


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


__snake_case            =   logging.get_logger(__name__)

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




class    UpperCAmelCase					(       __lowerCAmelCase    ):

			'''simple docstring'''





			lowercase						= '''table-transformer'''
			lowercase						= ['''past_key_values''']
			lowercase						= {
			    '''hidden_size''': '''d_model''',
			    '''num_attention_heads''': '''encoder_attention_heads''',
			}




			def __init__(						self							:		str       ,       __magic_name__							:		int=True       ,       __magic_name__							:		Dict=None       ,       __magic_name__							:		Optional[Any]=3       ,       __magic_name__							:		int=1_0_0       ,       __magic_name__							:		Dict=6       ,       __magic_name__							:		Dict=2_0_4_8       ,       __magic_name__							:		str=8       ,       __magic_name__							:		Any=6       ,       __magic_name__							:		Optional[Any]=2_0_4_8       ,       __magic_name__							:		Dict=8       ,       __magic_name__							:		Optional[int]=0.0       ,       __magic_name__							:		Optional[int]=0.0       ,       __magic_name__							:		List[str]=True       ,       __magic_name__							:		Any="relu"       ,       __magic_name__							:		Optional[int]=2_5_6       ,       __magic_name__							:		int=0.1       ,       __magic_name__							:		int=0.0       ,       __magic_name__							:		Union[str, Any]=0.0       ,       __magic_name__							:		List[str]=0.02       ,       __magic_name__							:		Tuple=1.0       ,       __magic_name__							:		Optional[Any]=False       ,       __magic_name__							:		List[Any]="sine"       ,       __magic_name__							:		Dict="resnet50"       ,       __magic_name__							:		Tuple=True       ,       __magic_name__							:		Optional[int]=False       ,       __magic_name__							:		Tuple=1       ,       __magic_name__							:		List[Any]=5       ,       __magic_name__							:		List[Any]=2       ,       __magic_name__							:		Any=1       ,       __magic_name__							:		str=1       ,       __magic_name__							:		Optional[int]=5       ,       __magic_name__							:		Optional[int]=2       ,       __magic_name__							:		Optional[Any]=0.1       ,       **__magic_name__							:		Union[str, 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(lowerCAmelCase_       ,       lowerCAmelCase_						):
												UpperCamelCase         =					backbone_config.get("""model_type"""						)
												UpperCamelCase         =					CONFIG_MAPPING[backbone_model_type]
												UpperCamelCase         =					config_class.from_dict(lowerCAmelCase_						)
									# set timm attributes to None
									UpperCamelCase  ,  UpperCamelCase  ,  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=lowerCAmelCase_       ,       **lowerCAmelCase_						)




			@property
			def   lowerCamelCase_					(						self							:		int						):







						"""simple docstring"""







						return self.encoder_attention_heads





			@property
			def   lowerCamelCase_					(						self							:		Union[str, Any]						):







						"""simple docstring"""







						return self.d_model




class    UpperCAmelCase					(       __lowerCAmelCase    ):

			'''simple docstring'''





			lowercase						= version.parse("""1.11"""    )




			@property
			def   lowerCamelCase_					(						self							:		Union[str, Any]						):







						"""simple docstring"""







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




			@property
			def   lowerCamelCase_					(						self							:		Optional[Any]						):







						"""simple docstring"""







						return 1e-5





			@property
			def   lowerCamelCase_					(						self							:		List[str]						):







						"""simple docstring"""







						return 1_2








from ..utils import DummyObject, requires_backends




class    UpperCAmelCase					(       metaclass=__snake_case    ):
			lowercase						= ["""keras_nlp"""]




			def __init__(						self							:		List[str]       ,       *__magic_name__							:		str       ,       **__magic_name__							:		int						):







						"""simple docstring"""







						requires_backends(self       ,       ["""keras_nlp"""]						)




