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

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?

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", line 317, in _handle_program_exit
    self.wait_for_events()
  File "/home/richard/.virtualenvs/temp_clearml/lib/python3.10/site-packages/clearml/backend_interface/metrics/reporter.py", line 337, in wait_for_events
    return report_service.wait_for_events(timeout=timeout)
  File "/home/richard/.virtualenvs/temp_clearml/lib/python3.10/site-packages/clearml/backend_interface/metrics/reporter.py", line 129, in wait_for_events
    if self._empty_state_event.wait(timeout=1.0):
  File "/home/richard/.virtualenvs/temp_clearml/lib/python3.10/site-packages/clearml/utilities/process/mp.py", line 445, in wait
    return self._event.wait(timeout=timeout)
  File "/usr/lib/python3.10/multiprocessing/synchronize.py", line 349, in wait
    self._cond.wait(timeout)
  File "/usr/lib/python3.10/multiprocessing/synchronize.py", line 261, in wait
    return self._wait_semaphore.acquire(True, timeout)
KeyboardInterrupt: 

I'm not sure if it still reports logs. But it will continue running on the machine

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

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.fromarray(tensor)
        output = io.BytesIO()
        image.save(output, format='PNG')
        image_string = output.getvalue()
        output.close()
        return tf.Summary.Image(height=height,
                                width=width,
                                colorspace=channels,
                                encoded_image_string=image_string)

    def on_epoch_end(self, epoch, logs=None):
        if logs is None:
            logs = {}
        super(TensorBoardImage, self).on_epoch_end(epoch, logs)
        images = self.validation_data[0]  # 0 - data; 1 - labels
        img = (255 * images[0].reshape(28, 28)).astype('uint8')

        image = self.make_image(img)
        summary = tf.Summary(value=[tf.Summary.Value(tag='image', image=image)])
        self.writer.add_summary(summary, epoch)

So it seems like there is some bug in the how ClearML is logging tensorbaord images that causes everything to fail

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

No it completes and exists the script

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

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?

I found that setting store_uncommitted_code_diff: false instead of true seems to fix the 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

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 do have uncommitted code changes. I can try to check at some point if it would not have the problem without them. It seems like it could be repeated just by making a git repo with that script and adding a very large file. If I can repeat it is it best to open an issue in GitHub?

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

@<1719524641879363584:profile|ThankfulClams64> , are logs showing up without issue on the 'problematic' machine?

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.

Console output and also what you get on the ClearML task page under the console section

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

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

Is this just the console output while training?

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?)

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.

Hi @<1719524641879363584:profile|ThankfulClams64> , stopping all processes should do that, there is no programmatic way of doing that specifically. Did you try calling task.close() for all tasks you're using?

@<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?

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

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

The machine currently having the issue is on tensorboard==2.16.2

I will try with clearml==1.16.3rc2 and see if it still has the issue

Hi @<1719524641879363584:profile|ThankfulClams64> ,the logging is done by a separate process, I'm pretty sure it's not terminating all of the sudden. Did you manage to get a full log of such an experiment to share?