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Answered
Hi Everyone, I Have One Quick Question Regarding The Artifact Uploading. I See The Output Models From Training Are Stored Under The "Output Models" Section In Artifacts Tab, And If I Do Upload Other Artifacts Using .Upload_Artifact() Api, They Are Stored

Hi everyone,
I have one quick question regarding the artifact uploading. I see the output models from training are stored under the "OUTPUT MODELS" section in artifacts tab, and if I do upload other artifacts using .upload_artifact() api, they are stored under the "OTHERS" section. I wonder if it possible to change the section name from "others" to, let's say "text"?
I have tried task.upload_artifact('/text/temp', 'temp.txt') but it's not working (I can access the task, but as soon as I click artifacts tab, it shows 404 error).
Thanks in advance

  
  
Posted one year ago
Votes Newest

Answers 11


So, the 1st image (jupyter) is the code I used to create a task and upload the artifact. Then the task was created and I can access it normally with web GUI (like in the 2nd image). But when I click "artifacts" tab, the 404 error page appears (3rd image).

  
  
Posted one year ago

I have tried

task.upload_artifact('/text/temp', 'temp.txt')

but it's not working (I can access the task, but as soon as I click artifacts tab, it shows 404 error).

Can you please elaborate on this? Can you please share a screenshot?

  
  
Posted one year ago

DeterminedOwl36 , what version of ClearML are you using? Also, does it happen if you run the script standalone and not through jupyter notebook?

  
  
Posted one year ago

DeterminedOwl36 I think for now you can't change this name

  
  
Posted one year ago

CostlyOstrich36 Yes, the same thing occurs. version: 1.1.2 for clearml-agent

  
  
Posted one year ago

SuccessfulKoala55 I see. Hope it will be added as a new feature in the future version. For me, it's quite important for the organization purpose, especially if the task outputs many artifacts.

  
  
Posted one year ago

DeterminedOwl36 can you please open a GitHub issue about it?

  
  
Posted one year ago

SuccessfulKoala55 Sure will do. :)

  
  
Posted one year ago

SuccessfulKoala55 I am trying to find a way to work around it for the time being. I have 2 requirements: 1) I want to log a custom metric that is computed only at the end of every epoch (unlike other tf metrics which are updated per mini-batch). If I follow the tf doc here, will ClearML log it for me and show on "scalars" tab? https://www.tensorflow.org/tensorboard/scalars_and_keras#logging_custom_scalars 2) It's the same thing as 1) but it's a image instead. https://www.tensorflow.org/tensorboard/image_summaries#logging_arbitrary_image_data

  
  
Posted one year ago

You can just use task.logger.report_scalar() and report_image() for that 🙂

  
  
Posted one year ago

I see. That's quite handy. Thanks!

  
  
Posted one year ago