When I push a job to an agent node, i got this error.
"Error response from daemon: network None not found"

Hi, sorry for the delayed response. Btw, all the pods are running all good.

Hi, will proceed to close this thread. We found some issue with the underlying docker in our machines. We've have not shifted to another k8 of ec2 instances in AWS.

kkie.. Will try it .. tks

Hi AgitatedDove14 , Thanks for the explanation .
python k8s_glue_example.py --queue high_priority_q --ports-mode --num-of-services 10 python k8s_glue_example.py --queue low_priority_q --ports-mode --num-of-services 2Would the above be a good way to simulate the below ?
clearml-agent daemon --queue high_priority_q low_priority_q

I just had to set up the clearml-agent on my machine. Closing this issue.

Is this some sort of polling ?
End of the day, we are just worried whether this will hog resources compared to a web-hook ? Any ideas

Hi TimelyPenguin76 ,
Instead of running the hyper_parameter_optimizer.py, I tried running the base_template_keras_simple.py instead.. It seems that I didnt use the GPU, however when i ssh into clearml-glueq-id-ffaf55c984ea4dbfb059387b983746ba:gpuall pod, and ran nvidia-smi, it gave an output.

The above screenshot is from my local settings... My agents run in the k8s system (like in a pod)

However, I am able to get it to work, if I launch a clearml-agent outside the kubernetes ecosystem.

kkie..now I get it.. I set up the clearml-agent on an EC2 instance. and it works now.
Thanks

` Could not load dynamic library 'libcupti.so.11.0'; dlerror: libcupti.so.11.0: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/nvidia/lib:/usr/local/nvidia/lib64
2021-03-11 09:11:17.368793: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcupti.so'; dlerror: libcupti.so: cannot open shared object file: No such file or directory; LD_LIBRARY_PATH: /usr/local/nvidia/lib:/usr/local/nvidia/lib64
2021-03-11 09...

Hi AgitatedDove14 , This isnt the issue. With or without specifying the queue, I have this error when I do the "Create version" as compared to the "Init version".
I wonder whether this is some issue with using the Create version together with execute_remotely() ..

Hi SuccessfulKoala55
I have set it True some time back already

I just downloaded the logs from the Failed task. Seem I have set the agent.package_manager.system_site_packages: true in the agent as well.

Hi AgitatedDove14 , Attached my create version compared to init version..
When I enqueue both the init and create version into my clearmlQueue, it seems the create version doesnt execute at all.
It just mentions "2021-05-26 16:02:13,053 - clearml - WARNING - Terminating local execution process" and says it has completed successfully.

Hi AgitatedDove14 , Just updated that flag, but the problem continues..
` agent.package_manager.system_site_packages = true
.....
Environment setup completed successfully

Starting Task Execution:

ClearML results page: files_server:
Traceback (most recent call last):
File "base_template_keras_simple.py", line 15, in <module>
import tensorflow as tf # noqa: F401
File "/root/.clearml/venvs-builds/3.6/lib/python3.6/site-packages/clearml/binding/import_bind.py", line 59, in __pat...

Just figured out..
Seems like the docker image below, didnt have tensorflow package.. 😮
tensorflow/tensorflow:latest-devel-gpuI shld have checked prior... My Bad..
Thanks for the help

Using clearml-task, I am able to pass in the exact requirements.txt file, I am not sure how we can accomplish that when you using the Python train_it.py and execute_remotely() option.
AgitatedDove14

Is there any documentation on how, we can use this ports mode ? I didnt seem to find any.. Tks

Hmm, unfortutenly it is still pending as in nothing is running

nice... we need moarrrrrrrr !!!!!!!!
It wud be really helpful, if you cud do the next episode on setting up clearml in kubernetes.. 😇
In anyways, keep up the good work for the community

Nice tutorial.. Though personally, I prefer a more clean-cut presentation (without the Yays and muaks or the the turtle). 😄 But usually, as long as content is there, it shldnt matter...

Hi, Some walk around I thought of.. Btw, I havent tried . AnxiousSeal95 , your comments

1 ) Attach a clearml-task id to each new dataset-id
So in the future, when new data comes in, get the last data commit from the project(Dataset) and get the clearml-task for it. Then clone the clearml-task, and pass in the new data. The only downside, is the need to clone the cleaml-task.
Or alternatively
2) Attach a gitsha-id of the processing code to each new dataset-id.
This can't give the exact code ...

Thanks , Got it

Yeah, that worked.. As I was the running the agent in a different machine as our deployment of clearml was in k8s.

yup, i updated this in my local clearml.conf... Or should be updating this elsewhere as well

i ran this in my local machine..
clearml-task --project playground --name tensorboard_toy --script tensorboard_toy.py --requirements requirements.txt --queue myqueue

Hi guys,
I filled up the default_output_ur in the conf file, but it doesnt get reflected in the clearml ui.
Disclaimer : Clearml is setup as a k8s pod using the Helm charts
sdk { development { # Default Task output_uri. if output_uri is not provided to Task.init, default_output_uri will be used instead. default_output_uri: " " } }