application: graph resource: gpus: [] cpu_per_gpu: auto dim: 128 graph: file_name: as_undirected: true build: optimizer: type: SGD lr: 0.025 weight_decay: 0.005 num_partition: auto num_negative: 1 batch_size: 100000 episode_size: 3500 train: # here the best setting uses no augmentation # in this case, DeepWalk is equal to LINE model: DeepWalk num_epoch: 2000 negative_weight: 5 augmentation_step: 1 random_walk_length: 40 random_walk_batch_size: 100 log_frequency: 1000 evaluate: task: node classification file_name: portions: [0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.08, 0.09, 0.10] times: 5 save: file_name: deepwalk_friendster-small.pkl