I think the only way you can get it is from the task attribute:

ds = Dataset.get(dataset_id="your dataset id") ds_uri = ds._task.artifacts.get("data").url

Hi ImmensePenguin78 ,

The problem seemed to be having a path with // and clearml not handling it well

Do you mean in the output_uri parameter?

ThickDove42 you can get the version with

clearml-agent --version

Thanks for the information. do you get any errors? Warnings?

Hi ReassuredTiger98 , can you share your clearml version?

I’m using some old agent I fear, since our infra person decided to use chart 3.3.0

That could be the issue, can you update to the latest version so we can check if this is the issue?

I’ll try with the env var too. Do you personally recommend docker over the simple AMI + virtual environment?

Depends, with docker you know what youll get and you can control many, venv should be quicker and you can set it before

More complete log does not add much information -

Can you sen...

Hi StaleMole4 ,

Hag Sameach 🙂 I just tried with the latest version and didn’t get any issues, can you try with it?

You can get your task logger any time with get_logger() function, like in this example:
https://github.com/allegroai/clearml/blob/master/examples/reporting/text_reporting.py#L73

Hi FlatStarfish45 ,

In the UI you can view the packages that the task will use (under EXECUTION tab), what do you get? Does it contains your packages in the INSTALLED PACKAGES section?

You changed the version from 10.2 to 10.1 and nvidia-smi output is the same? did you do a restart after the change?

The training task (child)

this is the task the HPO is cloning?
Do you have the packages in this task?

try pip install clearml==0.17.6rc1

Hi ElegantDeer55 ,

Are you referring to https://github.com/allegroai/trains-pycharm-plugin ? If so, it should sync you .git folder to the remote machine so the task will log the git.

Basically I am confused if “remote debugging” should work / kick in automatically when running in docker mode and starting a task like this:

 from trains import Task
task = Task.init(project_name=“my project”, task_name=“my task”)
task.execute_remotely()

When you are running this code from you P...

Hi NuttyOctopus69 ,

I’m getting the same, suspect its some pypi server issues (from https://status.python.org/ ).
You can install it the latest version from GitHub with
pip install git+

Can you share the exception for --gpus "0,1" ?

and again - feature request - add free text there.

LethalCentipede31 can you add a new https://github.com/allegroai/clearml/issues issue with this request? Just so it won’t get lost

yep

GiganticBat57 if you are running this code, do you get the output?
` import numpy as np
import matplotlib.pyplot as plt

from clearml import Task

task = Task.init(project_name='tests', task_name='test matplotlib')
logger = task.get_logger()

N = 50
x = np.random.rand(N)
y = np.random.rand(N)
colors = np.random.rand(N)
area = (30 * np.random.rand(N))**2 # 0 to 15 point radii
plt.scatter(x, y, s=area, c=colors, alpha=0.5)

Plot will be reported automatically

logger.report_matplotlib_figure(...

Hi ImmensePenguin78 , can you ping the server?

SubstantialElk6 you can try:

dataset_upload_task = Dataset.get(dataset_id=dataset_task) path_with_data = dataset_upload_task.get_local_copy()

Hi FlatStarfish45 ,

The HPO task will control the HPO process, means it will clone the base task (the one we are optimizing), change the parameters, enqueue it and collect the results.
The base task is the task we want to optimize.
Each one of those two tasks, have different requirements.
You can look at the https://clear.ml/docs/latest/docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt#set-up-the-arguments for how set the base task in the HPO task.
can this be ...

HelpfulHare30 try using CLEARML_AGENT_SKIP_PIP_VENV_INSTALL env var with the path you your python env:
CLEARML_AGENT_SKIP_PIP_VENV_INSTALL=/path/to/your/python

Hi TrickySheep9 ,

The Task.init call will detect your repository as part of the automagic. You can disable it with
auto_connect_frameworks={'detect_repository': False}but I dont think this is the case.

Maybe clearml-task ? You can https://clear.ml/docs/latest/docs/guides/clearml-task/clearml_task_tutorial

Hi TrickySheep9 , can you copy the docker run command? do you docker install and running on the machine running the agent?

Hi GhastlySquirrel83 ,

You can specify the repository ( repo=None, repo_branch=None, repo_commit=None parameters) in the add_function_step for connecting the specific repo into the step, you can view all the options with some examples here - https://clear.ml/docs/latest/docs/references/sdk/automation_controller_pipelinecontroller#add_function_step

Sure, all the auto magic can be configured too - https://clear.ml/docs/latest/docs/faq#experiments , search for Can I control what ClearML automatically logs? to view all the options 🙂

The running task in the UI for it

can you try with clearml 1.0.4 ?

can you try upgrade? I run it with trains==0.16.2rc0

Hey PanickyMoth78 ,

my_pipeline is wrapped with @PipelineDecorator.pipeline ? some other decorator?