lmgvp/modules.py [501:509]:
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        conv1_out = self.conv1(node_embeddings, edge_index)
        conv2_out = self.conv2(conv1_out, edge_index)
        conv3_out = self.conv3(conv2_out, edge_index)
        # residual concat
        out = torch.cat((conv1_out, conv2_out, conv3_out), dim=-1)
        out = self.dropout(self.relu(out))  # [n_nodes, 2048]
        # aggregate node vectors to graph
        out = scatter_mean(out, batch.batch, dim=0)  # [bs, 2048]
        return self.dense(out).squeeze(-1) + 0.5  # [bs]
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lmgvp/modules.py [835:843]:
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        conv1_out = self.conv1(node_embeddings, edge_index)
        conv2_out = self.conv2(conv1_out, edge_index)
        conv3_out = self.conv3(conv2_out, edge_index)
        # residual concat
        out = torch.cat((conv1_out, conv2_out, conv3_out), dim=-1)
        out = self.dropout(self.relu(out))  # [n_nodes, 2048]
        # aggregate node vectors to graph
        out = scatter_mean(out, batch.batch, dim=0)  # [bs, 2048]
        return self.dense(out).squeeze(-1) + 0.5  # [bs]
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