from neuralogic.core.constructs.metadata import Metadata
from neuralogic.core.constructs.function import Transformation, Aggregation
from neuralogic.core.constructs.factories import R, V
from neuralogic.nn.module.module import Module
[docs]
class GINConv(Module):
def __init__(
self,
in_channels: int,
out_channels: int,
output_name: str,
feature_name: str,
edge_name: str,
activation: Transformation = Transformation.IDENTITY,
aggregation: Aggregation = Aggregation.SUM,
):
self.output_name = output_name
self.feature_name = feature_name
self.edge_name = edge_name
self.in_channels = in_channels
self.out_channels = out_channels
self.aggregation = aggregation
self.activation = activation
def __call__(self):
head = R.get(self.output_name)(V.I)[self.out_channels, self.in_channels]
embed = R.get(f"embed__{self.output_name}")
metadata = Metadata(transformation=Transformation.IDENTITY, aggregation=self.aggregation)
return [
(head <= (R.get(self.feature_name)(V.J), R.get(self.edge_name)(V.J, V.I))) | metadata,
(embed(V.I) <= R.get(self.feature_name)(V.I)) | metadata,
(head <= embed(V.I)[self.in_channels, self.in_channels]) | Metadata(transformation=self.activation),
embed / 1 | Metadata(transformation=Transformation.IDENTITY),
R.get(self.output_name) / 1 | Metadata(transformation=self.activation),
]