can you check the agent’s logs? maybe we can find something there

I only want to save it as a template so I can later call it in a pipeline

running with task.execute_remotely() it wont really run the task. it will start it and abort it, so you will have it Aborted , and this is your template task

If you like, you can disable the auto magical for matplotlib and report manually.

For doing so, pass auto_connect_frameworks={"matplotlib": False} to Task.init .

Hi UnsightlySeagull42 ,

The clearml-agent use the credentials from your ~/clearml.conf file, if you changed those, you will need to re-run the clearml-agent.
Can you verify that your clearml-agent is running with the credentials of your https://app.community.clear.ml/dashboard ? if so, can you re-run it with config-file option?

clearml-agent --config-file <path to your clearml.conf file> daemon …

Can you try upgrade to the latest? pip install clearml-agent==0.17.2 ?

Hi GreasyPenguin14 ,

You can specify the configuration api section with environment variables, look at https://github.com/allegroai/trains-actions-get-stats for example (just change the TRAINS prefix to CLEARML, e.g. TRAINS_API_ACCESS_KEY -> CLEARML_API_ACCESS_KEY)

If this is the case (you have results and you want a new task to connect to each result), you can just clone the base task, update task parameters and enqueue it for execution (similar to https://github.com/allegroai/trains/blob/master/examples/automation/manual_random_param_search_example.py example), can this do the trick?

Hi PompousParrot44 ,

Do you use plt.imshow ? If you run this example, https://github.com/allegroai/trains/blob/master/examples/frameworks/matplotlib/matplotlib_example.py , do you get some outputs in the plots section?

https://clear.ml/docs/latest/docs/references/sdk/automation_controller_pipelinecontroller#pipelinedecoratorcomponent

which clearml version are you using? did you add it and re run it without clearml-agent?

Hi SoggyDog52

1. can you add, after the task has completed, some free text to write down my conclusion of this run?

What kind of information you like to add? You can add a tag to a task. If you like a free text, you can change the description part in the INFO tab. Can this do the trick?

2. I’m having troubles copying the config file from the UI. A simple copy past that’s all. When I try to mark the whole config with the courser it manege to catch just some part.

Do you have...

not much info 😕

Can you manually run the docker ?

Hi ColorfulRaven45 .

SSO is part of ClearML enterprise (view User Management & Permissions in https://clear.ml/pricing/ ), the enterprise version has full SSO integration. Also support permission, so you can control access and visibility inside the app.

With this scenario, your data should be updated when running the pipeline

Hey SarcasticSquirrel56 ,

are agents needed on the server installation?No, you can have it running on the same machine (there is no limitation about it), but you can run the clearml-agent in every machine and the clearml-server doesn’t need those.

how many agents are recommended?It depends on your needs. Each agent can run a single task each time, so if you have 2 agents running, you can have 2 tasks training in the same time, and N agents will give you N running tasks.

what best practice...

Hi LovelyHamster1 ,

Maybe this can help?

https://clearml.slack.com/archives/CTK20V944/p1627682444035400?thread_ts=1627680765.032600&cid=CTK20V944

You are definitely right! We will fix this issue, Thanks 🙂

If you want to get the pipeline task from a pipeline step, try Task.current_task().parent

Hi UnevenDolphin73 , what OS are you using? what is the clearml version?

Hi TrickySheep9 , is this model register in your clearml app?

PanickyMoth78 can I verify the setup with you?
python 3.8?
nvidia/cuda:11.2.2-runtime-ubuntu20.04 as image?

Hi GiganticTurtle0 ,

All the packages you are using should be under installed packages section in your task (in the UI). ClearML analyze and the full report should be under this section.

You can add any package you like with Task.add_requirements('tensorflow', '2.4.0') for tensorflow version 2.4.0 (or Task.add_requirements('tensorflow', '') for no limit).

If you dont want the package analyzer, you can configure in your ~/clearml.conf file: ` sdk.development.detect_with_...

Ohhh I thought you changed it from 10.2 to 10.1, my mistake.

What do you get for nvcc --version ?

👍

this is from the agent?

ImmensePenguin78 I think you can get it with the APIClient , you can add force to the call:
` from clearml import Task
from clearml.backend_api.session.client import APIClient

api_client = APIClient()
t = Task.init(project_name="Your project", task_name="Your task name")

t.close()
api_client.tasks.failed(t.id, force=True, status_reason="Your status reason", status_message="Your status message") `

You have to define it, but this can be done really quickly under the task, adding
task.set_base_docker(docker_image="your docker image", docker_arguments='-e CLEARML_AGENT_SKIP_PYTHON_ENV_INSTALL=1')for example, or you can also add it to the agent’s configuration if you want to set this always with agent.default_docker.arguments https://clear.ml/docs/latest/docs/configs/clearml_conf/#agentdefault_docker

about the error, do you have network manager running?

you can register the links only (no need to download and upload),
clearml-data add --linksfrom CLI, or add_external_files from code:

dataset.add_external_files(source_url=" ")

Hi DefeatedCrab47 ,

You can set the HP with a dict, like:

Task.current_task().set_user_properties( { "property_name": {"description": "This is a user property", "value": "property value"}, "another_property_name": {"description": "This is another user property", "value": "another value"}, "yet_another_property_name": "some value" } )or list of dicts, like:

` Task.current_task().set_user_properties(
[
{
"name": "prop...

you can just running with the env var at the beginning:

YOUR_ENV_VAR_NAME=/path/to/my/data clearml-agent …