Tnx!

Thanks a lot! I do not have problem executing the pipeline remotely, I have problam executing it locally.

I checked web ui, in execution section for pipeline there is repo_url, commit id... but in tasks's execution section repo_url filed is blank.

Didn't had that problem, sorry I can not help you. 😢

I solve problem by adding container argument

--network host 

I have GCP instance with official clearml image.

from clearml import StorageManager, Dataset

dataset = Dataset.create(
    dataset_project="Project", dataset_name="Dataset_name"
)

files = [
    'file.csv',
    'file1.csv',
]

for file in files:
    csv_file = StorageManager.get_local_copy(remote_url=file)
    dataset.add_files(path=csv_file)


# Upload dataset to ClearML server (customizable)
dataset.upload()
# commit dataset changes
dataset.finalize()

I am running clearml server on gcp, but I didn't exposed ports instead I ssh to machine and do port forwarding to localhost. The problem is localhost on my machine is not same as localhost inside docker on worker. If I check dataset, files are stored in localhost, but actually it is not localhost. Didn't fond the solution yet how to properly setup hostname for dataserver. Any ideas?

Thanks, I will check!

Hey, I had similar problem. Take a look here: None

As I understood, pipeline controller is a task, and it blocks queue. I solved problem by adding one more agent.

Found solution! None

@<1523701070390366208:profile|CostlyOstrich36> any idea? 🙂

Here is basic example:

from clearml import PipelineController

def step_function(param):
    print("Hello from function!")
    print("Param:", param)

if __name__ == '__main__':
    repo = '

'
    repo_branch = 'main'
    working_dir = 'pipelines'

    pipe = PipelineController(
        name='Test',
        project='Test',
        version='0.0.1',
        add_pipeline_tags=False,
        repo=repo,
        repo_branch=repo_branch,
        working_dir=working_dir
    )
    p...

Yes, there is one agent. As I said, I am able to execute task, but have problem with pipeline

Thanks for very fast replay!

One more question 🙂
How can I force clearML not to install requirements before running task? (already have everything installed on docker machine)

Ok, thanks for explanation. So pipeline controller is in Running state, while task 1 is in pending state. The solution will be to add one more agent?

It works! Thanks man, you save my day!!