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nikolausmayer avatar nikolausmayer commented on May 25, 2024

This is just a quick guess, but "deconvolution" is implemented as transposed convolution (both layers directly use the cublasSgemm matrix multiplication).

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r0drigor avatar r0drigor commented on May 25, 2024

I can't find any documentation on any of this, but maybe I'm just not looking hard enough.
There's probably some kind of transposition on the height and width parameters, right?
I'm having some difficulty getting reasonable values and it might be an explanation.

Thank you for the fast response.

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nikolausmayer avatar nikolausmayer commented on May 25, 2024

I think it's common to implement these "deconvolutions" like that; see e.g. http://deeplearning.net/software/theano_versions/dev/tutorial/conv_arithmetic.html#transposed-convolution-arithmetic

You can check the Forward_cpu implementations in the conv and deconv layers, they should match the method in the link.

I can't tell you why exactly the parameters are structured differently; I can only assume that the transposed convolution plays a role.

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nikolausmayer avatar nikolausmayer commented on May 25, 2024

(closed due to inactivity)

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