WorriedParrot51 trains should support subparsers etc.
Even if your code calls the parsing before trains.
The only thing you need is to import the package when argparser is called (not to initialize it, that can happen later)
It should (hopefully) solve the issue.

It will store the entire content of the file, then you can edit it in the UI, and in remote it will return a new local copy of the file (based on the data in the UI) for you to read.

Oh, then just make sure you call Task.init in your code,
as long as you have clearml.conf in the container or pass the ENV variables to configure your clearml, it should just work

JitteryCoyote63 you mean? (notice no brackets)
task.update_requirements(".") Either pass a text or a list of lines:
The safest would be '\n'.join(all_req_lines)

If we have the time maybe we could PR a fix?!

With env caching enabled, it won’t reinstall this private dependency, right?

It will, local packages (".") and git packages are alwyas reinstalled even if using venv caching, exactly for that reason 🙂

Exactly, that’s my problem: I want to remove it to make sure it is reinstalled (because the version can change)

JitteryCoyote63 yes, this is definitely a pip bug... can you test with the latest pip version, maybe it was fixed? (i.e. git+https:// link)

Ohh so the setup.py is the one containing these requirements, oops I totally missed that :( let me check what pep has to say about that ... (Basically this is not a clearml issue but a pip one...)

error in my-package setup command:

Okay this seems like an error in the setup.py you have in the "mypackage" folder

Try:
task.update_requirements('\n'.join([".", ])) 

oh dear 😞 if that's the case I think you should open an Issue on pypa/pip , I'm not sure what we can do other than that ...

WackyRabbit7 I'll make sure it is fixed

Hi @<1619867971730018304:profile|WhimsicalGorilla67>
No 😞 only the "admin" (owner) of the workspace has access to it

Thanks DefeatedOstrich93
Let me check if I can reproduce it.

should be the full path, or just the file name?

just file name, this is basically fname matching

Hi LudicrousDeer3
I have to admit I cannot remember one in the wild (I might be wrong though).
What's the specific use case you had in mind ?

Hi WorriedParrot51
Let me shed some light on this complicated mechanism, because this is not very straight forward.
Basically the agent signals the trains package it should ignore the code calls, and use a specific Task in the backend (i.e. if in manual mode, the trains package logs the data into the trains-server, in agent mode (remote mode), it does the opposite and takes the data from the trains-server "into" the code)

Specifically, just like in manual mode, calling argparse.parse is be...

Hi WorriedParrot51
Assuming you run the code "manually" once (i.e. without the agent). Then when you call Task.init it will register the argparser.
When running with the agent, the first time you will call parse, it will automatically override the argparse defaults with the values stored in the Task.
Make sesne?

am getting None for Task.current_task() at the beginning of my script.

Task.init() is doing the magic , only after this call you will have current_task (either running manua...

Hi WorriedParrot51 , what do you mean by "call get_parameters_as_dict() from agent" ?
Do you mean like change the trains-agent to run the task differently?
Or inside your code while the trains agent runs it?
From the code itself (regardless off how you run it) you can always call, and get the current states parameters (i.e. from backend if running with trains-agent, or copied from the code, if running manually)
task.get_parameters_as_dict()

(i.e. importing the trains package is enough to patch the argparser, only when you call the task.init the arguments will be logged, before they are stored in memory)

Oh, did you try task.connect_configuration
?
https://allegro.ai/docs/examples/reporting/model_config/#using-a-configuration-file

Hmm, I think it is this line:

WARNING - Model configuration only supports dictionary or string objects
done

Let me check something.

Hi @<1549202366266347520:profile|GorgeousMonkey78>

how do I integrate sagemaker with clearml ,

you mean to launch an experiment, or just to log it?

Hi @<1654294828365647872:profile|GorgeousShrimp11>

can you run a pipeline on a

schedule

or are schedules only for Tasks?

I think one tiny details got lost here, Pipelines (the logic driving them) are a type of Task, this means you can clone and enqueue them like other tasta
(Task.enqueue / Task.clone)
Other than that looks good to me, did I miss anything ?

BTW: if you feel like pushing forward with integration I'll be more than happy to help PRing new capabilities, even before the "official" release

and when you remove the "." line does it work?

But the git apply failed, the error message is the "xxx already exists in working directory" (xxx is the name of the untracked file)

DefeatedOstrich93 what's the clearml-agent version?

Hi SkinnyPanda43

No idea what the ImageId actually is.

That's the ami image string that the new EC2 will be started with, make sense ?

I think we should open a GitHub Issue and get some more feedback, maybe we should just add support in the backend side ?

😞 DilapidatedDucks58 how exactly are you "relaunching/continue" the execution? And what exactly are you setting?