Scalar plots are empty, log_scalar values only appear on experiment overview
- Plots of any
log_metricare empty, though the latest logged scalars do appear in the experiment overview table and the compare panel as single float values.
Setup:
- Windows 10
- Deepkit Release 2020.1.5
- Deepkit SDK 1.0.1
- Python 3.7.x (running local or remote)
@stocyr What do you mean with log_scalar? We don't have such a method. Can you please provide the source lines? Could you please also provide screenshots (of the experiment overview list vs experiment detail view)?
I updated the post above. Here's the snipped of the code:
import deepkit
def train(args, model, device, train_loader, optimizer, epoch):
# ...
for batch_idx, (data, target) in enumerate(train_loader):
data, target = data.to(device), target.to(device)
optimizer.zero_grad()
output = model(data)
loss = F.nll_loss(output, target)
loss.backward()
optimizer.step()
_, predicted = output.max(1)
total += target.size(0)
correct += predicted.eq(target).sum().item()
args.experiment.log_metric('loss/train', loss.item(), x=epoch + (batch_idx / len(train_loader)))
def main():
# ...
args = parser.parse_args()
experiment = deepkit.experiment()
args.experiment = experiment
# ...
for epoch in range(1, args.epochs + 1):
args.experiment.epoch(epoch, args.epochs)
train(args, model, device, train_loader, optimizer, epoch)
if __name__ == '__main__':
main()
The effect can be seen here on the running experiment (top most)



And here's what happens if I pull the "smoothing" slider a little:

update I recently noticed that the plots show up when the Deepkit App is connected to a remote-hosted Team Server (eg. a non-localhost account). So the bug only appears to happen on the localhost connected app.
That's interesting. Seems to be a windows issue. Can you open the devtools to see if there are any errors? STRG+SHIFT+I, then "console" tab.