Is there a way to specify our own custom kernel values for a convolution neural network in pytorch? Something like kernel_initialiser in tensorflow? Eg. I want a 3x3 kernel in
nn.Conv2d with initialization so that it acts as a identity kernel -
0 0 0
0 1 0
0 0 0
(this will effectively return the same output as my input in the very first iteration)
My non-exhaustive research on the subject -
I could use nn.init but it only has some pre-defined kernel initialisaition values.
I tried to follow the discussion on this thread but it doesn’t suit my needs.
I might have missed something in my research please feel free to point out.
I have asked the same on SO here but couldn’t find any answer.