Created
February 16, 2025 20:21
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program simple_2d | |
use nf, only: input, network, sgd, linear2d, mse, flatten | |
implicit none | |
type(network) :: net | |
real :: x(3, 4) = reshape(& | |
[0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.2, 0.2, 0.2, 0.2, 0.2, 0.2],& | |
[3, 4]) | |
real :: y(3) = [0.12, 0.1, 0.3] | |
type(mse) :: mean_se = mse() | |
integer, parameter :: num_iterations = 500 | |
integer :: n | |
net = network([ & | |
input(3, 4), & | |
linear2d(3, 4, 1), & | |
flatten() & | |
]) | |
call net % print_info() | |
do n = 0, 5 | |
call net % forward(x) | |
call net % backward(y, mean_se) | |
call net % update(optimizer=sgd(learning_rate=1.)) | |
print '(i4,2(3x,f8.6))', n, net % predict(x) | |
end do | |
end program simple_2d |
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