Hi @<1523703961872240640:profile|CrookedWalrus33> , metrics are considered as scalers, logs, plots, and the experiment objects themselves that are saved in the backend databases.
You must be reporting some very metric heavy experiments 🙂
Strange, maybe @<1523701087100473344:profile|SuccessfulKoala55> might have an idea
Hi @<1523707653782507520:profile|MelancholyElk85> , in Task.init()
you have the auto_connect_frameworks
Parameter.
Can you provide a snippet to try and reproduce?
You can add it manually to the requirements
WackyRabbit7 ,I am noticing that the files are saved locally, is there any chance that the files are over-written during the run or get deleted at some point and then replaced?
Also, is there a reason the files are being saved locally and not at the fileserver?
I couldn't manage to reproduce it on my end. But also in my cases it always saves the files to the fileserver. So I'm curious what's making it save locally in your case
Hi GentleSwallow91 ,
ClearML has seamless integration with git. ClearML automagically detects the repository the code was run from, specific commit AND uncommitted changes. Each experiment has it's git data logged individually. You can see this in the 'Execution' section in the webUI.
Hi @<1523701283830108160:profile|UnsightlyBeetle11> , I think you can store txt artifacts so you can store the string there. If it's not too long, you can even fetch it from the preview
What about if you specify the repo user/pass in clearml.conf?
I think it removes the user/pass so it wouldn't be shown in the logs
Hi @<1585078763312386048:profile|ArrogantButterfly10> , does the controller stay indefinitely in the running state?
And when you run it again under exactly the same circumstances it works fine?
What is the best way to achieve that please?
I think you would need to edit the webserver code to change iterations to epochs in the naming of the x axis
Yeah, I understand the logic of wanting this separation of iteration vs epoch since they sometimes correlate to different 'events'. I don't think there is an elegant way out of the box to do it currently.
Maybe open a GitHub feature request to follow up on this 🙂
I would suggest structuring everything around the Task object. After you clone and enqueue the agent can handle all the required packages / environment. You can even set environment variables so it won't try to create a new env but use the existing one in the docker container.
Hi @<1539417873305309184:profile|DangerousMole43> , I would suggest opening developer tools (F12) and then doing the specific search you're interested in through the UI. Then you can simply send the same via the REST API
@<1523703961872240640:profile|CrookedWalrus33> , pip instal clearml==1.5.3rc1
Hi @<1543766544847212544:profile|SorePelican79> , ClearML can certainly do that. For this you have the Datasets feature.
None
This will allow you to version and track your data super easily 🙂
@<1570220858075516928:profile|SlipperySheep79> , you can use top
or htop
to see running processes on your machine...
Hi @<1544853695869489152:profile|NonchalantOx99> , can you run that docker with the docker run
command?
I think this is what you're looking for
EcstaticBaldeagle77 , please lower all the dockers then run the following commands and then try raising them again.
` sudo mkdir -p /opt/clearml/data/elastic
sudo mkdir -p /opt/clearml/data/mongo/db
sudo mkdir -p /opt/clearml/data/mongo/configdb
sudo mkdir -p /opt/clearml/data/redis
sudo mkdir -p /opt/clearml/logs
sudo mkdir -p /opt/clearml/config
sudo mkdir -p /opt/clearml/data/fileserver
sudo chown -R 1000:1000 /opt/clearml `
Also, where did you find the instructions with 'trains' in it?
Hi VexedElephant56 , does it fail when it runs on the agent?
Hi @<1523701099620470784:profile|ElegantCoyote26> , what happens if you define the cache size to be -1?
Can you look in the UI if the execution parameters were logged?
StaleButterfly40 Hi!
You could clone the original task and edit the input model of the new task as the output model of the previous task 🙂
You can use the API to call tasks.get_by_id
and get that specific information. In the response it sits indata.tasks.0.completed
BTW - did the agent print out anything? Which version of clearml-agent are you using?
By default the agent will try to install packages according to what was logged in the 'installed packages' section of the task in 'execution' tab