Update python_bundle_workflow

[KumoLiu]

Fixes # .

Description

• add description for self._set_prop in python python_bundle_workflow.
• remove generate data outside of the Workflow class.

Checks

• Avoid including large-size files in the PR.
• Clean up long text outputs from code cells in the notebook.
• For security purposes, please check the contents and remove any sensitive info such as user names and private key.
• Ensure (1) hyperlinks and markdown anchors are working (2) use relative paths for tutorial repo files (3) put figure and graphs in the ./figure folder
• Notebook runs automatically ./runner.sh -t <path to .ipynb file>

[ericspod]

I guess this is fine to change unless there's a use for _set_props I don't see. @Nic-Ma any thoughts? Thanks!

[Nic-Ma]

Hi @KumoLiu @ericspod ,

I remember the idea of _set_props is to save the instantiated python objects, so if some python object is not changed and you can initialize() again for some changed objects, it can reuse it.
What do you think?

Thanks.

[ericspod]

Hi @KumoLiu @ericspod ,

I remember the idea of _set_props is to save the instantiated python objects, so if some python object is not changed and you can initialize() again for some changed objects, it can reuse it. What do you think?

Thanks.

Hi @Nic-Ma is this being used somewhere or will be? If it is we should write a bit more commentary since the semantics wasn't so clear. If not and won't ever be used I would take it out. Thanks!

[Nic-Ma]

Hi @KumoLiu @ericspod ,
I remember the idea of _set_props is to save the instantiated python objects, so if some python object is not changed and you can initialize() again for some changed objects, it can reuse it. What do you think?
Thanks.

Hi @Nic-Ma is this being used somewhere or will be? If it is we should write a bit more commentary since the semantics wasn't so clear. If not and won't ever be used I would take it out. Thanks!

Hi @ericspod ,

There is a typical use-case: if we want to set the bundle idle on GPU and run inference for every input image, we can only override the data part and re-initialize the workflow, it can help avoid recreating the model and loading weights file to GPU.
@KumoLiu Can we add some comments in the example to explain?
What do you think?

Thanks.

[KumoLiu]

Hi @ericspod,
Following an offline discussion with Nic, I've updated the tutorial. The self._set_props is utilized to store user-reset initialized objects, avoiding unnecessary re-initializations.

To aid understanding and also added as a note, I've provided a brief example.

wf = TrainWorkflow()
wf.initialize()
wf.run()
wf.loss = DiceFocalLoss(sigmoid=True)
# The workflow requires re-initialization, but the user-reset loss should remain as is.
wf.initialize()

[ericspod]

I have made a comment about the swapped order of the if-conditions in both classes, but the other changes look good to me so I can approve now and leave it up to you to swap the order of conditions or not. Thanks!