well there is no default one.. and in the docs there is nothing about it. would be nice to add a minimal requirements for the AMI in the docs, instead of just writing "The AWS AMI to launch".
thanks for the answer :)

After running your suggestion (which worked), i'll be more accurate, the issue is with datasets and not tasks. try running this:

from clearml import Task, Dataset
import pandas as pd

task = Task.init(project_name='examples', task_name='Artifacts with data_')
ds = Dataset.create(dataset_project="examples", dataset_name="test", use_current_task=True)

df = pd.DataFrame(
    {
        'num_legs': [2, 4, 8, 0],
        'num_wings': [2, 0, 0, 0],
        'num_specimen_seen': [10, 2, 1, 8]
 ...

setting ignore_remote_overrides = True help solve the issue, but obviously we can't use it as a solution. what reasons might be that it would take so much time when trying to find params override in the backend? is it a network issue? maybe needs to change the machine network configuration?

great, thank you!

thanks!
by application you mean the web UI? is it possible to estimate the amount of calls it's performing when idle? while viewing an experiment? or some other typical usage?

@<1523701070390366208:profile|CostlyOstrich36> i just edited my question, can you refer to it pls.

I'm currently overcoming it by just adding a "_ " ("data_ something" -> "_data_something")

any idea what it might be? or how can i test it with them?

hi, thanks for the reply, i can access the web UI, I am using the Pro plan (clearm's host)

It seems that when the working directory is set to '.' (root of the cloned repo) I am able to import my package as expected.
I thought about your solution but then it requires me to push every time I change my package which is inconvenient.

It worked, thanks! i spent a few hours trying to figure it out 😅

we are using the community server (pro account). full configuration is attached.

here is an example of the logged values, I was hoping for a way to log them so they could be visualize better.. any advice (beside making my own plot and log it)?

we would love to get some clarifications as well, how does strings should be provided? what is the step size param in the uniform type? is it normal that all unused hyperparams in the HPO are displayed as str typein the UI?
thanks!

it seems like it does finds the requirments file otherwise why would it install tsfel tsfresh and some other "non-basic" packages?

installed packages before the task is running:

# Python 3.10.10 | packaged by Anaconda, Inc. | (main, Mar 21 2023, 18:39:17) [MSC v.1916 64 bit (AMD64)]

GitPython == 3.1.31
bokeh == 2.4.3
boto3 == 1.26.158
botocore == 1.29.158
clearml == 1.11.1
h5py == 3.8.0
holoviews == 1.16.0
joblib == 1.2.0
lightgbm == 3.3.5
mat73 == 0.60
matplotlib == 3.7.1
numpy == 1.23.5
pandas == 1.5.3
pytest == 7.3.1
scikit_learn == 1.3.0
scipy == 1.10.1
shapely == 2.0.1
sktime == 0.21.0
statsmodels == 0.13.5
t...

since it is specifying the pandas==1.5.3 i thought it might be pulling the req file from my main branch so i updated the req file there as well (since i am working on a different branch) and it didn't changedanything (as you might expect)

my repo structure is:
|----my_package
|----scripts
|----some_folder
|----some_folder
|----task_script.py
|----requirements.txt

from the consule logs i can see that:
entry_point = preprocessing.py
working_dir = Scripts/Volvo/volvo_data_alignment

so how can i make clearml to install my req file? i thought that it is automatically detects the req file in the cloned repository..

update:
--docker-args "-v some_dir:other_dir -v some_dir:other_dir" is the correct format

yes @<1523701087100473344:profile|SuccessfulKoala55> , i'm using the pro plan, "Hyperparameter Optimization" app

@<1523701070390366208:profile|CostlyOstrich36> thanks for the reply!

yes i'm using app.clear.ml
the vm is initialized via the clearml autoscalers, in the aws autoscaler i didn't have to do some network configurations there, thus i assume that it should be the same in the gcp VMs.

can you direct me to tests that should reveal lagging issues?

Thanks!

no, im clonning only from gitlab.
another issue i had regarding clonning git raised when i tried using clearml-agent daemon, it was unable to find my git user name (i used the --git-user and --git-pass args). how can one debug these issues, if possible at all from the user side?

yes the agent has already cloned the same repo in the first task (from the same account with the same user and token).
do you mean the full log of the machine itself? the full log of the failed task is attached already

censored aws credentials

conf file:

# ClearML SDK configuration file
api { 
    # Tomer Roditi's workspace
    web_server: 

    api_server: 

    files_server: 

    # corractions server
    credentials {"access_key": "****", "secret_key": "****"}
}
sdk {
    # ClearML - default SDK configuration

    storage {
        cache {
            # Defaults to system temp folder / cache
            default_base_dir: "~/.clearml/cache"
            # default_cache_manager_size: 100
  ...