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


_SCREAMING_SNAKE_CASE										=						logging.get_logger(__name__)

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



class 				a							(			__lowerCAmelCase       ):







 """simple docstring"""






 lowerCamelCase	:List[str]    			=		'''table-transformer'''
 lowerCamelCase	:Tuple    			=		['''past_key_values''']
 lowerCamelCase	:Optional[int]    			=		{
     '''hidden_size''': '''d_model''',
     '''num_attention_heads''': '''encoder_attention_heads''',
 }



 def __init__(					self		,				lowerCAmelCase_=True		,				lowerCAmelCase_=None		,				lowerCAmelCase_=3		,				lowerCAmelCase_=1_00		,				lowerCAmelCase_=6		,				lowerCAmelCase_=20_48		,				lowerCAmelCase_=8		,				lowerCAmelCase_=6		,				lowerCAmelCase_=20_48		,				lowerCAmelCase_=8		,				lowerCAmelCase_=0.0		,				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_=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."""							)
                      _A        =  CONFIG_MAPPING["""resnet"""](out_features=["""stage4"""]							)
               elif isinstance(lowerCAmelCase_		,				lowerCAmelCase_							):
                      _A        =  backbone_config.get("""model_type"""							)
                      _A        =  CONFIG_MAPPING[backbone_model_type]
                      _A        =  config_class.from_dict(lowerCAmelCase_							)
               # set timm attributes to None
               _A   ,  _A   ,  _A        =  None, None, None

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



 @property
 def      UpperCAmelCase							(					self							)  ->					int:
        return self.encoder_attention_heads



 @property
 def      UpperCAmelCase							(					self							)  ->					int:
        return self.d_model



class 				a							(			__lowerCAmelCase       ):







 """simple docstring"""






 lowerCamelCase	:Dict    			=		version.parse('''1.11'''       )



 @property
 def      UpperCAmelCase							(					self							)  ->					Mapping[str, Mapping[int, str]]:
        return OrderedDict(
            [
                ("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""}),
                ("""pixel_mask""", {0: """batch"""}),
            ]							)



 @property
 def      UpperCAmelCase							(					self							)  ->					float:
        return 1E-5



 @property
 def      UpperCAmelCase							(					self							)  ->					int:
        return 12





import math
import sys






def  snake_case  (       snake_case__			:int)						->   int:
       if number != int(snake_case__):
              raise ValueError("""the value of input must be a natural number""")
       if number < 0:
              raise ValueError("""the value of input must not be a negative number""")
       if number == 0:
              return 1
       _A        =  [-1] * (number + 1)
       _A        =  0
       for i in range(1   ,	number + 1):
              _A        =  sys.maxsize
              _A        =  int(math.sqrt(snake_case__))
              for j in range(1   ,	root + 1):
                     _A        =  1 + answers[i - (j**2)]
                     _A        =  min(snake_case__   ,	snake_case__)
              _A        =  answer
       return answers[number]


if __name__ == "__main__":
    import doctest

    doctest.testmod()




