thanks!!

Awesome! I'll let you know if it works now

I'm plotting the confusion matrices the regular way, plot, then read figure from buffer to create the tensor, and save the tensor

oh wait, I was using clearml == 0.17.5 and I also had this issue

are you referring to extra_docker_shell_ scrip t SuccessfulKoala55 ?

I don't understand though..why doesn't this happen on my other experiments?

and would it be possible to run it using the normal local agent?

exactly 🙂

that worked, thanks!!

that worked, thanks!!

images?

So what changed?

We changed other bits of code, but not that one..
But maybe we are focusing on the wrong thing, the question now is why is ClearML only detecting these packages (running a different experiment than Diego)

Pillow == 8.0.1
clearml == 0.17.5
google_cloud_storage == 1.40.0
joblib == 0.17.0
numpy == 1.19.5
pandas == 1.3.1
seaborn == 0.11.0
tensorflow_gpu == 2.3.1
tqdm == 4.54.1

we are developing a model and I've built a webapp with Streamlit that let's you select the task, and you can see the confusion matrices, splits, data, and predictions on data train/val (all saved in the task), ...and also a model predict function in an image you upload

yes please 🙂

or I can make comparisons inside some projects but not others

I have 143 GB free in /

oh I meant now...so after the reboot everything goes back to "normal"..except that I can't make the comparisons

we'll create a minimal working example :-)

yes

it's also under Other

the thing is that this runs before you create the virtual environment, so then in the new environment those settings are no longer there

so what we should do is turn pip freeze on in the clearml.conf file?

thanks!

ok, so ClearML doesn't add all the imported packages needed to run the task to the Installed Packages, only the ones in the main script?

can I see an example please?

how can we debug this?

yes

Just want to know if it would be possible when you have your ClearML server inside your GCP environment, and you want to launch training jobs using Vertex AI. Would the training script be able to register to the server when there is no public IP?I guess it's more related to networking inside GCP, but just wanted to know if anyone tried it.

Ok, tried the following four things:
(fail = sklearn not listed in installed packages)
no _ init _.py file in the module_a folder, not a git repo: fail no _ init _.py file in module_a folder, git repo: fail with _ init _.py file in module_a folder, not git repo: fail with _ init _.py file in module_a folder, with git repo: OK!