
Reputation
Badges 1
85 × Eureka!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 ?
i understand.. its just if i have a docker image with correct env.. i would prefer if trains-agent can use that directly
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()
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
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