


'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_			:  Optional[int]										=   logging.get_logger(__name__)

UpperCAmelCase_			:  Union[str, Any]										=   {
    'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json',
}

class     _lowerCamelCase       (     snake_case_					):




 '''simple docstring'''
 __lowercase					:		str     				=    '''lxmert'''
 __lowercase					:		Dict     				=    {}


 def __init__(   self   ,   __lowercase=30_522   ,   __lowercase=768   ,   __lowercase=12   ,   __lowercase=9_500   ,   __lowercase=1_600   ,   __lowercase=400   ,   __lowercase=3_072   ,   __lowercase="gelu"   ,   __lowercase=0.1   ,   __lowercase=0.1   ,   __lowercase=512   ,   __lowercase=2   ,   __lowercase=0.0_2   ,   __lowercase=1E-12   ,   __lowercase=9   ,   __lowercase=5   ,   __lowercase=5   ,   __lowercase=2_048   ,   __lowercase=4   ,   __lowercase=6.6_7   ,   __lowercase=True   ,   __lowercase=True   ,   __lowercase=True   ,   __lowercase=True   ,   __lowercase=True   ,   __lowercase=True   ,   __lowercase=True   ,   **__lowercase   ,   ):

  """simple docstring"""







  __A	:		Optional[int]	  =      vocab_size
  __A	:		List[Any]	  =      hidden_size
  __A	:		str	  =      num_attention_heads
  __A	:		Any	  =      hidden_act
  __A	:		int	  =      intermediate_size
  __A	:		List[Any]	  =      hidden_dropout_prob
  __A	:		Dict	  =      attention_probs_dropout_prob
  __A	:		List[Any]	  =      max_position_embeddings
  __A	:		Union[str, Any]	  =      type_vocab_size
  __A	:		List[Any]	  =      initializer_range
  __A	:		int	  =      layer_norm_eps
  __A	:		Tuple	  =      num_qa_labels
  __A	:		Any	  =      num_object_labels
  __A	:		str	  =      num_attr_labels
  __A	:		Optional[Any]	  =      l_layers
  __A	:		str	  =      x_layers
  __A	:		Union[str, Any]	  =      r_layers
  __A	:		Any	  =      visual_feat_dim
  __A	:		Any	  =      visual_pos_dim
  __A	:		Any	  =      visual_loss_normalizer
  __A	:		int	  =      task_matched
  __A	:		List[str]	  =      task_mask_lm
  __A	:		Optional[int]	  =      task_obj_predict
  __A	:		Any	  =      task_qa
  __A	:		List[Any]	  =      visual_obj_loss
  __A	:		Union[str, Any]	  =      visual_attr_loss
  __A	:		List[Any]	  =      visual_feat_loss
  __A	:		List[Any]	  =      {'vision': r_layers, 'cross_encoder': x_layers, 'language': l_layers}
  super().__init__(**__lowercase    )










'''simple docstring'''
from math import ceil


def       _lowercase							(					UpperCamelCase__							:       int = 1001      ):
 __A	:		int	  =      1

 for i in range(1,					int(ceil(n / 2.0      )      )      ):
  __A	:		Any	  =      2 * i + 1
  __A	:		List[str]	  =      2 * i
  __A	:		str	  =      total + 4 * odd**2 - 6 * even

 return total


if __name__ == "__main__":
 import sys

 if len(sys.argv) == 1:
  print(solution())
 else:
  try:
   UpperCAmelCase_			:  int										=   int(sys.argv[1])
   print(solution(n))
  except ValueError:
   print('Invalid entry - please enter a number')






