






"""simple docstring"""



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


_UpperCamelCase		:  str						=		logging.get_logger(__name__)

_UpperCamelCase		:  Tuple						=		{
    # 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					(       a_     ):
    UpperCAmelCase_			:					Union[str, Any]     					="graphormer"
    UpperCAmelCase_			:					str     					=["past_key_values"]







    def __init__(      self							,		_lowerCamelCase = 1							,		_lowerCamelCase = 5_1_2 * 9							,		_lowerCamelCase = 5_1_2 * 3							,		_lowerCamelCase = 5_1_2							,		_lowerCamelCase = 5_1_2							,		_lowerCamelCase = 5_1_2							,		_lowerCamelCase = 1_2_8							,		_lowerCamelCase = 5							,		_lowerCamelCase = 1_0_2_4							,		_lowerCamelCase = "multi_hop"							,		_lowerCamelCase = 5_1_2							,		_lowerCamelCase = False							,		_lowerCamelCase = 1_2							,		_lowerCamelCase = 7_6_8							,		_lowerCamelCase = 7_6_8							,		_lowerCamelCase = 3_2							,		_lowerCamelCase = 0.1							,		_lowerCamelCase = 0.1							,		_lowerCamelCase = 0.0							,		_lowerCamelCase = False							,		_lowerCamelCase = False							,		_lowerCamelCase = False							,		_lowerCamelCase = "gelu"							,		_lowerCamelCase = None							,		_lowerCamelCase = False							,		_lowerCamelCase = 0							,		_lowerCamelCase = False							,		_lowerCamelCase = 0.0							,		_lowerCamelCase = 8							,		_lowerCamelCase = None							,		_lowerCamelCase = None							,		_lowerCamelCase = True							,		_lowerCamelCase = True							,		_lowerCamelCase=0							,		_lowerCamelCase=1							,		_lowerCamelCase=2							,		**_lowerCamelCase							,		):
      lowercase							   =	num_classes
      lowercase							   =	num_atoms
      lowercase							   =	num_in_degree
      lowercase							   =	num_out_degree
      lowercase							   =	num_edges
      lowercase							   =	num_spatial
      lowercase							   =	num_edge_dis
      lowercase							   =	edge_type
      lowercase							   =	multi_hop_max_dist
      lowercase							   =	spatial_pos_max
      lowercase							   =	max_nodes
      lowercase							   =	num_hidden_layers
      lowercase							   =	embedding_dim
      lowercase							   =	embedding_dim
      lowercase							   =	ffn_embedding_dim
      lowercase							   =	num_attention_heads
      lowercase							   =	dropout
      lowercase							   =	attention_dropout
      lowercase							   =	layerdrop
      lowercase							   =	encoder_normalize_before
      lowercase							   =	pre_layernorm
      lowercase							   =	apply_graphormer_init
      lowercase							   =	activation_fn
      lowercase							   =	embed_scale
      lowercase							   =	freeze_embeddings
      lowercase							   =	num_trans_layers_to_freeze
      lowercase							   =	share_input_output_embed
      lowercase							   =	traceable
      lowercase							   =	q_noise
      lowercase							   =	qn_block_size

      # These parameters are here for future extensions
      # atm, the model only supports self attention
      lowercase							   =	kdim
      lowercase							   =	vdim
      lowercase							   =	self_attention
      lowercase							   =	bias

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










"""simple docstring"""



def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  Dict		, __snake_case      :  str   ):





  '''simple docstring'''





  lowercase							   =	1
  while b > 0:
    if b & 1:
      res *= a

    a *= a
    b >>= 1

  return res
def 						_SCREAMING_SNAKE_CASE			(   __snake_case      :  int		, __snake_case      :  List[str]		, __snake_case      :  str   ):





  '''simple docstring'''





  lowercase							   =	1
  while b > 0:
    if b & 1:
      lowercase							   =	((res % c) * (a % c)) % c

    a *= a
    b >>= 1

  return res


