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

AgitatedDove14 Done!

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

/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:...

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 :)

Ok, it was indeed something with permission. When I chown everything to root (1000) and chmod 777 it worked. 777 is of course not desirable, so I'm going to narrow it down now.

Thank you for the reply! The migration indeed created this elastic_7 folder.

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.

` 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...

With PyTorch Lightning, I only use this line at the beginning of a Jup Notebook:
Task.init(project_name=project_name, task_name=task_name)The code to log the confusion matrix is in some .py file though that does not have any Trains code.

Is it possible to log it in a TB compatible way, that will be automatically picked up by Trains? I prefer to keep the .py Trains free.

Hi AgitatedDove14
Not using trains-agent yet. Just using PyTorch Lightning in Jupyter Notebook with as Logger Trains.
So I'm talking about runtime and GPU usage in experiments.

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:

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.

Thank you 😉

Same problem with 775

It seems to be related to trains-apiserver , based on the log inside the Docker compose:

` trains-apiserver | [2020-11-10 04:40:14,133] [8] [ERROR] [trains.service_repo] Returned 500 for queues.get_next_task in 20ms, msg=General data error: err=('1 document(s) failed to index.', [{'index': {'_index': 'queue_metrics_d1bd92a3b039400cbafc60a7a5b1e52b_2020-11', '_type': '_doc', '_id': 'rkh0sHUBwyiZSyeZUAov', 'status': 403, 'error': {'type': 'cluster_block_exception', 'reason': 'index [queu...

SuccessfulKoala55 Thank you. I stared myself dead at trains-apiserver , but by coincidence I found this message:
` trains-elastic | {"type": "server", "timestamp": "2020-11-10T06:11:08,956Z", "level": "WARN", "component": "o.e.c.r.a.DiskThresholdMonitor", "cluster.name": "trains", "node.name": "trains", "message": "flood stage disk watermark [95%] exceeded on [QyZ2i1mxTG6yR7uhVWjV9Q][trains][/usr/share/elasticsearch/data/nodes/0] free: 43.3gb[4.7%], all indices on this node will be ...

Is there anyway how I can figure out in the webinterface what version of Trains is actually running?

AgitatedDove14 Thank you, this code example is very helpful!

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

Ok, thanks for the info 🙂

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

Ah I see, it's based on a naming scheme, thanks. Sorry I forgot to link the tutorial I was looking at: https://allegro.ai/docs/examples/frameworks/pytorch/pytorch_tensorboard/

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?

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...

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.

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...

So if I want it under plots, I would need to call e.g. report_confusion_matrix right?

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?

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