deephyper.keras.layers.SparseMPNN

class deephyper.keras.layers.SparseMPNN(*args: Any, **kwargs: Any)

Bases: tensorflow.keras.layers.

Message passing cell.

Parameters

• state_dim (int) – number of output channels.

• T (int) – number of message passing repetition.

• attn_heads (int) – number of attention heads.

• attn_method (str) – type of attention methods.

• aggr_method (str) – type of aggregation methods.

• activation (str) – type of activation functions.

• update_method (str) – type of update functions.

Methods

build
call	Apply the layer on input tensors.

__call__(*args: Any, **kwargs: Any) → Any

Call self as a function.

call(inputs, **kwargs)

Apply the layer on input tensors.

Parameters

inputs (list) – X (tensor): node feature tensor (batch size * # nodes * # node features) A (tensor): edge pair tensor (batch size * # edges * 2), one is source ID, one is target ID E (tensor): edge feature tensor (batch size * # edges * # edge features) mask (tensor): node mask tensor to mask out non-existent nodes (batch size * # nodes) degree (tensor): node degree tensor for GCN attention (batch size * # edges)

Returns

results after several repetitions of edge network, attention, aggregation and update function (batch size * # nodes * # node features)

Return type

X (tensor)