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Explicit for-loop optimisation or SupervisedTrainer #16

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rijobro opened this issue Sep 2, 2020 · 3 comments
Open

Explicit for-loop optimisation or SupervisedTrainer #16

rijobro opened this issue Sep 2, 2020 · 3 comments
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@rijobro
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rijobro commented Sep 2, 2020

It seems that in the majority of tutorials, the optimisation for loop is given explicitly. In relatively few places, the SupervisedTrainer is used, despite existing for this reason.

I can see why having the explicit for loop is beneficial for tutorials - so that people are more aware of the inner workings. However, for the sake of conciseness, I would be in favour of having just one notebook (named suitably) in which the explicit for loop is given, and then from there on, using the SupervisedTrainer. Notebooks using SupervisedTrainer could then refer to the explicit notebook.

I think @ericspod is in favour of leaving the notebooks as they are, so as not to hide anything (which I understand). Anyone else have an opinion?

@rijobro
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rijobro commented Sep 2, 2020

@wyli
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wyli commented Sep 2, 2020

Thanks for bringing this up! Earlier we had the feedback from the users saying that they don't want to spend time to learn yet another framework (referring to the monai.engines and monai.handlers mechanism), we therefore create those explicit forloop examples to show that many of the monai components work well in a 'vanilla' pytorch script.
Now we might have too many such examples. Perhaps we could address this after properly rearrange the examples #2 what do you think @Nic-Ma?

@Nic-Ma
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Nic-Ma commented Sep 2, 2020

Sounds reasonable!
We should rearrange examples first then let's discuss the tutorials.
Thanks.

@Nic-Ma Nic-Ma added the question Further information is requested label Sep 2, 2020
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