ah ok.. anyway to avoid it or change it on my side

looking at the above link, it seems i might be able to create it with some boilerplate as it has concept of parent and child... but not sure how status checks and dependency get sorted out

yes delete experiments which are old or for some other reason are not required to keep around

it may be that i am new to trains but in my normal notebook flow they both are images and i as trains user expected it to be under the Plot section as i think this is an image.. as in nutshell all matplotlib plots display data as an image 🙂

AgitatedDove14 it seems uploading artifact and uploading models are two different things when it comes to treating fileserver... as when i upload artifact it works as expected but when uploading model using outputmodel class, it wants output_uri path.. wondering how can i as it to store it under the fileserver like artifacts LightGBM.1104445eca4749f89962669200481397/artifacts/Model%20object/model.pkl

looking at the code https://github.com/allegroai/trains/blob/65a4aa7aa90fc867993cf0d5e36c214e6c044270/trains/model.py#L1146 this happens when storage_uri is not defined where as i have this under trains.conf so task should have it ?

seems like setting to fileserver_url did the trick

AgitatedDove14 when using OutputModel(task, name='LightGBM model', framework='LightGBM').update_weights(f"{args.out}/model.pkl") i am seeing this in the logs No output storage destination defined, registering local model /tmp/model.pkl when i got to trains UI.. i see the model name and details but when i try to download it point to the path file:///tmp/model.pkl which is incorrect wondering how to fix it

so just under models dir rather than artifact... any way to achieve this or i should just treat it as artifact ?

with this layout.. it didn't work earlier

i understand.. its just if i have a docker image with correct env.. i would prefer if trains-agent can use that directly

0.15.1-367

this looks good... also do you have any info/eta on next controller/service release you mentioning

trains is run using docker-compose allegroai/trains-agent-services:latest and allegroai/trains:latest

this is when executed from directly with task.init()

thanks for your help AgitatedDove14

Cross-Origin Request Blocked: The Same Origin Policy disallows reading the remote resource at http://localhost:8081/Trains%20Test/LightGBM.56ca0c9c9ebf4800b7e4f537295d942c/metrics/LightGBM%20Feature%20Importance%20above%200.0%20threshold/plot%20image/LightGBM%20Feature%20Importance%20above%200.0%20threshold_plot%20image_00000000.png . (Reason: CORS request did not succeed).

ok will report back

while you guys gonna work on it.. just a small feature addition to it.. it would be cool to have a DAG figure which shows how models are linked under this task and ability to just click a circle in that DAG figure to navigate to given task... i think it will be very useful UX 🙂

AgitatedDove14 Morning... so what should the value of "upload_uri" to set to, fileserver_url e.g. http://localhost:8081 ?

TimelyPenguin76 is there any way to do this using UI directly or as a schedule... otherwise i think i will run the cleanup_service as given in docs...

you replied it already.. it was execute_remotely called with exit_true argument

thanks

i don't need this right away.. i just wanted to know the possibility fo dividing the current machine into multiple workers... i guess if its not readily available then may be you guys can discuss to see if it makes sense to have it on roadmap..

TimelyPenguin76 also is there any reason for trating show and imshow differently

yeah i still see it.. but that seems to be due to dns address being blocked by our datacenter

i mean linking more in UI.. as when i go to model detail page, i can see that a given experiment created this model and click on that to see its detail... so something similar to that for ensemble models

ok will give it a try and let you know

any example in the repo which i can go through

thanks... i was just wondering if i overlooked any config option for that... as cpu_set might be possibility to for cpu