Regarding 2. Again - can a task id be changed after it was created?

We need the automagic... 🙂
This is one of the great benefits of using clearml 🙂

AgitatedDove14 Regarding the agent - No particular reason. Can you point me on how to do it?

Thanks for the quick reply,
I have a task I run, that have access to the git repo.
Then it initiate a run on aws, which I want it to use the same task-id.
I tried:
reuse_last_task_id=a_task_id_stringBut it write-over the execution tab in the gui

working:
http://10.156.91.102:8080/projects/a5f62c76468a4a4c8a6cd4d8e88203e1/experiments/86df109a78e94a21ae000bdd4e4cae97/info-output/debugImages?columns=selected&columns=type&columns=name&columns=tags&columns=status&columns=project.name&columns=users&columns=started&columns=last_update&columns=last_iteration&columns=parent.name&order=-last_update

I

I killed and restarted the task (it created a new task, with same name, but different id) - and now I can see images again

at some point the button of "Older Images" become grey

CostlyOstrich36
When I just started seeing this issue I could see images from previous iteration. Now some time passed and in the viewer I can't go back to the very first iterations.

Whenever I restart the task, I can see images for a while, then after few iteration, I can't anymore

tf.summary.image('binary preds', plt_c1, max_outputs=5, step=self.get_step(),
description="Left to right: inputs | sigmoid prediction | labels (blue label, white ignore)") `plt_c1 is a tf tensor .

As for 1-
They all start with the same name space - since TB then showing them in a nicer view.
with tf.name_scope("accumulated"): for metric in self.metrics: tf.summary.scalar(metric.name, metric.result(), step=step)I want to group them by metric.name, and they are all grouped by the name_scope

The project name is:
"semantics_net/training"

Can I see the clearml.conf in the server view?
I think I changed it in the right place, but I don't see it in the graph.

CostlyOstrich36 - I don't want to change the TB behavior.
How can I check what is the "title" I guess I have multiple "/" separating "tf.name_scope", "metric.name", and something like summary_name.
TB knows to put all graphs from the same scope in the same section, in that section it has a graph for each "metric.name", and in the graph it have a series for each summary_name.

I guess I can change the scope name to be the metric name, and abandon all the scoping. But it is very useful to me t...

CostlyOstrich36 It splits the data not in the way I intended.
It have the 4 metrics of train in the same graph,
and the 4 metrics of test in the same graph.

Regarding the scalar visualization - If you have other solution, it will be nice to try

AgitatedDove14 Thanks again.
I'm not using a clearml-agent as far as I know (I just run task.init(...) on the AWS machine.
Is there a way to connect to the task without initiating a new one without overriding the execution?

not working: http://10.156.91.102:8081/semantics_net%2Ftraining/db_lms_preds_as_inputtest.86df109a78e94a21ae000bdd4e4cae97/metrics/Images/binary%20preds/Images_binary%20preds_00000070.jpeg

ok CostlyOstrich36 , SuccessfulKoala55 :
The links differ in the very beginning -
semantics_net%252Ftrainingbecomes:
semantics_net%2FtrainingWhen I change it, I can see the image.

2. This could work.

SuccessfulKoala55 No logs from clearml in the console, anywhere else I can look?

Thanks 🙏

CostlyOstrich36 Page Not Found

CostlyOstrich36

My question was is can I see the ~/clearml.conf in the web view. If I run two experiments with different config, where can I see it? It is less important now, I didn't see any changes since it didn't get to the test phase yet.

Run them manually, but it is not that important

I'll take a look

CostlyOstrich36 , The issue does come back, after I kill, restart, and wait a few cycles.
Any luck to reproduce it?