as I have wandb docker set up on the same VM for teting

I also get this from the logging

TRAINS Monitor: GPU monitoring failed getting GPU reading, switching off GPU monitoring

task_reporting = Task.init(project_name='project', task_name='report') tasks = Task.get_tasks(project_name='project', task_name='partial_task_name_here') for t in tasks: t.get_last_scalar_metrics() task_reporting.get_logger().report_somethingInstead of get_last_scalar_metrics() , I am using t._data.hyperparams['summary'] to get the metrics I needed

I see, I will look into the documentation of it, thanks Jake.

https://github.com/allegroai/clearml/commit/164fa357ed01704b11db67b8a7ac19791fbc49d1

This works. So it is still in master and should be included in 1.0.5?

Oh great! This works like a charm

Cool! Will have a look at the fix when it is done. Thanks a lot AgitatedDove14

It's for addition filtering only right? My use case is to prevent user accidentally querying the entire database.

I want to achieve something similar we would do in SQL

select * from user_query limit 100;

it's ok, I don''t think this is very important. thx

Thanks for your help. I will stick with task.connect() first. I have submit a Github Issue, thanks again AgitatedDove14

It's good that you have version your dataset with name, I have seen many trained model that people just replace the dataset directly.

using configuration directly it actually worse than using a dictionary for hyperparmaeters. It would do the diff line by line (notice the right experiment)

It would be nice if there is an "export" function to just export all/selected experiment table view

Great discussion, I agree with you both. For me, we are not using clearml-data, so I am a bit curious how does a "published experiment" locked everything (including input? I assume someone can still just go inside the S3 bucket and delete the file without Clearml noticing).

From my experience, absolute reproducibility is code + data + parameter + execution sequence. For example, random seed or some parallelism can cause different result and could be tricky to deal with sometimes. We did bu...

https://github.com/allegroai/trains/issues/250
https://github.com/allegroai/trains/pull/251

TimelyPenguin76

Ok, will prepare a PR and script to reproduce the error

I want the support for click as well, or is there any adhoc solution?

I have tried adding the line to conf but seems not working as well... are u able to run with proper logging?

Latest Run: https://app.community.clear.ml/projects/1e91d9f50c1744b8a52748d47af996be/experiments/f8a5923bd34d469b8c3afb5c91d5a32e/info-output/log?columns=selected&columns=type&columns=name&columns=tags&columns=status&columns=project.name&columns=users&columns=started&columns=last_update&columns=last_iteration&columns=parent.name&order=-last_update

https://github.com/allegroai/trains/blob/master/examples/frameworks/matplotlib/matplotlib_example.py

https://allegro.ai/docs/examples/frameworks/matplotlib/matplotlib_example/

I also don't understand why the last chart goes to DEBUG sample instead? the code does not seems to have difference with previous block.

Thanks Martin

Thanks! That's great

https://github.com/quantumblacklabs/kedro-examples/blob/master/kedro-tutorial/conf/base/catalog.yml

I am actually using Kedro (a pipeline library), you can check out the yaml config here. There will be a lot of cases that I need to insert a new argument or dataset in between

Could u give me some pointers where ClearML auto-capture log/stdout? I suspect as Kedro has configuration on logging and somehow ClearML fail to catch it.

Now my problem is clearml-agent pick up the job but fail to run the docker.

How do I confirm this?

I am running on Window 10 Machine, is this not compatible?

How often does Trains record the usage? I tried running a dummy programming which sleeps for 20 seconds and I don't see any plot.

Is this configurable?