
'''simple docstring'''







import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


lowercase    :							Tuple      =					logging.get_logger(__name__)

lowercase    :							Optional[int]      =					{
    'SenseTime/deformable-detr': 'https://huggingface.co/sensetime/deformable-detr/resolve/main/config.json',
    # See all Deformable DETR models at https://huggingface.co/models?filter=deformable-detr
}


class 						__UpperCAmelCase      (					_lowerCamelCase						):
							__lowercase      		=       """deformable_detr"""
							__lowercase      		=       {
							    """hidden_size""": """d_model""",
							    """num_attention_heads""": """encoder_attention_heads""",
							}


							def __init__(       self    ,   lowerCAmelCase_=True    ,   lowerCAmelCase_=None    ,   lowerCAmelCase_=3    ,   lowerCAmelCase_=3_00    ,   lowerCAmelCase_=10_24    ,   lowerCAmelCase_=6    ,   lowerCAmelCase_=10_24    ,   lowerCAmelCase_=8    ,   lowerCAmelCase_=6    ,   lowerCAmelCase_=10_24    ,   lowerCAmelCase_=8    ,   lowerCAmelCase_=0.0    ,   lowerCAmelCase_=True    ,   lowerCAmelCase_="relu"    ,   lowerCAmelCase_=2_56    ,   lowerCAmelCase_=0.1    ,   lowerCAmelCase_=0.0    ,   lowerCAmelCase_=0.0    ,   lowerCAmelCase_=0.02    ,   lowerCAmelCase_=1.0    ,   lowerCAmelCase_=True    ,   lowerCAmelCase_=False    ,   lowerCAmelCase_="sine"    ,   lowerCAmelCase_="resnet50"    ,   lowerCAmelCase_=True    ,   lowerCAmelCase_=False    ,   lowerCAmelCase_=4    ,   lowerCAmelCase_=4    ,   lowerCAmelCase_=4    ,   lowerCAmelCase_=False    ,   lowerCAmelCase_=3_00    ,   lowerCAmelCase_=False    ,   lowerCAmelCase_=1    ,   lowerCAmelCase_=5    ,   lowerCAmelCase_=2    ,   lowerCAmelCase_=1    ,   lowerCAmelCase_=1    ,   lowerCAmelCase_=5    ,   lowerCAmelCase_=2    ,   lowerCAmelCase_=0.1    ,   lowerCAmelCase_=0.25    ,   lowerCAmelCase_=False    ,   **lowerCAmelCase_    ,   ):





								"""simple docstring"""






								if backbone_config is not None and use_timm_backbone:
									raise ValueError('You can\'t specify both `backbone_config` and `use_timm_backbone`.'  )

								if not use_timm_backbone:
									if backbone_config is None:
										logger.info('`backbone_config` is `None`. Initializing the config with the default `ResNet` backbone.'  )
										_snake_case   						=		CONFIG_MAPPING['resnet'](out_features=['stage4']  )
									elif isinstance(_UpperCamelCase    ,   _UpperCamelCase  ):
										_snake_case   						=		backbone_config.get('model_type'  )
										_snake_case   						=		CONFIG_MAPPING[backbone_model_type]
										_snake_case   						=		config_class.from_dict(_UpperCamelCase  )
								_snake_case   						=		use_timm_backbone
								_snake_case   						=		backbone_config
								_snake_case   						=		num_channels
								_snake_case   						=		num_queries
								_snake_case   						=		max_position_embeddings
								_snake_case   						=		d_model
								_snake_case   						=		encoder_ffn_dim
								_snake_case   						=		encoder_layers
								_snake_case   						=		encoder_attention_heads
								_snake_case   						=		decoder_ffn_dim
								_snake_case   						=		decoder_layers
								_snake_case   						=		decoder_attention_heads
								_snake_case   						=		dropout
								_snake_case   						=		attention_dropout
								_snake_case   						=		activation_dropout
								_snake_case   						=		activation_function
								_snake_case   						=		init_std
								_snake_case   						=		init_xavier_std
								_snake_case   						=		encoder_layerdrop
								_snake_case   						=		auxiliary_loss
								_snake_case   						=		position_embedding_type
								_snake_case   						=		backbone
								_snake_case   						=		use_pretrained_backbone
								_snake_case   						=		dilation
								# deformable attributes
								_snake_case   						=		num_feature_levels
								_snake_case   						=		encoder_n_points
								_snake_case   						=		decoder_n_points
								_snake_case   						=		two_stage
								_snake_case   						=		two_stage_num_proposals
								_snake_case   						=		with_box_refine
								if two_stage is True and with_box_refine is False:
									raise ValueError('If two_stage is True, with_box_refine must be True.'  )
								# Hungarian matcher
								_snake_case   						=		class_cost
								_snake_case   						=		bbox_cost
								_snake_case   						=		giou_cost
								# Loss coefficients
								_snake_case   						=		mask_loss_coefficient
								_snake_case   						=		dice_loss_coefficient
								_snake_case   						=		bbox_loss_coefficient
								_snake_case   						=		giou_loss_coefficient
								_snake_case   						=		eos_coefficient
								_snake_case   						=		focal_alpha
								_snake_case   						=		disable_custom_kernels
								super().__init__(is_encoder_decoder=_UpperCamelCase    ,   **_UpperCamelCase  )


							@property
							def  lowerCamelCase				(       self  ):





								"""simple docstring"""






								return self.encoder_attention_heads


							@property
							def  lowerCamelCase				(       self  ):





								"""simple docstring"""






								return self.d_model




							def  lowerCamelCase				(       self  ):





								"""simple docstring"""






								_snake_case   						=		copy.deepcopy(self.__dict__  )
								if self.backbone_config is not None:
									_snake_case   						=		self.backbone_config.to_dict()
								_snake_case   						=		self.__class__.model_type
								return output








import os
from datetime import datetime as dt

from github import Github


snake_case__					:							Union[str, Any]													=     [
    'good first issue',
    'feature request',
    'wip',
]



def _a				(	)	->						List[Any]:







      '''simple docstring'''






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

      for issue in open_issues:
            __A          =				sorted([comment for comment in issue.get_comments()]					,				key=lambda lowerCamelCase : i.created_at					,				reverse=lowerCamelCase )
            __A          =				comments[0] if len(lowerCamelCase ) > 0 else None
            __A          =				dt.utcnow()
            __A          =				(current_time - issue.updated_at).days
            __A          =				(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()





