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5 × Eureka!ThoughtfulBadger56 Have you uncommented the existing venvs_cache section in the config file?
https://clear.ml/docs/latest/docs/clearml_agent#virtual-environment-reuse
So could you just setup your virtual environment with a task?
Have you triedlogger = Logger.current_logger()
in your code?
Logger is a singleton so you should get the same object from your previously created task
https://clear.ml/docs/latest/docs/references/sdk/logger/#loggercurrent_logger
As far as I know, you can start a docker container with the same version and the same volumes and you should be able to just continue.
You can disable it if you want to. Sometimes it's useful to retrace your steps but it works without :)
Or you can just load a config file or object: https://clear.ml/docs/latest/docs/references/sdk/task/#connect_configuration
Have you tried --verbose
?
Or you can give it a configuration object: https://clear.ml/docs/latest/docs/clearml_sdk/task_sdk#configuration-objects
Wait... Will it limit memory usage but not show it in overview or just plain stop the container if it happens to use more memory?
Wait, I noticed you need another set of quotes:
Sample in the docs is: --memory="300m"
https://docs.docker.com/config/containers/resource_constraints/
I don't see SB3 here so PyTorch would be best: https://clear.ml/docs/latest/docs/integrations/libraries
You can find more info here: https://clear.ml/docs/latest/docs/references/sdk/task#taskforce_requirements_env_freeze
I think if you use explicit logging it only logs things you've selected but I'm not entirely sure
https://clear.ml/docs/latest/docs/guides/reporting/clearml_logging_example/
I'd you've got a self hosted instance you can have a look yourself https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_config
But other then that I'm not sure. AnxiousSeal95 any thoughts?
I'm not sure about the preview part but after uploading I think you might find the images with list
and --filter
https://clear.ml/docs/latest/docs/clearml_data/clearml_data_cli#list
I'm not sure if that helps?
Do you mean in the WebUI or via the API?
Did you use --git-credentials ?
https://clear.ml/docs/latest/docs/apps/clearml_session#accessing-a-git-repository
Can you try again with "-m 16g" ?
If I'm 'ot mistaken closed status should only appear when you've used Close ()
ScaryBluewhale66 you shouldn't call mark_* on the main task, we're adding this as a notice and in documentation in the next release: https://github.com/allegroai/clearml/issues/830
Do you have the same python version locally as remotely?
Some ways you could continue now:
you can reuse an existing python virtual environment: https://clear.ml/docs/latest/docs/clearml_agent/#virtual-environment-reuse
You can also run the agent in docker mode: https://clear.ml/docs/latest/docs/clearml_agent/#docker-mode
I'll have a look at the differences concerning the dev disappearing.
This ^
If you're not getting any errors, it should work just fine 🙂
In https://github.com/thepycoder/urbansounds8k/blob/main/preprocessing.py i'm seeing dataset_task.get_logger().report_image
, dataset_task.get_logger().report_table
, dataset_task.get_logger().report_histogram
and dataset_task.get_logger().report_media
which are all manual loggings. Hence, why the author probably didn't use any automatic logging.
It should, or you might need to nest the objects.
Edit: I asked, it won't there's a difference in configs I mixed up.
Can you give me a bit more info what exactly you're trying to log and what framework you're using?
I'm afraid what you're trying to do isn't a supported implementation.
You'll have to choose between using docker mode to have one virtual environment for everything or using the pip mode where you can used the cached virtual environments but you can't reuse the one you currently have.