
Reputation
Badges 1
38 × Eureka!GrumpyPenguin23 Hi, thanks for your instruction!
Putting some metadata into the model sounds nice.
I was exactly wondering how to take care of labels and being afraid of handling them as a dataset even when inferring.
Relating to it but another question.
With that task, which is running under an agent, task.connect_label_enumeration
does not look working.
Even though I called task.connect_label_enumeration
, there is no data to show on the output model.
I tried clearml.model.InputModel
and successfully downloaded a model.
Is this an expected way to consume a trained model for inference?
For the agent run, I posted only the following params:
name project script typeto tasks.create
endpoint and let an agent to pick it.
now I am going AFK.
Thanks for your support!
I confirmed that worked if it is not started by an agent.
Um..
and if you clone the local task run and enqueue it to the agent?
It failed.
Saying: Could not read from remote repository.
We have a web server which accepts various requests and manages database resources.
This web server arranges the request and creates a task on the clearml api server, which is running an internal network.
Are you talking about the public demo server?
If so, it says:This server is reset daily at 24:00 PST.
No, I have checked it on the web frontend, following the model link and the LABELS tab.
As for the versionsroot@120eb0cddb60:~# pip list | grep clearml clearml 0.17.5 clearml-agent 0.17.1
Maybe I should have clone the repo with https instead of ssh.
The labels are attached for that clone task output model.
Hm, clearml-data looks very much like git.
Is there any example of how to use clearml-data
?
I mean, the output model comes with the labels which is posted.
Is it handling data just in a form of regular files?
Does this task
(started by an agent) have some limitation?
Like being disabled to connect labels?
I will set repository url as https and retry.
By the way, we found that when I added labels param and post a tasks.create
request, it worked.
BTW why using the api calls and not clearml sdk?
Because the training part is only the sub system of our whole system.
And the python stuff is not facing to the web, where training request is coming.