



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


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

__lowerCamelCase     :							Dict  							=				{
    """microsoft/table-transformer-detection""": (
        """https://huggingface.co/microsoft/table-transformer-detection/resolve/main/config.json"""
    ),
}





class  __magic_name__   (							_snake_case						):
  lowercase      :       str          ="""table-transformer"""
  lowercase      :       Optional[Any]          =["""past_key_values"""]
  lowercase      :       Dict          ={
      """hidden_size""": """d_model""",
      """num_attention_heads""": """encoder_attention_heads""",
  }






  def __init__(						self      :     int				,		UpperCamelCase__      :     Tuple=True				,		UpperCamelCase__      :     Optional[Any]=None				,		UpperCamelCase__      :     Optional[int]=3				,		UpperCamelCase__      :     List[Any]=1_00				,		UpperCamelCase__      :     Tuple=6				,		UpperCamelCase__      :     List[str]=20_48				,		UpperCamelCase__      :     Union[str, Any]=8				,		UpperCamelCase__      :     Union[str, Any]=6				,		UpperCamelCase__      :     Union[str, Any]=20_48				,		UpperCamelCase__      :     Any=8				,		UpperCamelCase__      :     Any=0.0				,		UpperCamelCase__      :     List[Any]=0.0				,		UpperCamelCase__      :     Optional[int]=True				,		UpperCamelCase__      :     List[Any]="relu"				,		UpperCamelCase__      :     List[Any]=2_56				,		UpperCamelCase__      :     Tuple=0.1				,		UpperCamelCase__      :     Dict=0.0				,		UpperCamelCase__      :     List[str]=0.0				,		UpperCamelCase__      :     str=0.02				,		UpperCamelCase__      :     List[str]=1.0				,		UpperCamelCase__      :     Optional[int]=False				,		UpperCamelCase__      :     Tuple="sine"				,		UpperCamelCase__      :     Optional[int]="resnet50"				,		UpperCamelCase__      :     Dict=True				,		UpperCamelCase__      :     List[Any]=False				,		UpperCamelCase__      :     int=1				,		UpperCamelCase__      :     Optional[Any]=5				,		UpperCamelCase__      :     str=2				,		UpperCamelCase__      :     Dict=1				,		UpperCamelCase__      :     Optional[Any]=1				,		UpperCamelCase__      :     Union[str, Any]=5				,		UpperCamelCase__      :     List[str]=2				,		UpperCamelCase__      :     List[Any]=0.1				,		**UpperCamelCase__      :     Optional[int]				,		)				->					Any:
        '''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."      )
                    UpperCAmelCase         =     CONFIG_MAPPING["resnet"](out_features=["stage4"]      )
              elif isinstance(snake_case_				,		snake_case_      ):
                    UpperCAmelCase         =     backbone_config.get("model_type"      )
                    UpperCAmelCase         =     CONFIG_MAPPING[backbone_model_type]
                    UpperCAmelCase         =     config_class.from_dict(snake_case_      )
              # set timm attributes to None
              UpperCAmelCase         =     None, None, None

        UpperCAmelCase         =     use_timm_backbone
        UpperCAmelCase         =     backbone_config
        UpperCAmelCase         =     num_channels
        UpperCAmelCase         =     num_queries
        UpperCAmelCase         =     d_model
        UpperCAmelCase         =     encoder_ffn_dim
        UpperCAmelCase         =     encoder_layers
        UpperCAmelCase         =     encoder_attention_heads
        UpperCAmelCase         =     decoder_ffn_dim
        UpperCAmelCase         =     decoder_layers
        UpperCAmelCase         =     decoder_attention_heads
        UpperCAmelCase         =     dropout
        UpperCAmelCase         =     attention_dropout
        UpperCAmelCase         =     activation_dropout
        UpperCAmelCase         =     activation_function
        UpperCAmelCase         =     init_std
        UpperCAmelCase         =     init_xavier_std
        UpperCAmelCase         =     encoder_layerdrop
        UpperCAmelCase         =     decoder_layerdrop
        UpperCAmelCase         =     encoder_layers
        UpperCAmelCase         =     auxiliary_loss
        UpperCAmelCase         =     position_embedding_type
        UpperCAmelCase         =     backbone
        UpperCAmelCase         =     use_pretrained_backbone
        UpperCAmelCase         =     dilation
        # Hungarian matcher
        UpperCAmelCase         =     class_cost
        UpperCAmelCase         =     bbox_cost
        UpperCAmelCase         =     giou_cost
        # Loss coefficients
        UpperCAmelCase         =     mask_loss_coefficient
        UpperCAmelCase         =     dice_loss_coefficient
        UpperCAmelCase         =     bbox_loss_coefficient
        UpperCAmelCase         =     giou_loss_coefficient
        UpperCAmelCase         =     eos_coefficient
        super().__init__(is_encoder_decoder=snake_case_				,		**snake_case_      )






  @property
  def SCREAMING_SNAKE_CASE_			(						self      :     List[str]      )				->					Tuple:
        '''simple docstring'''







        return self.encoder_attention_heads







  @property
  def SCREAMING_SNAKE_CASE_			(						self      :     Union[str, Any]      )				->					Union[str, Any]:
        '''simple docstring'''







        return self.d_model





class  __magic_name__   (							_snake_case						):
  lowercase      :       List[str]          =version.parse('''1.11'''						)






  @property
  def SCREAMING_SNAKE_CASE_			(						self      :     int      )				->					Tuple:
        '''simple docstring'''







        return OrderedDict(
            [
                ("pixel_values", {0: "batch", 1: "num_channels", 2: "height", 3: "width"}),
                ("pixel_mask", {0: "batch"}),
            ]      )






  @property
  def SCREAMING_SNAKE_CASE_			(						self      :     Tuple      )				->					int:
        '''simple docstring'''







        return 1e-5







  @property
  def SCREAMING_SNAKE_CASE_			(						self      :     str      )				->					Union[str, Any]:
        '''simple docstring'''







        return 12








from argparse import ArgumentParser

from .env import EnvironmentCommand

def    lowerCamelCase_() ->       Any:
						UpperCAmelCase         =     ArgumentParser("Diffusers CLI tool"    ,   usage="diffusers-cli <command> [<args>]"    )
						UpperCAmelCase         =     parser.add_subparsers(help="diffusers-cli command helpers"    )

						# Register commands
						EnvironmentCommand.register_subcommand(lowerCamelCase_    )

						# Let's go
						UpperCAmelCase         =     parser.parse_args()

						if not hasattr(lowerCamelCase_    ,   "func"    ):
												parser.print_help()
												exit(1    )

						# Run
						UpperCAmelCase         =     args.func(lowerCamelCase_    )
						service.run()


if __name__ == "__main__":
		main()



