Is there a rule whereby only python native datatypes can be used as the “outer” variable?

I have a dict of numpy np.array s elsewhere in my code and that works fine with caching.

The issue here is I don’t have the pipeline ID as it is a new version of the pipeline - i.e. the code has been updated, I want to run the updated pipeline (for the first time), get its ID, and then analyse the run/perform updates to tags (for example)

e.g. pseudo for illustration only
` def get_list(dataset_id):
from clearml import Dataset
ds= Dataset.get(dataset_id=dataset_id)
ds_dir=ds.get_local_copy()
etc...
return list_of_objs # one for each file, for example

def pipeline(dataset_id):
list_of_obj = get_list(dataset_id)
list_of_results = []
for obj in list_of_obj:
list_of_results.append(step(obj))
combine(list_of_results) `One benefit is being able to make use of the Pipeline caching so if ne...

I have already tested that the for loop does work, including caching, when spinning out multiple Tasks.

As I say, the issue is grouping the results of the tasks into a list and passing them into another step

Ahh that’s great, thank you.

And then I could use storage manager or whatever to get the files. Perfect

Hmm. Okay. Thanks

Yes, sorry, the final cell has the flush followed by the close

(including caching, even if the number of elements in the list of vals changes)

Thanks, I’ll check out those GitHub Actions examples but as you say, it’s the “template” step that is the key bit for this particular application.

the pipeline from tasks serializes itself to a configuration object that you can edit/create externally

I think if it has to come down to fiddling with lower-level objects, I’ll hold off for now and wait until something a bit more user-friendly comes along. Depends on how easy this is to work with.

This is something that we do need if we a...

You may indeed 😊 thanks!

I basically just mean having a date input like you would in excel where it brings up a calendar and a clock if it’s time – and defaults to “now”

Ahh okay.

I’m an absolute numpty.

I had enabled caching on the Pipeline Task that was grabbing a load of ClearML IDs and so it was trying to “get” datasets that had since been deleted.

Thanks for the nudge to minimal test – silly I didn’t do it before asking!

Appreciate your help.

Thanks, yes I am familiar with all of the above.

We want to validate the entire pipeline . I am not talking about using a ClearML Pipeline as the validator (which is the case in your examples).

Here is some further detail that will hopefully make things more obvious:

• The pipeline is a series of steps which creates a feature store – in fact, you might even call it a feature pipeline!
• Each pipeline step takes responsibility for a different bit of feature engineering.
• We want to val...

For reference, this works as expected:

Ah ok. I’m guessing the state file is auto uploaded in the background? I haven’t kicked that off “intentionally”

Sorry, I think something’s got lost in translation here, but thanks for the explanation.

Hopefully this is clearer:

• Say we have a new ClearML pipeline as code on a new commit in our repo.
• We want to build and run this new pipeline and have it available on the ClearML Server.
• We want to run a suite of tests that validate/verify/etc the performance of this entire ClearML Pipeline, e.g. by having it run on a set of predefined inputs and checking the various artifacts that were creat...

I am using the PipelineDecorator form of the pipeline and I am passing arguments as function arguments to the pipeline components

The Pipeline is defined using PipelineDecorators, so currently to “build and run” it would just involve running the script it is defined in (which enqueues it and runs it etc).

This is not ideal, as I need to access the Task ID and the only methods I can see are for use within the Task/Pipeline ( Task.current_task and PipelineDecorator.get_current_pipeline )

The reason I want to check completion etc outside the Pipeline Task is that I want to run data validation etc once when the pipe...

ClearML shows the new (child) dataset as “Uploading”, if that helps…

from tempfile import mkdtemp new_folder = with_feature.get_mutable_local_copy(mkdtemp())It’s this line that causes the issue

Thanks

Basically, for a bit more context, this is part of an effort to incorporate ClearML Pipelines in a CI/CD framework. Changes to the pipeline script create_pipeline_a.py that are pushed to a GitHub master branch would trigger the build and testing of the pipeline.

And I’d rather the testing/validation etc lived outside of the ClearML Pipeline itself, as stated earlier – and that’s what your pseudo code allows, so if it’s possible that would be great. 🙂

Producing it now — thanks for your help, won’t be a few mins

The return objects were stored to S3 but PipelineDecorator.upload_artifact still uploaded to the file server. Not sure what was up with that but as explained in my next comment it did work when I tried again.

It also seems that PipelineDecorator.upload_artifact is not compatible with caching, sadly, but that is another issue for another thread that I will be starting on Monday.

Have a good weekend

I have added a lot of detail to this, sorry.

The inline comments in the code talk about that specific script/implementation.

I have added a lot of context in the doc string at the top.

Thanks for you help 🙂

Hi John, we are using a self-hosted server with:

WebApp 1.9.2-317
Server: 1.9.2-317
API: 2.23

edit: clearml==1.11.0

Yep, that’s it. Obviously would be nice to not have to go via the shell but that’s by the by (edit: I don’t know of a way to build or run a new version of a pipeline without going via the shell, so this isn’t a big deal).

Yep, would be happy to run locally, but want to automate this so does running locally help with getting the pipeline run ID (programmatically)?

my colleague, @<1534706830800850944:profile|ZealousCoyote89> has been looking at this – I think he has used the relevant kwarg in the component decorator to specify the packages, and I think it worked but I’m not 100%. Connah?