Thanks! It looks like I can set

auto_connect_streams = False

in the task init at least to try.

We are using Keras so it is logging progress bars by default, which I think we could turn off. I just wouldn't expect logging text to require so many api calls. Especially since they charge by API calls I assumed it would be better managed.

Correct, so I get something like this

ClearML Task: created new task id=6ec57dcb007545aebc4ec51eb5b34c67
======> WARNING! Git diff too large to store (2536kb), skipping uncommitted changes <======
ClearML results page: 

but that is all

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

I'm not sure how to even troubleshoot this.

It seems similar to this None is it possible saving too many model weights causes metric logging thread to die?

Another thing I notice is that aborting the experiment does not work when this is happening. It just continues to run

Is this just the console output while training?

So I was able to repeat the same behavior on a machine running this example None

by adding the following callback

class TensorBoardImage(TensorBoard):
    @staticmethod
    def make_image(tensor):
        from PIL import Image
        import io
        tensor = np.stack((tensor, tensor, tensor), axis=2)
        height, width, channels = tensor.shape
        image = Image.from...

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

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

We are running the same code on multiple machines and it just randomly happens. Currently we are having the issue on 1 out of 4

Not sure if this is helpful but this is what I get when I cntrl-c out of the hung script

^C^CException ignored in atexit callback: <bound method Reporter._handle_program_exit of <clearml.backend_interface.metrics.reporter.Reporter object at 0x70fd8b7ff1c0>>
Event reporting sub-process lost, switching to thread based reporting
Traceback (most recent call last):
  File "/home/richard/.virtualenvs/temp_clearml/lib/python3.10/site-packages/clearml/backend_interface/metrics/reporter.py", lin...

Running clearml_example.py in None reproduces the issue

Yes it is logging to the console. The script does hang whenever it completes all the epochs when it is having the issue.

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

I just created a new virtual environment and the problem persists. There are only two dependencies clearml and tensorflow. @<1523701070390366208:profile|CostlyOstrich36> what logs are you referring to?

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

Yes I see it in the terminal on the machine

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

When I try to abort an experiment. I get this in the log

clearml.Task - WARNING - ### TASK STOPPED - USER ABORTED - STATUS CHANGED ###

but it does not stop anything it just continues to run

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

Not sure why that is related to saving images

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)

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

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

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

Hi we are currently having the issue. There is nothing in the console regarding ClearML besides

ClearML Task: created new task id=0174d5b9d7164f47bd10484fd268e3ff
======> WARNING! Git diff too large to store (3611kb), skipping uncommitted changes <======
ClearML results page: 

The console logs continue to come in put no scalers or debug images show up.

Do the metrics not get added from the training? I did not add any metadata data but I assumed you would be able to select metrics from the training that generated the model