



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__						:						List[Any]          =      '''src/transformers'''

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


A__						:						str          =      '''
{0} = None
'''

A__						:						Optional[Any]          =      '''
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
'''


A__						:						Optional[Any]          =      '''
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
'''


def     UpperCamelCase(						__UpperCamelCase							:	Union[str, Any]				):
		if _re_test_backend.search(__UpperCamelCase				) is None:
				return None
		lowerCAmelCase_    :  Dict             =				[b[0] for b in _re_backend.findall(__UpperCamelCase				)]
		backends.sort()
		return "_and_".join(__UpperCamelCase				)


def     UpperCamelCase(						):
		with open(os.path.join(__UpperCamelCase  ,'''__init__.py'''				)  ,'''r'''  ,encoding='''utf-8'''  ,newline='''\n'''				) as f:
				lowerCAmelCase_    :  Dict             =				f.readlines()

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

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

						lowerCAmelCase_    :  Tuple             =				[]
						# Until we unindent, add backend objects to the list
						while len(lines[line_index]				) <= 1 or lines[line_index].startswith(''' ''' * 8				):
								lowerCAmelCase_    :  Union[str, Any]             =				lines[line_index]
								lowerCAmelCase_    :  Any             =				_re_single_line_import.search(__UpperCamelCase				)
								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

						lowerCAmelCase_    :  int             =				objects
				else:
						line_index += 1

		return backend_specific_objects


def     UpperCamelCase(						__UpperCamelCase							:	Any  ,__UpperCamelCase							:	List[Any]				):
		if name.isupper():
				return DUMMY_CONSTANT.format(__UpperCamelCase				)
		elif name.islower():
				return DUMMY_FUNCTION.format(__UpperCamelCase  ,__UpperCamelCase				)
		else:
				return DUMMY_CLASS.format(__UpperCamelCase  ,__UpperCamelCase				)


def     UpperCamelCase(						__UpperCamelCase							:	Optional[int]=None				):
		if backend_specific_objects is None:
				lowerCAmelCase_    :  Dict             =				read_init()
		# For special correspondence backend to module name as used in the function requires_modulename
		lowerCAmelCase_    :  List[str]             =				{}

		for backend, objects in backend_specific_objects.items():
				lowerCAmelCase_    :  int             =				'''[''' + ''', '''.join(f"""\"{b}\"""" for b in backend.split('''_and_'''				)				) + ''']'''
				lowerCAmelCase_    :  List[str]             =				'''# 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(__UpperCamelCase  ,__UpperCamelCase				) for o in objects]				)
				lowerCAmelCase_    :  int             =				dummy_file

		return dummy_files


def     UpperCamelCase(						__UpperCamelCase							:	Optional[int]=False				):
		lowerCAmelCase_    :  Union[str, Any]             =				create_dummy_files()
		# For special correspondence backend to shortcut as used in utils/dummy_xxx_objects.py
		lowerCAmelCase_    :  Optional[Any]             =				{'''torch''': '''pt'''}

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

		lowerCAmelCase_    :  List[Any]             =				{}
		for backend, file_path in dummy_file_paths.items():
				if os.path.isfile(__UpperCamelCase				):
						with open(__UpperCamelCase  ,'''r'''  ,encoding='''utf-8'''  ,newline='''\n'''				) as f:
								lowerCAmelCase_    :  Any             =				f.read()
				else:
						lowerCAmelCase_    :  Optional[int]             =				''''''

		for backend in dummy_files.keys():
				if dummy_files[backend] != actual_dummies[backend]:
						if overwrite:
								print(
								    f"""Updating transformers.utils.dummy_{short_names.get(__UpperCamelCase  ,__UpperCamelCase				)}_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(__UpperCamelCase  ,__UpperCamelCase				)}_objects.py. Run `make fix-copies` """
								    '''to fix this.'''				)


if __name__ == "__main__":
						A__						:						int          =      argparse.ArgumentParser()
						parser.add_argument('''--fix_and_overwrite''', action='''store_true''', help='''Whether to fix inconsistencies.''')
						A__						:						str          =      parser.parse_args()

						check_dummies(args.fix_and_overwrite)










from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


A__						:						List[str]          =      {
    '''configuration_segformer''': ['''SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SegformerConfig''', '''SegformerOnnxConfig''']
}

try:
						if not is_vision_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A__						:						int          =      ['''SegformerFeatureExtractor''']
						A__						:						Dict          =      ['''SegformerImageProcessor''']

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A__						:						Any          =      [
						    '''SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''SegformerDecodeHead''',
						    '''SegformerForImageClassification''',
						    '''SegformerForSemanticSegmentation''',
						    '''SegformerLayer''',
						    '''SegformerModel''',
						    '''SegformerPreTrainedModel''',
						]

try:
						if not is_tf_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A__						:						List[Any]          =      [
						    '''TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST''',
						    '''TFSegformerDecodeHead''',
						    '''TFSegformerForImageClassification''',
						    '''TFSegformerForSemanticSegmentation''',
						    '''TFSegformerModel''',
						    '''TFSegformerPreTrainedModel''',
						]


if TYPE_CHECKING:
						from .configuration_segformer import SEGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, SegformerConfig, SegformerOnnxConfig

						try:
												if not is_vision_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .feature_extraction_segformer import SegformerFeatureExtractor
												from .image_processing_segformer import SegformerImageProcessor

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_segformer import (
												    SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    SegformerDecodeHead,
												    SegformerForImageClassification,
												    SegformerForSemanticSegmentation,
												    SegformerLayer,
												    SegformerModel,
												    SegformerPreTrainedModel,
												)
						try:
												if not is_tf_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_tf_segformer import (
												    TF_SEGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    TFSegformerDecodeHead,
												    TFSegformerForImageClassification,
												    TFSegformerForSemanticSegmentation,
												    TFSegformerModel,
												    TFSegformerPreTrainedModel,
												)

else:
						import sys

						A__						:						Dict          =      _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





