Now I remind you that using the same credentials exactly, the auto scaler task could launch instances before
I think you are talking about separate problems - the "WARNING DIFF IS TOO LARGE" is only a UI issue, that you can't see hte diff in the UI - correct me if I'm wrong with this
Maria seems to be saying that the execution FAILS when she has uncomitted changes, which is not the expected behavior - am I right maria?
moreover, in each pipeline I have 10 different settings of task A -> Task b (and then task C), each run 1-2 fails randomly
and when looking at the running task, I still see the credentials
but I can't seem to run docker-compose down
This error just keeps coming back... I already made the watermarks like 0.5gb
So regarding 1, I'm not really sure what is the difference
When running in docker mode what is different the the regular mode? No where in the instructions is nvidia docker a prerequisite, so how exacly will tasks on GPU get executed?
I feel I don't underatand enough of the mechanism to (1) understand the difference between docker mode and not and (2) what is the use casr for each
when spinning up the ami i just went for trains recommended settings
And once this is done, what is the file server IP good for? will it redirect to the bucket?
How do I get from the node to the task object?
Version 1.1.1
Snippet of which part exactly?
Yeah, logs saying "file not found", here is an example
Any news on this? This is kind of creepy, it's something so basic that I can't trust my prediction pipeline because sometimes it fails randomly with no reason
Couldn't find any logic on which tasks fail and why... all the lines are exactly the same, only different parameters
When you are inside a project, the search bar searches for experiments
so if you want to search inside a specific project, go to that project and use the search bar, if you want to search all over, go to the project called "All Experiments" and search there
The weirdest thing, is that the execution is "completed" but it actually failed
even though I apply append