


"""simple docstring"""
import argparse
import os
import re

import packaging.version


SCREAMING_SNAKE_CASE :    Optional[int]									=				"""examples/"""
SCREAMING_SNAKE_CASE :    Optional[Any]									=				{
    """examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
    """init""": (re.compile(r"""^__version__\s+=\s+\"([^\"]+)\"\s*$""", re.MULTILINE), """__version__ = \"VERSION\"\n"""),
    """setup""": (re.compile(r"""^(\s*)version\s*=\s*\"[^\"]+\",""", re.MULTILINE), r"""\1version=\"VERSION\","""),
    """doc""": (re.compile(r"""^(\s*)release\s*=\s*\"[^\"]+\"$""", re.MULTILINE), """release = \"VERSION\"\n"""),
}
SCREAMING_SNAKE_CASE :    Tuple									=				{
    """init""": """src/transformers/__init__.py""",
    """setup""": """setup.py""",
}
SCREAMING_SNAKE_CASE :    Optional[int]									=				"""README.md"""






def 		lowercase							(     _snake_case						:      str     ,   _snake_case						:      int     ,   _snake_case						:      List[str]     )     ->Tuple:
	"""simple docstring"""





	with open(_snake_case     ,   '''r'''     ,   encoding='''utf-8'''     ,   newline='''\n'''     ) as f:
		__snake_case	:						str						=				f.read()
	__snake_case	,							__snake_case	:						Optional[Any]						=				REPLACE_PATTERNS[pattern]
	__snake_case	:						List[str]						=				replace.replace('''VERSION'''     ,   _snake_case     )
	__snake_case	:						Any						=				re_pattern.sub(_snake_case     ,   _snake_case     )
	with open(_snake_case     ,   '''w'''     ,   encoding='''utf-8'''     ,   newline='''\n'''     ) as f:
		f.write(_snake_case     )






def 		lowercase							(     _snake_case						:      Any     )     ->Tuple:
	"""simple docstring"""





	for folder, directories, fnames in os.walk(_snake_case     ):
		# Removing some of the folders with non-actively maintained examples from the walk
		if "research_projects" in directories:
			directories.remove('''research_projects'''     )
		if "legacy" in directories:
			directories.remove('''legacy'''     )
		for fname in fnames:
			if fname.endswith('''.py'''     ):
				update_version_in_file(os.path.join(_snake_case     ,   _snake_case     )     ,   _snake_case     ,   pattern='''examples'''     )






def 		lowercase							(     _snake_case						:      Optional[int]     ,   _snake_case						:      str=False     )     ->str:
	"""simple docstring"""





	for pattern, fname in REPLACE_FILES.items():
		update_version_in_file(_snake_case     ,   _snake_case     ,   _snake_case     )
	if not patch:
		update_version_in_examples(_snake_case     )






def 		lowercase							(     )     ->List[str]:
	"""simple docstring"""





	__snake_case	:						List[Any]						=				'''🤗 Transformers currently provides the following architectures'''
	__snake_case	:						Optional[int]						=				'''1. Want to contribute a new model?'''
	with open(_snake_case     ,   '''r'''     ,   encoding='''utf-8'''     ,   newline='''\n'''     ) as f:
		__snake_case	:						List[Any]						=				f.readlines()

	# Find the start of the list.
	__snake_case	:						List[str]						=				0
	while not lines[start_index].startswith(_start_prompt     ):
		start_index += 1
	start_index += 1

	__snake_case	:						Any						=				start_index
	# Update the lines in the model list.
	while not lines[index].startswith(_end_prompt     ):
		if lines[index].startswith('''1.'''     ):
			__snake_case	:						str						=				lines[index].replace(
			    '''https://huggingface.co/docs/transformers/main/model_doc'''     ,   '''https://huggingface.co/docs/transformers/model_doc'''     ,   )
		index += 1

	with open(_snake_case     ,   '''w'''     ,   encoding='''utf-8'''     ,   newline='''\n'''     ) as f:
		f.writelines(_snake_case     )






def 		lowercase							(     )     ->List[str]:
	"""simple docstring"""





	with open(REPLACE_FILES['''init''']     ,   '''r'''     ) as f:
		__snake_case	:						Dict						=				f.read()
	__snake_case	:						Any						=				REPLACE_PATTERNS['''init'''][0].search(_snake_case     ).groups()[0]
	return packaging.version.parse(_snake_case     )






def 		lowercase							(     _snake_case						:      List[str]=False     )     ->str:
	"""simple docstring"""





	__snake_case	:						List[Any]						=				get_version()
	if patch and default_version.is_devrelease:
		raise ValueError('''Can\'t create a patch version from the dev branch, checkout a released version!'''     )
	if default_version.is_devrelease:
		__snake_case	:						Union[str, Any]						=				default_version.base_version
	elif patch:
		__snake_case	:						Union[str, Any]						=				f"""{default_version.major}.{default_version.minor}.{default_version.micro + 1}"""
	else:
		__snake_case	:						List[Any]						=				f"""{default_version.major}.{default_version.minor + 1}.0"""

	# Now let's ask nicely if that's the right one.
	__snake_case	:						str						=				input(f"""Which version are you releasing? [{default_version}]"""     )
	if len(_snake_case     ) == 0:
		__snake_case	:						str						=				default_version

	print(f"""Updating version to {version}."""     )
	global_version_update(_snake_case     ,   patch=_snake_case     )
	if not patch:
		print('''Cleaning main README, don\'t forget to run `make fix-copies`.'''     )
		clean_main_ref_in_model_list()






def 		lowercase							(     )     ->List[Any]:
	"""simple docstring"""





	__snake_case	:						Tuple						=				get_version()
	__snake_case	:						str						=				f"""{current_version.major}.{current_version.minor + 1}.0.dev0"""
	__snake_case	:						int						=				current_version.base_version

	# Check with the user we got that right.
	__snake_case	:						Tuple						=				input(f"""Which version are we developing now? [{dev_version}]"""     )
	if len(_snake_case     ) == 0:
		__snake_case	:						Any						=				dev_version

	print(f"""Updating version to {version}."""     )
	global_version_update(_snake_case     )
	print('''Cleaning main README, don\'t forget to run `make fix-copies`.'''     )
	clean_main_ref_in_model_list()


if __name__ == "__main__":
			SCREAMING_SNAKE_CASE :    Dict									=				argparse.ArgumentParser()
			parser.add_argument("""--post_release""", action="""store_true""", help="""Whether this is pre or post release.""")
			parser.add_argument("""--patch""", action="""store_true""", help="""Whether or not this is a patch release.""")
			SCREAMING_SNAKE_CASE :    Any									=				parser.parse_args()
			if not args.post_release:
						pre_release_work(patch=args.patch)
			elif args.patch:
						print("""Nothing to do after a patch :-)""")
			else:
						post_release_work()






from typing import TYPE_CHECKING

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


__UpperCamelCase		:       List[Any]									=     {'configuration_glpn': ['GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GLPNConfig']}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase		:       Optional[Any]									=     ['GLPNFeatureExtractor']
					__UpperCamelCase		:       List[str]									=     ['GLPNImageProcessor']

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase		:       str									=     [
					    'GLPN_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'GLPNForDepthEstimation',
					    'GLPNLayer',
					    'GLPNModel',
					    'GLPNPreTrainedModel',
					]


if TYPE_CHECKING:
					from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_glpn import GLPNFeatureExtractor
										from .image_processing_glpn import GLPNImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_glpn import (
										    GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
										    GLPNForDepthEstimation,
										    GLPNLayer,
										    GLPNModel,
										    GLPNPreTrainedModel,
										)


else:
					import sys

					__UpperCamelCase		:       Optional[Any]									=     _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





