

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


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

lowerCAmelCase       :				Union[str, Any]         =					{
    # pcqm4mv1 now deprecated
    'graphormer-base': 'https://huggingface.co/clefourrier/graphormer-base-pcqm4mv2/resolve/main/config.json',
    # See all Graphormer models at https://huggingface.co/models?filter=graphormer
}
class 	_A						(					__lowerCamelCase):
  SCREAMING_SNAKE_CASE      : str    =					"graphormer"
  SCREAMING_SNAKE_CASE      : Dict    =					["past_key_values"]

  def __init__(			self	,   _SCREAMING_SNAKE_CASE = 1	,   _SCREAMING_SNAKE_CASE = 512 * 9	,   _SCREAMING_SNAKE_CASE = 512 * 3	,   _SCREAMING_SNAKE_CASE = 512	,   _SCREAMING_SNAKE_CASE = 512	,   _SCREAMING_SNAKE_CASE = 512	,   _SCREAMING_SNAKE_CASE = 128	,   _SCREAMING_SNAKE_CASE = 5	,   _SCREAMING_SNAKE_CASE = 1024	,   _SCREAMING_SNAKE_CASE = "multi_hop"	,   _SCREAMING_SNAKE_CASE = 512	,   _SCREAMING_SNAKE_CASE = False	,   _SCREAMING_SNAKE_CASE = 12	,   _SCREAMING_SNAKE_CASE = 768	,   _SCREAMING_SNAKE_CASE = 768	,   _SCREAMING_SNAKE_CASE = 32	,   _SCREAMING_SNAKE_CASE = 0.1	,   _SCREAMING_SNAKE_CASE = 0.1	,   _SCREAMING_SNAKE_CASE = 0.0	,   _SCREAMING_SNAKE_CASE = False	,   _SCREAMING_SNAKE_CASE = False	,   _SCREAMING_SNAKE_CASE = False	,   _SCREAMING_SNAKE_CASE = "gelu"	,   _SCREAMING_SNAKE_CASE = None	,   _SCREAMING_SNAKE_CASE = False	,   _SCREAMING_SNAKE_CASE = 0	,   _SCREAMING_SNAKE_CASE = False	,   _SCREAMING_SNAKE_CASE = 0.0	,   _SCREAMING_SNAKE_CASE = 8	,   _SCREAMING_SNAKE_CASE = None	,   _SCREAMING_SNAKE_CASE = None	,   _SCREAMING_SNAKE_CASE = True	,   _SCREAMING_SNAKE_CASE = True	,   _SCREAMING_SNAKE_CASE=0	,   _SCREAMING_SNAKE_CASE=1	,   _SCREAMING_SNAKE_CASE=2	,   **_SCREAMING_SNAKE_CASE	,   ):





        """simple docstring"""







        SCREAMING_SNAKE_CASE_			:					Optional[Any]          =       num_classes
        SCREAMING_SNAKE_CASE_			:					str          =       num_atoms
        SCREAMING_SNAKE_CASE_			:					Optional[int]          =       num_in_degree
        SCREAMING_SNAKE_CASE_			:					str          =       num_out_degree
        SCREAMING_SNAKE_CASE_			:					Dict          =       num_edges
        SCREAMING_SNAKE_CASE_			:					int          =       num_spatial
        SCREAMING_SNAKE_CASE_			:					Dict          =       num_edge_dis
        SCREAMING_SNAKE_CASE_			:					int          =       edge_type
        SCREAMING_SNAKE_CASE_			:					Any          =       multi_hop_max_dist
        SCREAMING_SNAKE_CASE_			:					List[str]          =       spatial_pos_max
        SCREAMING_SNAKE_CASE_			:					List[str]          =       max_nodes
        SCREAMING_SNAKE_CASE_			:					Union[str, Any]          =       num_hidden_layers
        SCREAMING_SNAKE_CASE_			:					Union[str, Any]          =       embedding_dim
        SCREAMING_SNAKE_CASE_			:					Dict          =       embedding_dim
        SCREAMING_SNAKE_CASE_			:					Optional[int]          =       ffn_embedding_dim
        SCREAMING_SNAKE_CASE_			:					Dict          =       num_attention_heads
        SCREAMING_SNAKE_CASE_			:					Union[str, Any]          =       dropout
        SCREAMING_SNAKE_CASE_			:					int          =       attention_dropout
        SCREAMING_SNAKE_CASE_			:					Tuple          =       layerdrop
        SCREAMING_SNAKE_CASE_			:					List[Any]          =       encoder_normalize_before
        SCREAMING_SNAKE_CASE_			:					Optional[int]          =       pre_layernorm
        SCREAMING_SNAKE_CASE_			:					List[Any]          =       apply_graphormer_init
        SCREAMING_SNAKE_CASE_			:					Union[str, Any]          =       activation_fn
        SCREAMING_SNAKE_CASE_			:					Union[str, Any]          =       embed_scale
        SCREAMING_SNAKE_CASE_			:					List[str]          =       freeze_embeddings
        SCREAMING_SNAKE_CASE_			:					Optional[Any]          =       num_trans_layers_to_freeze
        SCREAMING_SNAKE_CASE_			:					List[str]          =       share_input_output_embed
        SCREAMING_SNAKE_CASE_			:					Any          =       traceable
        SCREAMING_SNAKE_CASE_			:					Optional[Any]          =       q_noise
        SCREAMING_SNAKE_CASE_			:					Optional[int]          =       qn_block_size

        # These parameters are here for future extensions
        # atm, the model only supports self attention
        SCREAMING_SNAKE_CASE_			:					Optional[Any]          =       kdim
        SCREAMING_SNAKE_CASE_			:					Optional[int]          =       vdim
        SCREAMING_SNAKE_CASE_			:					str          =       self_attention
        SCREAMING_SNAKE_CASE_			:					Tuple          =       bias

        super().__init__(
            pad_token_id=_UpperCamelCase	,   bos_token_id=_UpperCamelCase	,   eos_token_id=_UpperCamelCase	,   **_UpperCamelCase	,   )





from math import factorial

def 				A_					(							a   ,				a					):

      """simple docstring"""



      return factorial(a					) / (factorial(a					) * factorial(n - r					))

def 				A_					(							):

      """simple docstring"""



      SCREAMING_SNAKE_CASE_			:					Union[str, Any]          =       0

      for i in range(1   ,				1_0_1					):
            for j in range(1   ,				i + 1					):
                  if combinations(a   ,				a					) > 1e6:
                        total += 1
      return total


if __name__ == "__main__":
    print(solution())






