Thanks GreasyPenguin14 !

Do you want to open an issue in pip?
Funny enough this works in:

pip3 install "torch >=2.1.0.*, <2.1.1.*" --extra-index-url 

is it there ?

Thanks again for crazyfrogspb & Tim for helping to find the extra edge case

PompousBeetle71 so basically exclude parameters that are considered "local" only, so that other people will not accidentally use them?

Follow-up; any ideas how to avoid PEP 517 with the auto scaler?

Takes a

long

time to build the wheels

enable venv caching ?
https://github.com/allegroai/clearml-agent/blob/a5a797ec5e5e3e90b115213c0411a516cab60e83/docs/clearml.conf#L116

WickedGoat98 is this related to plotly opening a web page when you call show() method ?
You can do:
if not Task.running_locally() fig.show()

WickedGoat98 what's the clearml version you are using?

when I run it on my laptop...

Then yes, you need to set the default_output_uri on Your laptop's clearml.conf (just like you set it on the k8s glue)
Make sense ?

Hi ScantChimpanzee51
In order to get it to work:
conf_file = "options.yml" conf_file = task.connect_configuration(conf_file, "Yaml options") with open(conf_file, "r") as f: ...The reason is it will not overwrite the local file but return a temp file for you to read.
And come to think about it, maybe we should add an argument saying, it should allow it to overwrite the local file, wdyt?

Hi ReassuredTiger98
I think it used to be the default and then it was removed, it has no real affect on performance but it remove all asserts ... what is your use case ? do you see any performance gains ?

Oh I see your point, that makes sense, it should check the state of the Task and force it to aborted so it can be renequed, the issue with reset it will clear the previous run execution, which I think we do not want, Wdyt?

BTW:

======> WARNING! Git diff to large to store (1327kb), skipping uncommitted changes <======

This means all your git changes are stored as an artifact, which is consistent with the "wait for upload" message.

In my understanding requests still go through

clearml-server

which configuration I left

DefiantHippopotamus88 actually this is Not correct.
clearml-server only acts as a control plane, no actual requests are routed to it, it is used to sync model state, stats etc. not part of the request processing flow itself.
curl: (56) Recv failure: Connection reset by peerThis actually indicates 9090 port is not being listened to...
What's the final docker-compose you are usi...

CluelessFlamingo93 I would also fix the pip version requirements to:
pip_version: ["<20.2 ; python_version < '3.10'", "<22.3 ; python_version >= '3.10'"]

Would be very cool if you could include this use case!

I totally think we should, any chance you can open an Issue, so this feature is not lost?

Hi AverageBee39
What's the clearml-server and clearml packge you are using ?
(I looks like some capability that is missing from the server, i.e. needs upgrade ?!)

I see, let me check the code and get back to you, this seems indeed like an issue with the Triton configuration in the model monitoring scenario.

Awesome! Any chance you feel like contributing it, I'm sure ppl would be thrilled 🙂

This depends on how you spined the server, basically as long as you configure the clients (i.e. python clients) correctly, there is no issue.
But the auto generated configuration might be off (in the UI when you credentials it tells the clearml-init where the server is and the ports)
I would actually recommend subdomains if this is possible
https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_config#sub-domain-configuration
wdyt?

Hi BattyLizard6
Not that I'm aware of, which TF version are you using, and which clearml version?

but I have no idea what's behing 

1

, 

2

  and 

3

 compare to the first execution

This is why I would think multiple experiments, since it will store all the arguments (and I think these arguments are somehow being lost.
wdyt?

I think I know what the prob is

ClearML does

BTW: the agent will resolve pytorch based on the install CUDA version.

Hmm that is odd, let me see if I can reproduce it.
What's the clearml version you are using ?

is that what you want to happen ?

Sure go to the "All Projects" and filter by Task Type, application / service

Wait, with the Port it does not work?
Notice that since this is external S3 you have to have the port specified so it Knows this is not an AWS S3 but a different compatible service

ahh, because task_id is the "real" id of a task

Yes the ID is a global system wide unique ID (regardless of the project etc.)

Maybe we will call tasks as

slug_yyyymmdd

Notice that you can just copy-paste the link in the address bar, it will bring you to the exact same view, meaning easily shared among users 🙂 You can, but I would actually use the Task ID. This also means that programatically you can do , task=Task,get_task(task_id_here) and interact and query a...