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

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

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. 🙂

Sorry, I don’t understand how this helps with validating the pipeline run.
Where would the validation code sit?
And the ClearML Pipeline run needs to be available on the ClearML Server (at least as a draft) so that it can be marked as in-production and cloned in the future

The pseudo-code you wrote previously is what would be required, I believe

be able to get the pipeline’s Task ID back at the end

This is the missing piece. We can’t perform validation without this, afaik

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).

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

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?

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

I used task.flush(wait_for_uploads=True) in the final cell of the notebook

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 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”

Thanks for you help 🙂

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

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 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, 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...

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.

Hmm. Okay. Thanks

Ahh that’s great, thank you.

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

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

Do notice this will only work for pipelines from Tasks, is this a good fit for you?

The issue with this is that we would then presumably have to run/“build” each of the Tasks (pipeline steps) separately to put them on the ClearML server and then get their Task ID’s in order to even write the code for the Pipeline, which increases the complexity of any automated CI/CD flow. Correct me if I’m wrong.

Essentially, I think the key thing here is we want to be able to build the entire Pipe...

Thanks

I get an error about incorrect Task ID’s – in the above pseudo code it would be the ID of the step Task that was displayed in the error

The Dataset object itself is not being passed around. The point of showing you that was to say that the Dataset may change and therefore the number of objects (loaded from the Dataset, eg a number of pandas DataFrames that were CSV’s in the dataset) could change

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...

To illustrate, here’s an example repo:

repo/
    package1/
    package2/ # installed separately to package1
    task_script.py # requires package1 and package2 to have been pip installed
    

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