With pleasure 🙂

HighOtter69 inside the legend click on the color rectangle next to the series name, you can change the color of the series on the graph. This property is stored so it will always remember your color preferences (yes even logging from another machine 🙂 )

SillyPuppy19 are you aborting the experiment or are you trying to protect crash? Is it like a callback functionality you are looking for?

Ohh yes, if you deleted the token then you have to recreate the cleaml.conf
BTW: no need to generate a token, it will last 🙂

Isn't that risky? not knowing you need a package ?
How do you actually install it on the remote machine with the agent ?

AstonishingWorm64 can you share the full log (In the UI under Results/Console there is a download button)?

MuddySquid7 you mean you are creating them with TB ? or are you uploading them as debug images ?
Specifically in the ClearML UI, do you have it under "plots" tab or "debug samples" tab ?

Correct 🙂

Hi RobustHippopotamus53
The way "latest from branch" works:
On the Task you specify the branch name (e.g. "master", no need to add the origin/ prefix) The agent then pulls the latest commit from that branch and updates back the Task to the current commit ID (the latest on the branch at the time of execution) This process ensures reproduciblity and traceability as we can always be certain the exact commit that was executed.Could it be the you "forced-push" a commit/squash, hence the "origina...

TBH ClearML doesn't seem to be picking the model up so I need to do it manually

This is odd, cleamrl will pick framework level serialization, but not just any pickle call

Why do I need an output_uri for the model saving? The dataset API can figure this out on its own

So that it knows where to upload it, if your are setting True this will be the default files server, you can also set iy for shared files system, S3 GCP storage etc.
If no value is passed, it will just log th...

Hi @<1570583227918192640:profile|FloppySwallow46>

Hey I have a question, Can you monitor the time for one pipeline,

you mean to see the start / end time of the pipeline?
Click on the details link on the right hand side and you will have all the details on the pipeline task, including running time

Hi @<1547028116780617728:profile|TimelyRabbit96>

Trying to do model inference on a video, so first step in

Preprocess

class is to extract frames.

Basically this depends on the RestAPI, usually would will be sending a link to data to be processed and returned Synchronously
What you should have a custom endpoint doing the extraction, send Raw data into another endpoint doing the model inference, basically think "pipeline" end points:
[None](https://github.com/allegro...

If you have idea on where to start looking for a quick win, I'm open to suggestions 🙂

No 😞

SillyPuppy19 I think this is a great idea, basically having the ability to have a callback function called before aborting/exiting the process.

Unfortunately today abort will give the process 2 seconds to gracefully quit and then it kills the process. It was not designed to just send an abort signal, as these will more often than not, will not actually terminate the process.

Any chance I can ask you to open a GitHub Issue and suggest the callback feature. I have a feeling a few more users ...

YummyWhale40 you mean like continue training?
https://github.com/allegroai/trains/issues/160

Hi BrightGoat74
So merging general purpose plotly plots is very hard (i.e. putting both on the same graph)
But if you report using logger.report_scatter(...) the UI will merge the ROC curves into the dame graph, wdyt?
https://clear.ml/docs/latest/docs/guides/reporting/scatter_hist_confusion_mat_reporting#2d-scatter-plots

why are there indefinitely growing anonymous tasks, even after i've closed the main schedulers.

The anonymous Tasks are The Dataset you are creating (a Dataset version is also a Task of a certain type with artifacts, the idea is usually Datasets are created from code, hence the need to combine the two).
Make sense ?

Many thanks!

Thanks LethalCentipede31 , i think (3) is the most stable solution (as it doesn't require to add another package, and should work on any python version / OS)
This is actually what we do for downloads .
DO you know if there is a minimum required python requests version ?

Hmm I guess doable 🙂 could you open a github issue with feature request ?
If we have enough support it will bump it in the priority 🤞

Hi @<1631826770770530304:profile|GracefulHamster67>
if you want your current task:

task = Task.current_task()

if you need the pipeline Task from the pipeline component

pipeline = Task.get_task(Task.current_task().parent)

where are you trying to get the pipelines from? I'm not sure I understand the use case?

Can you verify by adding the the following to your extra_docker_shell_script:
https://github.com/allegroai/clearml-agent/blob/a5a797ec5e5e3e90b115213c0411a516cab60e83/docs/clearml.conf#L152
extra_docker_shell_script: ["echo machine example.com > ~/.netrc", "echo login MY_USERNAME >> ~/.netrc", "echo password MY_PASSWORD >> ~/.netrc"]

Hi @<1539780284646428672:profile|PoisedElephant79>

it's giving me no module name clearml

I'm assuming no clearml inside one og the pipeline components ? make sure you have all the imports inside the pipeline component function, like in this example:
None

Hi @<1523711619815706624:profile|StrangePelican34>
Hmm, I think this is missing from the docs, let me ping the guys about that 🙏

Hmmm, what's your trains version ?

Did you experiment any drop of performances using forkserver?

No, seems to be working properly for me.

If yes, did you test the variant suggested in the pytorch issue? If yes, did it solve the speed issue?

I haven't tested it, that said it seems like a generic optimization of the DataLoader

Hi @<1661542579272945664:profile|SaltySpider22>

question 1: are parallel writes to a dataset with the same version possible?

When you are saying parallel what do you mean? from multiple machines ?

Whats the recommended way to append the dataset in a future version?

Once a dataset was finalized the only way to add files is to add another version that inherits from the previous one (i.e. the finalized version becomes the parent of the new version)
If you are worried about multip...

follow the backup procedure, it is basically the same process

JitteryCoyote63 the new wizard was pushed, you can check it out here:
https://github.com/allegroai/trains/blob/master/examples/services/aws-autoscaler/aws_autoscaler.py

BTW: next release to include it all is next week (hopefully :))