LazyLeopard18 well done on locating the issue.
Yes Docker on Windows is a bit flacky...
MysteriousBee56 there is no way to tell the trains-agent to pull from local copy of your repository...
You might be able to hack it, if you copy the entire local repo to the trains-agent version control cache. would that help you?
Hi GreasyLeopard35
I try to resume a stopped or aborted parameter optimization experiment,
How are you continuing the HPO? are you runing everything locally? is this with an agent? are you seeing the '[0, 0]' value on the configuration when launching the HPO or when continuing it ?
FreshReindeer51
Could you provide some logs ?
if fails duringÂ
add_step
 stage for the very first step, becauseÂ
task_overrides
 contains invalid keys
I see, yes I guess it it makes sense to mark the pipeline as Failed 🙂
Could you add a GitHub issue on this behavior, so we do not miss it ?
First let's verify with the manual change, but yes
i hope can run in same day too.
Fix should be in the next RC 🙂
See the last package in the package list:
- wget~=3.2
- trains~=0.14.1
- pybullet~=2.6.5
- gym-cartpole-swingup~=0.0.4
- //github.com/ajliu/pytorch_baselines
WickedBee96 the return value of dataset.get_local_copy is the Folder where all your files are located, Not the filename itself 🙂
web-server seems okay, could you send the logs from the api-server?
Also if you can, the console logs from your browser, when you get the blank screen. Thanks.
Nice!!!
Are you aware of a limitation of "/events.get_task_events" preventing from fetching some of the images stored on the server
Are you saying you see them in the UI, but cannot access them via the API ?
(this would be strange as the UI is firing the same API requests to the back end)
MotionlessCoral18 I think there is a fix in the latest clearml-agent RC 1.4.0rc0 can you test and update if your are still having this issue?
regrading the actual artifact access, this is the usual Task.artifacts access: see example here:
https://github.com/allegroai/clearml/blob/master/examples/reporting/artifacts_retrieval.py
MuddySquid7
are you saying that for some reason the models pick the artifacts ? Is that reproducible ? (they are two different things)
Can you see the df.pkl on the Models section of the Task (in the UI) ?
LOL AlertBlackbird30 had a PR and pulled it 🙂
Major release due next week after that we will put a a roadmap on the main GitHub page.
Anything specific you have in mind ?
. So to conclude: it has to be executed manually first, then with trains agent?
Yes, that said, as you mentioned, you can always edit the "installed packages" once manually, from that point you are basically cloning the experiment, including the "installed packages" so it should work if the original worked.
Make sense ?
in the UI the installed packages will be determined through the code via the imports as usual ...
This is only in a case where a user manually executed their code (i.e. without trains-agent), then in the UI after they clone the experiment, they can click on the "Clear" button (hover over the "installed packages" to see it) and remove all the automatically detected packages. This will results in the trains-agent using the "requirements.txt".
Generally speaking, for the exact reason if you are passing a list of files, or a folder, it will actually zip them and upload the zip file. Specifically to pipeline it should be similar. BTW I think you can change the number of parallel upload threads in StorageManager, but as you mentioned it is faster to zip into one file. Make sense?
Do you have to have a value there ?
Hi SuperiorCockroach75
You mean like turning on caching ? What do you mean by taking too long?
In the side bar you get the title of the graphs, then when you click on them you can see the diff series on the graphs themselves
Hi UnevenBee3
the optuna study is stored on the optuna class
https://github.com/allegroai/clearml/blob/fcad50b6266f445424a1f1fb361f5a4bc5c7f6a3/clearml/automation/optuna/optuna.py#L186
And actually you could store and restore it
https://github.com/allegroai/clearml/blob/fcad50b6266f445424a1f1fb361f5a4bc5c7f6a3/clearml/automation/optuna/optuna.py#L104
I think we should improve the interface though, maybe also add get_study(), wdyt?
Thanks for pinging OutrageousGiraffe8
I think I was able to reproduce.
model is saved to the clearml as an output model when
b
is not a dictionary.
How did you make the example work with the automagic ?
quick video of the search not working
Thank you! this is very helpful, passing along to front-end guys 🙂
and ctrl-f (of the browser) doesn’t work as lines below not loaded (even when you scroll it will remove the other lines not visible, so you can’t ctrl-f them)
Yeah, that's because they are added lazily