I think so, thank you.

Also my execution just completed and as of yet, I can only see the hyperparameters as a report. not in a configurable form. I've just started with ClearML and am having these issues.

bump

On both the main ubuntu and the vm, I simply installed it in a conda environment using pip

Found it.

https://clear.ml/docs/latest/docs/guides/clearml-task/clearml_task_tutorial/

The second example here, executing a local script. I think that was it. Thank you for the help.

Basically, as soon as I get the trigger that a new dataset has been published, I want to pass the dataset id to the script as an cli argument and pass the code to the agent

I'll look into it. Thank you everyone.

yeah.

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.

I've tried the ip of the ClearML Server and the IP of my local machine on which the agent is also running on and none of the two work.

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

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.

Good point

this is it.

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?

I normally just upload the data to the ClearML server and then remove it locally from my machine but I understand that isn't what you want. A quick hack was the only thing I could come up with at the moment xd. Anyway you're welcome. Hope you find a solution.

Basically when I'm loading the model in InputModel, it loads it fine but I can't seem to get a local copy.

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

trigger_scheduler.add_dataset_trigger(schedule_task_id=TASK_ID, schedule_queue='default',
trigger_project='Cassava Leaf Disease Classification', name='start task on data - End Game')

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

My draft is View Only but the cloned toy task one is in normal Draft mode.

There's a whole task bar on the left in the server. I only get this page when i use the ip 0.0.0.0

This is the task scheduler btw which will run a function every 6 hours.

Alright. Can you guide me on how to edit the task configuration object? Is it done via the UI or programatically? Is there a config file and can it work with any config file I create or is it a specific config file? Sorry for the barrage of questions.

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

Thank you.

I would normally like for it to install any requirements needed on its own.

For anyone who's struggling with this. This is how I solved it. I'd personally not worked with GRPC so I instead looked at the HTTP docs and that one was much simpler to use.

the one mentioned on the page.

I'd like to add an update to this, when I use schedule function instead of schedule task with the dataset trigger scheduler, it works as intended. It runs the desired function when triggered. Then is asleep again next time since no other trigger was fired.