[SOLVED] Create Parallel layers

Hi all,

Currently, I’m studying different approximation schemes in NN propagations.
Suppose I have input feature maps like 100 X 3 X 28 X 28 and kernels like 32 X 3 X 3 X3.
Because of approximate computing, I’d like to adapt the IFMs for different OFMs.
This means I have 100 X 32 X 3 X 28 X 28 inputs, and I need to conv2 the inputs with 32 X 3 X 3 X 3 one by one correspondingly. Is there a way to parallelize the process? Right now I use a loop implementation which is too slow.
Thank you in advanced!


Problem solved by using GROUP conv2.
First repeat the input tensor for 32 times, then set the group option in conv2.