


import argparse
import os
import re

import packaging.version


_UpperCAmelCase			:  Tuple     ="""examples/"""
_UpperCAmelCase			:  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"""),
}
_UpperCAmelCase			:  Tuple     ={
    """init""": """src/transformers/__init__.py""",
    """setup""": """setup.py""",
}
_UpperCAmelCase			:  Union[str, Any]     ="""README.md"""



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )-> List[Any]:
				with open(lowerCAmelCase_ ,   '''r''' ,   encoding='''utf-8''' ,   newline='''\n''' ) as f:
								lowerCAmelCase_ :      Any    				=				f.read()
				lowerCAmelCase_				,  lowerCAmelCase_ :      Optional[int]    				=				REPLACE_PATTERNS[pattern]
				lowerCAmelCase_ :      Dict    				=				replace.replace('''VERSION''' ,   lowerCAmelCase_ )
				lowerCAmelCase_ :      Tuple    				=				re_pattern.sub(lowerCAmelCase_ ,   lowerCAmelCase_ )
				with open(lowerCAmelCase_ ,   '''w''' ,   encoding='''utf-8''' ,   newline='''\n''' ) as f:
								f.write(lowerCAmelCase_ )



def 			lowerCAmelCase (		lowerCAmelCase_ )-> Tuple:
				for folder, directories, fnames in os.walk(lowerCAmelCase_ ):
								# 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(lowerCAmelCase_ ,   lowerCAmelCase_ ) ,   lowerCAmelCase_ ,   pattern='''examples''' )



def 			lowerCAmelCase (		lowerCAmelCase_ ,   lowerCAmelCase_=False )-> Optional[Any]:
				for pattern, fname in REPLACE_FILES.items():
								update_version_in_file(lowerCAmelCase_ ,   lowerCAmelCase_ ,   lowerCAmelCase_ )
				if not patch:
								update_version_in_examples(lowerCAmelCase_ )



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

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

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

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



def 			lowerCAmelCase (		)-> Dict:
				with open(REPLACE_FILES['''init'''] ,   '''r''' ) as f:
								lowerCAmelCase_ :      Union[str, Any]    				=				f.read()
				lowerCAmelCase_ :      Union[str, Any]    				=				REPLACE_PATTERNS['''init'''][0].search(lowerCAmelCase_ ).groups()[0]
				return packaging.version.parse(lowerCAmelCase_ )



def 			lowerCAmelCase (		lowerCAmelCase_=False )-> List[Any]:
				lowerCAmelCase_ :      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:
								lowerCAmelCase_ :      str    				=				default_version.base_version
				elif patch:
								lowerCAmelCase_ :      Dict    				=				f"""{default_version.major}.{default_version.minor}.{default_version.micro + 1}"""
				else:
								lowerCAmelCase_ :      Optional[Any]    				=				f"""{default_version.major}.{default_version.minor + 1}.0"""

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

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



def 			lowerCAmelCase (		)-> Any:
				lowerCAmelCase_ :      str    				=				get_version()
				lowerCAmelCase_ :      int    				=				f"""{current_version.major}.{current_version.minor + 1}.0.dev0"""
				lowerCAmelCase_ :      Any    				=				current_version.base_version

				# Check with the user we got that right.
				lowerCAmelCase_ :      Optional[int]    				=				input(f"""Which version are we developing now? [{dev_version}]""" )
				if len(lowerCAmelCase_ ) == 0:
								lowerCAmelCase_ :      str    				=				dev_version

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


if __name__ == "__main__":
						_UpperCAmelCase			:  Union[str, Any]     =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.""")
						_UpperCAmelCase			:  List[str]     =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_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


_UpperCAmelCase			:  Union[str, Any]     ={
    """configuration_llama""": ["""LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LlamaConfig"""],
}

try:
						if not is_sentencepiece_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_UpperCAmelCase			:  Optional[Any]     =["""LlamaTokenizer"""]

try:
						if not is_tokenizers_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_UpperCAmelCase			:  Optional[int]     =["""LlamaTokenizerFast"""]

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_UpperCAmelCase			:  Tuple     =[
						    """LlamaForCausalLM""",
						    """LlamaModel""",
						    """LlamaPreTrainedModel""",
						    """LlamaForSequenceClassification""",
						]


if TYPE_CHECKING:
						from .configuration_llama import LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP, LlamaConfig

						try:
												if not is_sentencepiece_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_llama import LlamaTokenizer

						try:
												if not is_tokenizers_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .tokenization_llama_fast import LlamaTokenizerFast

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_llama import LlamaForCausalLM, LlamaForSequenceClassification, LlamaModel, LlamaPreTrainedModel


else:
						import sys

						_UpperCAmelCase			:  List[Any]     =_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)