SuccessfulKoala55 seems like you got it spot on, it contains the entire repo, but no .git
directory
So what can we do about it? All I want is to create templates for some tasks, so I can later execute them through a Pipelinecontroller
I only have like 40 tasks including the example ones
:face_palm: 🤔 :man-tipping-hand:
So prior to doing any work on the trains autoscaler servcice, I should first create a auto scaling group in AWS?
How did it come to this? I didn't configure anything, I'm using the trains AMI, with the suggested instance type
this is the selection from the column setting menu
Wait but I don't want to execute it
What does that mean? How can I access this data?
logger.report_table(title="Inference Data", series="Inference Values", iteration=0, table_plot=inference_table)
Okay, so if my python script imports some other scripts I've written - I must use git?
I'm not, just want to be very precise an consice about them when I do ask... but bear with me, its coming 🙂
Makes sense
So I assume, trains assumes I have nvidia-docker installed on the agent machine?
Moreover, since I'm going to use Task.execute_remotely
(and not through the UI) is there any code way to specify the docker image to be used?
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
Very nice thanks, I'm going to try the SA server + agents setup this week, let's see how it goes ✌
Sorry.. I still don't get it - when I'm launching an agent with the --docker
flag or with the --services-mode
flag, what is the difference? Can I use both flags? what does it mean? 🤔
Yeah but I don't get what it is for - for now I have 2 agents, each listening to some queues. I actually ignore the "services" queue until now
I don't get the difference between how I'm using my agents now, just starting them on machines, and making them listen to queues, to using the "services" mode
or its the same palce in the config file for configuring the docker mode agent base image?
Oh I get it, that also makes sense with the docs directing this at inference jobs and avoiding GPU - because of the 1-N thing