config.yaml

# graph data config
edge_path: "./data/data_processed"
edge_files: "p2a:paper_author.txt,p2c:paper_conference.txt,p2t:paper_type.txt"
node_types_file: "node_types.txt"
num_nodes: 37791
symmetry: True

# skipgram pair data config 
win_size: 5
neg_num: 5
# average; m2v_plus
neg_sample_type: "average" 

# random walk config
# m2v; multi_m2v;
walk_mode: "m2v" 
meta_path: "c2p-p2a-a2p-p2c"
first_node_type: "c"
walk_len: 24
batch_size: 4
node_shuffle: True
node_files: null
num_sample_workers: 2

# model config
embed_dim: 64
is_sparse: True
# only use when num_nodes > 100,000,000, slower than noraml embedding
is_distributed: False 

# trainging config
epochs: 10
optimizer: "sgd"
lr: 0.1
warm_start_from_dir: null
walkpath_files: "None"
train_files: "None"
steps_per_save: 1000
save_path: "./checkpoints"
log_dir: "./logs"
CPU_NUM: 16