



"""simple docstring"""






import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida

from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
from huggingface_hub.utils import (
    EntryNotFoundError,
    RepositoryNotFoundError,
    RevisionNotFoundError,
    is_jinja_available,
)
from packaging import version
from requests import HTTPError

from .. import __version__
from .constants import (
    DEPRECATED_REVISION_ARGS,
    DIFFUSERS_CACHE,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    SAFETENSORS_WEIGHTS_NAME,
    WEIGHTS_NAME,
)
from .import_utils import (
    ENV_VARS_TRUE_VALUES,
    _flax_version,
    _jax_version,
    _onnxruntime_version,
    _torch_version,
    is_flax_available,
    is_onnx_available,
    is_torch_available,
)
from .logging import get_logger


__snake_case							:   List[Any]      =    get_logger(__name__)


__snake_case							:   Union[str, Any]      =    Path(__file__).parent / 'model_card_template.md'
__snake_case							:   Union[str, Any]      =    uuida().hex
__snake_case							:   List[Any]      =    os.getenv('HF_HUB_OFFLINE', '').upper() in ENV_VARS_TRUE_VALUES
__snake_case							:   str      =    os.getenv('DISABLE_TELEMETRY', '').upper() in ENV_VARS_TRUE_VALUES
__snake_case							:   Dict      =    HUGGINGFACE_CO_RESOLVE_ENDPOINT + '/api/telemetry/'


def 			_lowercase				(  __snake_case = None	)						->   str:
			__lowerCAmelCase      :  Union[str, Any]												=       F"""diffusers/{__version__}; python/{sys.version.split()[0]}; session_id/{SESSION_ID}"""
			if DISABLE_TELEMETRY or HF_HUB_OFFLINE:
						return ua + "; telemetry/off"
			if is_torch_available():
						ua += F"""; torch/{_torch_version}"""
			if is_flax_available():
						ua += F"""; jax/{_jax_version}"""
						ua += F"""; flax/{_flax_version}"""
			if is_onnx_available():
						ua += F"""; onnxruntime/{_onnxruntime_version}"""
			# CI will set this value to True
			if os.environ.get("DIFFUSERS_IS_CI"					,""	).upper() in ENV_VARS_TRUE_VALUES:
						ua += "; is_ci/true"
			if isinstance(__snake_case					,__snake_case	):
						ua += "; " + "; ".join(F"""{k}/{v}""" for k, v in user_agent.items()	)
			elif isinstance(__snake_case					,__snake_case	):
						ua += "; " + user_agent
			return ua


def 			_lowercase				(  __snake_case					,__snake_case = None					,__snake_case = None	)						->   str:
			if token is None:
						__lowerCAmelCase      :  List[str]												=       HfFolder.get_token()
			if organization is None:
						__lowerCAmelCase      :  Any												=       whoami(__snake_case	)["name"]
						return F"""{username}/{model_id}"""
			else:
						return F"""{organization}/{model_id}"""


def 			_lowercase				(  __snake_case					,__snake_case	)						->   Dict:
			if not is_jinja_available():
						raise ValueError(
						    "Modelcard rendering is based on Jinja templates."
						    " Please make sure to have `jinja` installed before using `create_model_card`."
						    " To install it, please run `pip install Jinja2`."	)

			if hasattr(__snake_case					,"local_rank"	) and args.local_rank not in [-1, 0]:
						return

			__lowerCAmelCase      :  List[Any]												=       args.hub_token if hasattr(__snake_case					,"hub_token"	) else None
			__lowerCAmelCase      :  List[str]												=       get_full_repo_name(__snake_case					,token=__snake_case	)

			__lowerCAmelCase      :  Tuple												=       ModelCard.from_template(
			    card_data=ModelCardData(  # Card metadata object that will be converted to YAML block
			        language="en"					,license="apache-2.0"					,library_name="diffusers"					,tags=[]					,datasets=args.dataset_name					,metrics=[]					,)					,template_path=__snake_case					,model_name=__snake_case					,repo_name=__snake_case					,dataset_name=args.dataset_name if hasattr(__snake_case					,"dataset_name"	) else None					,learning_rate=args.learning_rate					,train_batch_size=args.train_batch_size					,eval_batch_size=args.eval_batch_size					,gradient_accumulation_steps=(
			        args.gradient_accumulation_steps if hasattr(__snake_case					,"gradient_accumulation_steps"	) else None
			    )					,adam_betaa=args.adam_betaa if hasattr(__snake_case					,"adam_beta1"	) else None					,adam_betaa=args.adam_betaa if hasattr(__snake_case					,"adam_beta2"	) else None					,adam_weight_decay=args.adam_weight_decay if hasattr(__snake_case					,"adam_weight_decay"	) else None					,adam_epsilon=args.adam_epsilon if hasattr(__snake_case					,"adam_epsilon"	) else None					,lr_scheduler=args.lr_scheduler if hasattr(__snake_case					,"lr_scheduler"	) else None					,lr_warmup_steps=args.lr_warmup_steps if hasattr(__snake_case					,"lr_warmup_steps"	) else None					,ema_inv_gamma=args.ema_inv_gamma if hasattr(__snake_case					,"ema_inv_gamma"	) else None					,ema_power=args.ema_power if hasattr(__snake_case					,"ema_power"	) else None					,ema_max_decay=args.ema_max_decay if hasattr(__snake_case					,"ema_max_decay"	) else None					,mixed_precision=args.mixed_precision					,)

			__lowerCAmelCase      :  List[str]												=       os.path.join(args.output_dir					,"README.md"	)
			model_card.save(__snake_case	)


def 			_lowercase				(  __snake_case					,__snake_case = None	)						->   List[str]:
			if resolved_file is None or commit_hash is not None:
						return commit_hash
			__lowerCAmelCase      :  str												=       str(Path(__snake_case	).as_posix()	)
			__lowerCAmelCase      :  List[str]												=       re.search(r"snapshots/([^/]+)/"					,__snake_case	)
			if search is None:
						return None
			__lowerCAmelCase      :  int												=       search.groups()[0]
			return commit_hash if REGEX_COMMIT_HASH.match(__snake_case	) else None


# Old default cache path, potentially to be migrated.
# This logic was more or less taken from `transformers`, with the following differences:
# - Diffusers doesn't use custom environment variables to specify the cache path.
# - There is no need to migrate the cache format, just move the files to the new location.
__snake_case							:   List[Any]      =    os.path.expanduser(
    os.getenv('HF_HOME', os.path.join(os.getenv('XDG_CACHE_HOME', '~/.cache'), 'huggingface'))
)
__snake_case							:   List[Any]      =    os.path.join(hf_cache_home, 'diffusers')


def 			_lowercase				(  __snake_case = None					,__snake_case = None	)						->   None:
			if new_cache_dir is None:
						__lowerCAmelCase      :  Tuple												=       DIFFUSERS_CACHE
			if old_cache_dir is None:
						__lowerCAmelCase      :  Optional[int]												=       old_diffusers_cache

			__lowerCAmelCase      :  Dict												=       Path(__snake_case	).expanduser()
			__lowerCAmelCase      :  Dict												=       Path(__snake_case	).expanduser()
			for old_blob_path in old_cache_dir.glob("**/blobs/*"	):
						if old_blob_path.is_file() and not old_blob_path.is_symlink():
									__lowerCAmelCase      :  Tuple												=       new_cache_dir / old_blob_path.relative_to(__snake_case	)
									new_blob_path.parent.mkdir(parents=__snake_case					,exist_ok=__snake_case	)
									os.replace(__snake_case					,__snake_case	)
									try:
												os.symlink(__snake_case					,__snake_case	)
									except OSError:
												logger.warning(
												    "Could not create symlink between old cache and new cache. If you use an older version of diffusers again, files will be re-downloaded."	)
			# At this point, old_cache_dir contains symlinks to the new cache (it can still be used).


__snake_case							:   Any      =    os.path.join(DIFFUSERS_CACHE, 'version_diffusers_cache.txt')
if not os.path.isfile(cache_version_file):
	__snake_case							:   Union[str, Any]      =    0
else:
	with open(cache_version_file) as f:
		try:
			__snake_case							:   Optional[Any]      =    int(f.read())
		except ValueError:
			__snake_case							:   str      =    0

if cache_version < 1:
	__snake_case							:   List[str]      =    os.path.isdir(old_diffusers_cache) and len(os.listdir(old_diffusers_cache)) > 0
	if old_cache_is_not_empty:
		logger.warning(
		    'The cache for model files in Diffusers v0.14.0 has moved to a new location. Moving your '
		    'existing cached models. This is a one-time operation, you can interrupt it or run it '
		    'later by calling `diffusers.utils.hub_utils.move_cache()`.'
		)
		try:
			move_cache()
		except Exception as e:
			__snake_case							:   Dict      =    '\n'.join(traceback.format_tb(e.__traceback__))
			logger.error(
			    F"""There was a problem when trying to move your cache:\n\n{trace}\n{e.__class__.__name__}: {e}\n\nPlease """
			    'file an issue at https://github.com/huggingface/diffusers/issues/new/choose, copy paste this whole '
			    'message and we will do our best to help.'
			)

if cache_version < 1:
	try:
		os.makedirs(DIFFUSERS_CACHE, exist_ok=True)
		with open(cache_version_file, 'w') as f:
			f.write('1')
	except Exception:
		logger.warning(
		    F"""There was a problem when trying to write in your cache folder ({DIFFUSERS_CACHE}). Please, ensure """
		    'the directory exists and can be written to.'
		)


def 			_lowercase				(  __snake_case					,__snake_case = None	)						->   str:
			if variant is not None:
						__lowerCAmelCase      :  Tuple												=       weights_name.split("."	)
						__lowerCAmelCase      :  Optional[Any]												=       splits[:-1] + [variant] + splits[-1:]
						__lowerCAmelCase      :  Dict												=       ".".join(__snake_case	)

			return weights_name





def 			_lowercase				(  __snake_case					,*,
    __snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case					,__snake_case=None					,)						->   List[str]:
			__lowerCAmelCase      :  Optional[Any]												=       str(__snake_case	)
			if os.path.isfile(__snake_case	):
						return pretrained_model_name_or_path
			elif os.path.isdir(__snake_case	):
						if os.path.isfile(os.path.join(__snake_case					,__snake_case	)	):
									# Load from a PyTorch checkpoint
									__lowerCAmelCase      :  str												=       os.path.join(__snake_case					,__snake_case	)
									return model_file
						elif subfolder is not None and os.path.isfile(
						    os.path.join(__snake_case					,__snake_case					,__snake_case	)	):
									__lowerCAmelCase      :  Union[str, Any]												=       os.path.join(__snake_case					,__snake_case					,__snake_case	)
									return model_file
						else:
									raise EnvironmentError(
									    F"""Error no file named {weights_name} found in directory {pretrained_model_name_or_path}."""	)
			else:
						# 1. First check if deprecated way of loading from branches is used
						if (
						    revision in DEPRECATED_REVISION_ARGS
						    and (weights_name == WEIGHTS_NAME or weights_name == SAFETENSORS_WEIGHTS_NAME)
						    and version.parse(version.parse(__snake_case	).base_version	) >= version.parse("0.20.0"	)
						):
									try:
												__lowerCAmelCase      :  Union[str, Any]												=       hf_hub_download(
												    __snake_case					,filename=_add_variant(__snake_case					,__snake_case	)					,cache_dir=__snake_case					,force_download=__snake_case					,proxies=__snake_case					,resume_download=__snake_case					,local_files_only=__snake_case					,use_auth_token=__snake_case					,user_agent=__snake_case					,subfolder=__snake_case					,revision=revision or commit_hash					,)
												warnings.warn(
												    F"""Loading the variant {revision} from {pretrained_model_name_or_path} via `revision='{revision}'` is deprecated. Loading instead from `revision='main'` with `variant={revision}`. Loading model variants via `revision='{revision}'` will be removed in diffusers v1. Please use `variant='{revision}'` instead."""					,__snake_case					,)
												return model_file
									except:  # noqa: E722
												warnings.warn(
												    F"""You are loading the variant {revision} from {pretrained_model_name_or_path} via `revision='{revision}'`. This behavior is deprecated and will be removed in diffusers v1. One should use `variant='{revision}'` instead. However, it appears that {pretrained_model_name_or_path} currently does not have a {_add_variant(__snake_case					,__snake_case	)} file in the 'main' branch of {pretrained_model_name_or_path}. \n The Diffusers team and community would be very grateful if you could open an issue: https://github.com/huggingface/diffusers/issues/new with the title '{pretrained_model_name_or_path} is missing {_add_variant(__snake_case					,__snake_case	)}' so that the correct variant file can be added."""					,__snake_case					,)
						try:
									# 2. Load model file as usual
									__lowerCAmelCase      :  Any												=       hf_hub_download(
									    __snake_case					,filename=__snake_case					,cache_dir=__snake_case					,force_download=__snake_case					,proxies=__snake_case					,resume_download=__snake_case					,local_files_only=__snake_case					,use_auth_token=__snake_case					,user_agent=__snake_case					,subfolder=__snake_case					,revision=revision or commit_hash					,)
									return model_file

						except RepositoryNotFoundError:
									raise EnvironmentError(
									    F"""{pretrained_model_name_or_path} is not a local folder and is not a valid model identifier """
									    "listed on 'https://huggingface.co/models'\nIf this is a private repository, make sure to pass a "
									    "token having permission to this repo with `use_auth_token` or log in with `huggingface-cli "
									    "login`."	)
						except RevisionNotFoundError:
									raise EnvironmentError(
									    F"""{revision} is not a valid git identifier (branch name, tag name or commit id) that exists for """
									    "this model name. Check the model page at "
									    F"""'https://huggingface.co/{pretrained_model_name_or_path}' for available revisions."""	)
						except EntryNotFoundError:
									raise EnvironmentError(
									    F"""{pretrained_model_name_or_path} does not appear to have a file named {weights_name}."""	)
						except HTTPError as err:
									raise EnvironmentError(
									    F"""There was a specific connection error when trying to load {pretrained_model_name_or_path}:\n{err}"""	)
						except ValueError:
									raise EnvironmentError(
									    F"""We couldn't connect to '{HUGGINGFACE_CO_RESOLVE_ENDPOINT}' to load this model, couldn't find it"""
									    F""" in the cached files and it looks like {pretrained_model_name_or_path} is not the path to a"""
									    F""" directory containing a file named {weights_name} or"""
									    " \nCheckout your internet connection or see how to run the library in"
									    " offline mode at 'https://huggingface.co/docs/diffusers/installation#offline-mode'."	)
						except EnvironmentError:
									raise EnvironmentError(
									    F"""Can't load the model for '{pretrained_model_name_or_path}'. If you were trying to load it from """
									    "'https://huggingface.co/models', make sure you don't have a local directory with the same name. "
									    F"""Otherwise, make sure '{pretrained_model_name_or_path}' is the correct path to a directory """
									    F"""containing a file named {weights_name}"""	)




"""simple docstring"""






from ..utils import DummyObject, requires_backends



class 			A__   (  metaclass=__SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	SCREAMING_SNAKE_CASE          =	['torch', 'torchsde']

	def __init__(     self:		int       ,			*_SCREAMING_SNAKE_CASE:		Optional[Any]       ,			**_SCREAMING_SNAKE_CASE:		str)				->       Dict:

				"""simple docstring"""

				requires_backends(self       ,			["torch", "torchsde"])

	@classmethod
	def 							_SCREAMING_SNAKE_CASE   (     cls:		Optional[Any]       ,			*_SCREAMING_SNAKE_CASE:		Optional[int]       ,			**_SCREAMING_SNAKE_CASE:		Optional[int])				->       Optional[Any]:

				"""simple docstring"""

				requires_backends(cls       ,			["torch", "torchsde"])







	@classmethod
	def 							_SCREAMING_SNAKE_CASE   (     cls:		Dict       ,			*_SCREAMING_SNAKE_CASE:		List[Any]       ,			**_SCREAMING_SNAKE_CASE:		Any)				->       Optional[int]:

				"""simple docstring"""

				requires_backends(cls       ,			["torch", "torchsde"])