Of course you can edit which parameters you like

I think I know what happens TimelyPenguin76
Could it be that trains automatically logs these images to plots?
Because when I removed the report_media/report_image the images were still logged into plots

Will do 🙂

Nevermind, you can find it in the apiserver.conf

Found it in the init docs 🙂

Fixed. the issue was the project name containing /

Since my servers have a shared file system, the init process tells me that the configuration file already exists. Can I tell it to place it in another location? GrumpyPenguin23

Well, I do exactly that but it still puts them under plots

Oh I see, I think this will work. Thanks 🙂

Oof, if all I have is a project bame to set? (Which could be a non existing project as well)

Logger.current_logger().report_media(title=f"visualization images f{output_category}", series=output_path.split('.')[-2].split('/')[-1], iteration=1, local_path=output_path)

Obviously I am working with my trains-server, as I can see the new pipeline task under the new project 😮

Is there a way to set this via a config file? like the docker compose yml?

I do this:
` base_task = Task.create(project_name=self.regression_project_name,
task_name=BASE_TASKS[block_type][engine], task_type=task_type)
params = base_task.export_task()

Git repo

params['script']['repository'] = subprocess.check_output(['git', 'config', '--get', 'remote.origin.url'],
cwd=REPO_NAME).decode().strip()

Git commit

params['script']['version_num'] = subprocess.check_output(['git', 'rev-parse',...

When you say I can still get race/starvation cases, you mean in the enterprise or regular version?

AgitatedDove14 Quite hard for me to try this right now. but I've validated that the relevant code segments are untouched between the versions. (at least current master branch at the ClearML repo)

If I'm exact I would like to add "commit id" to the override arguments when adding a task as a step to the pipeline

Thanks

Matplotlib

For example HPO, early stopping. It would mark the Task as abortedWhy? The task should have completed successfully, how is this aborting?

Yep. Works as you said.

I use local path instead of providing the image as an object, does this change things?

(The one that was created with initial task)

I see, will keep that in mind. Thanks Martin!

in the file's name

AgitatedDove14
The easiest example for such use case as I describe is for example trying to run the full pipeline but in this experiment I wish to try Batch Norm which I haven't used in the pre executed Task. How can I do that without running this Task by it's own? (Which is quite problematic for me since it runs as a part of a pipeline, therefore using DAG)

If I change the file at the entry point (let's say, I delete all of its content), how will trains behave when I try to clone and execute such task?

Oh, that seems right, how can I get the project id of the newly created project?

Great! Thanks 🙂

No, the task it was cloned from was created with Task.create, but there is a Task.init in the file that is run by Task.create