chaslie:

why are the in_channels stored and what are they telling me?


Can you expand on this? I’m not sure what you mean by the in_channels being stored. Are you asking about that dimension in general? I see that in your plot making that you’re always indexing into in_channels with 0 (so you might not be seeing all the data in your plots).



 chaslie:

values of the out_channels do not change significantly


Convolution kernel weights are typically pretty small in the first place. For example, in resnet18, some of their kernels weights, on average, are around 0.002 or even 0.0002 (depending on where you sample). I think it would be more appropriate to take a look at their gradients overtime. That will be a better indicator of seeing how those layers are doing.