@<1570220844972511232:profile|ObnoxiousBluewhale25> it creates a new Model here
None
If you want it to log to something other than the default file server create the clearml Task before starting the training:

task = Task.init(..., outout_uri="file:///home/karol/data/")
# now training

It will use the existing Task and upload to the destination folder

So it is the automagic that is not working.
Can you print the following before calling Both Task.debug_simulate_remote_task and Task.init , Notice you have to call Task.init
print(os.environ)

None
notice there is a scroll_id there, you might need to call the API multiple times until you scroll over All the events
could that be it?

Hi SmallDeer34
Can you try with the latest RC , I think we fixed something with the jupyter/colab/vscode support
!pip install clearml==1.0.3rc1

'config.pbtxt' could not be inferred. please provide specific config.pbtxt definition.

This basically means there is no configuration on how to serve the mode, i.e. size/type of lower (input) layer and output layer.
You can wither store the configuration on the creating Task, like is done here:
https://github.com/allegroai/clearml-serving/blob/b5f5d72046f878bd09505606ca1147d93a5df069/examples/keras/keras_mnist.py#L51
Or you can provide it as standalone file when registering the mo...

Hi @<1523701868901961728:profile|ReassuredTiger98> when you get to it...
please download the wheel, then install it with

pip3 install -U clearml_agent-0.17.3rc0-py3-none-any.whl

Then run the daemon with the additional --debug argument, basically:

clearml-agent --debug daemon --foreground ...

Once the agent is running please send the Task's log from your console 🙂

JitteryCoyote63 it should just "freeze" after a while as it will constantly try to resend logs. Basically you should be fine 🙂
(If for some reason something crashed, please let me know so we can fix it)

without the ClearML Server in-between.

You mean the upload/download is slow? What is the reasoning behind removing the ClearML server ?

ClearML Agent per step

You can use the ClearML agent to build a socker per Task, so all you need is just to run the docker. will that help ?

WDYT?

Can you see the repo itself ? the commit id ?

maybe this can cause the issue?

Not likely.
In the original pipeline (the one executed from the Pycharm) do you see the "Pipeline" section under Configuration -> "Config objects" in the UI?

LOL

BTW, this one seems to work ....
` from time import sleep
from clearml import Task

Task.set_offline(True)
task = Task.init(project_name="debug", task_name="offline test")

print("starting")

for i in range(300):
print(f"{i}")
sleep(1)

print("done") `

When a remote task runs

Dataset.get()

it is not using the correct URL

BoredHedgehog47 it will get the link the data was Registered with, when creating the Dataset.
This has Nothing to do with the local configuration, it can point to any arbitrary file location on the internet.
It was created there, because at the time of the dataset creation someone (manually or via the config) set a specific host as the file location, and to that host the files were uploaded (again ...

Hi MinuteGiraffe30
Are you saying that when you are running you code locally with a gitea repository, cleamrl incorrectly adds a link to gitlab ?

I can't find out how to pass my custom clearml.conf

Hi @<1544491301435609088:profile|TeenyElk27>
The easiest is to map it into the container in your docker-compose
(map a host clearml.conf into /root/clearml.conf inside the container)

Thank you!

one thing i noticed is that it's not able to find the branch name on >=1.0.6x , while on 1.0.5 it can

That might be it! let me check the code again...

CooperativeFox72 I would think the easiest would be to configure it globally in the clearml.conf (rather than add more arguments to the already packed Task.init) 🙂
I'm with on 60 messages being way too much..
Could you open a Github Issue on it, so we do not forget ?

No worries 🙂

In our case, we have a custom YAML instruction

!include

, i.e.

Hmm interesting, in theory this might work since configuration encoding (when passing dicts), is handled with HOCON which does support referencing.
That said currently it is not aware of "remote configurations" only ENV variables and local files.
It will be cool to add, do we have a github issue on that? (would you like to see if you can PR such a thing?)

yey working 🙂

JitteryCoyote63 , just making sure, does refresh fixes the issue ?

What’s the general pattern for running a pipeline - train model, evaluate metrics and publish the model if satisfactory (based on a threshold, for example)

Basically I would do:
parameters for pipeline:
TaskA = Training model Task (think of it as our template Task)
Metric = title/series/sign we want to choose based on, where sign is max/min
Project = Project to compare the performance so that we could decide to publish based on the best Metric.

Pipeline:
Clone TaskA Change TaskA argu...

Can you run the entire thing on your own machine (just making sure it doesn't give this odd error) ?

Hi QuaintJellyfish58
You can always set it inside the function, with
Task.current_task().output_uri = "s3://"I have to ask, I would assume the agents are pre-configured with "default_output_uri" in the clearml.conf, why would you need to set it manually?

But this is not copy, this is mount, your log showed cp failing

Hi JitteryCoyote63

I change the project.default_output_destination? I tried setting it to None but it is not updated

How did yo try to change it? and where do you see the effect ?

Yes, only task.execute_remotely() should be the last call. because it literally will stop the local run before you add the Args section

Thank you AttractiveWoodpecker16 !
Removing the uncommitted changes so that you can launch it from an agent? Or is it visual only?

Hi ExasperatedCrocodile76
It seems like it is using conda package manager, were you using conda when you run the code manually ?
ERROR: This cross-compiler package contains no program /home/ivan/miniconda3/envs/clearML/bin/x86_64-conda_cos6-linux-gnu-gfortranWhy is it trying to install from source code?
BTW: can you test with the latest agent RC? ( pip install clearml-agent==1.4.0rc4 )