AgitatedDove14 , yes. i tried 3 times, and it always happen.

hi @<1576381444509405184:profile|ManiacalLizard2> thanks for the answer, i will try that!

remove this params will solve use_current_task=True,

Hi @<1523701087100473344:profile|SuccessfulKoala55> , Thanks for your response.

I'm not entirely sure about the use of CLEARML_ENV since I haven't interacted with it before. Could you guide me on what I should set as its value?

Previously, the system was running smoothly. However, I've run into some issues after making certain configuration changes to modify the server permissions. Specifically, I'm curious if these changes might have influenced the agent's permission to access certain...

Hi @<1523701070390366208:profile|CostlyOstrich36>
i mean we can do a form dropdown for others configuration like hyperparameters (task.connect)

oh okay, so i need to set that to path ssd, yeah?
is it this one? or there is

    docker_internal_mounts {
        sdk_cache: "/clearml_agent_cache"
        apt_cache: "path/to/ssd/apt-cache"
        ssh_folder: "/root/.ssh"
        pip_cache: "path/to/ssd/clearml-cache/pip"
        poetry_cache: "/mnt/hdd_2/clearml-cache/pypoetry"
        vcs_cache: "path/to/ssd/clearml-cache/vcs-cache"
        venv_build: "path/to/ssd/clearml-cache/venvs-builds"
        pip_download: "path/to/ssd/cle...

wow, okay, i think will move all logs/plot/artifacs to my storage s3. Thanks! really helpful!

Hi @<1523701070390366208:profile|CostlyOstrich36> , thanks for response, sorry for late replay,

this is my configuration in yaml, i facing difficulty when there is params in list. somehow, form to display bunch list not easy to see. do you have suggestion? Thanks!

download-data:
  dataset_train:
  - 

  - 

  - 

  dataset_test:
  - 

  - 

  - 

train:
  data:
    batch: 4
    input_size: 224
    split:
      t...

Hi CostlyOstrich36 ,
nope, i mean my server does not have pip/conda. so i will go for docker/container, is that possible if i install clearml-agent inside python:3.10 container?

it seems i forgot using clearml-agent init.
i follow this way: https://clear.ml/docs/latest/docs/guides/ide/google_colab/

Hi @<1523701205467926528:profile|AgitatedDove14> , Thanks for rresponse!
this my simple code to test scheduler

import datetime
from clearml.automation import TaskScheduler
  
def test_make():
    print('test running', datetime.datetime.now())

if __name__ == '__main__':
    task_scheduler = TaskScheduler(
        sync_frequency_minutes=30,
        force_create_task_name='controller_feedback',
        force_create_task_project='Automation/Controller',
    )

    print('\n[utc_timestamp]...

do you mean i can change?

files_server: 

 -> 

that so simple, thanks!

i see, it solved right now using default_output_uri, Thanks!
i need custom output_uri for some function because split dataset and model artifacs.

I see, yeah my alternative solution right now is just to show the list of options outside on ClearML UI.

i running this on 2.35 am, but the job not launching after 2.40 am

nope, still looking away to set AWS S3 secret_key without doing clearml-agent init

yup,
example just need choosing between SGD, Adam, AdamW on optimizer field

wow, so cool!
Thanks, really great tools!

alright, will try, i just worried about if execution mode is docker mode? should i mount to /var/run/docker.sock?

Thanks! i just prove it can run in next day, but not for the same day. i hope can run in same day too.

Syncing scheduler
Waiting for next run, sleeping for 5.13 minutes, until next sync.
Launching job: ScheduleJob(name='fetch feedback', base_task_id='', base_function=<function test_make at 0x7f91fd123d90>, queue=None, target_project='Automation/testing', single_instance=False, task_parameters={}, task_overrides={}, clone_task=True, _executed_instances=None, execution_limit_hours=None, r...

Hi @<1523701087100473344:profile|SuccessfulKoala55> ,
We have successfully created a sample for the migration. Here are the changes:

• URL for MongoDB from s3:// to azure://
• Elasticsearch as you suggested
  However, our main focus is that most of our production fetches models from ClearML, which are configured with s3:// URLs.

There is an issue/bug in the UI when downloading via Azure. Here are the details: None .

Thanks guys, i will try to learn that first. i will updates when executing these ideas. @<1523701087100473344:profile|SuccessfulKoala55> @<1590514584836378624:profile|AmiableSeaturtle81> 🙌

Thanks for response.

from clearml import Task
from clearml.automation import TaskScheduler
from datetime import timedelta, datetime

def my_task():
    task = Task.init(...)
    # do somthinge
    print("do something")
    # sleep 10
    condition = True
    if condition:
        # i want to trigger run another task by 
        # set some config in task, but execute tomorrow/sometime
        # not directly run at the time.
        # here i use
        task_id = task.id 
        task.cl...

hmm i want to make custom function that need credential registed on clearml.conf, like aws s3.
is clearml-agent have clearml.conf? where the path for that? i just test it, running using clearml-agent, but not found /root/clearml.conf

i see okay thanks

it seems if i access with my dns cannot see
and if access with ip address can see

clearml-agent, if you looking for clearml.conf, the place is '/root/default_clearml.conf'

i am using dictionary, more convinient for me and can categorize each params.
Thanks, hope that feature will ready soon!

clearml is awsome ❤ 🤩