pub_soft/dgl
3
0
Fork 0
mirror of https://github.com/dmlc/dgl.git synced 2026-06-04 19:44:23 +08:00
Code Issues Packages Projects Releases Wiki Activity

Improving the output for the Cluster GCN example. (#6079)

Browse Source
This commit is contained in:
Andrei Ivanov
2023-08-02 19:32:24 -07:00
committed by GitHub
parent 0383941375
commit ee6518113f
1 changed files with 9 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files

14
examples/pytorch/cluster_gcn/cluster_gcn.py
View File

@@ -59,7 +59,7 @@ dataloader = dgl.dataloading.DataLoader(
)
durations = []
for _ in range(10):
for epoch in range(10):
t0 = time.time()
model.train()
for it, sg in enumerate(dataloader):
@@ -80,9 +80,10 @@ for _ in range(10):
)
mem = torch.cuda.max_memory_allocated() / 1000000
print("Loss", loss.item(), "Acc", acc.item(), "GPU Mem", mem, "MB")
tt = time.time()
print(tt - t0)
durations.append(tt - t0)
tt = time.time() - t0
print("Run time for epoch# %d: %.2fs" % (epoch, tt))
durations.append(tt)
model.eval()
with torch.no_grad():
@@ -116,4 +117,7 @@ for _ in range(10):
)
print("Validation acc:", val_acc.item(), "Test acc:", test_acc.item())
print(np.mean(durations[4:]), np.std(durations[4:]))
print(
"Average run time for last %d epochs: %.2fs standard deviation: %.3f"
% ((epoch - 3), np.mean(durations[4:]), np.std(durations[4:]))
)