def forward()

in source/sagemaker/sagemaker_graph_fraud_detection/dgl_fraud_detection/model/pytorch.py [0:0]

• 8 lines of code
• 6 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 = self.embed
        h_dict['user'] = 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[i], h_dict)

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