why do we do this instead of
weights = init_params((28*28))?
Both give us the same thing but I heard Jeremy say something about wanting columns? Please bear with me i am rather confused here, both give us
torch.Size([784]) when we do the .shape to them
std argument is 1.0 by default. So it will give same result if you pass std = 1
hi vivek so it doesnt matter if I dont include the 1 right? also , why do we do the multiplication of 1 ? in torch.randn(size)*std where std = 1 , Jeremy said std is the variance but if we are multiplying by 1 what’s the point?
Thanks in advance Mr Vivek
Hi Shay, multiplying by 1.0 is useless but think that since std is a parameter, you can also run the function for, let us say, std=2.0 , and that becomes useful. It is just to create a function more general.
hi , what is the value of std with respect to this case ? for background info i am doing lecture 4 , solving the mnist 3s and 7s dataset ,on the fastai website we are initialising the weights before the matrix multiplication
In that case, we use 1 to initialise the weights. It is just parametrised if you want to reuse the function, it is good software engineering practise but you can delete the std parameter without problem.
Noted Mr Charles thank you very much
