and then?

The thing is programmatically this is not easy to do as API, because at the end the "function" (i.e. LCI) never leaves, it connects to the SSH and stays

But you can query the Task it creates, the project is known, the user is known and it is of special type/tag

Hi RoughTiger69
Interesting question, maybe something like:

` @PipelineDecorator.component(...)
def process_sub_list(things_to_do=[0,1,2]):
r = []
for i in things_to_do:
print("doing", i)
r.append("done{}".format(i))
return r

@PipelineDecorator.pipeline(...)
def pipeline():

create some stuff to do:

results = []
for step in range(10):
r = process_sub_list(list(range(step*10, (step+1)*10)))
results.append(r)

push into one list with all result, this will ac...

Yes, found the issue :) I'll see to it there is a fix in the next RC. ETA early next week

3. Could you explain how I can reproduce the missing jupyter notebook (i.e. the ipykernel_launcher.py)

trains-agent RC (which they tell me will be out tomorrow) will have a switch to do that, just so it is easier 🙂

Let me check... I think you might need to docker exec
Anyhow, I would start by upgrading the server itself.
Sounds good?

okay so it is downloaded to your machine, and unzipped , is that part correct?

I think this is the issue, it was search and replaced . The thing is I'm not sure the helm chart is updated to clearml. Let me check

EnviousStarfish54 something is also off in the git detection, it has not remote address, it just says "origin"
Any chance you have no git server ?
Regrading the installed packages, any chance you can send a sample code for me to debug ?

Correct, but do notice that (1) task names are not unique and you can change them after the Task was executed (2) when you clone the Task, you can actually rename it, when an agent is running the Task, basically the init function is ignored, because the Task already exists. Make sense ?

We workaround the issue by downloading the file with a request and unzipping only when needed.

We have located the issue, it seems the file-server is changing the header when sending back the file (basically saying CSV with gzip compression, which in turn will cause any http download client to automatically unzip the content). Working on a hot fix for it 🙂

Yes the one you create manually is not really of the same "type" as the one you create online, this is why you do not see it there 😞

Long story short, this is done internally when you call the Task.init (I think, there is a chance it is called before)
One way of controlling it would be to have something like:
Task.init(auto_connect_frameworks={'hydra': {'log_before_resolve': True}})That said, I think it will be simpler to store both (in different section of course)
Maybe "Configuration Object: OmegaConf" and "Configuration Object: OmegaConfDefinition" ?

I guess we should have obfuscated the name better 😄

or can I directly open a PR?

Open a direct PR and link to this thread, I will make sure it is passed along 🙂

What's the trains-server version ?

I think I found something, let me test my theory

that should have worked, do you want send the log?

The experiment finished completely this time again

With the RC version or the latest ?

Apparently the error comes when I try to access from

get_model_and_features

the pipeline component

load_model

. If it is not set as pipeline component and only as helper function (provided it is declared before the components that calls it (I already understood that and fixed, different from the code I sent above).

ShallowGoldfish8 so now I'm a bit confused, are you saying that now it works as expected ?

could one also limit the number of CPU cores available?

If you are running in docker mode you can add:
--cpus=<value>see ref here: https://docs.docker.com/config/containers/resource_constraints/

Just add it to extra_docker_arguments :
https://github.com/allegroai/clearml-agent/blob/2cb452b1c21191f17635bcb6222fa8bfd82afe29/docs/clearml.conf#L142

Done 🙂

JitteryCoyote63 see if upgrading the packages as they suggest somehow fixes it.
I have the feeling this is the same problem (the first error might be trains masking the original error)

No sure I follow, you mean to launch it on the kubernretes cluster from the ClearML UI?
(like the clearml-k8s-glue ?)

EnviousStarfish54 quick update, regardless of the logging.config.dictConfig issue, I will make sure that even when the logger is removed, the clearml logging will continue to function 🙂
The commit will be synced after the weekend

JitteryCoyote63 sure, this is how it was designed to work 🙂

I located the issue, I'm assuming the fix will be in the next RC 🙂
(probably tomorrow or before the weekend)

Okay Let me check

Let me know if I can be of help 🙂

Sorry my bad, you are looking for:
None