I am using pip as a package manager, but i start the trains-agent inside a conda env 😄

So it looks like the agent, from time to time thinks it is not running an experiment

When an experiment on trains-agent-1 is finished, I see randomly no experiment/long experiment and when two experiments are running, I see randomly one of the two experiments

by mistake I have two agents started in one machine

the latest version, but I think its normal: I set the TRAINS_WORKER_ID = "trains-agent":$DYNAMIC_INSTANCE_ID, where DYNAMIC_INSTANCE_ID is the ID of the machine

yes SparklingHedgehong28 🙂

Hi @<1523701205467926528:profile|AgitatedDove14> @<1537605940121964544:profile|EnthusiasticShrimp49> , the issue above seemed to be the memory leak and it looks like there is no problem from clearml side.
I trained successfully without mem leak with num_workers=0 and I am now testing with num_workers=8.
Sorry for the false positive :man-bowing:

I think that somehow somewhere a reference to the figure is still living, so plt.close("all") and gc cannot free the figure and it ends up accumulating. I don't know where yet

Is it exactly agg or something different?

Early debugging signals show that auto_connect_frameworks={'matplotlib': False, 'joblib': False} seem to have a positive impact - it is running now, I will confirm in a bit

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

I am happy if I can be of any help to fix that 😄

AgitatedDove14 SuccessfulKoala55 I just saw that clearml-server 1.4.0 was released, congrats 🚀 🙌 Was this bug fixed with this new version?

clearml doesn't change the matplotlib backend under the hood, right? Just making sure 😄

There was no possible cache, the agent was running on a new ec2 instance

SuccessfulKoala55 I can try to make one, let’s see 🙂

Does that mean that agents do not read this parameter?

What will this parameter do?

Hi CostlyOstrich36 , this weekend I took a look at the diffs with the previous version ( https://github.com/allegroai/clearml-server/compare/1.1.1...1.2.0# ) and I saw several changes related to the scrolling/logging:
apiserver/bll/event/ http://log_events_iterator.py apiserver/bll/event/ http://events_iterator.py apiserver/config/default/services/_mongo.conf apiserver/database/model/ http://base.py apiserver/services/ http://events.pyI suspect that one of these changes might be responsible ...

using trains RC, trains-agent 0.15.0

so the task they execute must have clearml installed?

Disclaimer: I didn't check this will reproduce the bug, but that's all the components that should reproduce it: a for loop creating figures and clearml logging them

Yes, I would like to update all references to the old bucket unfortunately… I think I’ll simply delete the old s3 bucket, wait or his name to be available again and recreate it where on the other aws account and move the data there. This way I don’t have to mess with clearml data - I am afraid to do something wrong and loose data

For me it is definitely reproducible 😄 But the codebase is quite large, I cannot share. The gist is the following:

import matplotlib.pyplot as plt
import numpy as np
from clearml import Task
from tqdm import tqdm

task = Task.init("Debug memory leak", "reproduce")

def plot_data():
    fig, ax = plt.subplots(1, 1)
    t = np.arange(0., 5., 0.2)
    ax.plot(t, t, 'r--', t, t**2, 'bs', t, t**3, 'g^')
    return fig

for i in tqdm(range(1000), total=1000):
    fig = plot_data()
  ...

Default would be venv, only use docker if an image is passed. Use case: not have to duplicate all queues to accept both docker and venv agents on the same instances

Hi SuccessfulKoala55 , will I be able to update all references to the old s3 bucket using this command?

` 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...

Alright, I will try with that one

Thanks for your answer! I am in the process of adding subnet_id/security_groups_id/key_name to the config to be able to ssh in the machine, will keep you informed 😄

If I remove security_group_ids and just let subnet_id in the configuration, it is not taken into account (the instances are created in a the default subnet)