THx SmugDolphin23 - looks OK

Just for the record - for who ever will be searching for a similar setup with colab

prerequisitecreate a dedicated Service Account (I was not able to authenticate with a regular User credentials (and not SA)) get SA key ( credentials.json ) Upload json to an ephemeral location (e.g. root of colab)login into ClearML Web UI - Create access key for user - https://clear.ml/docs/latest/docs/webapp/webapp_profile#creating-clearml-credentials prepare credentials` %%bash

export api=`ca...

I saw https://clear.ml/docs/latest/docs/references/sdk/dataset/#verify_dataset_hash - but I don't think it is the correct one. the https://pandas.pydata.org/pandas-docs/stable/reference/api/pandas.DataFrame.shape.html property

Correct

Are we suppose to use the "Extra Configurations" from the https://clear.ml/docs/latest/assets/images/ClearML_Server_Diagram-7ea19db8e22a7737f062cce207befe38.png ?
https://docs.google.com/drawings/d/11f-AWVmIq7P0e8bP5OnMUz0hguXm2T_Xqq7iNMA-ANA/edit?usp=sharing

Just for the record - I guess there is an option to use os.environ
https://github.com/allegroai/clearml/blob/ca7909f0349b255f7edca0500878a8e08f3b1c99/clearml/automation/auto_scaler.py#L152-L157

SmugDolphin23 Where can I check the lates RC? I was not able to find it in the clearml github repo

Feeling that we are nearly there ....
One more question -
Is there a way to configure Clearml to store all  the  artifacts    and the  Plots   etc. in a bucket instead of manually uploading/downloading the artifacts from within the client's code?
Specifying the output_uri in Task.init saves the the checkpoints, what about the rest of the outputs?
https://clear.ml/docs/latest/docs/faq#git-and-storage

Strange
I ran
clearml-agent daemon --stopand after 10 min I ran
clearml-agent listand I still see a worker

Great - Thx for the clarifications!

Hi

you will have to configure the credentials there (in a local 

clearml.conf

 or using environment variables

This is the part that confuses me - is there a way to configure clearml.conf from the values.yaml ? I would like the GKE to load the cluster with the correct credentials without logging into the pods and manually updating the claerml.conf file

updated the clearml.conf with empty worker_id/name ran

clearml-agent daemon --stop

top | grep clearmKilled the pidsran

clearml-agent list

still both of the workers are listed

Distributor ID: Ubuntu
Description: Ubuntu 20.04.4 LTS
Release: 20.04
Codename: focal

Please advise on how to remove a worker

shape -> tuple([int],[int])
I decided to use

._task.upload_artifact(name='metadata', artifact_object=metadata)

where metadata is a dict

metadata = {**metadata, **{"name":f"{Path(file_tmp_path).name}", "shape": f"{df.shape}"}}

Hi SuccessfulKoala55
Thx again for your help

in case of the google colab, the values can be provided as environment variables

We still need to run the code in a colab environment (or remote client)
do you have any example for setting the environment variables?
For a general environment variable there is an example
! export MPLBACKEND=TkAgBut what would be for the clearml.conf ?
retrieving we can use

config_obj.get('sdk.google')

but how would the setting work? we did ...

not sure I understand
running
clearml-agent listI get
`
workers:

• company:
  id: d1bd92...1e52b
  name: clearml
  id: clearml-server-...wdh:0
  ip: x.x.x.x
  ... `

Also, what version are you on?

of what?

CLEARML-AGENT version 1.2.2

But this is not on the pods, isn't it? We're talking about the python code running from COLAB or locally...?

correct - but where is the clearml.conf file?

here is the https://github.com/allegroai/clearml-blogs/tree/e2f563bd24c2201f995bae56f253059ea223f5b6/urbansounds8k