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978 × Eureka!Hi SoggyFrog26 , https://github.com/allegroai/clearml/blob/master/docs/datasets.md
Hi SuccessfulKoala55 , thanks for the idea! the function isn’t called with atexit.register() though, maybe the way the agent kills the task is not supported by atexit
Hi SuccessfulKoala55 , super that’s what I was looking for
TimelyPenguin76 That sounds amazing! will there be a fallback mechanism as well? often p3.2xlarge are on shortage, would be nice to define one resources req as first choice (eg. p3.2xlarge) -> if not available -> use another resources req (eg. g4dn)
I don't think there is an example for this use case in the repo currently, but the code should be fairly simple (below is a rough draft of what it could look like)
` controller_task = Task.init(...)
controller_task.execute_remotely(queue_name="services", clone=False, exit_process=True)
while True:
periodic_task = Task.clone(template_task_id)
# Change parameters of {periodic_task} if necessary
Task.enqueue(periodic_task, queue="default")
time.sleep(TRIGGER_TASK_INTERVAL_SECS) `
Actually was not related to clearml, the higher level error causing this one was (somewhere in the stack trace): RuntimeError: module compiled against API version 0xe but this version of numpy is 0xd
-> wrong numpy version
This is no coincidence - Any data versioning tool you will find are somehow close to how git works (dvc, etc.) since they aim to solve a similar problem. In the end, datasets are just files.
Where clearml-data stands out imo is the straightfoward CLI combined with the Pythonic API that allows you to register/retrieve datasets very easily
Hi AgitatedDove14 , coming by after a few experiments this morning:
Indeed torch 1.3.1 does not support cuda, I tried with 1.7.0 and it worked, BUT trains was not able to pick the right wheel when I updated the torch req from 1.3.1 to 1.7.0: It downloaded wheel for cuda version 101. But in the experiment log, the agent correctly reported the cuda version (111). I then replaced the torch==1.7.0 with the direct https link to the torch wheel for cuda 110, and that worked (I also tried specifyin...
(I use trains-agent 0.16.1 and trains 0.16.2)
Interestingly, I do see the 100gb volume in the aws console:
did you try with another availability zone?
CostlyOstrich36 , this also happens with clearml-agent 1.1.1 on a aws instance…
CostlyOstrich36 I updated both agents to 1.1.2 and still go the same problem unfortunately. Since I can download the full log file from the Web UI, I guess the agents are reporting correctly?
Could it be that the elasticsearch does not return all the requested logs when it is queried from the WebUI to display it in the console?
Now that I think about it, I remember that on the changelog of the clearml-server 1.2.0 the following is listed:
` Fix UI Workers & Queues and Experiment Table pages ...
My use case it: in a spot instance marked for termination after 2 mins by aws, I want to close a task and prevent the clearml-agent to pick up a new task after.
Sure 🙂 Opened https://github.com/allegroai/clearml/issues/568
Thanks a lot AgitatedDove14 !
Ok, I could reproduce with Firefox and Chromium. Steps:
Add creds (either via the popup or in the settings) Go the /settings/webapp-configuration -> Creds should be there Hit F5 Creds are gone
Hi SuccessfulKoala55 , Yes it’s for the same host/bucket - I’ll try with a different browser
it also happens without hitting F5 after some time (~hours)
Thats how I would do it, maybe guys from allegro-ai can come up with a better approach 👍
AgitatedDove14 So in the https://pytorch.org/ignite/_modules/ignite/handlers/early_stopping.html#EarlyStopping class I see that some infos are logged (in the __call__
function), and I would like to have these infos logged by clearml
Hi AgitatedDove14 , Here is the full log.
Both python versions (local and remote) are python 3.6 Locally (macos), I get pytorch3d== (from versions: 0.0.1, 0.1.1, 0.2.0, 0.2.5, 0.3.0, 0.4.0, 0.5.0)
Remotely (Ubuntu), I get (from versions: 0.0.1, 0.1.1, 0.2.0, 0.2.5, 0.3.0)
So I guess it’s not related to clearml-agent really, rather pip that cannot find the proper wheel for ubuntu for latest versions of pytorch3d, right? If yes, is there a way to build the wheel on the remote machine...
Could you please share the stacktrace?
Hi PompousParrot44 , you could have a Controller task running in the services queue that periodically schedules the task you want to run