






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__       =     logging.get_logger(__name__)

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


class    _lowerCAmelCase			(		lowercase_      ):



				"""simple docstring"""



				_lowercase				:   Tuple      =  '''table-transformer'''
				_lowercase				:   Union[str, Any]      =  ['''past_key_values''']
				_lowercase				:   List[Any]      =  {
				    '''hidden_size''': '''d_model''',
				    '''num_attention_heads''': '''encoder_attention_heads''',
				}



				def __init__(      self    :    Dict			,		UpperCamelCase__    :    Optional[Any]=True			,		UpperCamelCase__    :    Tuple=None			,		UpperCamelCase__    :    Optional[Any]=3			,		UpperCamelCase__    :    Tuple=1_0_0			,		UpperCamelCase__    :    Tuple=6			,		UpperCamelCase__    :    Tuple=2_0_4_8			,		UpperCamelCase__    :    List[Any]=8			,		UpperCamelCase__    :    List[Any]=6			,		UpperCamelCase__    :    Tuple=2_0_4_8			,		UpperCamelCase__    :    Union[str, Any]=8			,		UpperCamelCase__    :    Tuple=0.0			,		UpperCamelCase__    :    Dict=0.0			,		UpperCamelCase__    :    str=True			,		UpperCamelCase__    :    str="relu"			,		UpperCamelCase__    :    List[str]=2_5_6			,		UpperCamelCase__    :    List[Any]=0.1			,		UpperCamelCase__    :    Optional[Any]=0.0			,		UpperCamelCase__    :    str=0.0			,		UpperCamelCase__    :    List[Any]=0.02			,		UpperCamelCase__    :    int=1.0			,		UpperCamelCase__    :    Tuple=False			,		UpperCamelCase__    :    Tuple="sine"			,		UpperCamelCase__    :    str="resnet50"			,		UpperCamelCase__    :    List[Any]=True			,		UpperCamelCase__    :    str=False			,		UpperCamelCase__    :    Tuple=1			,		UpperCamelCase__    :    Any=5			,		UpperCamelCase__    :    List[Any]=2			,		UpperCamelCase__    :    Dict=1			,		UpperCamelCase__    :    Optional[Any]=1			,		UpperCamelCase__    :    Any=5			,		UpperCamelCase__    :    int=2			,		UpperCamelCase__    :    Optional[Any]=0.1			,		**UpperCamelCase__    :    Dict			,		):






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

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



				@property
				def 					__magic_name__							(      self    :    str):






											'''simple docstring'''







											return self.encoder_attention_heads



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






											'''simple docstring'''







											return self.d_model


class    _lowerCAmelCase			(		lowercase_      ):



				"""simple docstring"""



				_lowercase				:   Optional[int]      =  version.parse('''1.11'''      )



				@property
				def 					__magic_name__							(      self    :    Any):






											'''simple docstring'''







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



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






											'''simple docstring'''







											return 1E-5



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






											'''simple docstring'''







											return 1_2








import math
from collections.abc import Iterator
from itertools import takewhile

def _UpperCAmelCase   (	a						:	int ):

							if 1 < number < 4:
														# 2 and 3 are primes
														return True
							elif number < 2 or number % 2 == 0 or number % 3 == 0:
														# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
														return False

							# All primes number are in format of 6k +/- 1
							for i in range(5  ,					int(math.sqrt(a ) + 1 )  ,					6 ):
														if number % i == 0 or number % (i + 2) == 0:
																					return False
							return True

def _UpperCAmelCase   (	):
							snake_case__	  =       2
							while True:
														if is_prime(a ):
																					yield num
														num += 1

def _UpperCAmelCase   (	a						:	int = 200_0000 ):
							return sum(takewhile(lambda a : x < n  ,					prime_generator() ) )


if __name__ == "__main__":
	print(F'''{solution() = }''')
