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

btw, I tried with alpine instead of ubuntu:18.04, got :

Unable to find image 'alpine:latest' locally
latest: Pulling from library/alpine
df20fa9351a1: Pulling fs layer
df20fa9351a1: Verifying Checksum
df20fa9351a1: Download complete
df20fa9351a1: Pull complete
Digest: sha256:185518070891758909c9f839cf4ca393ee977ac378609f700f60a771a2dfe321
Status: Downloaded newer image for alpine:latest
docker: Error response from daemon: OCI runtime create failed: container_linux.go:349: starting containe...

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 |

Nope, I’d like to wait and see how the different tools improve over this year before picking THE one 😄

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 👍

Sorry, its actually
task.update_requirements(["."]) 

AgitatedDove14 So I’ll just replace task = clearml.Task.get_task(clearml.config.get_remote_task_id()) with Task.init() and wait for your fix 🙂

(Just to know if I should wait a bit or go with the first solution)

Ok so it seems that the single quote is the reason, using double quotes works

edited the aws_auto_scaler.py, actually I think it’s just a typo, I just need to double the brackets

AppetizingMouse58 the events_plot.json template misses the plot_len declaration, could you please give me the definition of this field? (reindexing with dynamic: strict fails with: "mapping set to strict, dynamic introduction of [plot_len] within [_doc] is not allowed )

Ho I see, I think we are now touching a very important point:
I thought that torch wheels already included cuda/cudnn libraries, so you don't need to care about the system cuda/cudnn version because eventually only the cuda/cudnn libraries extracted from the torch wheels were used. Is this correct? If not, then does that mean that one should use conda to install the correct cuda/cudnn cudatoolkit?

and just run the same code I run production

Sorry, I was actually able to fix it (using 1.1.3) not sure what was the problem 😄

Awesome, thanks WackyRabbit7 , AgitatedDove14 !

Yes that’s what I did initially, but eventually I decided that it’s too much complexity added for nothing really, I’d rather drop omegaconf and if one day clearml supports it out of the box take advantage of it