AgitatedDove14 hm, I don’t know what is the right expected behaviour, I’ve expected 2 plots. If my assumption looks right, should I make an issue on github?

sure
print(APIClient().tasks.get_all(["95db561a08304a1faac3aabcb117412e"]))
{‘id’: ‘95db561a08304a1faac3aabcb117412e’, ‘name’: ‘task’}

upd: the status is changed to “Aborted”

the same result

task log
` task ca3ab0ce39aa436f9e656fff378a2c25 pulled from c39519fcfb3f4353808fd266d6100795 by worker v012-0:gpuGPU-0929fd0f-eff1-91f1-854e-9874599660c3
2022-12-12 16:32:21
Current configuration (clearml_agent v1.5.1, location: /tmp/.clearml_agent.guezjnez.cfg):

api.version = 1.5
api.verify_certificate = true
api.default_version = 1.5
api.http.max_req_size = 15728640
api.http.retries.total = 240
api.http.retries.connect = 240
api.http.retries.read = 240
api.http.retri...

@<1523701070390366208:profile|CostlyOstrich36> yes, WebApp: 1.12.1-397 • Server: 1.12.1-397 • API: 2.26.
Docker version 28.0.1, build 068a01e (updated to this version few weeks ago).

AgitatedDove14 for example let’s add to https://github.com/allegroai/clearml/blob/master/examples/frameworks/catboost/catboost_example.py second catboost model training:
` ...
catboost_model = CatBoostRegressor(iterations=iterations, verbose=False)
catboost_model2 = CatBoostRegressor(iterations=iterations+200, verbose=False)
...
catboost_model.fit(train_pool, eval_set=test_pool, verbose=True, plot=False, save_snapshot=True)
catboost_model2.fit(train_pool, eval_set=test_pool, verbose=True,...

AgitatedDove14 the best option would be custom charts in Web UI, like in wandb: https://docs.wandb.ai/ref/app/features/custom-charts
But pdf is acceptable too.

SuccessfulKoala55 yes, I have /usr/bin/python3.8, but it doesn’t help if I set it in agent.python_binary. python3.8 set as alternative #1 for python. but conda for some reason creating env with python3.6...

Executing Conda: /home/user/conda/bin/conda env remove -p /home/jovyan/.clearml/venvs-builds/3.6 --quiet --json

Hi AgitatedDove14 , I’m using clearml clearml-task to queue a task in a remote agent. The git remote URL is “ ssh://git@0.0.0.0:1234/path/to/repo.git ”, clearml https://github.com/allegroai/clearml/blob/aad01056b548660bb271c4f98447b715b8ba4c7d/clearml/backend_interface/task/repo/scriptinfo.py#L909 username from it (to cover cases like https://username@github.com/username/repository.git ), so the final URL is ssh://0.0.0.0:1234/path/to/repo.git , not ssh://git@0.0.0.0:1234/path/to/repo.g...

this is the case of developing AutoML: when I have a lot of datasets and the model should be nice at all datasets in average. So projects here are different versions of AutoML and I need to compare them

CostlyOstrich36 self hosted,
clearml ==1.6.4
clearml -agent==1.4.0rc0

` import numpy as np
import pandas as pd

from sklearn.metrics import roc_auc_score
from sklearn.model_selection import train_test_split

from lightautoml.tasks import Task
from lightautoml.automl.presets.tabular_presets import TabularAutoML

import clearml

cml_task = clearml.Task.get_task(clearml.config.get_remote_task_id())
logger = cml_task.get_logger()

data = pd.read_csv("./examples/data/sampled_app_train.csv")
....

automl = TabularAutoML(task=Task('binary'))
cml_task.connect(automl)
o...

docker will Not actually limit the “vioew of the memory” it will just kill the container if you pass the memory limit, this is a limitation of docker runtime

it will only if oom killer is enabled

what was the old version?

AgitatedDove14 we can read sys/fs/cgroup/memory/memory.limit_in_bytes to get the limit

https://faun.pub/understanding-docker-container-memory-limit-behavior-41add155236c

https://stackoverflow.com/questions/62227738/docker-run-memory-how-internal-applications-can-know-about-docker-memory-pr

no, other

/opt/clearml/logs/apiserver.log:

When I updated the URL of the remote repository in my git client

SuperiorPanda77 did you just replace “remote” for the client?

My remote in git client is ok:
ssh://git @<address>:5109<repo_path>.git
so I don’t understand why and where it changes :(