Console output and also what you get on the ClearML task page under the console section
Can you try with auto_connect_streams=True ? Also, what version of clearml sdk are you using?
Does any exit code appear? What is the status message and status reason in the 'INFO' section?
Do you also see the same in the terminal itself on the machine?
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
STATUS MESSAGE: N/A
STATUS REASON: Signal None
The same training works sometimes. But I'm not sure how to troubleshoot when it stops logging the metrics
I'm not sure how to even troubleshoot this.
Is there someway to kill all connections of a machine to the ClearML server this does seem to be related to restarting a task / running a new task quickly after a task fails or is aborted
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.
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
Not sure why that is related to saving images
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?)
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
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 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
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?
If you remove any reference of ClearML from the code on that machine, does it still hang?
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)
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.
Yes it shows on the UI and has the first epoch for some of the metrics but that's it. It has run like 50 epochs, it says it is still running but there are no updates to the scalars or debug samples
So even if you abort it on the start of the experiment it will keep running and reporting logs?
It seems similar to this None is it possible saving too many model weights causes metric logging thread to die?
Then we also connect two dictionaries for configs
task.connect(model_config)
task.connect(DataAugConfig)
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
Yea I am fine not having the console logging. My issues is the scalers and debug images occasionally don't record to ClearML
@<1719524641879363584:profile|ThankfulClams64> , can you provide a small code snippet that reproduces this behaviour? Can you also test with the latest version of clearml ?