Auto-Diff is an implementation of Modern Fortran's backward mode automatic differentiation.

This project is still in the experimental stage, feedback is welcome!

This library is only available in the gfortran compiler, and there is a risk of memory leakage, which is still a toy project. And I can't think of a more appropriate way to further improve them. For a more reasonable inverse differential library, see fazang.

git clone https://github.com/zoziha/Auto-Diff.git
cd Auto-Diff

Fortran Package Manager (fpm) is a package manager and build system for Fortran. You can build Auto-Diff using the provided fpm.toml:

fpm build
fpm run --example --list

To use Auto-Diff within your fpm project, add the following lines to your fpm.toml file:

[dependencies]
Auto-Diff = { git="https://github.com/zoziha/Auto-Diff" }

!> Staged solution, run this code: fpm run --example demo3
program main

    use auto_diff
    implicit none
    type(tree_t) :: x1, x2
    type(tree_t) :: y

    x1 = 3.0_rk
    x2 = -4.0_rk

    print *, "staged demo: y = (x1 + sigmoid(x2))/(sigmoid(x1) + (x1 + x2)**2)"
    y = (x1 + sigmoid(x2))/(sigmoid(x1) + (x1 + x2)**2)

    print *, "y      = ", y%get_value()
    call y%backward()

    print *, "dy/dx1 = ", x1%get_grad()
    print *, "dy/dx2 = ", x2%get_grad()

end program main

!> staged demo: y = (x1 + sigmoid(x2))/(sigmoid(x1) + (x1 + x2)**2)
!> y      =    1.5456448841066441     
!> dy/dx1 =   -1.1068039935182090
!> dy/dx2 =   -1.5741410376065648

$ fpm run --example bench1 --profile debug
 Forward
 Elapsed time (seconds):   1.7968750000000000     
 Ordinary arithmetic
 Elapsed time (seconds):  0.14062500000000000     
 Backward
 Elapsed time (seconds):  0.29687500000000000

$ fpm run --example bench1 --profile release
 Forward
 Elapsed time (seconds):   1.6718750000000000     
 Ordinary arithmetic
 Elapsed time (seconds):   0.0000000000000000
 Backward
 Elapsed time (seconds):  0.20312500000000000

The Bench1 code for arrays (1000*1000) is here.

• St-Maxwell/backward(F90)
• KT19/automatic_differentiation
• 李理的博客/自动微分
• Fortran-lang Discourse: Backward Mode Auto-Diff in Modern Fortran
• joddlehod/DNAD
• SCM-NV/ftl
• reverse-mode-automatic-differentiation
• fazang