Open kklots opened 9 years ago
Hi,
This assertion requires the number of channels to be either <=3 or divisible to 4. This is why it fails with 6 channels. This requirement is a part of kernels from cuda-convnet2, and cannot be fixed quickly. The alternative is to use cuDNN, which should not be difficult, but will also take some time. Sorry for inconvenience.
Regards, Sergey.
Thanks for your advice. It's helpful!
Best wishes, Xuan Li
Hello Sergey,
Thank you very much for this nice toolbox! I have the same problem (can't use 6 channels), and I've tried to compile everything with CuDNN v3 without any success. Can you please advice me how to do it properly?
Thank you in advance, Majd
Hi Majd,
I think the quickest would be to use MatConvNet, it should be able to work with 6 channels.
Regards, Sergey.
Hi Sergey,
thank you for sharing this code. Now, I'm trying to train a cnn model from the data which have 6 channels (RGB and some other informations, for example: the depth information). The CPU version and Matlab version can work well, but it fails with the following error when I try to use the CUDA version:
Error using cnntrain_mex Assertion Failed: fa1
Error in cnntrain(line 10) [weights, trainerr]=cnntrain_mex(layers,weights_in,params,train_x,train_y);
How can I fix it, THX.