


from math import ceil







def SCREAMING_SNAKE_CASE	(			__lowerCAmelCase = 1001				)    ->				int:
  snake_case__						= 1

  for i in range(1							,   int(ceil(n / 2.0				)				)				):
    snake_case__						= 2 * i + 1
    snake_case__						= 2 * i
    snake_case__						= total + 4 * odd**2 - 6 * even

  return total


if __name__ == "__main__":
   import sys

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








'''simple docstring'''




from ....configuration_utils import PretrainedConfig
from ....utils import logging


_SCREAMING_SNAKE_CASE							     =			logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							     =			{
    "CarlCochet/trajectory-transformer-halfcheetah-medium-v2": (
        "https://huggingface.co/CarlCochet/trajectory-transformer-halfcheetah-medium-v2/resolve/main/config.json"
    ),
    # See all TrajectoryTransformer models at https://huggingface.co/models?filter=trajectory_transformer
}
class 			_lowerCAmelCase		(			A__	):






     """simple docstring"""






     snake_case_						      =   "trajectory_transformer"
     snake_case_						      =   ["past_key_values"]
     snake_case_						      =   {
         "hidden_size": "n_embd",
         "num_attention_heads": "n_head",
         "num_hidden_layers": "n_layer",
     }



     def __init__(   self							:			Optional[Any]   ,       __snake_case							:			int=1_00   ,       __snake_case							:			List[str]=5   ,       __snake_case							:			str=1   ,       __snake_case							:			Union[str, Any]=1   ,       __snake_case							:			Union[str, Any]=2_49   ,       __snake_case							:			List[Any]=6   ,       __snake_case							:			Optional[int]=17   ,       __snake_case							:			Optional[Any]=25   ,       __snake_case							:			Union[str, Any]=4   ,       __snake_case							:			List[Any]=4   ,       __snake_case							:			Optional[int]=1_28   ,       __snake_case							:			Optional[Any]=0.1   ,       __snake_case							:			Any=0.1   ,       __snake_case							:			int=0.1   ,       __snake_case							:			Union[str, Any]=0.00_06   ,       __snake_case							:			Tuple=5_12   ,       __snake_case							:			int=0.02   ,       __snake_case							:			Any=1e-12   ,       __snake_case							:			Optional[Any]=1   ,       __snake_case							:			List[Any]=True   ,       __snake_case							:			Dict=1   ,       __snake_case							:			Dict=5_02_56   ,       __snake_case							:			Union[str, Any]=5_02_56   ,       **__snake_case							:			Tuple   ,       )->	Optional[int]:
        snake_case 						=   vocab_size
        snake_case 						=   action_weight
        snake_case 						=   reward_weight
        snake_case 						=   value_weight
        snake_case 						=   max_position_embeddings
        snake_case 						=   block_size
        snake_case 						=   action_dim
        snake_case 						=   observation_dim
        snake_case 						=   transition_dim
        snake_case 						=   learning_rate
        snake_case 						=   n_layer
        snake_case 						=   n_head
        snake_case 						=   n_embd
        snake_case 						=   embd_pdrop
        snake_case 						=   attn_pdrop
        snake_case 						=   resid_pdrop
        snake_case 						=   initializer_range
        snake_case 						=   layer_norm_eps
        snake_case 						=   kaiming_initializer_range
        snake_case 						=   use_cache
        super().__init__(pad_token_id=__snake_case   ,       bos_token_id=__snake_case   ,       eos_token_id=__snake_case   ,       **__snake_case						)

