There is no need to add creds on the machine, since the EC2 instance has an attached IAM profile that grants access to s3. Boto3 is able retrieve the files from the s3 bucket

in clearml.conf:
agent.package_manager.system_site_packages = true agent.package_manager.pip_version = "==20.2.3"

still same errors 😕

Hey SuccessfulKoala55 , unfortunately this doesn’t work, because the dict contains others dicts, and only the first level dict becomes a dict, the inner dicts still are ProxyDictPostWrite and will make OmegaConf.create fail

with what I shared above, I now get:
docker: Error response from daemon: network 'host' not found.

Probably something's wrong with the instance, which AMI you used? the default one?

The default one is not existing/accessible anymore, I replaced it with the one that was shown in the NVIDIA Deep Learning AMI markplace page https://aws.amazon.com/marketplace/pp/B076K31M1S?qid=1610377938050&sr=0-1&ref_=srh_res_product_title that is: ami-04c0416d6bd8e4b1f

Ho I wasn't aware of that new implementation, was it introduced silently? I don't remember reading it in the release notes! To answer your question: no, for gcp I used the old version, but for azure I will use this one, maybe send a PR if code is clean 👍

So I guess the problem is that the following snippet:
from clearml import Task Task.init()Should be added before the if __name__ == "__main__": ?

Interestingly, I do see the 100gb volume in the aws console:

I'll try to pass these values using the env vars

The rest of the configuration is set with env variables

Alright, how can I then mount a volume of the disk?

Yes AgitatedDove14 🙂

Interesting - I can reproduce easily

AgitatedDove14 So what you are saying is that since I have trains-server 0.16.1, I should use trains>=0.16.1? And what about trains-agent? Only version 0.16 is released atm, this is the one I use

yes

mmmh good point actually, I didn’t think about it

Just caught another star 😄

because at some point it introduces too much overhead I guess

AgitatedDove14 This seems to be consistent even if I specify the absolute path to /home/user/trains.conf

Some more context: the second experiment finished and now, in the UI, in workers&queues tab, I see randomly
trains-agent-1 | - | - | - | ... (refresh page) trains-agent-1 | long-experiment | 12h | 72000 |

Hi SuccessfulKoala55 , yes indeed

Hi CostlyOstrich36 , most of the time I want to compare two experiments in the DEBUG SAMPLE, so if I click on one sample to enlarge it I cannot see the others. Also once I closed the panel, the iteration number is not updated

Thanks AgitatedDove14 !
What would be the exact content of NVIDIA_VISIBLE_DEVICES if I run the following command?
trains-agent daemon --gpus 0,1 --queue default &

yes, will do now!

After some investigation, I think it could come from the way you catch error when checking the creds in trains.conf: When I passed the aws creds using env vars, another error poped up: https://github.com/boto/botocore/issues/2187 , linked to boto3

They are, but this doesn’t work - I guess it’s because temp IAM accesses have an extra token, that should be passed as well, but there is no such option on the web UI, right?

from 10 to 11

` resource_configurations {
A100 {
instance_type = "p3.2xlarge"
is_spot = false
availability_zone = "us-east-1b"
ami_id = "ami-04c0416d6bd8e4b1f"
ebs_device_name = "/dev/xvda"
ebs_volume_size = 100
ebs_volume_type = "gp3"
}
}

queues {
aws_a100 = [["A100", 15]]
}

extra_trains_conf = """
agent.package_manager.system_site_packages = true
agent.package_manager.pip_version = "==20.2.3"
"""

extra_vm_bash_script = """

sudo apt-get install -y libsm6 libxext6 libx...

awesome, thank you 👍