
"""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


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   (     _snake_case = None ):
    UpperCAmelCase__	:      int     							=					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 					lowerCamelCase   (     _snake_case    ,_snake_case = None    ,_snake_case = None ):
    if token is None:
        UpperCAmelCase__	:      int     							=					HfFolder.get_token()
    if organization is None:
        UpperCAmelCase__	:      Any     							=					whoami(_snake_case )['name']
        return F'''{username}/{model_id}'''
    else:
        return F'''{organization}/{model_id}'''
def 					lowerCamelCase   (     _snake_case    ,_snake_case ):
    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

    UpperCAmelCase__	:      List[Any]     							=					args.hub_token if hasattr(_snake_case    ,'hub_token' ) else None
    UpperCAmelCase__	:      Dict     							=					get_full_repo_name(_snake_case    ,token=_snake_case )

    UpperCAmelCase__	:      str     							=					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    ,)

    UpperCAmelCase__	:      List[str]     							=					os.path.join(args.output_dir    ,'README.md' )
    model_card.save(_snake_case )
def 					lowerCamelCase   (     _snake_case    ,_snake_case = None ):
    if resolved_file is None or commit_hash is not None:
        return commit_hash
    UpperCAmelCase__	:      Tuple     							=					str(Path(_snake_case ).as_posix() )
    UpperCAmelCase__	:      str     							=					re.search(r'snapshots/([^/]+)/'    ,_snake_case )
    if search is None:
        return None
    UpperCAmelCase__	:      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.
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   (     _snake_case = None    ,_snake_case = None ):
    if new_cache_dir is None:
        UpperCAmelCase__	:      Dict     							=					DIFFUSERS_CACHE
    if old_cache_dir is None:
        UpperCAmelCase__	:      List[str]     							=					old_diffusers_cache

    UpperCAmelCase__	:      List[str]     							=					Path(_snake_case ).expanduser()
    UpperCAmelCase__	:      Optional[Any]     							=					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():
            UpperCAmelCase__	:      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).


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   (     _snake_case    ,_snake_case = None ):
    if variant is not None:
        UpperCAmelCase__	:      List[Any]     							=					weights_name.split('.' )
        UpperCAmelCase__	:      Optional[int]     							=					splits[:-1] + [variant] + splits[-1:]
        UpperCAmelCase__	:      List[str]     							=					'.'.join(_snake_case )

    return weights_name

def 					lowerCamelCase   (     _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    ,):
    UpperCAmelCase__	:      Tuple     							=					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
            UpperCAmelCase__	:      List[Any]     							=					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 ) ):
            UpperCAmelCase__	:      List[str]     							=					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:
                UpperCAmelCase__	:      Optional[int]     							=					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
            UpperCAmelCase__	:      Dict     							=					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}''' )




import math






class      lowerCamelCase_      :




	def __init__(     self						:     Union[str, Any]					,      __A						:     List[str]=0							):  # a graph with Node 0,1,...,N-1
		__A :			List[str]		    =			n
		__A :			List[str]		    =			[
		    [math.inf for j in range(0					,      __A							)] for i in range(0					,      __A							)
		]  # adjacency matrix for weight
		__A :			str		    =			[
		    [math.inf for j in range(0					,      __A							)] for i in range(0					,      __A							)
		]  # dp[i][j] stores minimum distance from i to j




	def        lowerCAmelCase_       (     self						:     str					,      __A						:     Union[str, Any]					,      __A						:     Any					,      __A						:     Optional[int]							):
		__A :			List[Any]		    =			w




	def        lowerCAmelCase_       (     self						:     Union[str, Any]							):
		for k in range(0					,      self.n							):
			for i in range(0					,      self.n							):
				for j in range(0					,      self.n							):
					__A :			List[Any]		    =			min(self.dp[i][j]					,      self.dp[i][k] + self.dp[k][j]							)




	def        lowerCAmelCase_       (     self						:     int					,      __A						:     List[str]					,      __A						:     List[str]							):
		return self.dp[u][v]


if __name__ == "__main__":
			UpperCAmelCase_							:					Tuple		 =   Graph(5)
			graph.add_edge(0, 2, 9)
			graph.add_edge(0, 4, 10)
			graph.add_edge(1, 3, 5)
			graph.add_edge(2, 3, 7)
			graph.add_edge(3, 0, 10)
			graph.add_edge(3, 1, 2)
			graph.add_edge(3, 2, 1)
			graph.add_edge(3, 4, 6)
			graph.add_edge(4, 1, 3)
			graph.add_edge(4, 2, 4)
			graph.add_edge(4, 3, 9)
			graph.floyd_warshall()
			graph.show_min(1, 4)
			graph.show_min(0, 3)





