but realized calling that from the extension would be hard, so we opted to have the TypeScript code make calls to the ClearML API server directly, e.g.
POST /tasks.get_all_ex
.
did you manage to get that working?
- To get the credentials, we read the
~/clearml.conffile. I tried hard, but couldn't get a TypeScript library to work to parse the HOCON config file format... so I eventually resorted to using (likely brittle) regex to grab the ClearML endpoint and API ke...
VictoriousPenguin97 I'm assuming the exact same server version ?
LudicrousParrot69 there is already
Task.add_tags
https://github.com/allegroai/clearml/blob/2d561bf4b3598b61525511a1a5f72a9dba74953e/clearml/task.py#L964
They inherit from one another, so it does make sense. Also the add_tags is on the "main" Task and not the backend parent
repeat it until they are all dead 🙂
Hi CharmingBeetle38
On the base task, do you see those arguments under the Configuration tab?
Also, if they are under Args section, you should add "Args/" prefix to the HP optimization (this is how you differentiate between the sections)
the Task scheduler itself is a Task. What we did is we added a new parameter section on the Task (the task.connect call), so that we can later clone and modify it and use the new value in runtime
(Task.connect will put the data from the Task/UI back into the dict when the agent is running the Scheduler)
Does that make sense?
WickedGoat98 give me a minute, I'm not sure it is not ClearML related
GrotesqueOctopus42
The problem is that when I import some function from a file in another folder, that task doesn't catch the files depencies.
Just to be clear, if this is another file, you have to have all the files in the same git repo for the agent to actually be able to fetch them on the remote machine.
If you have a mix of notebooks and code, you have to have the local code in a git repo,
Make sense ?
So clearml server already contains an authentication layer (JWT Token), and you do have a full user management on top:
https://clear.ml/docs/latest/docs/deploying_clearml/clearml_server_config#web-login-authentication
Basically what I'm saying if you add httpS on top of the communication, and only open the 3 ports, you should be good to go. Now if you really need SSO (AD included) for user login etc, unfortunately this is not part of the open source, but I know they have it in the scale/ent...
Hi ImpressionableRaven99
In the UI the re is a download button when you hover over the graph.
Are you asking if there is a programmatic interface?
What is the use case for all experiments ?
ohh AbruptHedgehog21 if this is the case, why don't you store the model with torch.jit.save and use Triton to run the model ?
See example:
https://github.com/allegroai/clearml-serving/tree/main/examples/pytorch
(BTW: if you want a full custom model serve, in this case you would need to add torch to the list of python packages)
(since you are using venv mode, if the cuda is not detected at startup time, it will not install the GPU version, as it has no CUDA support)
GiddyTurkey39 Hmm I'm assuming that by default it cannot access that IP range.
Are you using virtual-box for the VM?
EDIT:
Can I assume the machine running the VM (a.k.a the host) can access the trains-server ?
AttributeError: 'PosixPath' object has no attribute 'loc'
SarcasticSquirrel56 I'm assuming the artifacts is pandas and you forgot to either import before or add as requirement for the Task 🙂
This is causing the artifact .get() method to revert to returning the local path to the artifact, instead of actually de-serializing
(We should print a warning though, I'll make sure we do 🙂 )
EDIT: basically clearml failed to realize you also need pandas because it was never imported ...
cuda 10.1, I guess this is because no wheel exists for torch==1.3.1 and cuda 11.0
Correct
how can I enforce a specific wheel to be installed?
You mean like specific CUDA wheel ?
you can simple put the http link to the wheel in the "installed packages", it should work
That is odd ...
Could you open a GitHub issue?
Is this on any upload, how do I reproduce it ?
Martin, thank you very much for your time and dedication, I really appreciate it
My pleasure 🙂
Yes, I have latest 1.0.5 version now and it gives same result in UI as previous version that I used
Hmm are you saying the auto hydra connection doesn't work ? is it the folder structure ?
When is the Task.init is called ?
See example here:
https://github.com/allegroai/clearml/blob/master/examples/frameworks/hydra/hydra_example.py
Basically if I pass an arg with a default value of False, which is a bool, it'll run fine originally, since it just accepted the default value.
I think this is the nargs="?" , is that right ?
Hi DeliciousBluewhale87
This is the latest clearml-serving (stable release at GTC at the end of the month)
https://github.com/allegroai/clearml-serving/tree/dev
Generally speaking, clearml-sering is a control plane, preprocessing, ML inference, with Nvidia Triton for DL inference (fully transparent).
It allows you to spin an entire fully dynamic & scalable serving on top of k8s cluster. Once you spin the base containers, you can configure them live with a CLI, this includes adding new en...
Hi WickedStarfish97
As a result, I don’t want the Agent to parse what imports are being used / install dependencies whatsoever
Nothing to worry about here, even if the agent detects the python packages, they are installed on top of the preexisting packages inside the docker. That said if you want to over ride it, you can also pass packages=[]
Hi RoundMosquito25
The main problem here is there is no way to know before running the Task how much memory it would need ... And without that parameter maximizing GPUs is quite challenging. wdyt?
I assume the account name and key refers to the storage account credentials that you can from Azure Storage Explorer?
correct
HealthyStarfish45
No, it should work 🙂