And then we want to compare backtests or just this week's estimates across multiple of those models/branches

But we're also testing out new models all the time, which are typically implemented as git branches - they run on the same set of inputs but don't output their results into production

awesome, I'll test it out - thanks for the tips!

I could just loop through and create separate pipelines with different parameters, but seems sort of inefficient. the hyperparameter optimization might actually work in this case utilizing grid search, but seems like kind of a hack

Just ran the same notebook in a local Jupyter Lab session and it worked as I expected it might, saving a copy to Artifacts

yeah, even then it'll run but return 0 notebooks

environ{'PYTHONNOUSERSITE': '0',
        'HOSTNAME': 'gfp-science-ml-t3-medium-d579233e8c4b53bc5ad626f2b385',
        'AWS_CONTAINER_CREDENTIALS_RELATIVE_URI': '/_sagemaker-instance-credentials/xxx',
        'JUPYTER_PATH': '/usr/share/jupyter/',
        'SAGEMAKER_LOG_FILE': '/var/log/studio/kernel_gateway.log',
        'PATH': '/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/tmp/miniconda3/condabin:/tmp/anaconda3/condabin:/tmp/miniconda2/condabin:/tmp/anaconda2/condabin'...

the server_info is

[{'base_url': '/jupyter/default/',
  'hostname': '0.0.0.0',
  'password': False,
  'pid': 9,
  'port': 8888,
  'root_dir': '/home/sagemaker-user',
  'secure': False,
  'sock': '',
  'token': '',
  'url': '

',
  'version': '1.23.2'}]

but the only exception handler is for requests.exceptions.SSLError

those look like linear DAGs to me, but maybe I'm missing something. I'm thinking something like the map operator in Prefect where I can provide an array of ["A", "B", "C"] and run the steps outlined with dotted lines independently for each of those are arguments

My use case is running forecasting models in production across multiple businesses

so notebook path is empty

I can get it to run up to here: None

I think it just ends up in /home/sagemaker-user/{notebook}.ipynb every time

I'll give it a shot and see! Just setting up a test server now, so it's still a hypothetical question just from reading the docs so far

thanks for the thoughtful response, @<1523701205467926528:profile|AgitatedDove14> ! I think I'll need to test out some workflows to see what works

one possibility for getting the notebook filepath is finding and parsing /home/sagemaker-user/.jupyter/lab/workspaces/default-37a8.jupyterlab-workspace I think, but I don't know if I can tie that to a specific session

I'm not sure if Subprojects will work for that - can you use the Web UI to compare the artifacts from two separate subprojects?

poking around a little bit, and clearml.backend_interface.task.repo.scriptinfo.ScriptInfo._get_jupyter_notebook_filename() returns None