models.emb.gatne
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Module Contents¶
Classes¶
The GATNE model from the `”Representation Learning for Attributed Multiplex Heterogeneous Network” |
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Functions¶
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class
models.emb.gatne.
GATNE
(dimension, walk_length, walk_num, window_size, worker, epoch, batch_size, edge_dim, att_dim, negative_samples, neighbor_samples, schema)[source]¶ Bases:
models.BaseModel
The GATNE model from the “Representation Learning for Attributed Multiplex Heterogeneous Network” paper
- Args:
walk_length (int) : The walk length. walk_num (int) : The number of walks to sample for each node. window_size (int) : The actual context size which is considered in language model. worker (int) : The number of workers for word2vec. epoch (int) : The number of training epochs. batch_size (int) : The size of each training batch. edge_dim (int) : Number of edge embedding dimensions. att_dim (int) : Number of attention dimensions. negative_samples (int) : Negative samples for optimization. neighbor_samples (int) : Neighbor samples for aggregation schema (str) : The metapath schema used in model. Metapaths are splited with “,”, while each node type are connected with “-” in each metapath. For example:”0-1-0,0-1-2-1-0”
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class
models.emb.gatne.
GATNEModel
(num_nodes, embedding_size, embedding_u_size, edge_type_count, dim_a)[source]¶ Bases:
torch.nn.Module
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class
models.emb.gatne.
NSLoss
(num_nodes, num_sampled, embedding_size)[source]¶ Bases:
torch.nn.Module