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


lowercase									=				get_logger(__name__)


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






def        lowerCamelCase_					(     UpperCamelCase__       :						List[str] = None			):







				'''simple docstring'''







				UpperCamelCase__					=				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_					(     UpperCamelCase__       :						int,		UpperCamelCase__       :						List[Any] = None,		UpperCamelCase__       :						List[Any] = None			):







				'''simple docstring'''







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






def        lowerCamelCase_					(     UpperCamelCase__       :						List[str],		UpperCamelCase__       :						Union[str, 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(__a,		'''local_rank'''			) and args.local_rank not in [-1, 0]:
								return

				UpperCamelCase__					=				args.hub_token if hasattr(__a,		'''hub_token'''			) else None
				UpperCamelCase__					=				get_full_repo_name(__a,		token=__a			)

				UpperCamelCase__					=				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,		)

				UpperCamelCase__					=				os.path.join(args.output_dir,		'''README.md'''			)
				model_card.save(__a			)






def        lowerCamelCase_					(     UpperCamelCase__       :						str,		UpperCamelCase__       :						Union[str, Any] = None			):







				'''simple docstring'''







				if resolved_file is None or commit_hash is not None:
								return commit_hash
				UpperCamelCase__					=				str(Path(__a			).as_posix()			)
				UpperCamelCase__					=				re.search(r'''snapshots/([^/]+)/''',		__a			)
				if search is None:
								return None
				UpperCamelCase__					=				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.
lowercase									=				os.path.expanduser(
    os.getenv("""HF_HOME""", os.path.join(os.getenv("""XDG_CACHE_HOME""", """~/.cache"""), """huggingface"""))
)
lowercase									=				os.path.join(hf_cache_home, """diffusers""")






def        lowerCamelCase_					(     UpperCamelCase__       :						Any = None,		UpperCamelCase__       :						int = None			):







				'''simple docstring'''







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

				UpperCamelCase__					=				Path(__a			).expanduser()
				UpperCamelCase__					=				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():
												UpperCamelCase__					=				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).


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

if cache_version < 1:
		lowercase									=				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:
						lowercase									=				'''\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_					(     UpperCamelCase__       :						int,		UpperCamelCase__       :						Optional[Any] = None			):







				'''simple docstring'''







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

				return weights_name







def        lowerCamelCase_					(     UpperCamelCase__       :						Optional[Any],		*,
    UpperCamelCase__       :						Dict,		UpperCamelCase__       :						Any,		UpperCamelCase__       :						Tuple,		UpperCamelCase__       :						Dict,		UpperCamelCase__       :						int,		UpperCamelCase__       :						Union[str, Any],		UpperCamelCase__       :						Union[str, Any],		UpperCamelCase__       :						Dict,		UpperCamelCase__       :						Tuple,		UpperCamelCase__       :						Any,		UpperCamelCase__       :						Union[str, Any]=None,		):







				'''simple docstring'''







				UpperCamelCase__					=				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
												UpperCamelCase__					=				os.path.join(__a,		__a			)
												return model_file
								elif subfolder is not None and os.path.isfile(
								    os.path.join(__a,		__a,		__a			)			):
												UpperCamelCase__					=				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:
																UpperCamelCase__					=				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
												UpperCamelCase__					=				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"""





from __future__ import annotations
def 				A_  (__a					, __a = None					, __a = None					):

					'''simple docstring'''





					if start is None:
										A_								=    0

					if end is None:
										A_								=    len(__a					) - 1

					if start >= end:
										return

					A_								=    (start + end) // 2

					slowsort(__a					, __a					, __a					)
					slowsort(__a					, mid + 1					, __a					)

					if sequence[end] < sequence[mid]:
										A_			,     A_								=    sequence[mid], sequence[end]

					slowsort(__a					, __a					, end - 1					)


if __name__ == "__main__":
		from doctest import testmod

		testmod()




