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


_UpperCAmelCase            =		get_logger(__name__)


_UpperCAmelCase            =		Path(__file__).parent / """model_card_template.md"""
_UpperCAmelCase            =		uuida().hex
_UpperCAmelCase            =		os.getenv("""HF_HUB_OFFLINE""", """""").upper() in ENV_VARS_TRUE_VALUES
_UpperCAmelCase            =		os.getenv("""DISABLE_TELEMETRY""", """""").upper() in ENV_VARS_TRUE_VALUES
_UpperCAmelCase            =		HUGGINGFACE_CO_RESOLVE_ENDPOINT + """/api/telemetry/"""




def     UpperCamelCase						(	__lowercase						:			Union[Dict, str, None] = None     ):
		'''simple docstring'''




		A_		:    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(__lowercase						,__lowercase     ):
				ua += "; " + "; ".join(f'''{k}/{v}''' for k, v in user_agent.items()     )
		elif isinstance(__lowercase						,__lowercase     ):
				ua += "; " + user_agent
		return ua




def     UpperCamelCase						(	__lowercase						:			str						,__lowercase						:			Optional[str] = None						,__lowercase						:			Optional[str] = None     ):
		'''simple docstring'''




		if token is None:
				A_		:    int         =				HfFolder.get_token()
		if organization is None:
				A_		:    Union[str, Any]         =				whoami(__lowercase     )['name']
				return f'''{username}/{model_id}'''
		else:
				return f'''{organization}/{model_id}'''




def     UpperCamelCase						(	__lowercase						:			Optional[Any]						,__lowercase						:			Any     ):
		'''simple docstring'''




		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(__lowercase						,'local_rank'     ) and args.local_rank not in [-1, 0]:
				return

		A_		:    Optional[Any]         =				args.hub_token if hasattr(__lowercase						,'hub_token'     ) else None
		A_		:    Dict         =				get_full_repo_name(__lowercase						,token=__lowercase     )

		A_		:    List[Any]         =				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=__lowercase						,model_name=__lowercase						,repo_name=__lowercase						,dataset_name=args.dataset_name if hasattr(__lowercase						,'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(__lowercase						,'gradient_accumulation_steps'     ) else None
		    )						,adam_betaa=args.adam_betaa if hasattr(__lowercase						,'adam_beta1'     ) else None						,adam_betaa=args.adam_betaa if hasattr(__lowercase						,'adam_beta2'     ) else None						,adam_weight_decay=args.adam_weight_decay if hasattr(__lowercase						,'adam_weight_decay'     ) else None						,adam_epsilon=args.adam_epsilon if hasattr(__lowercase						,'adam_epsilon'     ) else None						,lr_scheduler=args.lr_scheduler if hasattr(__lowercase						,'lr_scheduler'     ) else None						,lr_warmup_steps=args.lr_warmup_steps if hasattr(__lowercase						,'lr_warmup_steps'     ) else None						,ema_inv_gamma=args.ema_inv_gamma if hasattr(__lowercase						,'ema_inv_gamma'     ) else None						,ema_power=args.ema_power if hasattr(__lowercase						,'ema_power'     ) else None						,ema_max_decay=args.ema_max_decay if hasattr(__lowercase						,'ema_max_decay'     ) else None						,mixed_precision=args.mixed_precision						,)

		A_		:    List[Any]         =				os.path.join(args.output_dir						,'README.md'     )
		model_card.save(__lowercase     )




def     UpperCamelCase						(	__lowercase						:			Optional[str]						,__lowercase						:			Optional[str] = None     ):
		'''simple docstring'''




		if resolved_file is None or commit_hash is not None:
				return commit_hash
		A_		:    Dict         =				str(Path(__lowercase     ).as_posix()     )
		A_		:    Dict         =				re.search(r'snapshots/([^/]+)/'						,__lowercase     )
		if search is None:
				return None
		A_		:    int         =				search.groups()[0]
		return commit_hash if REGEX_COMMIT_HASH.match(__lowercase     ) 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.
_UpperCAmelCase            =		os.path.expanduser(
    os.getenv("""HF_HOME""", os.path.join(os.getenv("""XDG_CACHE_HOME""", """~/.cache"""), """huggingface"""))
)
_UpperCAmelCase            =		os.path.join(hf_cache_home, """diffusers""")




def     UpperCamelCase						(	__lowercase						:			Optional[str] = None						,__lowercase						:			Optional[str] = None     ):
		'''simple docstring'''




		if new_cache_dir is None:
				A_		:    Optional[Any]         =				DIFFUSERS_CACHE
		if old_cache_dir is None:
				A_		:    Tuple         =				old_diffusers_cache

		A_		:    int         =				Path(__lowercase     ).expanduser()
		A_		:    Optional[Any]         =				Path(__lowercase     ).expanduser()
		for old_blob_path in old_cache_dir.glob('**/blobs/*'     ):
				if old_blob_path.is_file() and not old_blob_path.is_symlink():
						A_		:    Any         =				new_cache_dir / old_blob_path.relative_to(__lowercase     )
						new_blob_path.parent.mkdir(parents=__lowercase						,exist_ok=__lowercase     )
						os.replace(__lowercase						,__lowercase     )
						try:
								os.symlink(__lowercase						,__lowercase     )
						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).


_UpperCAmelCase            =		os.path.join(DIFFUSERS_CACHE, """version_diffusers_cache.txt""")
if not os.path.isfile(cache_version_file):
					_UpperCAmelCase            =		0
else:
					with open(cache_version_file) as f:
										try:
															_UpperCAmelCase            =		int(f.read())
										except ValueError:
															_UpperCAmelCase            =		0

if cache_version < 1:
					_UpperCAmelCase            =		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:
															_UpperCAmelCase            =		"""\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     UpperCamelCase						(	__lowercase						:			str						,__lowercase						:			Optional[str] = None     ):
		'''simple docstring'''




		if variant is not None:
				A_		:    Optional[int]         =				weights_name.split('.'     )
				A_		:    Optional[int]         =				splits[:-1] + [variant] + splits[-1:]
				A_		:    Any         =				'.'.join(__lowercase     )

		return weights_name




def     UpperCamelCase						(	__lowercase						:			Any						,*,
    __lowercase						:			List[str]						,__lowercase						:			Any						,__lowercase						:			Optional[int]						,__lowercase						:			Any						,__lowercase						:			List[Any]						,__lowercase						:			List[Any]						,__lowercase						:			str						,__lowercase						:			List[str]						,__lowercase						:			Dict						,__lowercase						:			Dict						,__lowercase						:			Union[str, Any]=None						,):
		'''simple docstring'''




		A_		:    List[str]         =				str(__lowercase     )
		if os.path.isfile(__lowercase     ):
				return pretrained_model_name_or_path
		elif os.path.isdir(__lowercase     ):
				if os.path.isfile(os.path.join(__lowercase						,__lowercase     )     ):
						# Load from a PyTorch checkpoint
						A_		:    Tuple         =				os.path.join(__lowercase						,__lowercase     )
						return model_file
				elif subfolder is not None and os.path.isfile(
				    os.path.join(__lowercase						,__lowercase						,__lowercase     )     ):
						A_		:    List[str]         =				os.path.join(__lowercase						,__lowercase						,__lowercase     )
						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(__lowercase     ).base_version     ) >= version.parse('0.20.0'     )
				):
						try:
								A_		:    Tuple         =				hf_hub_download(
								    __lowercase						,filename=_add_variant(__lowercase						,__lowercase     )						,cache_dir=__lowercase						,force_download=__lowercase						,proxies=__lowercase						,resume_download=__lowercase						,local_files_only=__lowercase						,use_auth_token=__lowercase						,user_agent=__lowercase						,subfolder=__lowercase						,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.'''						,__lowercase						,)
								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(__lowercase						,__lowercase     )} 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(__lowercase						,__lowercase     )}\' so that the correct variant file can be added.'''						,__lowercase						,)
				try:
						# 2. Load model file as usual
						A_		:    Any         =				hf_hub_download(
						    __lowercase						,filename=__lowercase						,cache_dir=__lowercase						,force_download=__lowercase						,proxies=__lowercase						,resume_download=__lowercase						,local_files_only=__lowercase						,use_auth_token=__lowercase						,user_agent=__lowercase						,subfolder=__lowercase						,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}'''     )







import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


_UpperCAmelCase            =		logging.get_logger(__name__)





class UpperCAmelCase						( __A  ):


				'''simple docstring'''






				def __init__(						self		,     *lowercase		,     **lowercase ):



						"""simple docstring"""





						warnings.warn(
						    'The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
						    ' use DonutImageProcessor instead.'		,     lowercase		,     )
						super().__init__(*lowercase		,     **lowercase )






