Having used Torch (the Lua library) before, the comparison between the Sequential models seems very absurd. Even the pyTorch documentation gives an almost equivalent model defintion method:
# Example of using Sequential
model = nn.Sequential(
nn.Conv2d(1,20,5),
nn.ReLU(),
nn.Conv2d(20,64,5),
nn.ReLU()
)
These sequential models are are like Fibonacci function comparisons between programming languages.
They are simple and basic, difference between 5 lines of code or 20 lines of code makes no difference. You spend very little time actually coding these layers. Understanding the model, default parameters used underneath is more important.
It would be nice to see some examples with skip-layers, weight sharing etc. You you have to drop sequential model to do them or not?
