ui_embedding_size: 64           # (int) The embedding size of user and item.
neigh_embedding_size: 32        # (int) The embedding size of neighborhood information.
num_conv_kernel: 128            # (int) The number of kernels in convolution layer.
conv_kernel_size: 5             # (int) The size of kernel in convolution layer.
pool_kernel_size: 5             # (int) The size of kernel in pooling layer.
mlp_hidden_size: [128,64,32,16] # (list of int) The hidden size of each layer in MLP.
neigh_num: 20                   # (int) The number of neighbors we choose.
dropout: 0.5                    # (float) The dropout rate in MLP layers.

# The method to use neighborhood information, you can choose random, knn or louvain algorithm 
# e.g. neigh_info_method: "knn" or neigh_info_method: "louvain"
neigh_info_method: "random"

resolution: 1                   # (float) The parameter in louvain algorithm.