[GraphBolt] Fix sparse example. (#7234)

Co-authored-by: Ubuntu <ubuntu@ip-172-31-0-133.us-west-2.compute.internal>

examples/sampling/graphbolt/sparse/graphsage.py

@@ -36,6 +36,7 @@ import torch.nn.functional as F
 import torchmetrics.functional as MF
 from dgl.graphbolt.subgraph_sampler import SubgraphSampler
 from torch.utils.data import functional_datapipe
+from tqdm import tqdm
 
 
 class SAGEConv(nn.Module):
@@ -113,7 +114,7 @@ class SparseNeighborSampler(SubgraphSampler):
                 fanout = torch.LongTensor([int(fanout)])
             self.fanouts.insert(0, fanout)
 
-    def sample_subgraphs(self, seeds):
+    def sample_subgraphs(self, seeds, seeds_timestamp=None):
         sampled_matrices = []
         src = seeds
 
@@ -152,7 +153,7 @@ def evaluate(model, dataloader, num_classes):
     model.eval()
     ys = []
     y_hats = []
-    for it, data in enumerate(dataloader):
+    for it, data in tqdm(enumerate(dataloader), "Evaluating"):
         with torch.no_grad():
             node_feature = data.node_features["feat"].float()
             blocks = data.sampled_subgraphs
@@ -194,7 +195,7 @@ def train(device, A, features, dataset, num_classes, model):
     for epoch in range(10):
         model.train()
         total_loss = 0
-        for it, data in enumerate(train_dataloader):
+        for it, data in tqdm(enumerate(train_dataloader), "Training"):
             node_feature = data.node_features["feat"].float()
             blocks = data.sampled_subgraphs
             y = data.labels