Hmm, after connecting with the VPN again and using ctrl + F5, there is no complaint anymore. Although a colleague uploaded a Seaborn plot, but it's still not showing up, which I thought was fixed in the new version?
The plots page is pure white of that experiment, and not the usual "No chart data" if no plot was uploaded.

Aah, I couldn't find it under PLOTS, but indeed it's there under DEBUG SAMPLES.

` trains-elastic exited with code 1
trains-elastic | OpenJDK 64-Bit Server VM warning: Option UseConcMarkSweepGC was deprecated in version 9.0 and will likely be removed in a future release.
trains-elastic | {"type": "server", "timestamp": "2020-11-02T08:04:57,699Z", "level": "ERROR", "component": "o.e.b.ElasticsearchUncaughtExceptionHandler", "cluster.name": "trains", "node.name": "trains", "message": "uncaught exception in thread [main]",
trains-elastic | "stacktrace": ["org.elast...

Ok it's that the user group also has to be root. I ran the following:
sudo chmod 775 -R /opt/trains/ sudo chown -R root:root /opt/trainsand it works.

It seems that it has to be 775 with both user and group as root. E.g. 771 does not work, because than the docker command has to be used with sudo (if I want to use my default sudo-user account)

AppetizingMouse58 If I:
sudo chmod 771 -R /opt/trains/(taking all permission away from other except execution)
The file permission error comes back, even though everything is under the root user.

Is it possible it's not just about the root user, but also the root group?

Even when I do a "clean install" (renamed the /opt/trains ) folder and followed the instructions to setup TRAINS, the error appears.

Thank you for your impression! I get a bit more of a Airflow feel for running many tasks to train models with different parameters, which is a good thing.

I'm still skimming through the documents, but TRAINS documentation on how models are stored is a bit vague to me. The https://allegro.ai/docs/examples/examples_models/ only quickly mentions that you can set an output location. Which is a bit shallow compared with the https://mlflow.org/docs/latest/model-registry.html . Any good resource...

FrothyDog40 Thank you for your reply. I agree that MLflow's serving solution is not going to be of much help for real deployment. However, to me the advantage of quickly setting-up an API access point with just 1 line of code helps with some internal trying out. To colleague: "Hey, this new model seems to do good, want to give it a try?".

I've setup my own Docker container with Sanic (like Flask) and indeed it's not too difficult. However, you'll still hit issues like " https://stackoverflo...

I see that Trains has been removed 2 days ago: https://github.com/PyTorchLightning/pytorch-lightning/commit/41f5df18a4b96ce753263fadd9c27f1d30e5d7a2

and instead has been moved to Bolts: https://github.com/PyTorchLightning/pytorch-lightning-bolts

However, I cannot find a reason why only Trains has been moved?

Would have been nice if they would have reached out to you guys/gals before removing Trains 😅

Thank you 😉

Ok, thanks for the info 🙂

What's the abc issue ? Something Lightning team is responsible for?

Port 8008 cannot be changed apparently:
https://allegroai-trains.slack.com/archives/CTK20V944/p1592478619463200?thread_ts=1592476990.463100&cid=CTK20V944

The relevant commit that deleted the trains logger from Bolts:
https://github.com/PyTorchLightning/pytorch-lightning-bolts/commit/91393eaa2751dc58c26cec6581aba19d63fa42f8

trains ( 0.15.1-367 ) appears to be the version, same as you. Thank you. Appears Trains is up to date.

Apparently there should be 6 of them:

AgitatedDove14 Done!

After a while I get the message:

New version available
Click the reload button below to reload the web page

I click the "RELOAD" button and the "newer version" message disappear. However, some plots still don't show up (fixed in 0.15.1). If I refresh the TRAINS webinterface, the "newer version" message appears again.

That's useful to know! But actually in this case I want to just test if the code works (run 2 epochs and see if it works). I don't want this to be logged, so I don't Task.init in those cases.
I don't want the code to crash on Trains in those cases.

I see that Task.current_task() returns None if no task is running, so I can use that with an if statement 🙂

It's my colleague's experiment (with scikit-learn), so I'm not sure about the details.

TimelyPenguin76 The colleague is actually a her, but she replied that how it's looking now is correct? We're actually both already passed our work time (weekend :D), so we'll take a look at it after the weekend. If there is still something wrong, I'll get back to you. Thanks for offering help though :)

First I tried without build, but same problem. --build just means that it will re-download all layers instead of using the ones already cached.

Exactly, so that remapping of port 8080 should not be the reason for this issue

AgitatedDove14 TB has the confusion matrix like this:

/opt/trains/ :

` $ ls -al
total 120
drwxrwsrwx 7 root miniconda 4096 Nov 2 18:15 .
drwxr-xr-x 15 root root 4096 Oct 5 15:12 ..
drwxrwxrwx 38 root miniconda 4096 Nov 2 18:15 agent
drwxrwxrwx 2 root miniconda 4096 Jun 19 14:43 config
drwxrwxrwx 8 root miniconda 4096 Nov 2 18:11 data
-rwxrwxrwx 1 root miniconda 4383 Jun 19 14:46 docker-compose_0.15.0.yml
-rwxrwxrwx 1 root miniconda 4375 Jun 26 15:06 docker-compose_0.15.1.yml
-rwxrwxrwx 1 root miniconda 4324 Nov 2 18:...

AgitatedDove14 There is only a events.out.tfevents.1604567610.system.30991.0 file.
If I open this with a text editor, most is unreadable, but I do find a the letters "PNG" close to the name of the confusion matrix. So it looks like the image is encoded inside the TB log file?

The only change I made in the .yml file was:
` ports:

• "8080:80" to ports:
• "8082:80" `
  I already had something running on 8080, but since it's the trains-apiserver and not the webserver, this shouldn't be an issue.

Thank you

Ah my bad, it seems I had to run
docker-compose -f /opt/trains/docker-compose.yml pullonce. I quickly tried trains like half a year ago, so maybe it was using the old images? However, I thought --build would take care of that.

Now it's working 🙂