After the job has finished, the outputs are available as a dataset.
This is what is shown in Azure ML Studio in the "Overview" tab for job ivory_octopus_yd6by49kxf:
The dataset is successfully stored in the workspaceblobstore datastore. I checked it in the Azure ML Studio and it looks fine.
4. accessing the persisted data
After the job has finished, I access the run using a MlflowClient()
I have a training job that persists some files in an URI_FOLDER output. How can I access those through the v2 SDK API after the job has finished?
1. job setup
The output is set up like this in the
command
:This seems to work fine, the corresponding folder is mounted correctly and accessible in the training script.
2. training script
In the training script, I persist a dataframe like this:
This works fine.
3. resulting dataset
After the job has finished, the outputs are available as a dataset. This is what is shown in Azure ML Studio in the "Overview" tab for job
ivory_octopus_yd6by49kxf
:The dataset is successfully stored in the
workspaceblobstore
datastore. I checked it in the Azure ML Studio and it looks fine.4. accessing the persisted data
After the job has finished, I access the run using a
MlflowClient()
or
How can I programmatically list / get / download the outputs connected to the job?
Thanks!