Comments (8)
I assume you replaced the Conv2DDNNLayer
with a Conv2DLayer
to run on CPU. In this case, you need to flip the filter kernels, because Conv2DDNNLayer
by default performs a correlation rather than a convolution.
try running this after loading the parameters:
for layer in net.values():
if type(layer) == ConvLayer:
W = layer.W.get_value()
W = W[:, :, ::-1, ::-1]
layer.W.set_value(W)
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Thank
I tried as you suggested, but it did not help.
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I had a typo, should be W = W[:, :, ::-1, ::-1]
.
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Yes I noticed tried both...
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Have you made any other changes to the code? What versions of Theano and Lasagne are you using?
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No, I have not changed anything.
theano.version = 0.7.0.dev-15c90dd36c95ea2989a2c0085399147d15a6a477
lasagne.version = 0.2.dev1
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Hmm.. it works for me: https://gist.github.com/ebenolson/e41398fe067d42fc16d8, if you still see a different result try running the Lasagne test suite, perhaps there is something wrong with your installation.
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Thank you very much I will try.
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