LudicrousDeer3 when using Logger you can provide 'iteration' argument, is this what you are looking for?

does that mean that it will install my package lastly?

It will install last, but not because it was last in the list, but because it is local/repo package 🙂

Can I do in setup.py the modifications to the tensorflow code?

You mean like have the changes as part of the "uncommitted changes" section ?

As long as the ~/.aws is configured, I "think" it should work. (I'm assuming you are referring IAM roles?)
I would also suggest using the latest aws_autoscaler (basically it adds a CLI wizard, I think the functionality is very much the same)

SubstantialElk6 on the client side?

When you are running the base-task, are you proving any arguments to it?
Can you share the "execution" Tab? and the Args tab of the base-task ?

Hi SubstantialElk6

noted that clearml-serving does not support Spacy models out of the box and

So this is a good point.

To add any pissing package to the preprocessing docker you can just add them in the following environment variable here: https://github.com/allegroai/clearml-serving/blob/d15bfcade54c7bdd8f3765408adc480d5ceb4b45/docker/docker-compose.yml#L83
EXTRA_PYTHON_PACKAGES="spacy>1"
Regrading a custom engine, basically this is supported with --engine custom
you c...

Can you share the modified help/yaml ?
Did you run any specific migration script after the upgrade ?
How many apiserver instances do you have ?
How did you configure the elastic container? is it booting?

Ohh okay something seems to half work in terms of configuration, the agent has enough configuration to register itself, but fails to pass it to the task.
Can you test with the latest agent RC:
0.17.2rc4

SubstantialElk6 "Execution Tab" scroll down you should have "Installed Packages" section, what do you have there?

Hi @<1523704207914307584:profile|ObedientToad56>

hat would be the right way to extend this with let's say a custom engine that is currently not supported ?

as you said 'custom' 🙂
None
This is actually a custom engine, (see (3) in the readme, and the preprocessing.py implementing it) I think we should actually add a specific example to custom so this is more visible. Any thoughts on what would...

HungryArcticwolf62 the new clearml-serving is almost out (eta late next week), you can already start playing here:
https://github.com/allegroai/clearml-serving/tree/dev
Example:
train+serve
https://github.com/allegroai/clearml-serving/tree/dev/examples/sklearn

Hi @<1628565287957696512:profile|AloofBat92>
Yeah the name is confusing, we should probably change that. The idea is it is a low code / high code , train your own LLM and deploy it. Not really chatgpt 1:1 comparison, more like, GenAI for enterprises. make sense ?

Hi ResponsiveCamel97
The agent generates a new configuration file to be mounted into the docker, with all the new folders as they will be seen inside the docker itself. One of the changes is the system_site_packages as inside the docker we want the new venv to inherit everything from the docker system installed packages.
Make sense ?

Hi JitteryCoyote63
FYI: https://allegro.ai/docs/examples/reporting/scatter_hist_confusion_mat_reporting/#2d-scatter-plots

Hmm and you are getting empty list for thi one:

server_info['url'] = f"http://{server_info['hostname']}:{server_info['port']}/"

well cudnn is actually missing from the base image...

but I still clearml-agent will raise the same error

which one?

Hi @<1569858449813016576:profile|JumpyRaven4>

task.add_requirements()

This is the problem, if you look closely this is a class method, meant for helping the Task.init better capture python packages, it does Not change the task requirements.
To do that, use " task.set_packages "

basically PVC for all the DBs 🙂

callbacks.append( tensorflow.keras.callbacks.TensorBoard( log_dir=str(log_dir), update_freq=tensorboard_config.get("update_freq", "epoch"), ) )Might be! what's the actual value you are passing there?

I think the main difference is that I can see a value of having access to the raw format within the cloud vendor and not only have it as an archive

I see it does make sense.
Two options, one, as you mentioned use the ClearML StorageManager to upload the files, then register them as external links with Dataset.
Two, I know the enterprise tier has HyperDatasets, that are essentially what you describe, with version control over the "metadata" and "raw storage" on the GCP, including the ab...

Good point!
I'll make sure we do 🙂

the only port configurations that will work are 8080 / 8008 / 8081

Nice! So out of curiosity why didn't it work this time and you had to do it manually?

EnviousStarfish54

and the 8 charts are actually identical

Are you plotting the same plot 8 times?

Hi @<1619867994005966848:profile|HungryTurtle13>

I'm using Python's joblib library and the Parallel class to run an experiment in multiple parallel threads.

I believe joblib creates subprocesses not threads, but yes you are correct,
Basically once Task.init is called, every forked/spawned process will be automatically logged to the main process Task (you can, and probably should call either Task.init or Task.current_task() from the forked processes, but this is just a detial)
The mai...

UnevenDolphin73

we'd like the remote task to be able to spawn new tasks,

Why is this an issue? this should work out of the box ?

@<1540142651142049792:profile|BurlyHorse22> do you mean the one refereed in the video ? (I think this is the raw data in kaggle)

Hi JitteryCoyote63
The NVIDIA_VISIBLE_DEVICES is set automatically for the process the trains-agent spins, so from your code, it is transparent, you can only "see" GPU 0.
(Obviously not using docker you can forcefully change the OS environment in runtime, but you should avoid that ;))

ShallowCat10 Of course it is 🙂