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8 × Eureka!AgitatedDove14 Thx for the clear explanation!
For some reason my code results in one node even though I think the logic above should result in a bipartite graph
CostlyOstrich36 The commented section is the 3 layer part which I am not currently using due to the lag
` # def update_datasets(dataset_projects, parents, is_ppg=False):
current_steps = []
for dataset_project in dataset_projects:
dataset_project_split = dataset_project.split('-')
campaign_num = dataset_project_split[2]
parameters = {
'Args/XXX': args.XXX_template.replace('*', campaign_num),
'Args/XXX': args.XXX_template....
CostlyOstrich36 This resulted in a bipartite graph that I expected but why? 😕
AgitatedDove14 CostlyOstrich36 [FYI] I’m not sure if this is an optimization issue in ClearML or my computer’s issue but when I make the pipeline a tri-partite graph (add another parent layer) the DAG becomes weird (I think because of the lag) and the web app lags so much until I delete this pipeline in the web app a (I can’t interact will any nodes in the graph and switching between tasks takes a long time)
Here is my log after task execution**Deleted**