


import argparse
import os
import re


A				:       Tuple      =  'src/transformers/models/auto'


# re pattern that matches mapping introductions:
#    SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
A				:       List[Any]      =  re.compile(r'[A-Z_]+_MAPPING(\s+|_[A-Z_]+\s+)=\s+OrderedDict')
# re pattern that matches identifiers in mappings
A				:       Dict      =  re.compile(r'\s*\(\s*"(\S[^"]+)"')





def 						_lowerCAmelCase							(     _lowerCAmelCase   ,						_lowerCAmelCase = False			)    ->						Optional[Any]:


						'''simple docstring'''






						with open(_lowerCAmelCase   ,						"r"   ,						encoding="utf-8"			) as f:
												__snake_case				=		f.read()

						__snake_case				=		content.split("\n"			)
						__snake_case				=		[]
						__snake_case				=		0
						while line_idx < len(_lowerCAmelCase			):
												if _re_intro_mapping.search(lines[line_idx]			) is not None:
																		__snake_case				=		len(re.search(r"^(\s*)\S"   ,						lines[line_idx]			).groups()[0]			) + 8
																		# Start of a new mapping!
																		while not lines[line_idx].startswith(" " * indent + "("			):
																								new_lines.append(lines[line_idx]			)
																								line_idx += 1

																		__snake_case				=		[]
																		while lines[line_idx].strip() != "]":
																								# Blocks either fit in one line or not
																								if lines[line_idx].strip() == "(":
																														__snake_case				=		line_idx
																														while not lines[line_idx].startswith(" " * indent + ")"			):
																																				line_idx += 1
																														blocks.append("\n".join(lines[start_idx : line_idx + 1]			)			)
																								else:
																														blocks.append(lines[line_idx]			)
																								line_idx += 1

																		# Sort blocks by their identifiers
																		__snake_case				=		sorted(_lowerCAmelCase   ,						key=lambda _lowerCAmelCase			: _re_identifier.search(_lowerCAmelCase			).groups()[0]			)
																		new_lines += blocks
												else:
																		new_lines.append(lines[line_idx]			)
																		line_idx += 1

						if overwrite:
												with open(_lowerCAmelCase   ,						"w"   ,						encoding="utf-8"			) as f:
																		f.write("\n".join(_lowerCAmelCase			)			)
						elif "\n".join(_lowerCAmelCase			) != content:
												return True





def 						_lowerCAmelCase							(     _lowerCAmelCase = False			)    ->						Any:


						'''simple docstring'''






						__snake_case				=		[os.path.join(_lowerCAmelCase   ,						_lowerCAmelCase			) for f in os.listdir(_lowerCAmelCase			) if f.endswith(".py"			)]
						__snake_case				=		[sort_auto_mapping(_lowerCAmelCase   ,						overwrite=_lowerCAmelCase			) for fname in fnames]

						if not overwrite and any(_lowerCAmelCase			):
												__snake_case				=		[f for f, d in zip(_lowerCAmelCase   ,						_lowerCAmelCase			) if d]
												raise ValueError(
												    F'''The following files have auto mappings that need sorting: {', '.join(_lowerCAmelCase			)}. Run `make style` to fix'''
												    " this."			)


if __name__ == "__main__":
	A				:       Any      =  argparse.ArgumentParser()
	parser.add_argument('--check_only', action='store_true', help='Whether to only check or fix style.')
	A				:       Union[str, Any]      =  parser.parse_args()

	sort_all_auto_mappings(not args.check_only)









from typing import TYPE_CHECKING

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


A				:       Optional[Any]      =  {'configuration_van': ['VAN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VanConfig']}


try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	A				:       Optional[Any]      =  [
	    'VAN_PRETRAINED_MODEL_ARCHIVE_LIST',
	    'VanForImageClassification',
	    'VanModel',
	    'VanPreTrainedModel',
	]

if TYPE_CHECKING:
	from .configuration_van import VAN_PRETRAINED_CONFIG_ARCHIVE_MAP, VanConfig

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_van import (
		    VAN_PRETRAINED_MODEL_ARCHIVE_LIST,
		    VanForImageClassification,
		    VanModel,
		    VanPreTrainedModel,
		)

else:
	import sys

	A				:       Union[str, Any]      =  _LazyModule(__name__, globals()['__file__'], _import_structure)





