Root
├── data
│   └── {dataset*} // Dataset
│   │   ├── train.txt
│   │   ├── test.txt
│   │   └── valid.txt
├── output
│   ├── {dataset*} // Result training of each dataset
│   │   ├── WN18RR_cuda_gat_3599.pt ~ "{dataset}_{device}_{model-name}_{last-epoch}"
│   │   └── WN18RR_cuda_result.txt
├── config.json # Config for traning
└── *.py # Source code
└── README.md

"dataset": "WN18RR", # Dataset
"data_folder": "./data",
"output_folder": "./output",
"save_gdrive": false, # Use Google Drive to save object
"drive_folder": "/content/drive/My Drive",
"cuda": false, # Use GPU to training
"epochs_gat": 1,
"epochs_conv": 1,
"weight_decay_gat": 5e-06,
"weight_decay_conv": 1e-05,
"pretrained_emb": false,
"embedding_size": 50,
"lr": 0.001,
"get_2hop": true,
"use_2hop": true,
"partial_2hop": false,
"batch_size_gat": 86835,
"valid_invalid_ratio_gat": 2,
"drop_GAT": 0.3,
"alpha": 0.2,
"entity_out_dim": [100, 200],
"nheads_GAT": [2, 2],
"margin": 5,
"batch_size_conv": 128,
"alpha_conv": 0.2,
"valid_invalid_ratio_conv": 40,
"out_channels": 500,
"drop_conv": 0.0