercase__  ,       lowercase__    :						Optional[Any]       =			get_aligned_output_features_output_indices(
        out_features=UpperCAmelCase__			,		out_indices=UpperCAmelCase__			,		stage_names=self.stage_names						)



 @property
 def     UpperCAmelCase     (						self : List[str]						):

    """simple docstring"""






    return self._out_indices



 @out_indices.setter
 def     UpperCAmelCase     (						self : Optional[Any]			,		UpperCAmelCase__ : Union[Tuple[int], List[int]]						):

    """simple docstring"""






    lowercase__  ,       lowercase__    :						Any       =			get_aligned_output_features_output_indices(
        out_features=UpperCAmelCase__			,		out_indices=UpperCAmelCase__			,		stage_names=self.stage_names						)



 @property
 def     UpperCAmelCase     (						self : int						):

    """simple docstring"""






    return {stage: self.num_features[i] for i, stage in enumerate(self.stage_names						)}



 @property
 def     UpperCAmelCase     (						self : Optional[Any]						):

    """simple docstring"""






    return [self.out_feature_channels[name] for name in self.out_features]



 def     UpperCAmelCase     (						self : Optional[Any]			,		*UpperCAmelCase__ : Tuple			,		**UpperCAmelCase__ : Dict						):

    """simple docstring"""






    lowercase__    :						Optional[Any]       =			dict(inspect.signature(self.forward						).parameters						)
    lowercase__    :						Tuple       =			{k: v for k, v in kwargs.items() if k in signature}
    return self(*UpperCAmelCase__			,		**UpperCAmelCase__						)



 def     UpperCAmelCase     (						self : int			,		UpperCAmelCase__ : List[str]			,		UpperCAmelCase__ : Optional[bool] = None			,		UpperCAmelCase__ : Optional[bool] = None			,		UpperCAmelCase__ : Optional[bool] = None			,		):

    """simple docstring"""






    raise NotImplementedError("""This method should be implemented by the derived class."""						)







 def     UpperCAmelCase     (						self : Any						):

    """simple docstring"""






    lowercase__    :						Union[str, Any]       =			super().to_dict()
    lowercase__    :						Tuple       =			output.pop("""_out_features"""						)
    lowercase__    :						Union[str, Any]       =			output.pop("""_out_indices"""						)
    return output
class 							__snake_case:



 @property
 def     UpperCAmelCase     (						self : str						):

    """simple docstring"""






    return self._out_features



 @out_features.setter
 def     UpperCAmelCase     (						self : Union[str, Any]			,		UpperCAmelCase__ : List[str]						):

    """simple docstring"""






    lowercase__  ,       lowercase__    :						Dict       =			get_aligned_output_features_output_indices(
        out_features=UpperCAmelCase__			,		out_indices=UpperCAmelCase__			,		stage_names=self.stage_names						)



 @property
 def     UpperCAmelCase     (						self : Tuple						):

    """simple docstring"""






    return self._out_indices



 @out_indices.setter
 def     UpperCAmelCase     (						self : int			,		UpperCAmelCase__ : Union[Tuple[int], List[int]]						):

    """simple docstring"""






    lowercase__  ,       lowercase__    :						Any       =			get_aligned_output_features_output_indices(
        out_features=UpperCAmelCase__			,		out_indices=UpperCAmelCase__			,		stage_names=self.stage_names						)







 def     UpperCAmelCase     (						self : List[Any]						):

    """simple docstring"""






    lowercase__    :						Dict       =			super().to_dict()
    lowercase__    :						Union[str, Any]       =			output.pop("""_out_features"""						)
    lowercase__    :						Dict       =			output.pop("""_out_indices"""						)
    return output


