Yey!
My pleasure 🙂

Great if this is what you do how come you need to change the entry script in the ui?

CostlyOstrich36 did you manage to reproduce it?
I tried conda w/ python3.9 on a clean Windows VM , and it worked as expected ....

Hi CourageousDove78
Not the cleanest, but you can basically pass everything here:
https://allegro.ai/clearml/docs/rst/references/clearml_api_ref/index.html#post--tasks.get_all
Reasoning is that it is passed almost as is to the server for the actual query.

 I want to schedule bulk tasks to run via agents, so I'm running 

create

I see, that makes sense.

specially when dealing with submodules,

BTW: submodule diff should always get stored, can you provide some error logs on fail cases?

Before manually modifying the diff:
If you have local commits (i.e. un-pushed) this might fail the diff apply, in that case you can set the following in your clearml.conf
store_code_diff_from_remote: truehttps://github.com/allegroai/clear...

JitteryCoyote63 any specific reason for the question?

BTW: I think we had a better example, I'll try to look for one

You can always access the entire experiment data from python
'Task.get_task(Id).data'
It should all be there.
What's the exact use case you had in mind?

sorry the point where you select the interpreter for pycharm

Oh I see...

OddShrimp85
the Task id is UUID that is generated by the backend server, there is no real way to force it to have a specific value 😞

Come to think about it, maybe we should have "parallel_for" as a utility for the pipeline since this is so useful

Hi AdventurousRabbit79
Try:
"extra_clearml_conf" : "aws { s3 {key: A, secret : B, region: C, }} ",Generally speaking no need for the quotes on the secret/key
You also need the comma to separate between keys.
You can test if it is working by adding the same string to your local clearml.conf and importing the cleaml package

The fact is that I use docker for running clearml server both on Linux and Windows.

My question was on running the agent, is it running with --docker flag, i.e. docker mode

Also, just forgot to note, that I'm running clearml-agent and clearml processes in virtual environment - conda environment on Windows and venv on Linux.

Yep that answers my question above 🙂

Does it make any sense to chdnge 

system_site_packages

 to 

true

 if I r...

Hi @<1566596960691949568:profile|UpsetWalrus59>
All correct with the exception of " ...or 1GB Metric" this is a limit, since metrics (and meta data) is always stored on the clearml-server, so it is metered. There is also an API limit, basically anti abuse, which of course resets every month, but if you are running tens of experiments at the same time you will hit this limit. Make sense ?

Hi MysteriousBee56 ,
what do you mean by:

Can we upload our project repository to trains server?

UnevenDolphin73 something like this one?
https://github.com/allegroai/clearml/pull/225

at the end of the manual execution

WhimsicalLion91

What would you say the use case for running an experiment with iterations

That could be loss value per iteration, or accuracy per epoch (iteration is just a name for the x-axis in a sense , this is equivalent to time series)
Make sense?

Hmm, this means the step should have included the git repo itself, which means the code should have been able to import the .py
Can you see the link to the git repository on the Pipeline step Task ?

instead of the one that I want or the one of the env which it is started from.

The default is the python that is used to run the agent.
agent.ignore_requested_python_version = true agent.python_binary = /my/selected/python3.8

Hi TenderCoyote78

I'm trying to clearml-agent in my dockerfile,

I'm not sure I'm following, Are you traying to create a docker container containing the agent inside? for what purpose ?
(notice that the agent can spin any off the shelf container, there is no need to add the agent into the container it will take of itself when it is running it)

Specifically to your docker file:

RUN curl -sSL

| sh

No need for this line

COPY clearml.conf ~/clearml.conf

Try the ab...

😄

Still this issue inside a child thread was not detected as failure and the training task resulted in "completed". This error happens now with the Task.init inside the 

if name == "main":

  as seen above in the code snippet.

I'm not sure I follow, the error seems like your internal code issue, does that means clearml works as expected ?

[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...

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

Actually with

base-task-id

it uses the cached venv, thanks for this suggestion! Seems like this is equivalent to cloning via UI.

exactly !

But “cloning” via UI runs an exact copy of the code/config, not a variant,

You can override the commit/branch and get the latest ...

run exp tweak code/configs in IDE, or tweak configs via CLI have it re-rerun in exact same venv (with no install overhead etc)So you can actually launch it remotely directly from the code:
...

GleamingGrasshopper63 what do you have configured in the "package manager" section?
https://github.com/allegroai/clearml-agent/blob/5446aed9cf6217f876d3b62226e38f21d88374f7/docs/clearml.conf#L64

Legit, if you have a cached_file (i.e. exists and accessible), you can return it to the caller

Also this message suggests that I can change the configuration, but as said I can't find it anywhere and wouldn't know hot to change the configuration.

This means that you can launch a new one (i.e. abort, clone, edit, enqueue) directly from the web UI and in the UI edit the configuration. Unfortunately it does not support changing the configuration "live"

Hi VastShells9
2022-12-20 12:48:02,560 - clearml.automation.optimization - WARNING - Could not find requested hyper-parameters ['duration'] on base task a6262a151f3b454cba9e22a77f4861e3Basically it is telling you it is setting a parameter it never found on the original Task you want to run the HPO o.
The parameter name should be (based on the screenshot) "Args/duration" (you have to add the section name to the HPO params). Make sense ?