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103 × Eureka!Hi SmugDolphin23
Do you have a timeline for fixing this https://clearml.slack.com/archives/CTK20V944/p1661260956007059?thread_ts=1661256295.774349&cid=CTK20V944
upgrading to 1.12.1 didn't help
I think the issue is that when I create the dataset
- i used
use_current_task=True,
If I change it to
use_current_task=False,
then it finalizes
Hi AnxiousSeal95 ,
Is there an estimate when the above feature will be available?
Well it seems that we have similar https://github.com/allegroai/clearml-agent/issues/86
currently we are just creating a new worker and on a separate queue
CostlyOstrich36 - but we will use any method that will allow us to save the files as parquet.
We are not yet using clearml Dataset
- i'm not sure if this is a solution
AgitatedDove14 -
I also tried to https://github.com/allegroai/clearml-session
running the session
within docker but got the same error
clearml-session --docker
--git-credentials
(there is a typo in git - --git-credent ila s -> --git-credent ials)
and still got the same error
clearml_agent: ERROR: Can not run task without repository or literal script in
script.diff
Hi SweetBadger76 -
I'm I misunderstanding how this tests
worker runs?
Thx - it worked!
BTW - maybe it worth while to add this comment in the ClearML Agent daemon documentation - that when ever you update the clearml.conf
you need to
clearml-agent daemon --stop recreate all the daemonclearml-agent daemon ....
I'm checking the possibility of our firewall between the clearml-agent
machine and the local computer running the session
Hi AgitatedDove14
OK - the issue was the firewall rules that we had.
Now both of the jupyter lab
and vscode
servers are up.
But now there is an issue with the Setting up connection to remote session
After the
Environment setup completed successfully
Starting Task Execution:
ClearML results page:
There is a WARNING
clearml - WARNING - Could not retrieve remote configuration named 'SSH'...
using the helm charts
https://github.com/allegroai/clearml-helm-charts
Feeling that we are nearly there ....
One more question -
Is there a way to configure Clearml to store all the artifacts
and the Plots
etc. in a bucket instead of manually uploading/downloading the artifacts from within the client's code?
Specifying the output_uri
in Task.init
saves the the checkpoints, what about the rest of the outputs?
https://clear.ml/docs/latest/docs/faq#git-and-storage
ClearML key/secret provided to the agent
When is this provided? Is this during the build
?
Hi HugeArcticwolf77
I'v run the following code - which uploads the files with compression, although compression=None
ds.upload(show_progress=True, verbose=True, output_url='
', compression=None)
ds.finalize(verbose=True, auto_upload=True)
Any idea way?
In order to create a webdataset
we need to create tar files -
so we need to unzip and then recreate the tar file.
Additionally when the files are in GCS in the raw format you can easily review them with the preview (e.g. a wav file can be directly listened within the GCP console - web browser).
I think the main difference is that I can see a value of having access to the raw format within the cloud vendor and not only have it as an archive
Distributor ID: Ubuntu
Description: Ubuntu 20.04.4 LTS
Release: 20.04Codename: focal
google.storage { credentials = [ { bucket: "clearml-storage" project: "my-project" credentials_json: "/path/to/creds.json" }, ] }
No - just emulating - it is more of /home/... /creds.json
But this is not on the pods, isn't it? We're talking about the python code running from COLAB or locally...?
correct - but where is the clearml.conf
file?
Strange
I ranclearml-agent daemon --stop
and after 10 min I ranclearml-agent list
and I still see a worker
Looking in the repo I was not able to see an example - only reference to https://github.com/allegroai/clearml/blob/b9b0a506f35a414f6a9c2da7748f3ec3445b7d2d/docs/clearml.conf#L13 - I just need to add company.id
or user.id
in the credential dict?
Btw -after updating clearml.conf
do I need to restart the agent?
I can't see the additional tab under https://clearml.slack.com/archives/CTK20V944/p1658199530781499?thread_ts=1658166689.168039&cid=CTK20V944 , and I reran the task and got the same error
@<1523701205467926528:profile|AgitatedDove14> -
I'm getting the following error when running the following code within the mp_worker
command = ["ffmpeg","-i",f"{url}","-vcodec","libx264", "output.mp4"]
subprocess.run(command, stderr=subprocess.STDOUT)
TypeError: fork_exec() takes exactly 21 arguments (17 given)
Any suggestions?
not sure I understand
runningclearml-agent list
I get
`
workers:
- company:
id: d1bd92...1e52b
name: clearml
id: clearml-server-...wdh:0
ip: x.x.x.x
... `