Thanks TimelyPenguin76 , let me try it out now.

Ok thanks.

Ok thanks, we'll try it out on next availability.

Hi AgitatedDove14 , thanks.
In this case i am running k8s glue (machine glue), which will then spawn off pods in kubernetes worker (machine worker). So when you say direct access, are you refering to the Glue machine or K8S Worker machine?

In the ClearML config that's being run by the ClearML container?

clearml=1.0.3
python=3.8.10
clearml-data upload --id 12314jhg42342j4j --storagehttp://ecs.ai is an on-prem DELL EMC ECS that serves as our S3 storage configured with s self signed cert.

Sorry, dev end I was referring to my developers.

I didn't think Horovod needs to be as complicated as you described. It can also work by running on multiple known nodes. How would i add a glue for multinode?

Horovod does also work with other similar products such as yours (E.g. Polyaxon).

Hi,
basically i run this block first and ended the script.
task = Task.init(project_name="afro-nmt", task_name=args.taskname, continue_last_task=args.taskid) Logger.current_logger().report_scalar(title="BLEU",series="JW300",value=args.jwbleu, iteration=args.lastiter)Then i run another script, with series different.
` task = Task.init(project_name="afro-nmt", task_name=args.taskname, continue_last_task=args.taskid)
Logger.current_logger().report_scalar(title="BLEU",series="SS900",value=arg...

Hi, currently the ClearML SDK only supports python. If i want to run my ML in other languages, can i use a SDK in that language? Or is there other means such as a Web API calls that does the same as the SDK?

Thanks could you share the URL to this full API documentation?

Hi. Yup the model was not physically uploaded with the up:port into the bucket, although ClearML does indicate that it's there, except that I can't download it. I also verified this with another S3 client, the model was not there as well.

Hi, when i tried ip:port, it references the right host and bucket....BUT... the file is not found on the ECS S3 even though i can see from the logs that it states Completed model upload to s3://ecs.ai:80/clearml-models/artifacts/ ...

Hi,
I'm running on Dell ECS storage appliance, which offers S3 compatibility.
yes http://ECS.ai is the DNS name of the server.
ClearML-models is the bucket.
Let me try with ip:port.

No, i can't see the files. But i can see if i don't use ':port' in the URL when uploading. I can't access the machine today, i'll try to check the S3 logs when i'm back.

ah ok, so if i see Jax's workspace on https://app.community.clear.ml/dashboard , then i'm on the right track? How regular does this reset then?

Hi thanks for the examples! I will look into them. Quite a fair bit of my teams uses tf datasets to pull data directly from object stores, so tfrecords and stuff are heavily involved. I'm trying to figure if they should version the raw data or the tfrecords with ClearML, and if downloading entire set of data to local can be avoided as tf datasets is able to handle batch downloading quite well.

Its actually in your documentation. Its removed since 0.17 apparently.
https://allegro.ai/clearml/docs/docs/release_notes/ver_0_17.html#clearml-agent-0-17-2

And this is my logs, it tried to install something and encountered permission denied. It wouldn't if it obeyed the force_repo_requirements_txt.

1620664917916 Kahs-MacBook-Pro.local info ClearML Task: created new task id=024a421c0e174650a1c7ff64af756c26 ClearML results page: `
1620664920359 Kahs-MacBook-Pro.local info ClearML Mon...

which clearml.conf is it refering to? I'm executing on my client, which is then remotely executed by the agent. Both of them has ~/clearml.conf.

I managed to find out why. The docker image I'm using is not set as root user thus the error. But I'm wondering why this is the case as docker best practices does indicate we should use a non root on production images.

Clearing the cache entirely works. Thanks.

Hi. Anything that can point to activity by user.

Hi CostlyOstrich36 , thanks. I will check with the Enterprise team then.

I thought of another potential way but not sure if the SDK supports it.
We will perform manual save and upload of model using vanilla boto3 and credentials passed in as env var. Use ClearML SDK to update the Model Repo on the location of the model, without ClearML uploading it explicitly.Would the above work?

Thanks. We set this configuration and the client ran and submitted the job for remote execution (agent running k8s glue). However when the job runs, and tries to save into model repo, this error came up.
ClearML.storage - ERROR - Failed creating storage object S3://ecs.ai Reason; Missing key and secret for S3 storage access ( S3://ECS.ai ).

I remember being told that the ClearML.conf on the client will not be used in a remote execution like the above so I think this was the problem. I also...

It would make sense on a very large resource cluster. Unfortunately we only have less than 50 GPUs to share across. A multi-tenant SAAS would cut the resources into even more smaller clusters and not help with efficiency. Or would you have a suggestion?

ok that's the latest? Will do.

Is there anyway to see an error log from that?

Hi SuccessfulKoala55 , just wondering how i can follow up on this.

Yes of cos, its a long one.

Hi erez, i think i would want to reference the code that transformed the data. Take for example, i received 10k images, i performed some transformation and save it as a next version before i split it up for my ML training. Some time later, i receive a new set of 10k images and wants to apply the same transformation and then append it to the previous 10k as another version. Clearml-data does well for the data-versioning part, but in terms of data provenance, its not clear how i can associate t...