





"""simple docstring"""





from collections import OrderedDict
from typing import Mapping

from packaging import version

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


_UpperCamelCase					      =   logging.get_logger(__name__)

_UpperCamelCase					      =   {
    'microsoft/table-transformer-detection': (
        'https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json'
    ),
}
class 		SCREAMING_SNAKE_CASE_				(     UpperCamelCase__ ):
				"""simple docstring"""
				__snake_case :							Optional[Any]									=		"""table-transformer"""
				__snake_case :							Optional[Any]									=		["""past_key_values"""]
				__snake_case :							Union[str, Any]									=		{
				    """hidden_size""": """d_model""",
				    """num_attention_heads""": """encoder_attention_heads""",
				}




				def __init__(  self	:Any    ,     __lowercase	:int=True    ,     __lowercase	:List[str]=None    ,     __lowercase	:Tuple=3    ,     __lowercase	:Tuple=100    ,     __lowercase	:Union[str, Any]=6    ,     __lowercase	:Tuple=2048    ,     __lowercase	:List[str]=8    ,     __lowercase	:str=6    ,     __lowercase	:List[Any]=2048    ,     __lowercase	:Dict=8    ,     __lowercase	:str=0.0    ,     __lowercase	:List[str]=0.0    ,     __lowercase	:Tuple=True    ,     __lowercase	:Tuple="relu"    ,     __lowercase	:Dict=256    ,     __lowercase	:str=0.1    ,     __lowercase	:str=0.0    ,     __lowercase	:int=0.0    ,     __lowercase	:Union[str, Any]=0.02    ,     __lowercase	:List[str]=1.0    ,     __lowercase	:List[Any]=False    ,     __lowercase	:List[Any]="sine"    ,     __lowercase	:Dict="resnet50"    ,     __lowercase	:str=True    ,     __lowercase	:str=False    ,     __lowercase	:Tuple=1    ,     __lowercase	:str=5    ,     __lowercase	:Optional[int]=2    ,     __lowercase	:Union[str, Any]=1    ,     __lowercase	:Union[str, Any]=1    ,     __lowercase	:Union[str, Any]=5    ,     __lowercase	:List[Any]=2    ,     __lowercase	:Tuple=0.1    ,     **__lowercase	:str    ,     ):



											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.'''      )
																									__lowerCamelCase   :   Any       =CONFIG_MAPPING['''resnet'''](out_features=['''stage4''']      )
																		elif isinstance(__A    ,     __A      ):
																									__lowerCamelCase   :   List[Any]       =backbone_config.get('''model_type'''      )
																									__lowerCamelCase   :   Optional[Any]       =CONFIG_MAPPING[backbone_model_type]
																									__lowerCamelCase   :   List[str]       =config_class.from_dict(__A      )
																		# set timm attributes to None
																		__lowerCamelCase     ,    __lowerCamelCase     ,    __lowerCamelCase   :   str       =None, None, None

											__lowerCamelCase   :   Dict       =use_timm_backbone
											__lowerCamelCase   :   Union[str, Any]       =backbone_config
											__lowerCamelCase   :   Optional[int]       =num_channels
											__lowerCamelCase   :   int       =num_queries
											__lowerCamelCase   :   Tuple       =d_model
											__lowerCamelCase   :   int       =encoder_ffn_dim
											__lowerCamelCase   :   List[Any]       =encoder_layers
											__lowerCamelCase   :   List[Any]       =encoder_attention_heads
											__lowerCamelCase   :   str       =decoder_ffn_dim
											__lowerCamelCase   :   str       =decoder_layers
											__lowerCamelCase   :   Tuple       =decoder_attention_heads
											__lowerCamelCase   :   Any       =dropout
											__lowerCamelCase   :   Optional[int]       =attention_dropout
											__lowerCamelCase   :   Union[str, Any]       =activation_dropout
											__lowerCamelCase   :   Any       =activation_function
											__lowerCamelCase   :   Union[str, Any]       =init_std
											__lowerCamelCase   :   Optional[int]       =init_xavier_std
											__lowerCamelCase   :   List[str]       =encoder_layerdrop
											__lowerCamelCase   :   int       =decoder_layerdrop
											__lowerCamelCase   :   int       =encoder_layers
											__lowerCamelCase   :   Tuple       =auxiliary_loss
											__lowerCamelCase   :   List[str]       =position_embedding_type
											__lowerCamelCase   :   List[str]       =backbone
											__lowerCamelCase   :   List[str]       =use_pretrained_backbone
											__lowerCamelCase   :   Dict       =dilation
											# Hungarian matcher
											__lowerCamelCase   :   Dict       =class_cost
											__lowerCamelCase   :   Dict       =bbox_cost
											__lowerCamelCase   :   Union[str, Any]       =giou_cost
											# Loss coefficients
											__lowerCamelCase   :   str       =mask_loss_coefficient
											__lowerCamelCase   :   Optional[int]       =dice_loss_coefficient
											__lowerCamelCase   :   Any       =bbox_loss_coefficient
											__lowerCamelCase   :   List[str]       =giou_loss_coefficient
											__lowerCamelCase   :   Dict       =eos_coefficient
											super().__init__(is_encoder_decoder=__A    ,     **__A      )




				@property
				def        __lowercase	(  self	:Tuple      ):
											return self.encoder_attention_heads




				@property
				def        __lowercase	(  self	:Optional[Any]      ):
											return self.d_model

class 		SCREAMING_SNAKE_CASE_				(     UpperCamelCase__ ):
				"""simple docstring"""
				__snake_case :							List[Any]									=		version.parse("""1.11""" )




				@property
				def        __lowercase	(  self	:Optional[int]      ):
											return OrderedDict(
											    [
											        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
											        ('''pixel_mask''', {0: '''batch'''}),
											    ]      )




				@property
				def        __lowercase	(  self	:int      ):
											return 1e-5




				@property
				def        __lowercase	(  self	:Optional[int]      ):
											return 12











def 					SCREAMING_SNAKE_CASE__				(							UpperCamelCase__:				float       , UpperCamelCase__:				float     ):
		if mass < 0:
				raise ValueError("""The mass of a body cannot be negative"""     )
		return 0.5 * mass * abs(UpperCamelCase__     ) * abs(UpperCamelCase__     )


if __name__ == "__main__":
	import doctest

	doctest.testmod(verbose=True)