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I'Ll Just Ask This Question Again To Get Some Fresh Attention To This. Is There Any Way To Run A Pipeline Step Conditionally? E.G, Under Certain Condition, Execute The Step Otherwise Don'T?

I'll just ask this question again to get some fresh attention to this. Is there any way to run a pipeline step conditionally? E.g, under certain condition, execute the step otherwise don't?

  
  
Posted 2 years ago
Votes Newest

Answers 25


VexedCat68 you mean the artifact in the previous step is called "merged_dataset_id"? Is it an artifact or is it a parameter? And what issues are you having with accessing the parameter?

  
  
Posted 2 years ago

You can use pre \ post step callbacks.

  
  
Posted 2 years ago

AnxiousSeal95 I just have a question, can you share an example of accessing an artifact of a previous step in the pre execute callback?

  
  
Posted 2 years ago

I initially wasn't able to get the value this way.

  
  
Posted 2 years ago

So I'm looking at the example in the github, this is step1:
def step_one(pickle_data_url): # make sure we have scikit-learn for this step, we need it to use to unpickle the object import sklearn # noqa import pickle import pandas as pd from clearml import StorageManager pickle_data_url = \ pickle_data_url or \ ' ' local_iris_pkl = StorageManager.get_local_copy(remote_url=pickle_data_url) with open(local_iris_pkl, 'rb') as f: iris = pickle.load(f) data_frame = pd.DataFrame(iris['data'], columns=iris['feature_names']) data_frame.columns += ['target'] data_frame['target'] = iris['target'] return data_frame

  
  
Posted 2 years ago

pipe._nodes['stage_data'].job.task.artifacts

  
  
Posted 2 years ago

And in the pre_execute_callback, I can access this:
a_pipeline._nodes[a_node.parents[0]].job.task.artifacts['data_frame']

  
  
Posted 2 years ago

Thank you, this is a big help. I'll give this a go now.

  
  
Posted 2 years ago

I then did what MartinB suggested and got the id of the task from the pipeline DAG, and then it worked.

  
  
Posted 2 years ago

I think so, thank you.

  
  
Posted 2 years ago

Happy to hear 🙂

  
  
Posted 2 years ago

pipe.add_step(name='stage_process', parents=['stage_data', ],
base_task_project='examples', base_task_name='pipeline step 2 process dataset',
parameter_override={'General/dataset_url': '${stage_data.artifacts.dataset.url}',
'General/test_size': 0.25}, pre_execute_callback=pre_execute_callback_example, post_execute_callback=post_execute_callback_example)

  
  
Posted 2 years ago

If you return on a pre_execute_callback false (or 0, not 100% sure 🙂 ) the step just won't run.
Makes sense?

  
  
Posted 2 years ago

Hi VexedCat68

  
  
Posted 2 years ago

I checked the value is being returned, but I'm having issues accessing merged_dataset_id in the preexecute_callback like the way you showed me.

  
  
Posted 2 years ago

I'm both printing it and writing it to a file

  
  
Posted 2 years ago

you can do this

  
  
Posted 2 years ago

I'm not using decorators. I have a bunch of function_steps followed by a normal task step, where I've passed a base_task_id.

I want to check the value of one of the functional steps, and if it holds true, I want to execute the task step otherwise I want the pipeline to end there, since the task step is the last one.

  
  
Posted 2 years ago

It's an artifact.

  
  
Posted 2 years ago

AnxiousSeal95 I'm trying to access the specific value. I checked the type of task.artifacts and it's a ReadOnlyDict. Given that the return value I'm looking for is called merged_dataset_id, how would I go about doing that?

  
  
Posted 2 years ago

If you're using method decorators like https://github.com/allegroai/clearml/blob/master/examples/pipeline/pipeline_from_decorator.py , calling the steps is just like calling functions (The pipeline code translates them to tasks). Then the pipeline is a logic you write on your own and then you can add whatever logic needed. Makes sense?

  
  
Posted 2 years ago

in the pre_execute_callback, you can actually access any task in the pipeline. You can either directly access a node (task) in the pipe like the example above, or you can use the parent like this:
pipe._nodes[a_node.parents[0]].job.task.artifacts

  
  
Posted 2 years ago

Now in step2, I add a pre_execute_callback

  
  
Posted 2 years ago

This gets me the artifact that I return in step1
I think this is what you wanted

  
  
Posted 2 years ago

AnxiousSeal95 Basically its a function step return. if I do, artifacts.keys(), there are no keys, even though the step prior to it does return the output

  
  
Posted 2 years ago
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