😅

the worst part of debugging this is waiting for the docker to install tensorflow each time over and over again 😞

AgitatedDove14
So I couldn't kill the service agent myself (permission denied, I'm not sudo). What I did is I docker-compose down ed, commented out only the environment variable of GOOGLE_APPLICATION_CREDENTIALS from the clearml services agent service and upped the docker-compose again. I enqueued the Cleanup Service and now it works. Really weird, looks like the setting of GOOGLE_APPLICATION_CREDENTIALS causes an error when set even though I'm 100% is it not used for storag...

nvidia/cuda:10.1-base-ubuntu18.04

Yep, the warnings no longer appear

That was the issue then

🤞

🤔 is the "installed packages" part editable? good to know

Isn't it a bit risky manually changing a package version? what if it won't be compatible with the rest?

and the machine I have is 10.2.

I also tried nvidia/cuda:10.2-base-ubuntu18.04 which is the latest

Let's try

But I'm naive enough to believe that 10.2 is compatible with 10.1 as it is a minor upgrade

glad I managed to help back in some way

oops m ybad

Okay, I'll try that

🤞

I don't have ifconfig

the path to the JSON file

I'll try to put it again

Trains docs have at no point any mention on what should I do on the AWS interface... So I'm not sure at what point I should encounter this wizard

I'm going to play with it a bit and see if I can figure out how to make it work

Now I remind you that using the same credentials exactly, the auto scaler task could launch instances before

the ones in the export are like you said

yep

Will try this out and report

or its the same palce in the config file for configuring the docker mode agent base image?

Okay, looks interesting but actually there is no final task, this is the pipeline layout

Yep what 😄

Well done to you!

It works!

👍

👍