Hi everybody! I'm running an example pipeline from a web UI. I notice very strange behavior. After the first local run, I can create a NEW RUN and pass initialization parameters there, but after a successful run, I lose the ability to create new runs with passing new parameters there.
As far as I understand, when I first start the server, the clearml can read the configuration parameters, but after the remote launch, it apparently loses this ability. Is there a possibility that the feedback from the server is broken during the remote start, or something should be corrected in the configuration file.
from clearml import PipelineDecorator
def step(size: int):
import numpy as np
def pipeline_logic(do_stuff: bool):
if __name__ == '__main__':
# run the pipeline on the current machine, for local debugging
# for scale-out, comment-out the following line (Make sure a
# 'services' queue is available and serviced by a ClearML agent
# running either in services mode or through K8S/Autoscaler)