I think that is good enough

HighOtter69 , let me check something

Hi SmallDeer34
ClearML automagical logging will work on the current python process. But in your example yyour Bash is running another python script (that has nothing to do with the original notebook), hence clearml automagic is not aware of it (i.e. it cannot "patch" the tensorboard calls).
In order to make it work.
you should do something like:
from joeynmt import train train.main(...)Or something similar 🙂
Make sense ?

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?

BoredHedgehog47 I tried changing the order of imports on the sample code I shared before, it worked in both cases ...

I basically moved the Task.init() call below the imports

Okay that is odd, can you copy pate the before/after of the import, so we can fix that?!

Maybe before everything else, can you share some background on the rational if starting a new sub process?

BoredHedgehog47 can you test this one? Is it close to your code ?

ReassuredTiger98 do you know if tensorboard (not tensorboardX) also supports gif there ?

MelancholyBeetle72 I think we collect them in Issue 81 on GitHub, feel free to add it if it is missing 🙂
https://github.com/allegroai/clearml/issues/81

Hi WickedBee96

How can I do that?

clearml-task
https://clear.ml/docs/latest/docs/apps/clearml_task#what-is-clearml-task-for

I know this way to run it in the agent only by enqueue the draft after running it on my local machine so is there another way?

Or maybe are you looking for task.execute_remotely
https://clear.ml/docs/latest/docs/references/sdk/task#execute_remotely

Hi @<1571308003204796416:profile|HollowPeacock58>
could you share the full log ?

Ok..so I should generally avoid connecting complex objects? I guess I would create a 'mini dictionary' with a subset of params, and connectvthis instead.

In theory it should always work, but this specific one fails on a very pythonic paradigm (see below)

from copy import copy
an_object = copy(object)

A good rule of thumb is to connect any object/dict that you want to track or change later

@<1571308003204796416:profile|HollowPeacock58> seems like an internal issue copying this object config.model
This is a complex object, and it seems that for some reason
None

As a workaround just do not connect this object. it seems you cannot pickle it / copy it (see GH issue)

OddAlligator72 FYI, in you current code you can always do
if use_trains: from trains import Task Task.init()Might be easier 😉

Yes, I think you are correct, verified on Firefox & Chrome. I'll make sure to pass it along.
Thanks SteadyFox10 !

OddAlligator72 FYI you can also import / export an entire Task (basically allowing you to create it from scratch/json, even without calling Task.create)
Task.import_task(...) Task.export_task(...)

now that I know I could use the right click I'll use it like in google drive etc.

That was the initial thought, but I think right clicking on a web page is not you "go to action", especially for Mac ppl ...

Hmm I guess that now that you mention it, not that obvious when I'm on a Mac as well, maybe we should have the archive button at the bottom as well..
SteadyFox10 What do you think?

trains was not able to pick the right wheel when I updated the torch req from 1.3.1 to 1.7.0: It downloaded wheel for cuda version 101.

Could you send a log, it should have worked 😞

OddAlligator72 okay, that is possible, how would you specify the main python script entry point? (wouldn't that make more sense rather than a function call?)

How do you determine which packages to require now?

Analysis of the actual repository (i.e. it will actually look for imports 🙂 ) this way you get the exact versions you hve, but nit the clutter of the entire virtual environment

SteadyFox10 With pleasure 🙂
BTW: you can retrieve the Task id from its name with
Task.get_tasks(project_name='my project', task_name='my task name')See https://allegro.ai/docs/task.html?highlight=get_tasks#trains.task.Task.get_tasks

Hi MagnificentPig49 unfortunately it's only in the trains-server docker, we are working on making it "presentable" and uploading it to it's repo.
It's written in Angular (v8 I think). Do you want to help out, it will definitely incentive the guys to tidy up the code and upload it :)

MagnificentPig49 quick update, front-end guys updated me that with the next trains-server update they will have the web client code available on the repository , ETA probably mid May or so :)

MagnificentPig49 that's a good question, I'll ask the guys 🙂
BTW, I think the main issues is actually making sure there is enough documentation on how to compile it...
Anyhow I'll update here

You can also see the code there, could you run a quick test against the demo-server, this might be a UI issue that was fixed in the last version.

CloudyHamster42
RC probably in a few days, but notice that it will just remove the warnings, I still can't reproduce the double axis issue.

It will be helpful if you could send a small script to reproduce the problem.

Maybe this example code can help ? https://github.com/allegroai/trains/blob/master/examples/manual_reporting.py

FranticCormorant35 As far as I understand what you have going is a multi-node setup, that you manage yourself. Something like Horovod Torch distributed or any MPI setup. Since Trains support all of the above standard multi-node. The easiest way is to do the following:

On the master Node set OS environment:
OMPI_COMM_WORLD_NODE_RANK=0Then on any client node:
OMPI_COMM_WORLD_NODE_RANK=unique_client_node_numberIn all processes you can Call Task.init - with all the automagic kicking in....

so if i plot image with matplot lib..it would not upload? i need use the logger.

Correct, if you have no "main" task , no automagic 😞

so how can i make it run with the "auto magic"

Automagic logs a single instance... unless those are subprocesses, in which case, the main task takes care of "copying" itself to the subprocess.

Again what is the use case for multiple machines?

Correct, and that also means the code the runs is not auto-magically logged.