gistfile1.txt

def forward(self, user_indices, item_indices, titles):
    user_embedding_mlp = self.embedding_user_mlp(user_indices)
    item_embedding_mlp = self.embedding_item_mlp(item_indices)
    user_embedding_mf = self.embedding_user_mf(user_indices)
    item_embedding_mf = self.embedding_item_mf(item_indices)

    #### mf part
    mf_vector =torch.mul(user_embedding_mf, item_embedding_mf)
    mf_vector = torch.nn.Dropout(self.config.dropout_rate_mf)(mf_vector)

    #### mlp part        
    mlp_vector = torch.cat([user_embedding_mlp, item_embedding_mlp], dim=-1)  # the concat latent vector

    for idx, _ in enumerate(range(len(self.fc_layers))):
        mlp_vector = self.fc_layers[idx](mlp_vector)
        mlp_vector = torch.nn.ReLU()(mlp_vector)
    mlp_vector = torch.nn.Dropout(self.config.dropout_rate_mlp)(mlp_vector)

    vector = torch.cat([mlp_vector, mf_vector], dim=-1)
    logits = self.logits(vector)
    output = self.sigmoid(logits)
    return output