Yes, sorry, that wasn't clear 🙂

Hi SmarmyDolphin68
Maybe the plot_report can help?
See here:
https://github.com/allegroai/trains/blob/a28a97b16067fd5c548ec73b061badde2515aa9f/examples/reporting/pandas_reporting.py#L32

Which means you currently save the argument after resolving and I'm looking to save them explicitly so the user will not forget to change some dependencies.

That is correct

I'm looking to save them explicitly so the user will not forget to change some dependencies.

Hmm interesting point. What's the use case for storing the values before the resolving ?
Do we want to store both ?
The main reason for storing the post resolve values, is that you have full visibility to the actual...

AntsySeagull45 kudos on sorting it out 🙂
quick note, trains-agent will try to run the python version specified by the original Task. i.e. if you were running python3.7 it will first try to look for python 3.7 then if it is not there it will run the default python3. This allows a system with multiple python versions to run exactly the python version you had on your original machine. The fact that it was trying to run python2 is quite odd, one explanation I can think of is if the original e...

SweetGiraffe8 Works when I'm using plotly...
Can you please copy paste the code with the plotly, it's probably something I'm missing

, when I am running the pipeline remotely is there a way the remote machine can access it?

Well for the dataset to be accessible, you need to upload it with Dataset class, then the remote machine can do Dataset.get(...).get_local_copy() to get the actual data on the remote machine

BattyLion34 are you saying you do not have the "APP CREDENTIALS" section in the profile page?

Is it possible in Clearml to somehow allocate resources so that maybe after running a number of Alice's tasks, Bob's task get processed (Like maybe Round robin fashion)

Hi DeliciousBluewhale87
A few options here:
set the agent with high / low priority queues. Make sure Alice pushes into low priority (aka HPO) then Bob can push into high priority when he needs. This makes a lot of sense when you have automation processes spinning many experiments. expanding (1) you could set differe...

seems working to me

Hi LovelyHamster1
As you noted, passing overrides in Args/overrides , for example ['training.max_epochs=1000']
should work when running with the agent.

Could you verify with the latest RC, there was a fix to support the latest hydra version
pip install clearml==0.17.5rc5

Do you think It can be fixed somehow? It would be the easiest way to launch new experiments with a different configuration

Let me check, it might be it.

It would be the easiest way to launch new experiments with a different configuration

Definitely

Hi RobustHippopotamus53
The way "latest from branch" works:
On the Task you specify the branch name (e.g. "master", no need to add the origin/ prefix) The agent then pulls the latest commit from that branch and updates back the Task to the current commit ID (the latest on the branch at the time of execution) This process ensures reproduciblity and traceability as we can always be certain the exact commit that was executed.Could it be the you "forced-push" a commit/squash, hence the "origina...

BTW: get_tasks has project_name argument, I would just use it 🙂

Task.get_projects() 🙂

GreasyPenguin14 I think this is what you are looking for
Task.get_project_id('project_name')

Hi UpsetBlackbird87
This is an Optuna decision on how many concurrent tests to run simultaneously.
You limited it to 100, but remember Optuna does a Bayesian optimization process, where it decides on the best set of arguments based on the performance of the previous set, this means it will first try X trials, then decide on the next batch.
That said you can a pruner to Optuna specifying how it should start
https://optuna.readthedocs.io/en/v1.4.0/reference/pruners.html#optuna.pruners.Median...

Hmm. What's the Hydra version you have?

[Assuming the above is what you are seeing]
What I "think" is happening is that the Pipeline creates it's own Task. When the pipeline completes, it closes it's own Task, basically making any later calls to Tasl.current_task() return None, because there is no active Task. I think this is the reason that when you are calling process_results(...) you end up with None.
For a quick fix, you can do
pipeline = Pipeline(...) MedianPredictionCollector.process_results(pipeline._task)Maybe we should...

Thank you GreasyPenguin14 , I think you are correct, in offline mode it should not check the "demo server" configuration (as it will not try to connect to a server anyhow).
Could you open a github issue? so this issue is addressed quickly

Hi GrievingTurkey78
How are you getting different version than what is used in run time? it analyzes the PYTHONPATH just as python does ? How can I reproduce it? Currently you can use Task.add_requirements(package_name, package_version=None) This will not force it though, it is a recommendation (if it fails to find the package itself) maybe we can add force ?!What do you think?

GrievingTurkey78 I see,
Basically the arguments after the -m src.train in the remote execution should be ignored (they are not needed).
Change the m in the Args section under the configuration. Let me know if it solved it.

MiniatureCrocodile39 from the screen shot I imagine you are running inside a docker, this means that when you restart the docker, the configuration file is lost.
Could that be the case ?

is it there ?

It is currently only enabled when using ports mode, it should be enabled by default , i.e a new feature :)

DeliciousBluewhale87 let me check

👍

that was an odd error

hurray

Now I am passing it the same way you have mentioned, but my code still gets stuck as in above screenshot.

The screenshot shows warning from pyplot (matplotlib) not ClearML, or am I mising something ?

My guess is that it can't resolve credentials. It does not give me any pop up to login also

If it fails, you will get an error, there will never a popup from code 🙂

... We need a more permanent place to store data

FYI you can store the "Dataset" itself on GS (instead of...

Can you print the actual values you are passing? (i.e. local_file remote_url )