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nan gradients with BCHW layout

Open jj0mst opened this issue 7 years ago • 0 comments

I recently tried to use the new BCHW functions with my network, since i always use that layout and it simplifies my code.

I noticed that all the gradients of my convolutional layers are nan now, which makes also the weights full of nan after the parameters' update.

I'm sure i made all the necessary conversions and i get no error like inconsistency between tensors or anything else.

jj0mst avatar Jun 22 '17 08:06 jj0mst