






'''simple docstring'''
import os
import shutil
from pathlib import Path
from typing import Optional, Union

import numpy as np
from huggingface_hub import hf_hub_download

from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging


if is_onnx_available():
  import onnxruntime as ort


a_					=	logging.get_logger(__name__)

a_					=	{
    'tensor(bool)': np.bool_,
    'tensor(int8)': np.inta,
    'tensor(uint8)': np.uinta,
    'tensor(int16)': np.intaa,
    'tensor(uint16)': np.uintaa,
    'tensor(int32)': np.intaa,
    'tensor(uint32)': np.uintaa,
    'tensor(int64)': np.intaa,
    'tensor(uint64)': np.uintaa,
    'tensor(float16)': np.floataa,
    'tensor(float)': np.floataa,
    'tensor(double)': np.floataa,
}






class        __SCREAMING_SNAKE_CASE :




 def __init__( self		:							Any   , __lowercase		:							List[str]=None   , **__lowercase		:							Dict )		->  Optional[Any]:
       logger.info('''`diffusers.OnnxRuntimeModel` is experimental and might change in the future.''' )
       SCREAMING_SNAKE_CASE__       :			List[str]													=model
       SCREAMING_SNAKE_CASE__       :			str													=kwargs.get('''model_save_dir'''   , __lowercase )
       SCREAMING_SNAKE_CASE__       :			List[str]													=kwargs.get('''latest_model_name'''   , __lowercase )




 def __call__( self		:							int   , **__lowercase		:							str )		->  Any:
       SCREAMING_SNAKE_CASE__       :			Any													={k: np.array(__lowercase ) for k, v in kwargs.items()}
       return self.model.run(__lowercase   , __lowercase )




 @staticmethod
 def        __magic_name__		( __lowercase		:							Union[str, Path]   , __lowercase		:							Optional[Any]=None   , __lowercase		:							Tuple=None )		->  Any:
       if provider is None:
             logger.info('''No onnxruntime provider specified, using CPUExecutionProvider''' )
             SCREAMING_SNAKE_CASE__       :			Union[str, Any]													='''CPUExecutionProvider'''

       return ort.InferenceSession(__lowercase   , providers=[provider]   , sess_options=__lowercase )




 def        __magic_name__		( self		:							List[str]   , __lowercase		:							Union[str, Path]   , __lowercase		:							Optional[str] = None   , **__lowercase		:							Any )		->  Tuple:
       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=file_name if file_name is not None else ONNX_WEIGHTS_NAME

       SCREAMING_SNAKE_CASE__       :			Optional[Any]													=self.model_save_dir.joinpath(self.latest_model_name )
       SCREAMING_SNAKE_CASE__       :			Any													=Path(__lowercase ).joinpath(__lowercase )
       try:
             shutil.copyfile(__lowercase   , __lowercase )
       except shutil.SameFileError:
             pass

       # copy external weights (for models >2GB)
       SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=self.model_save_dir.joinpath(__lowercase )
       if src_path.exists():
             SCREAMING_SNAKE_CASE__       :			str													=Path(__lowercase ).joinpath(__lowercase )
             try:
                   shutil.copyfile(__lowercase   , __lowercase )
             except shutil.SameFileError:
                   pass




 def        __magic_name__		( self		:							Tuple   , __lowercase		:							Union[str, os.PathLike]   , **__lowercase		:							List[Any]   , )		->  Any:
       if os.path.isfile(__lowercase ):
             logger.error(F"Provided path ({save_directory}) should be a directory, not a file" )
             return

       os.makedirs(__lowercase   , exist_ok=__lowercase )

       # saving model weights/files
       self._save_pretrained(__lowercase   , **__lowercase )




 @classmethod
 def        __magic_name__		( cls		:							List[Any]   , __lowercase		:							Union[str, Path]   , __lowercase		:							Optional[Union[bool, str, None]] = None   , __lowercase		:							Optional[Union[str, None]] = None   , __lowercase		:							bool = False   , __lowercase		:							Optional[str] = None   , __lowercase		:							Optional[str] = None   , __lowercase		:							Optional[str] = None   , __lowercase		:							Optional["ort.SessionOptions"] = None   , **__lowercase		:							Union[str, Any]   , )		->  Optional[int]:
       SCREAMING_SNAKE_CASE__       :			Tuple													=file_name if file_name is not None else ONNX_WEIGHTS_NAME
       # load model from local directory
       if os.path.isdir(__lowercase ):
             SCREAMING_SNAKE_CASE__       :			int													=OnnxRuntimeModel.load_model(
                 os.path.join(__lowercase   , __lowercase )   , provider=__lowercase   , sess_options=__lowercase )
             SCREAMING_SNAKE_CASE__       :			List[str]													=Path(__lowercase )
       # load model from hub
       else:
             # download model
             SCREAMING_SNAKE_CASE__       :			int													=hf_hub_download(
                 repo_id=__lowercase   , filename=__lowercase   , use_auth_token=__lowercase   , revision=__lowercase   , cache_dir=__lowercase   , force_download=__lowercase   , )
             SCREAMING_SNAKE_CASE__       :			Union[str, Any]													=Path(__lowercase ).parent
             SCREAMING_SNAKE_CASE__       :			List[str]													=Path(__lowercase ).name
             SCREAMING_SNAKE_CASE__       :			int													=OnnxRuntimeModel.load_model(__lowercase   , provider=__lowercase   , sess_options=__lowercase )
       return cls(model=__lowercase   , **__lowercase )




 @classmethod
 def        __magic_name__		( cls		:							List[Any]   , __lowercase		:							Union[str, Path]   , __lowercase		:							bool = True   , __lowercase		:							Optional[str] = None   , __lowercase		:							Optional[str] = None   , **__lowercase		:							List[str]   , )		->  Dict:
       SCREAMING_SNAKE_CASE__       :			Dict													=None
       if len(str(__lowercase ).split('''@''' ) ) == 2:
             SCREAMING_SNAKE_CASE__						,		SCREAMING_SNAKE_CASE__       :			Optional[int]													=model_id.split('''@''' )

       return cls._from_pretrained(
           model_id=__lowercase   , revision=__lowercase   , cache_dir=__lowercase   , force_download=__lowercase   , use_auth_token=__lowercase   , **__lowercase   , )







'''simple docstring'''
from datetime import datetime as dt
import os

from github import Github


a_					=	[
    'good first issue',
    'good second issue',
    'good difficult issue',
    'feature request',
    'new model',
    'wip',
]





def 	_a(					):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			List[str]													=Github(os.environ['''GITHUB_TOKEN''']							)
      SCREAMING_SNAKE_CASE__       :			List[Any]													=g.get_repo('''huggingface/transformers'''							)
      SCREAMING_SNAKE_CASE__       :			List[Any]													=repo.get_issues(state='''open'''							)

      for issue in open_issues:
            SCREAMING_SNAKE_CASE__       :			List[Any]													=sorted([comment for comment in issue.get_comments()],		key=lambda UpperCamelCase__							: i.created_at,		reverse=UpperCamelCase__							)
            SCREAMING_SNAKE_CASE__       :			Dict													=comments[0] if len(UpperCamelCase__							) > 0 else None
            if (
                last_comment is not None
                and last_comment.user.login == "github-actions[bot]"
                and (dt.utcnow() - issue.updated_at).days > 7
                and (dt.utcnow() - issue.created_at).days >= 3_0
                and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()							)
            ):
                  # print(f"Would close issue {issue.number} since it has been 7 days of inactivity since bot mention.")
                  issue.edit(state='''closed'''							)
            elif (
                (dt.utcnow() - issue.updated_at).days > 2_3
                and (dt.utcnow() - issue.created_at).days >= 3_0
                and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()							)
            ):
                  # print(f"Would add stale comment to {issue.number}")
                  issue.create_comment(
                      '''This issue has been automatically marked as stale because it has not had '''
                      '''recent activity. If you think this still needs to be addressed '''
                      '''please comment on this thread.\n\nPlease note that issues that do not follow the '''
                      '''[contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) '''
                      '''are likely to be ignored.'''							)


if __name__ == "__main__":
  main()