




"""simple docstring"""





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


_lowercase						   =     logging.get_logger(__name__)

_lowercase						   =     {
    # 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    __lowercase							(      snake_case_						):


				'''simple docstring'''


				_lowerCAmelCase						      ="graphormer"
				_lowerCAmelCase						      =["past_key_values"]

				def __init__( self :  List[str]   ,SCREAMING_SNAKE_CASE_ :  int = 1   ,SCREAMING_SNAKE_CASE_ :  int = 5_1_2 * 9   ,SCREAMING_SNAKE_CASE_ :  int = 5_1_2 * 3   ,SCREAMING_SNAKE_CASE_ :  int = 5_1_2   ,SCREAMING_SNAKE_CASE_ :  int = 5_1_2   ,SCREAMING_SNAKE_CASE_ :  int = 5_1_2   ,SCREAMING_SNAKE_CASE_ :  int = 1_2_8   ,SCREAMING_SNAKE_CASE_ :  int = 5   ,SCREAMING_SNAKE_CASE_ :  int = 1_0_2_4   ,SCREAMING_SNAKE_CASE_ :  str = "multi_hop"   ,SCREAMING_SNAKE_CASE_ :  int = 5_1_2   ,SCREAMING_SNAKE_CASE_ :  bool = False   ,SCREAMING_SNAKE_CASE_ :  int = 1_2   ,SCREAMING_SNAKE_CASE_ :  int = 7_6_8   ,SCREAMING_SNAKE_CASE_ :  int = 7_6_8   ,SCREAMING_SNAKE_CASE_ :  int = 3_2   ,SCREAMING_SNAKE_CASE_ :  float = 0.1   ,SCREAMING_SNAKE_CASE_ :  float = 0.1   ,SCREAMING_SNAKE_CASE_ :  float = 0.0   ,SCREAMING_SNAKE_CASE_ :  bool = False   ,SCREAMING_SNAKE_CASE_ :  bool = False   ,SCREAMING_SNAKE_CASE_ :  bool = False   ,SCREAMING_SNAKE_CASE_ :  str = "gelu"   ,SCREAMING_SNAKE_CASE_ :  float = None   ,SCREAMING_SNAKE_CASE_ :  bool = False   ,SCREAMING_SNAKE_CASE_ :  int = 0   ,SCREAMING_SNAKE_CASE_ :  bool = False   ,SCREAMING_SNAKE_CASE_ :  float = 0.0   ,SCREAMING_SNAKE_CASE_ :  int = 8   ,SCREAMING_SNAKE_CASE_ :  int = None   ,SCREAMING_SNAKE_CASE_ :  int = None   ,SCREAMING_SNAKE_CASE_ :  bool = True   ,SCREAMING_SNAKE_CASE_ :  bool = True   ,SCREAMING_SNAKE_CASE_ :  str=0   ,SCREAMING_SNAKE_CASE_ :  List[str]=1   ,SCREAMING_SNAKE_CASE_ :  Any=2   ,**SCREAMING_SNAKE_CASE_ :  Optional[Any]   ,):
										snake_case__							:       List[str]				      =       num_classes
										snake_case__							:       Tuple				      =       num_atoms
										snake_case__							:       Union[str, Any]				      =       num_in_degree
										snake_case__							:       Any				      =       num_out_degree
										snake_case__							:       Optional[Any]				      =       num_edges
										snake_case__							:       Optional[int]				      =       num_spatial
										snake_case__							:       Optional[Any]				      =       num_edge_dis
										snake_case__							:       str				      =       edge_type
										snake_case__							:       Optional[int]				      =       multi_hop_max_dist
										snake_case__							:       Optional[int]				      =       spatial_pos_max
										snake_case__							:       Optional[Any]				      =       max_nodes
										snake_case__							:       Optional[Any]				      =       num_hidden_layers
										snake_case__							:       Union[str, Any]				      =       embedding_dim
										snake_case__							:       Dict				      =       embedding_dim
										snake_case__							:       Dict				      =       ffn_embedding_dim
										snake_case__							:       str				      =       num_attention_heads
										snake_case__							:       List[Any]				      =       dropout
										snake_case__							:       Dict				      =       attention_dropout
										snake_case__							:       Optional[int]				      =       layerdrop
										snake_case__							:       Any				      =       encoder_normalize_before
										snake_case__							:       Any				      =       pre_layernorm
										snake_case__							:       Optional[Any]				      =       apply_graphormer_init
										snake_case__							:       Optional[int]				      =       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[Any]				      =       share_input_output_embed
										snake_case__							:       int				      =       traceable
										snake_case__							:       List[str]				      =       q_noise
										snake_case__							:       Dict				      =       qn_block_size

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

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








"""simple docstring"""





_lowercase						   =     {0: [1, 2], 1: [0, 3], 2: [0], 3: [1], 4: [5, 6], 5: [4, 6], 6: [4, 5]}

_lowercase						   =     {0: [1, 2, 3], 1: [0, 3], 2: [0], 3: [0, 1], 4: [], 5: []}

def 		lowerCAmelCase				(			lowerCamelCase   ,      lowerCamelCase   ,      lowerCamelCase		):
						'''simple docstring'''


						snake_case__							:       Any				      =       True
						snake_case__							:       int				      =       []

						for neighbour in graph[vert]:
												if not visited[neighbour]:
																		connected_verts += dfs(lowerCamelCase   ,      lowerCamelCase   ,      lowerCamelCase		)

						return [vert, *connected_verts]

def 		lowerCAmelCase				(			lowerCamelCase		):
						'''simple docstring'''


						snake_case__							:       Optional[int]				      =       len(lowerCamelCase		)
						snake_case__							:       str				      =       graph_size * [False]
						snake_case__							:       List[str]				      =       []

						for i in range(lowerCamelCase		):
												if not visited[i]:
																		snake_case__							:       Dict				      =       dfs(lowerCamelCase   ,      lowerCamelCase   ,      lowerCamelCase		)
																		components_list.append(lowerCamelCase		)

						return components_list


if __name__ == "__main__":
							import doctest

							doctest.testmod()


