






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


A__	:			Optional[Any]			   = logging.get_logger(__name__)

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

				"""simple docstring"""




				lowercase__											=       """table-transformer"""
				lowercase__											=       ["""past_key_values"""]
				lowercase__											=       {
				    """hidden_size""": """d_model""",
				    """num_attention_heads""": """encoder_attention_heads""",
				}




				def __init__(     self						:    List[str],  lowerCamelCase						:    List[str]=True,  lowerCamelCase						:    Union[str, Any]=None,  lowerCamelCase						:    List[Any]=3,  lowerCamelCase						:    str=100,  lowerCamelCase						:    int=6,  lowerCamelCase						:    Dict=2_048,  lowerCamelCase						:    Tuple=8,  lowerCamelCase						:    Optional[int]=6,  lowerCamelCase						:    List[str]=2_048,  lowerCamelCase						:    Optional[Any]=8,  lowerCamelCase						:    int=0.0,  lowerCamelCase						:    int=0.0,  lowerCamelCase						:    Dict=True,  lowerCamelCase						:    Dict="relu",  lowerCamelCase						:    Any=256,  lowerCamelCase						:    Union[str, Any]=0.1,  lowerCamelCase						:    Union[str, Any]=0.0,  lowerCamelCase						:    str=0.0,  lowerCamelCase						:    List[Any]=0.02,  lowerCamelCase						:    str=1.0,  lowerCamelCase						:    Optional[int]=False,  lowerCamelCase						:    List[Any]="sine",  lowerCamelCase						:    List[str]="resnet50",  lowerCamelCase						:    Optional[int]=True,  lowerCamelCase						:    str=False,  lowerCamelCase						:    Tuple=1,  lowerCamelCase						:    Optional[Any]=5,  lowerCamelCase						:    Tuple=2,  lowerCamelCase						:    Dict=1,  lowerCamelCase						:    Optional[int]=1,  lowerCamelCase						:    Dict=5,  lowerCamelCase						:    List[Any]=2,  lowerCamelCase						:    Optional[Any]=0.1,  **lowerCamelCase						:    List[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.'''  )
																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__ ,						lowercase__ ,						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 				lowercase__   (     self						:    Union[str, Any]  ):

								'''simple docstring'''
								return self.encoder_attention_heads




				@property
				def 				lowercase__   (     self						:    Optional[int]  ):

								'''simple docstring'''
								return self.d_model



class       _UpperCAmelCase					(       A__	):

				"""simple docstring"""




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




				@property
				def 				lowercase__   (     self						:    Tuple  ):

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




				@property
				def 				lowercase__   (     self						:    Tuple  ):

								'''simple docstring'''
								return 1E-5




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

								'''simple docstring'''
								return 12












def   a			(						lowerCamelCase_				):






				'''simple docstring'''
				lowercase__    =			[1]

				lowercase__ ,						lowercase__ ,						lowercase__    =			0, 0, 0
				lowercase__    =			ugly_nums[ia] * 2
				lowercase__    =			ugly_nums[ia] * 3
				lowercase__    =			ugly_nums[ia] * 5

				for _ in range(1		,   lowerCamelCase_				):
								lowercase__    =			min(lowerCamelCase_		,   lowerCamelCase_		,   lowerCamelCase_				)
								ugly_nums.append(lowerCamelCase_				)
								if next_num == next_a:
												ia += 1
												lowercase__    =			ugly_nums[ia] * 2
								if next_num == next_a:
												ia += 1
												lowercase__    =			ugly_nums[ia] * 3
								if next_num == next_a:
												ia += 1
												lowercase__    =			ugly_nums[ia] * 5
				return ugly_nums[-1]


if __name__ == "__main__":
							from doctest import testmod

							testmod(verbose=True)
							print(F"{ugly_numbers(2_00) = }")




