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8 × Eureka!Thanks - Is there plan to add more display manipulating functionality? Right now it's not really ideal for long texts
@<1576381444509405184:profile|ManiacalLizard2> Thanks for your reply.
Due to security considerations, not sure if I can provide the full log but attached is the error message.
Just use the pipeline ID, and make sure you push it into the services queue, voila
@<1523701205467926528:profile|AgitatedDove14> A somewhat related question - why is pushing into the services queue required as opposed to just pushing it into other queues? I have had experience where triggering a pipeline would not show up under the Pipelines tab in the web UI - it just shows up in Projects. Wondering if the queue matters for this.
I think I was able to find a fix by adding task.execute_remotely()
to the script and execute from VSCode once. From there, all cloned tasks were able to run successfully. Is this the expected behavior?
Hi @<1523701205467926528:profile|AgitatedDove14>
Thanks for responding. I see where you are getting to but it doesn't appear there's any task being created here. The task_stats_to_comment.py is being run on the GitHub runner hence it is able to access the Github_event environment variable.
What you mentioned seems like is the case for my particular setup where the step in Github Actions triggers a clearml task by using the clearml-task command and the execution is happening on the clearml...
@<1523701087100473344:profile|SuccessfulKoala55> I mean in the ClearML UI (under PLOTS), you can't change the column width of a table reported this way. I tried to adjust the width but all it does is drag the column around.
For new line, I just add line breaks "\n" to the cells and the reported table basically just ignores it.
Hi @<1523701087100473344:profile|SuccessfulKoala55> , yeah here's the relevant code:
df = pd.DataFrame.from_dict(results)
logger = task.get_logger()
logger.report_table(
table_plot = df,
series = f"URL: {args['URL']}, Dataset: {args['Dataset']}",
title = "Full Response"
)
Yeah, plus I already see it in the Github webpage.