yeah, I think this is what I need!

we're using EC2

parents and children. maybe tags, maybe separate tab or section, idk. I wonder if anyone else is interested in this functionality, for us this is a very common case

tags are somewhat fine for this, I guess, but there will be too many of them eventually, and they do not reflect sequential nature of the experiments

nope, that's the point, quite often we run experiments separately, but they are related to each other. currently there's no way to see that one experiment is using checkpoint from the previous experiment since we need to manually insert S3 link as a hyperparameter. it would be useful to see these connections. maybe instead of grouping we could see which experiments are using artifacts of this experiment

sorry, my bad, after some manipulations I made it work. I have to manually change HTTP to HTTPS in config file for Web and Files (not API) server after initialization, but besides that it works

I'm not sure since names of these parameters do not match with boto3 names, and num_download_attempt is passed https://github.com/allegroai/clearml/blob/3d3a835435cc2f01ff19fe0a58a8d7db10fd2de2/clearml/storage/helper.py#L1439 as container.config.retries

okay, give me a sec

we do log a lot of the different metrics, maybe this can be part of the problem

Error
Failed to get Scalar Charts

nice, thanks for the info

oh wow, I didn't see delete_artifacts_and_models option

I guess we'll have to manually find old artifacts that are related to already deleted tasks

what if cleanup service is launched using ClearML-Agent Services container (part of the ClearML server)? adding clearml.conf to the home directory doesn't help

LOL
wow 😃
I was trying to find how to create a queue using CLI 😃

{
username: "username"
password: "password"
name: "John Doe"
},

will do, thanks

will do

1.3.0

dnk if it's relevant, but I also added a new user to apiserver.conf today

standalone-mode gives me "Could not freeze installed packages"

sorry that I keep bothering you, I love ClearML and try to promote it whenever I can, but this thing is a real pain in the ass 😃

I added the link just in case anyway 😃

also, is there any way to install a repo that we clone as a package. we often use absolute imports and do "pip install -e ." to utilize it
sorry there are so many questions, we just really want to migrate to trains-agent)

weird
this is what I got in installed packages without adding the direct link:
torch==1.6.0.dev20200430+cu101
torchvision==0.7.0.dev20200430+cu101

maybe I should use explicit reporting instead of Tensorboard

I use the following Base Docker image setting: my-docker-hub/my-repo:latest -v /data/project/data:/data

I assume, temporary fix is to switch to trains-server?

do you have any idea why cleanup task keeps failing then (it used to work before the update)

problem is solved. I had to replace /opt/trains/data/fileserver to /opt/clearml/data/fileserver in Agent configuration, and replace trains to clearml in Requirements

I'll get back to you with the logs when the problem occurs again

hmmm allegroai/trains:latest whatever it is