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A couple of pretrained models? #8

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317070 opened this issue Aug 17, 2015 · 6 comments
Open

A couple of pretrained models? #8

317070 opened this issue Aug 17, 2015 · 6 comments

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@317070
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317070 commented Aug 17, 2015

I have Lasagne versions of vgg-16, vgg-19 and googlenet with their pretrained parameters:
http://www.vlfeat.org/matconvnet/pretrained/
https://github.com/BVLC/caffe/tree/master/models/bvlc_googlenet

Would there be interest in adding these recipes? I reckon these recipes are more the microwave lasagne kind, but this might interest people too?
Microwave Lasagne

@f0k
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f0k commented Aug 17, 2015

Would there be interest in adding these recipes?

I guess so, yes! In what form would these recipes be? Ideally, I guess they'd construct the network in Python code, download and read the original model files (e.g., in matlab format for the first web site) and use set_all_param_values() to set the parameters to the correct state. For demonstration purposes, they could compile a prediction function.
Not sure where to put such recipes, though... they could live in the "Examples" category or be given their own (something like a model zoo, although model fridge or model freezer might be more appropriate here).

@dnouri
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dnouri commented Aug 17, 2015

I'm wondering if these should really be recipes. Maybe a small add-on library is better suited? Just a serving suggestion.

@ebenolson
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Since pretrained models are nearly all we have in Recipes so far, I think it's a pretty good fit :)

But maybe creating a new top level directory for models would make sense.

@benanne
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benanne commented Aug 17, 2015

Yeah, I think we should also keep them here, this is where people will come looking for them. A separate subdirectory for pre-trained models is not a bad idea.

@f0k
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f0k commented Aug 18, 2015

A separate subdirectory for pre-trained models is not a bad idea.

I'm still sad we didn't go for food-related directory names: starters (tutorials), mains (papers), sides (snippets), and now takeaway (premade models).

@benanne
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benanne commented Aug 18, 2015

there's no guarantee that this (remarkably well working) analogy will keep being productive though :p

@f0k f0k mentioned this issue Sep 1, 2015
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