def forward()

in source/sagemaker/sagemaker_graph_entity_resolution/dgl_entity_resolution/model.py [0:0]

• 12 lines of code
• 8 McCabe index (conditional complexity)

    def forward(self, g, user_features, website_features):
        # get embeddings for all node types. for user node type, use passed in user features
        h_dict = {}
        h_dict['user'] = nn.Parameter(user_features)
        h_dict['website'] = nn.Parameter(website_features)

        for ntype in self.embed:
            if g[0].number_of_nodes(ntype) > 0:
                h_dict[ntype] = self.embed[ntype][g[0].nodes(ntype).long(), :]

        # pass through all layers
        for i, layer in enumerate(self.layers):
            if i != 0:
                h_dict = {k: F.leaky_relu(h) for k, h in h_dict.items()}
            h_dict = layer(g[i], h_dict)

        # get user logits
        return h_dict['user']