[Graphbolt[ Add reverse edgs in link prediction example (#6751)

Co-authored-by: Ubuntu <ubuntu@ip-172-31-21-218.ap-northeast-1.compute.internal>

examples/sampling/graphbolt/link_prediction.py

@@ -43,6 +43,7 @@ main
 """
 import argparse
 import time
+from functools import partial
 
 import dgl.graphbolt as gb
 import dgl.nn as dglnn
@@ -191,7 +192,9 @@ def create_dataloader(args, graph, features, itemset, is_train=True):
     # the negative samples.
     ############################################################################
     if is_train and args.exclude_edges:
-        datapipe = datapipe.transform(gb.exclude_seed_edges)
+        datapipe = datapipe.transform(
+            partial(gb.exclude_seed_edges, include_reverse_edges=True)
+        )
 
     ############################################################################
     # [Input]:

examples/sampling/link_prediction.py

@@ -349,10 +349,10 @@ def train(
         use_uva=use_uva,
     )
     opt = torch.optim.Adam(model.parameters(), lr=args.lr)
-    start_epoch_time = time.time()
     for epoch in range(args.epochs):
         model.train()
         total_loss = 0
+        start_epoch_time = time.time()
         # A block is a graph consisting of two sets of nodes: the
         # source nodes and destination nodes. The source and destination
         # nodes can have multiple node types. All the edges connect from