Great - Thx for the clarifications!

Hi @<1523701205467926528:profile|AgitatedDove14>
I'm having a similar issue.

Also notice the cleaml-agent will not change the entry point of the docker meaning if the entry point does not end with plain bash, it will not actually run anything

Not sure I understand how to run a docker_bash_setup_script and then run a python script - Do you have an example? I could not find one.
Here is our CLI command

clearml-task --name <TASK NAME> \
		--project <PRJ NAME> \
		--repo git@gi...

I'm looking for the bucket URI
I think my work flow needs to alter.
get the data into the bucket and then create the Dataset using the add_external_file and then be able to consume the data locally or stream And then I can use - link_entries

here is a video of the steps

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

so running the command clearml-agent -d list returns the https://clearml.slack.com/archives/CTK20V944/p1657174280006479?thread_ts=1657117193.653579&cid=CTK20V944

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

Btw -after updating clearml.conf do I need to restart the agent?
I can't see the additional tab under https://clearml.slack.com/archives/CTK20V944/p1658199530781499?thread_ts=1658166689.168039&cid=CTK20V944 , and I reran the task and got the same error

BTW SuccessfulKoala55 we are running with
CLEARML-AGENT version 1.3.0

How do you do so?
can't find it under
clearml-agent daemon -h

yes - the agent is running with --docker
Great - where do I define the volume mount?
Should I build a base image that runs on the server and then use it as the base image in the container?

i've doubled checked the Path- and it is correct

Thx - it worked!
BTW - maybe it worth while to add this comment in the ClearML Agent daemon documentation - that when ever you update the clearml.conf you need to
clearml-agent daemon --stop recreate all the daemonclearml-agent daemon ....

google.storage { credentials = [ { bucket: "clearml-storage" project: "my-project" credentials_json: "/path/to/creds.json" }, ] }No - just emulating - it is more of /home/... /creds.json

but it is on the host server

This also may help with the configuration for GCS
https://clearml.slack.com/archives/CTK20V944/p1635957916292500?thread_ts=1635781244.237800&cid=CTK20V944

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

Thx again for your time -

Where the experiment is being executed

Not sure I understand what you mean by this -
Assuming that we are running the ClearML on GKE (we have succeeded doing so) - and running the python code from COLAB or locally. Where do we configure the Google Storage ? how can the helm / k8s dynamically load the clearml.conf ? is it only from values.yaml ?

Where you view your experiment

In mlflow I was able to view the artifact directly (a...

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 ...

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?

Also, what version are you on?

of what?