

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


a__      =		logging.get_logger(__name__)

a__      =		{
    # 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 						snake_case  (		__lowerCamelCase					):



   '''simple docstring'''






   snake_case_   :	str       =						"graphormer"
   snake_case_   :	Dict       =						["past_key_values"]

   def __init__(   self							:     int			,						lowerCAmelCase							:     int = 1			,						lowerCAmelCase							:     int = 512 * 9			,						lowerCAmelCase							:     int = 512 * 3			,						lowerCAmelCase							:     int = 512			,						lowerCAmelCase							:     int = 512			,						lowerCAmelCase							:     int = 512			,						lowerCAmelCase							:     int = 128			,						lowerCAmelCase							:     int = 5			,						lowerCAmelCase							:     int = 1024			,						lowerCAmelCase							:     str = "multi_hop"			,						lowerCAmelCase							:     int = 512			,						lowerCAmelCase							:     bool = False			,						lowerCAmelCase							:     int = 12			,						lowerCAmelCase							:     int = 768			,						lowerCAmelCase							:     int = 768			,						lowerCAmelCase							:     int = 32			,						lowerCAmelCase							:     float = 0.1			,						lowerCAmelCase							:     float = 0.1			,						lowerCAmelCase							:     float = 0.0			,						lowerCAmelCase							:     bool = False			,						lowerCAmelCase							:     bool = False			,						lowerCAmelCase							:     bool = False			,						lowerCAmelCase							:     str = "gelu"			,						lowerCAmelCase							:     float = None			,						lowerCAmelCase							:     bool = False			,						lowerCAmelCase							:     int = 0			,						lowerCAmelCase							:     bool = False			,						lowerCAmelCase							:     float = 0.0			,						lowerCAmelCase							:     int = 8			,						lowerCAmelCase							:     int = None			,						lowerCAmelCase							:     int = None			,						lowerCAmelCase							:     bool = True			,						lowerCAmelCase							:     bool = True			,						lowerCAmelCase							:     Dict=0			,						lowerCAmelCase							:     str=1			,						lowerCAmelCase							:     List[str]=2			,						**lowerCAmelCase							:     Union[str, Any]			,						)			->			List[Any]:

    """simple docstring"""







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

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

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





def  lowercase    (				SCREAMING_SNAKE_CASE__    :		Any			)					->       Optional[int]:
 _snake_case      :					Any					=   [701, 301, 132, 57, 23, 10, 4, 1]
 for gap in gaps:
  for i in range(SCREAMING_SNAKE_CASE__			,    len(SCREAMING_SNAKE_CASE__			)			):
   _snake_case      :					List[Any]					=   collection[i]
   _snake_case      :					List[str]					=   i
   while j >= gap and collection[j - gap] > insert_value:
    _snake_case      :					int					=   collection[j - gap]
    j -= gap
   if j != i:
    _snake_case      :					Tuple					=   insert_value
 return collection


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

  testmod()
  a__      =		input("""Enter numbers separated by a comma:\n""").strip()
  a__      =		[int(item) for item in user_input.split(""",""")]
  print(shell_sort(unsorted))
