SubstantialElk6 you are right, only agent running docker mode will do it, you are running venv mode.
The clearml-agent will try to build a specific virtual environment for your task, with virtualenv . You can just install it in the environment the clearml-agent is running from (python3.6?) with python3.6 -m pip install virtualenv and it should work 🙂

yep

Hi SubstantialElk6 ,

Which clearml version did you use? and which python version?
Can you write a small how to reproduce this issue?

Hi StaleMole4 ,

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

can you try with clearml 1.0.4 ?

yep, you need it to be part of the environment

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

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(...

Can you try with the latest? pip install clearml==1.0.4 ?

resources configuration, so you have subnet ID and the security group ID and it failed with it?

thanks SmugTurtle78 , checking it

'CLEARML_DOCKER_IMAGE=' can you try running with an image ? the command now is the same as you will do docker run ... without any image

Hi RattySeagull0 ,

Can you try quote the gpus numbers? like --gpus "0,1" ?
looks the same issue as https://github.com/allegroai/trains-agent/issues/35

Hi SubstantialElk6 , can you update your ClearML agent to the latest ( 0.17.2rc4 )?
pip install clearml-agent== 0.17.2rc4 and try with it?

not sure about the Other , but maybe adding some metadata to the artifact can do the trick?

You can get all the artifacts with task.artifacts and you can go over it and filter with the metadata, wdyt?

Hi SmugTurtle78 , can you share you configuration? (without the secrets)

• are you working vpc? did you try configure only one of the params?

yes, this fix almost done testing and will be part of the next release, will keep you updated about it

you need to run it, but not actually execute it. You can execute it on the ClearML agent with task.execute_remotely(queue_name='YOUR QUEUE NAME', exit_process=True) .

with this, the task wont actually run from your local machine but just register in the ClearML app and will run with the ClearML agent listening to 'YOUR QUEUE NAME' .

Hi CooperativeSealion8 ,

Sure, we will check that and reactivate soon

Hi SmallDeer34 👋

The dataset task will download all the dataset when using clearml-data task, you have both in the same one?

Hi TenseOstrich47 , the StorageManager does use boto3 for those upload (so if its not supported by boto3, same for StorageManager :/ )
Maybe you can use the 'wait_for_upload' and delete the local file after?

Hi WackyRabbit7 ,

Did you try using sdk.development.detect_with_pip_freeze as true in your ~/clearml.conf file? It should take the same environment as the one you are running from.

I can help you with that 🙂

task.set_base_docker("dockerrepo/mydocker:custom --env GIT_SSL_NO_VERIFY=true")

Checking that

In the AWS autoscaler wizard, you need to enter your credentials to AWS. The wizard will use those so it should have the same permissions

Hi NarrowLobster19 , Is this S3 bucket?

So according to it, you are using the repo requirements, and you have torch there?

Why not using it directly from S3?

You can https://allegro.ai/clearml/docs/docs/examples/examples_storagehelper.html#downloading-a-file it with the storageManager

basically it run pip freeze in your execution env and create the requirements according to it, without any analysis

In the task you cloned, do you have torch as part of the requirements?