` # define pipeline
pipe = clearml.PipelineController(
name=TASK_NAME,
project=PROJECT_NAME,
version='0.0.1',
add_pipeline_tags=False,
)
pipe.set_default_execution_queue('default')

Adding steps

pipe.add_step(name=f'{start_date_train}_{end_date_train}_choose_best',
base_task_project=CHOOSE_PROJECT_NAME,
base_task_name=CHOOSE_TASK_NAME,
parameter_override=params_override,
...

I'll share some screenshots

AgitatedDove14 sorry for the late reply,

It's right after executing all the steps. So we have the following block which determines whether we run locally or remotely

if not arguments.enqueue: pipe.start_locally(run_pipeline_steps_locally=True) else: pipe.start(queue=arguments.enqueue)
And right after we have a method that calls Task.current_task() which returns None

😄

it works without any problem

🤞

Also being able to separate their configurations files would be good (maybe there is and I don't know?)

No I don't have trains anywhere in my code

FriendlySquid61

Just updating, I still haven't touched this.... I did not consider the time it would take me to set up the auto scaling, so I must attend other issues now, I hope to get back to this soon and make it work

that will require restarting the agent again?

btw my site packages is false - should it be true? You pasted that but I'm not sure what it should be, in the paste is false but you are asking about true

SuccessfulKoala55 this actually doesn't work

` apiserver_conf = ConfigFactory.parse_file(API_SERVER_CONF_PATH)

POINT 1

conf_content = HOCONConverter.to_hocon(config=ConfigFactory.from_dict(apiserver_conf.as_plain_ordered_dict()),
compact=False,
level=0, indent=2)

apiserver_conf['auth']['fixed_users']['users'].append(
ConfigFactory.from_dict({'username': username, 'password': password, 'name': name}))

##...

I see it's a plotly plot, even though I report a matplotlib one

Can I force it to output the static image?

Yes, I have the controller task in hand

This is what I meant should be documented - the permissions...

and I'll open an issue

you know what let me try in a sec

AgitatedDove14 I still can't get it to work... I couldn't figure out how can I change the clearml version in the runtime of the Cleanup Service as I'm not in control of the agent that executes it

AgitatedDove14 sorry for delayed reply - where do I read the version the Cleanup Service is using?

So just to be clear - the file server has nothing to do with the storage?

Will try this out and report

No absolutely not. Yes I do have a GOOGLE_APPLICATION_CREDENTIALS environment variable set, but nowhere do we save anything to GCS. The only usage is in the code which reads from BigQuery

AgitatedDove14 clearml version on the Cleanup Service is 0.17.0

so it is not defined

Thanks 🙂

this

I don't have ifconfig

I doubled checked the credentials in the configurations, and they have full EC2 access