Hi @<1742355077231808512:profile|DisturbedLizard6> , you can use the output_uri parameter of Task.init() to specify where to upload models.
None

Ok, maybe someone knows: how does a pod created by a K8s agent know the model registry URL? When I added the output_uri parameter in the Task, like output_uri=" None ", it doesn't show anything now. Previously, without this parameter, it showed a path like " None ...." in WebUI->Experiments->Artifacts

Hi @<1523701070390366208:profile|CostlyOstrich36> , I tried this, but It doesn't work, should it be fileserver url?

'True' should point to the files server

@<1523701070390366208:profile|CostlyOstrich36> Yes, I read this at documentation and tried it. But when I use "True" It changes path from " None ...." to " None ..." It's very strange behavior

Pod easily can download dataset, upload to fileserver logs, but can't upload model 😀

Are you sure the files server is correctly configured on the pods ?

I'm currently unsure about the correct approach. Would you kindly review my attempts and point out where I might have made a mistake? Here's what I've tried:

1. I've added the default url in agent helm chart

    clearml:
      ...
      clearmlConfig: |-
       sdk {
         development {
           default_output_uri: "

"
          }
       }

2. I've added url in agent section:

    agentk8sglue:
      ...
      fileServerUrlReference: 

3. In the Python file, when using Task.init, I've tried the 'output_uri' key argument with both 'True' and the file server URL ' None '.

I run code from pod created by agent and model has been uploaded. But when task was started by agent command it doesn't upload) Magic

Ok, I found out that using scikit-learn the model is uploading, but pytorch doesn't.

Ok, guys, I done it, by manually uploading model.
task = Task.init(project_name='test', task_name='PyTorch MNIST train filserver dataset')
output_model = OutputModel(task=task, framework="PyTorch")
output_model.set_upload_destination(uri=" None ")
tmp_dir = os.path.join(gettempdir(), " mnist_cnn.pt ")
torch.save(model.state_dict(), tmp_dir)
output_model.update_weights(weights_filename=tmp_dir)

How were you saving the model with pytorch?

I didn't save it in any way. I relied on the auto-save from Clearml

So when you do torch.save() it doesn't save the model?

Hi @<1742355077231808512:profile|DisturbedLizard6> , not sure I get that, did you use torch.save (like in here ) or some other command to save the models? When running with the clearml-agent. you have a print of all the configurations at the beginning of the log, can you verify your values are as you configure it?

Additionally, which version of clearml , clearml-agent and torch are you using?