application: knowledge graph resource: gpus: [] cpu_per_gpu: auto dim: 1024 graph: file_name: build: optimizer: type: Adam lr: 5.0e-6 weight_decay: 0 num_partition: auto num_negative: 64 batch_size: 100000 episode_size: 1 train: model: RotatE num_epoch: 4000 margin: 9 sample_batch_size: 2000 adversarial_temperature: 2 log_frequency: 100 evaluate: task: link prediction file_name: filter_files: - - - # fast_mode: 3000 save: file_name: rotate_wn18.pkl