An example for something like spacy would be useful for the community.

That awesome, any chance you can PR something? (no need for it to be perfect, we can take it from there)

Follow up: I see that if I move an Experiment to a new project, it does not copy the associated model files and must be done manually. Once I moved the models to the new project, the query works as expected.

Correct 🙂
Nice catch!

GiddyTurkey39 Just making sure, you ran ping IP not ping ip:port right ?

PlainSquid19 I will also look into it as well.
maybe for some reason model.keras_model.save_weights is not caught ...

Hi EnthusiasticCoyote38

Does clearml-agent has option

Fully supported 🙂
Should work out of the box, it will always clone with --recursive and will bring all submodules

p.s. you should remove this line 🙂
extra_index_url: ["git@github.com:salimmj/xxxx"]

And it is not working ? what's the Working Dir you have under the Execution Tab ?

BTW: do notice to install the agent on the system python packages and Not on any venv.

MysteriousBee56 when you run the trains-agent with --foreground , before it starts the docker it print the full command line, could you send it please?
I can't figure out where the extra ' came from...
Also could you send the trains.conf file?
(feel free to redact and confidential information)

ClumsyElephant70
Can you manually run the same command ?
['python3.6', '-m', 'virtualenv', '/home/user/.clearml/venvs-builds/3.6']Basically:
python3.6 -m virtualenv /home/user/.clearml/venvs-builds/3.6'

Regrading resetting it via code, if you need I can write a few lines for you to do that , although that might be a bit hacky.
Maybe we should just add a flag saying, use requirements.txt ?
What do you think?

Is there a way to move existing pipelines between projects?

You should be able to, go to your settings page and turn on "show hidden folders"
Then go to your project, you should see " .pipeline " sub project there, right click it and move it to another folder.

YEY 🙂

Hi CurvedDolphin95
I would first check the free space on the instance (it might be that git is reporting an inaccurate error and it's free space not permission that causing it to fail the clone).
I would also check your GitHub account, notice that the now only support user/api-key (and not user/pass), which means you need to create an api-key and add it as your password in the clearml.conf.
Any chance that for some reason some of the Tasks are running from a diff user? or not using a docker ?

Hi SkinnyPanda43
Yes, I think you are right the documentation might be missing it. I'll make sure they know it 🙂
In the meantime :
task.update_output_model
https://github.com/allegroai/clearml/blob/d3929033c016476c580557639ff44f900e65904a/clearml/backend_interface/task/task.py#L734

JitteryCoyote63 I think this only holds for the conda distribution.
(Actually quite interesting, I wonder what happens if you already installed cudatoolkit...)

Thanks @<1630377234361487360:profile|RoughSeaturtle43>

server certificate verification failed. CAfile: none CRLfile: none

Oh I see this is an https issue inside the container, you need to mount your self signed certificate
add something like that to your agent.conf:

extra_docker_arguments: ["-v", "/path/to/cert.pem:/etc/ssl/certs/myca.pem"]

None

Hmm how do you launch the autoscaler, code?

(2) yes weekdays with specific hour should do exactly that:)
(3) yes I see your point, maybe we should add boolean allowing you to run immediately?
Back to (1) , let me see if I can reproduce, anything specific I need to add to the schedule call?

So as you say, it seems hydra kills these

Hmm let me check in the code, maybe we can somehow hook into it

Hi AttractiveCockroach17
when exactly are you seeing this error ?

Thanks StaleKangaroo85 bug is verified. Let me check to see where exactly is the bug.

Two points
Notice that x_labels should be the size of the histogram It seems that you have to pass the labels as well (otherwise you get the trace-0), so if you add labels=['random histogram'] and labels=['random histogram2'] , you'll get the correct legend.Anyhow I'll make sure we also fix it in code so it is automatically labels are [series] if not specified, thanks!

No worries, condatoolkit is not part of it. "trains-agent" will create a new clean venv for every experiment, and by default it will not inherit the system packages.
So basically I think you are "stuck" with the cuda drivers you have on the system

Now I suspect what happened is it stayed on another node, and your k8s never took care of that

And if this is the case, that would explain the empty elastic as well

You can however change the prefix, and you can always have access to these links.
Any reason for controlling the exact output destination ?
(BTW: You can manually upload via StorageManager, and then register the uploaded link)

yea the api server configuration also went away

okay that proves it

JumpyPig73 Do you see all the configurations under the Args section in the "Configuration" Tab ?
(Maybe I'm wrong and the latest RC does Not include the python-fire support)

Is this example working for you?
https://github.com/allegroai/clearml/blob/master/examples/reporting/model_config.py

python package