i could use k8s but thats bit overkill currently

its not that they are blank.. whole page is blank including plotly plots

whereas i am using simple matplotlib now

as if its couple of weeks away.. i can wait

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... is there any way to enforce using a given system wide env.. so agent doesn't need to spend time with env. creation

seems like CORS issue in the console logs

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

that seems like a bit of extra thing a user needs to bother about.. better deployment model should be that its part of api-server deployment and configurable from UI itself.. may be i am asking too much 😛

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

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

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..

in the above example task id is from a newly generated task like Task.init() ?

AgitatedDove14 it seems i am having issues when i restart the agent... it fails in creating/setting up the env again... when i clean up the .trains/venv-builds folder and run a job for agent.. it is able to create the env fine and run job successfully.. when i restart the agent it fails with messages like
` Requirement already satisfied: cffi@ file:///home/conda/feedstock_root/build_artifacts/cffi_1595805535531/work from file:///home/conda/feedstock_root/build_artifacts/cffi_1595805535...

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 🙂

thanks for your help AgitatedDove14

is it because of something wrong with this package build from their owner or something else

i am simply proxying it using ssh port forwarding

screenshot

will report back

as when it run first time after .trains/venv-build cleaning, it output this message for this package - pycparser @ file:///home/conda/feedstock_root/build_artifacts/pycparser_1593275161868/work wondering why it specify this package as for most other packages it just prints the version number

ok will report back

i know it support conda.. but i have another system wide env which is not base .. say ml so wondering if i can comnfigure trains-agent to use that... not standard practice but just asking if it is possible

the use case i have is to allow people from my team to run their workloads on set of servers without stepping over each other..

allegroai/trains image hash f038c8c6652d

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

simply changing to show doesn't work in my case as i am displaying CM.. what about if i use matshow

my use case is more like 1st one where run the training at a certain given schedule

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