




'''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


_lowerCAmelCase  		=      logging.get_logger(__name__)

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



   """simple docstring"""







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

   def __init__(      self				, _lowerCamelCase=True				, _lowerCamelCase=None				, _lowerCamelCase=3				, _lowerCamelCase=1_0_0				, _lowerCamelCase=6				, _lowerCamelCase=2_0_4_8				, _lowerCamelCase=8				, _lowerCamelCase=6				, _lowerCamelCase=2_0_4_8				, _lowerCamelCase=8				, _lowerCamelCase=0.0				, _lowerCamelCase=0.0				, _lowerCamelCase=True				, _lowerCamelCase="relu"				, _lowerCamelCase=2_5_6				, _lowerCamelCase=0.1				, _lowerCamelCase=0.0				, _lowerCamelCase=0.0				, _lowerCamelCase=0.0_2				, _lowerCamelCase=1.0				, _lowerCamelCase=False				, _lowerCamelCase="sine"				, _lowerCamelCase="resnet50"				, _lowerCamelCase=True				, _lowerCamelCase=False				, _lowerCamelCase=1				, _lowerCamelCase=5				, _lowerCamelCase=2				, _lowerCamelCase=1				, _lowerCamelCase=1				, _lowerCamelCase=5				, _lowerCamelCase=2				, _lowerCamelCase=0.1				, **_lowerCamelCase				, )->       Any:




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

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

   @property
   def snake_case_(      self						)->       List[Any]:
      return self.encoder_attention_heads

   @property
   def snake_case_(      self						)->       List[str]:
      return self.d_model



class   __A (							SCREAMING_SNAKE_CASE__  ):



   """simple docstring"""







   A_												=				version.parse('1.11'  )

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

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

   @property
   def snake_case_(      self						)->       Tuple:
      return 1_2











"""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


a_					=     logging.get_logger(__name__)

a_					=     {
    """sail/poolformer_s12""": """https://huggingface.co/sail/poolformer_s12/resolve/main/config.json""",
    # See all PoolFormer models at https://huggingface.co/models?filter=poolformer
}






class 						__snake_case   (						SCREAMING_SNAKE_CASE__	):





 """simple docstring"""


 _lowerCamelCase								=	"""poolformer"""

 def __init__(       self   ,		__lowerCamelCase=3   ,		__lowerCamelCase=16   ,		__lowerCamelCase=16   ,		__lowerCamelCase=3   ,		__lowerCamelCase=4.0   ,		__lowerCamelCase=[2, 2, 6, 2]   ,		__lowerCamelCase=[64, 128, 320, 512]   ,		__lowerCamelCase=[7, 3, 3, 3]   ,		__lowerCamelCase=[4, 2, 2, 2]   ,		__lowerCamelCase=[2, 1, 1, 1]   ,		__lowerCamelCase=4   ,		__lowerCamelCase=0.0   ,		__lowerCamelCase="gelu"   ,		__lowerCamelCase=True   ,		__lowerCamelCase=1e-5   ,		__lowerCamelCase=0.0_2   ,		**__lowerCamelCase   ,		):



     '''simple docstring'''




     __A       :		str							=	num_channels
     __A       :		List[str]							=	patch_size
     __A       :		str							=	stride
     __A       :		Any							=	padding
     __A       :		Any							=	pool_size
     __A       :		Dict							=	hidden_sizes
     __A       :		Optional[Any]							=	mlp_ratio
     __A       :		Any							=	depths
     __A       :		List[str]							=	patch_sizes
     __A       :		Union[str, Any]							=	strides
     __A       :		List[str]							=	num_encoder_blocks
     __A       :		Optional[int]							=	drop_path_rate
     __A       :		Union[str, Any]							=	hidden_act
     __A       :		Optional[Any]							=	use_layer_scale
     __A       :		List[Any]							=	layer_scale_init_value
     __A       :		List[Any]							=	initializer_range
     super().__init__(**__lowerCamelCase    )






class 						__snake_case   (						SCREAMING_SNAKE_CASE__	):





 """simple docstring"""


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

 @property
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




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







 @property
 def    UpperCamelCase__(       self    ):



     '''simple docstring'''




     return 2e-3




