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...

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. 🙂

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

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...

Thanks for you help 🙂

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

But yeah, more generally having a different UI for different data types could be useful (e.g. categorical variables, integers, decimals, etc), just not a direct concern for me at this moment

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

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

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

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

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

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
    

There are no experiments in the project, let alone the pipeline; they’ve all been archived

And the app is presumably crashed because I can’t click the “Close” button – it’s (the whole page) totally unresponsive and I have to refresh the page, at which point the pipeline still exists (ie was not deleted).

I have left it on the deletion screen (screenshot) for 20-30 mins at one point and it didn’t do anything, so this seems to be a bug

I’m just the messenger here, didn’t set up the web app...

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

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)

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”

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).

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

Hmm. Okay. Thanks

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

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

You may indeed 😊 thanks!

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...

Ahh. This is a shame. I really want to use ClearML to efficiently compute features but it’s proving a challenge!
Thanks

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...

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.

Ah okay, that is a very easy solution to the problem. I wasn’t aware that you could build and run pipelines like that, and I especially wasn’t aware that you could return values from a pipeline and have them accessible to a script in the way that you have given.

Does this require you run the pipeline locally (I see you have set default execution queue) or do any other specific set-up?

I will give it a go tomorrow and report back – the only issue I foresee will be if doing this somehow inc...

Ahh that’s great, thank you.

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

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?