






import os
from datetime import datetime as dt

from github import Github


snake_case__      :	Optional[Any]       	=      [
    """good first issue""",
    """feature request""",
    """wip""",
]






def     _snake_case    ():
			UpperCamelCase_									=     Github(os.environ['GITHUB_TOKEN'])
			UpperCamelCase_									=     g.get_repo('huggingface/accelerate')
			UpperCamelCase_									=     repo.get_issues(state='open')

			for issue in open_issues:
						UpperCamelCase_									=     sorted([comment for comment in issue.get_comments()]    ,      key=lambda __lowercase: i.created_at    ,      reverse=__lowercase)
						UpperCamelCase_									=     comments[0] if len(__lowercase) > 0 else None
						UpperCamelCase_									=     dt.utcnow()
						UpperCamelCase_									=     (current_time - issue.updated_at).days
						UpperCamelCase_									=     (current_time - issue.created_at).days
						if (
						    last_comment is not None
						    and last_comment.user.login == "github-actions[bot]"
						    and days_since_updated > 7
						    and days_since_creation >= 30
						    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels())
						):
									# Close issue since it has been 7 days of inactivity since bot mention.
									issue.edit(state='closed')
						elif (
						    days_since_updated > 23
						    and days_since_creation >= 30
						    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels())
						):
									# Add stale comment
									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/accelerate/blob/main/CONTRIBUTING.md) '
									    'are likely to be ignored.')


if __name__ == "__main__":
	main()













import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case__      :	Optional[int]       	=      logging.get_logger(__name__)

snake_case__      :	List[Any]       	=      {
    """microsoft/git-base""": """https://huggingface.co/microsoft/git-base/resolve/main/config.json""",
}


class 						_a       (  UpperCAmelCase__    ):






  """simple docstring"""





  A_						=   """git_vision_model"""




  def __init__(     self		,		_UpperCAmelCase=768		,		_UpperCAmelCase=3072		,		_UpperCAmelCase=12		,		_UpperCAmelCase=12		,		_UpperCAmelCase=3		,		_UpperCAmelCase=224		,		_UpperCAmelCase=16		,		_UpperCAmelCase="quick_gelu"		,		_UpperCAmelCase=1e-5		,		_UpperCAmelCase=0.0		,		_UpperCAmelCase=0.0_2		,		**_UpperCAmelCase		,		)			-> Optional[Any]:
     super().__init__(**_UpperCAmelCase )

     UpperCamelCase_									=     hidden_size
     UpperCamelCase_									=     intermediate_size
     UpperCamelCase_									=     num_hidden_layers
     UpperCamelCase_									=     num_attention_heads
     UpperCamelCase_									=     num_channels
     UpperCamelCase_									=     patch_size
     UpperCamelCase_									=     image_size
     UpperCamelCase_									=     initializer_range
     UpperCamelCase_									=     attention_dropout
     UpperCamelCase_									=     layer_norm_eps
     UpperCamelCase_									=     hidden_act




  @classmethod
  def    _UpperCAmelCase     (     cls		,		_UpperCAmelCase		,		**_UpperCAmelCase )			-> "PretrainedConfig":
     cls._set_token_in_kwargs(_UpperCAmelCase )

     UpperCamelCase_		,      UpperCamelCase_									=     cls.get_config_dict(_UpperCAmelCase		,		**_UpperCAmelCase )

     # get the vision config dict if we are loading from GITConfig
     if config_dict.get('model_type' ) == "git":
        UpperCamelCase_									=     config_dict['vision_config']

     if "model_type" in config_dict and hasattr(cls		,		'model_type' ) and config_dict["model_type"] != cls.model_type:
        logger.warning(
            f"""You are using a model of type {config_dict["model_type"]} to instantiate a model of type """
            f"""{cls.model_type}. This is not supported for all configurations of models and can yield errors.""" )

     return cls.from_dict(_UpperCAmelCase		,		**_UpperCAmelCase )




class 						_a       (  UpperCAmelCase__    ):






  """simple docstring"""





  A_						=   """git"""




  def __init__(     self		,		_UpperCAmelCase=None		,		_UpperCAmelCase=30522		,		_UpperCAmelCase=768		,		_UpperCAmelCase=6		,		_UpperCAmelCase=12		,		_UpperCAmelCase=3072		,		_UpperCAmelCase="gelu"		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=0.1		,		_UpperCAmelCase=1024		,		_UpperCAmelCase=0.0_2		,		_UpperCAmelCase=1e-12		,		_UpperCAmelCase=0		,		_UpperCAmelCase="absolute"		,		_UpperCAmelCase=True		,		_UpperCAmelCase=False		,		_UpperCAmelCase=101		,		_UpperCAmelCase=102		,		_UpperCAmelCase=None		,		**_UpperCAmelCase		,		)			-> Optional[int]:
     super().__init__(bos_token_id=_UpperCAmelCase		,		eos_token_id=_UpperCAmelCase		,		pad_token_id=_UpperCAmelCase		,		**_UpperCAmelCase )

     if vision_config is None:
        UpperCamelCase_									=     {}
        logger.info('vision_config is None. initializing the GitVisionConfig with default values.' )

     UpperCamelCase_									=     GitVisionConfig(**_UpperCAmelCase )
     UpperCamelCase_									=     vocab_size
     UpperCamelCase_									=     hidden_size
     UpperCamelCase_									=     num_hidden_layers
     UpperCamelCase_									=     num_attention_heads
     UpperCamelCase_									=     hidden_act
     UpperCamelCase_									=     intermediate_size
     UpperCamelCase_									=     hidden_dropout_prob
     UpperCamelCase_									=     attention_probs_dropout_prob
     UpperCamelCase_									=     max_position_embeddings
     UpperCamelCase_									=     initializer_range
     UpperCamelCase_									=     layer_norm_eps
     UpperCamelCase_									=     position_embedding_type
     UpperCamelCase_									=     use_cache
     UpperCamelCase_									=     tie_word_embeddings
     UpperCamelCase_									=     num_image_with_embedding

     UpperCamelCase_									=     bos_token_id
     UpperCamelCase_									=     eos_token_id




  def    _UpperCAmelCase     (     self )			-> str:
     UpperCamelCase_									=     copy.deepcopy(self.__dict__ )
     UpperCamelCase_									=     self.vision_config.to_dict()
     UpperCamelCase_									=     self.__class__.model_type
     return output





