




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 					lowerCamelCase__       (						A__       :					str = None	):





       '''simple docstring'''



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




def 					lowerCamelCase__       (						A__       :					Union[str, Any]  ,			A__       :					Tuple = None  ,			A__       :					List[str] = None	):





       '''simple docstring'''



       if token is None:
              __lowerCamelCase   =						HfFolder.get_token()
       if organization is None:
              __lowerCamelCase   =						whoami(__a	)['''name''']
              return f'{username}/{model_id}'
       else:
              return f'{organization}/{model_id}'




def 					lowerCamelCase__       (						A__       :					Dict  ,			A__       :					List[str]	):





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

       __lowerCamelCase   =						args.hub_token if hasattr(__a  ,			"""hub_token"""	) else None
       __lowerCamelCase   =						get_full_repo_name(__a  ,			token=__a	)

       __lowerCamelCase   =						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=__a  ,			model_name=__a  ,			repo_name=__a  ,			dataset_name=args.dataset_name if hasattr(__a  ,			"""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(__a  ,			"""gradient_accumulation_steps"""	) else None
           )  ,			adam_betaa=args.adam_betaa if hasattr(__a  ,			"""adam_beta1"""	) else None  ,			adam_betaa=args.adam_betaa if hasattr(__a  ,			"""adam_beta2"""	) else None  ,			adam_weight_decay=args.adam_weight_decay if hasattr(__a  ,			"""adam_weight_decay"""	) else None  ,			adam_epsilon=args.adam_epsilon if hasattr(__a  ,			"""adam_epsilon"""	) else None  ,			lr_scheduler=args.lr_scheduler if hasattr(__a  ,			"""lr_scheduler"""	) else None  ,			lr_warmup_steps=args.lr_warmup_steps if hasattr(__a  ,			"""lr_warmup_steps"""	) else None  ,			ema_inv_gamma=args.ema_inv_gamma if hasattr(__a  ,			"""ema_inv_gamma"""	) else None  ,			ema_power=args.ema_power if hasattr(__a  ,			"""ema_power"""	) else None  ,			ema_max_decay=args.ema_max_decay if hasattr(__a  ,			"""ema_max_decay"""	) else None  ,			mixed_precision=args.mixed_precision  ,			)

       __lowerCamelCase   =						os.path.join(args.output_dir  ,			"""README.md"""	)
       model_card.save(__a	)




def 					lowerCamelCase__       (						A__       :					Any  ,			A__       :					str = None	):





       '''simple docstring'''



       if resolved_file is None or commit_hash is not None:
              return commit_hash
       __lowerCamelCase   =						str(Path(__a	).as_posix()	)
       __lowerCamelCase   =						re.search(R"""snapshots/([^/]+)/"""  ,			__a	)
       if search is None:
              return None
       __lowerCamelCase   =						search.groups()[0]
       return commit_hash if REGEX_COMMIT_HASH.match(__a	) 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 					lowerCamelCase__       (						A__       :					Tuple = None  ,			A__       :					str = None	):





       '''simple docstring'''



       if new_cache_dir is None:
              __lowerCamelCase   =						DIFFUSERS_CACHE
       if old_cache_dir is None:
              __lowerCamelCase   =						old_diffusers_cache

       __lowerCamelCase   =						Path(__a	).expanduser()
       __lowerCamelCase   =						Path(__a	).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   =						new_cache_dir / old_blob_path.relative_to(__a	)
                     new_blob_path.parent.mkdir(parents=__a  ,			exist_ok=__a	)
                     os.replace(__a  ,			__a	)
                     try:
                            os.symlink(__a  ,			__a	)
                     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 					lowerCamelCase__       (						A__       :					List[str]  ,			A__       :					List[Any] = None	):





       '''simple docstring'''



       if variant is not None:
              __lowerCamelCase   =						weights_name.split("""."""	)
              __lowerCamelCase   =						splits[:-1] + [variant] + splits[-1:]
              __lowerCamelCase   =						'''.'''.join(__a	)

       return weights_name




def 					lowerCamelCase__       (						A__       :					Tuple  ,			*,
    A__       :					Tuple  ,			A__       :					Optional[Any]  ,			A__       :					List[Any]  ,			A__       :					List[Any]  ,			A__       :					Union[str, Any]  ,			A__       :					int  ,			A__       :					List[Any]  ,			A__       :					str  ,			A__       :					str  ,			A__       :					Any  ,			A__       :					Dict=None  ,			):





       '''simple docstring'''



       __lowerCamelCase   =						str(__a	)
       if os.path.isfile(__a	):
              return pretrained_model_name_or_path
       elif os.path.isdir(__a	):
              if os.path.isfile(os.path.join(__a  ,			__a	)	):
                     # Load from a PyTorch checkpoint
                     __lowerCamelCase   =						os.path.join(__a  ,			__a	)
                     return model_file
              elif subfolder is not None and os.path.isfile(
                  os.path.join(__a  ,			__a  ,			__a	)	):
                     __lowerCamelCase   =						os.path.join(__a  ,			__a  ,			__a	)
                     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(__a	).base_version	) >= version.parse("""0.20.0"""	)
              ):
                     try:
                            __lowerCamelCase   =						hf_hub_download(
                                __a  ,			filename=_add_variant(__a  ,			__a	)  ,			cache_dir=__a  ,			force_download=__a  ,			proxies=__a  ,			resume_download=__a  ,			local_files_only=__a  ,			use_auth_token=__a  ,			user_agent=__a  ,			subfolder=__a  ,			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.'  ,			__a  ,			)
                            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(__a  ,			__a	)} 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(__a  ,			__a	)}\' so that the correct variant file can be added.'  ,			__a  ,			)
              try:
                     # 2. Load model file as usual
                     __lowerCamelCase   =						hf_hub_download(
                         __a  ,			filename=__a  ,			cache_dir=__a  ,			force_download=__a  ,			proxies=__a  ,			resume_download=__a  ,			local_files_only=__a  ,			use_auth_token=__a  ,			user_agent=__a  ,			subfolder=__a  ,			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'''
__snake_case							      =     65521


def 			a      (			__a   )  ->	int:



					'''simple docstring'''






					UpperCamelCase__   :Tuple												= 1
					UpperCamelCase__   :Any												= 0
					for plain_chr in plain_text:
										UpperCamelCase__   :List[str]												= (a + ord(__a   )) % MOD_ADLER
										UpperCamelCase__   :Tuple												= (b + a) % MOD_ADLER
					return (b << 16) | a