Yes tensorboard. It is still logging the tensorboard scalers and images. It just doesn't log the console output

My bad, if you set auto_connect_streams to false, you basically disable the console logging... Please see the documentation:

auto_connect_streams (Union[bool, Mapping[str, bool]]) – Control the automatic logging of stdout and stderr.

That makes sense... If you turn auto_connect_streams to false this mean that auto reporting will be disabled as per the documentation.. If you turn it to True then logging should resume.

I'll update my clearml version. Unfortunately I do not have a small code snippet and it is not always repeatable. Is there some additional logging that can be turned on?

Yea I am fine not having the console logging. My issues is the scalers and debug images occasionally don't record to ClearML

There is clearly some connection to the ClearML server as it remains "running" the entire training session but there are no metrics or debug samples. And I see nothing in the logs to indicate there is an issue

I am using 1.15.0. Yes I can try with auto_connect_streams set to True I believe I will still have the issue

Do you also see the same in the terminal itself on the machine?

Okay I will do another run to capture the console output. We currently set auto_connect_streams to False to reduce the number of API calls. So there isn't really anything in the ClearML task page console section

Hi @<1719524641879363584:profile|ThankfulClams64> , does the experiment itself show on the ClearML UI?

The same training works sometimes. But I'm not sure how to troubleshoot when it stops logging the metrics

Can someone help with this?

@<1719524641879363584:profile|ThankfulClams64> , if you set auto_connect_streams to false nothing will be reported from your frameworks. With what frameworks are you working, tensorboard?

What happens if you're running the reporting example from the ClearML github repository?

When the script is hung at the end the experiment says failed in ClearML

If you remove any reference of ClearML from the code on that machine, does it still hang?

It was working for me. Anyway I modified the callback. Attached is the script that has the issue for me whenever I add random_image_logger to the callbacks It only logs some of the scalars for 1 epoch. It then is stuck and never recovers. When I remove random_image_logger the scalars are correctly logged. Again this only on 1 computer, other computers we have logging work perfectly fine

STATUS MESSAGE: N/A
STATUS REASON: Signal None

It is still getting stuck. I think the issue might have something to do with the iterations versus epochs. I notice that one of the scalars that gets logged early is logging the epoch while the remaining scalars seem to be iterations because the iteration value is 1355 instead of 26

I am still having this issue. An update is that the "abort" does not work. Even though the state is correctly tracked in ClearML when I try to abort the experiment through the UI it says it does it but the experiment remains running on the computer.

Just to make sure, did the logging to the clearml server work previously and stoped working at some point?

The console logging still works. Aborting the task was in the log but did not work and the process continued until I killed it.

Hi @<1719524641879363584:profile|ThankfulClams64>

I am using ClearML Pro and pretty regularly I will restart an experiment and nothing will get logged to ClearML.
I use ClearML with pytorch 1.7.1, pytorch-lightning 1.2.2 and Tensorboard auto
All ClearML has the latest stable updates. (clearml 1.7.4, clearml-agent 1.7.2)

Is this still happening with the latest clearml ( clearml==1.16.3rc2 ) ?
What is the TB version?
I remember a fix regrading lightining support
Also just making sure, are you using the default lightning TB logger ?
How are you initializing the Task.init (i.e. could you copy here the code?)

So I am only seeing values for the first epoch. It seems like it does not track all of them so maybe something is happening when it tries to log scalars.
I have seen it only log iterations but setting task.set_initial_iteration(0) seemed to fix that so it now seems to be logging the correct epoch
Tensorboard is correct and works. I have never seen an issue in the tensorboard logs

I created an issue: None

@<1719524641879363584:profile|ThankfulClams64> , can you provide a small code snippet that reproduces this behaviour? Can you also test with the latest version of clearml ?

Then we also connect two dictionaries for configs

    task.connect(model_config)
    task.connect(DataAugConfig)

I am on 1.16.2

    task = Task.init(project_name=model_config['ClearML']['project_name'],
                     task_name=model_config['ClearML']['task_name'],
                     continue_last_task=False,
                     auto_connect_streams=True)

This was on the same machine I am having issues with it logs scalars correctly using the example code, but when I add in that callback which just logs a random image to tensorboard I don't get any scalars logged

It is not always reproducible it seems like something that we do not understand happens then the machine consistently has this issue. We believe it has something to do with stopping and starting experiments