Add disabling checkpoint

During parallel training on different KGs simultaneously on an HPC cluster, checkpointing can result in models looking at different checkpoints of diferent KGs which results in inconsistency.

This commit is to avoid that inconsistency.

dicee/scripts/run.py

@@ -123,6 +123,7 @@ def get_default_arguments(description=None):
                         help="Stochastic weight averaging")
     parser.add_argument('--degree', type=int, default=0,
                         help='degree for polynomial embeddings')
+    parser.add_argument('--disable_checkpointing', action='store_false', help='Disable creation of checkpoints during training')
 
     if description is None:
         return parser.parse_args()

dicee/trainer/dice_trainer.py

@@ -75,7 +75,8 @@ def initialize_trainer(args, callbacks):
                           max_steps=kwargs.get("max_step", -1),
                           min_steps=kwargs.get("min_steps", None),
                           detect_anomaly=False,
-                          barebones=False)
+                          barebones=False,
+                          enable_checkpointing=kwargs['disable_checkpointing'])
     else:
         print('Initialize TorchTrainer CPU Trainer', end='\t')
         return TorchTrainer(args, callbacks=callbacks)