ReassuredTiger98 can you send the full log?
Also, what's the clearml-agent version?
fyi: we fixed an issue where the default order of the conda repositories cause pytorch to be installed form the conda forge instead of the pytorch repo, making it the cpu version instead of the gpu version:
This is the correct conda repo orderL
https://github.com/allegroai/clearml-agent/blob/cb6bdece39751eaef975287609b8bab603f116e5/docs/clearml.conf#L66

Hi UnevenHorse85

As far as I understand, users use logins and passwords specified in config/apiserver.conf to access webserver UI and key/secret key from their local ~/clearml.conf to access apiserver.

Correct 🙂

access apiserver. What is the use of all other security keys

To be able to configure the SDK client (i.e. clearml package) from OS environment and not clearml.conf file

Oh I see, these are to secure your server (basically we recommend you replace the default key/secret 🙂 )
Make sense ?

I'm assuming you mean for the clients, right?

When are those keys used?

They are the default keys for internal access, basically just make up something, otherwise someoune could access the server with the default keys

clearml.conf is the file that 

clearml-init

 suppose to create, right?

Correct, specifically ~/clearml.conf

Are you hosting your own server? Is it on http://app.clear.ml ?

GiddyTurkey39
I would guess your VM cannot access the trains-server , meaning actual network configuration issue.
What are VM ip and the trains-server IP (the first two numbers are enough, e.g. 10.1.X.Y 174.4.X.Y)

GiddyTurkey39 Just making sure, you ran ping IP not ping ip:port right ?

We should probably add (set_task_type :))

Thank you so much @<1572395184505753600:profile|GleamingSeagull15> !

looks like your

faq.clear.ml

site is missing from your main sites sitemap files,

Thank you for noticing! I'll check with the webdevs

Also missing the

robots

meta tag on that site,

🙏

Last tip is to add a link on the

faq.clear.ml

site back to

clear.ml

for search index relevancy ( connects the two sites as being related in content...

Nice!

Hi

, It works if I dont specify the project name and just give the task name

But now it searches for it globally , which is not very stable:

Let me check why it fails to find the project...

The class documentation itself is also there under "References" -> "Trains Python Package"
Notice that due to a bug in the documentation (we are working on a fix) the reference part is not searchable in the main search bar

BroadMole98 thank you for noticing !
I'll make sure it is fixed (a few other properties are also missing there, not sure why, I'll ask them to take a look)

🙂

ElegantCoyote26 can you browse to http://localhost:8080 on the machine that was running the trains-init ?

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 ?

JitteryCoyote63 There is a basic elastic license that should always be there. If for some reason it was deleted/expired then the following command should fix it:
curl -XPOST ' http://localhost:9200/_xpack/license/start_basic '

Hi CharmingShrimp37
Go to Github to your newly forked repo, you should have a green button suggesting to take your branch and making it a PR. It is that simple 🙂

By default the remote link (i..e the Task you are creating with Task.create will have all the auto logging turned on)
For finer control we kind of assume you have Task.init inside your remote script, and then just pass add_task_init_call=False does that make sense ?
Do you think we should have a way to configure those auto_connect args when creating the Task?

None

Hi DisgustedDove53

Is redis used as permanent data storage or just cache?

Mostly cache (Ithink)

Would there be any problems if it is restarted and comes up clean?

Pretty sure it should be fine, why do you ask ?

I don't have the compose file, or at least can't seem to find it in 

/opt

you can manually take down all dockers with:
docker psthen docker stop <container id> for each container id

instead of the one that I want or the one of the env which it is started from.

The default is the python that is used to run the agent.
agent.ignore_requested_python_version = true agent.python_binary = /my/selected/python3.8

Hi WorriedParrot51
So I think what you need is to map your external code into the docker, is that correct?
Also you want to always set the PYTHONPATH.
You can achieve both by configuring the trains.conf:

Here you can always add a predefined environment and mount point, regardless of the docker image or other docker argument arguments:
https://github.com/allegroai/trains-agent/blob/master/docs/trains.conf#L98

Will this solve the issue?

Ohh yes, if you deleted the token then you have to recreate the cleaml.conf
BTW: no need to generate a token, it will last 🙂

Damn 😞

Scenario 1 & 2 are essentially the same from caching perspective (the face B != B` means they have different caching hashes, but in both cases are cached).
Scenario 3 is the basically removing the cache flag from those components.

Not sure if I'm missing something.

Back to the @<1523701083040387072:profile|UnevenDolphin73>

From decorators - when the pipeline logic is very straightforward ...

Actually I would disagree, the decorators should be used when the pipeline Logic is not a D...

JitteryCoyote63 is this still an issue?