def forward()

in src/sagemaker/FD_SL_DGL/gnn_fraud_detection_dgl/pytorch_model.py [0:0]

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

    def forward(self, g, features):
        # get embeddings for all node types. for user node type, use passed in user features
        h_dict = {ntype: emb for ntype, emb in self.embed.items()}
        # feat_para = torch.tensor(features)
        h_dict['target'] = features

        # pass through all layers
        for i, layer in enumerate(self.layers[:-1]):
            if i != 0:
                h_dict = {k: F.leaky_relu(h) for k, h in h_dict.items()}
            h_dict = layer(g, h_dict)

        # get user logits
        return self.layers[-1](h_dict['target'])