Value is sometimes not set when using DiffResults

[gdalle]

Here's an MWE I'm struggling to understand. My best guess sofar is that this is hitting a Julia compiler optimization which somehow eludes the value computation. Unless I'm just holding the thing wrong?

using ReverseDiff: ReverseDiff
using DiffResults: DiffResults

f(x) = sum(abs2, x)
x = [3.0, 5.0]
compiled_tape = ReverseDiff.compile(ReverseDiff.GradientTape(f, x))

function value_and_gradient1!(grad, tape, x)
    result = DiffResults.MutableDiffResult(zero(eltype(x)), (grad,))
    result = ReverseDiff.gradient!(result, tape, x)
    return DiffResults.value(result), DiffResults.gradient(result)
end

function value_and_gradient2!(grad, tape, x)
    result = DiffResults.MutableDiffResult(zero(eltype(x)), (grad,))
    result = ReverseDiff.gradient!(result, tape, x)
    return DiffResults.value(result), grad
end

function value_and_gradient_nested1!(grad, tape, x)
    y, _ = value_and_gradient1!(grad, tape, x)
    return y, grad
end

function value_and_gradient_nested2!(grad, tape, x)
    y, _ = value_and_gradient2!(grad, tape, x)
    return y, grad
end

julia> value_and_gradient1!(similar(x), compiled_tape, x)
(34.0, [6.0, 10.0])

julia> value_and_gradient_nested1!(similar(x), compiled_tape, x)  # wrong value
(0.0, [6.0, 10.0])

julia> value_and_gradient2!(similar(x), compiled_tape, x)
(34.0, [6.0, 10.0])

julia> value_and_gradient_nested2!(similar(x), compiled_tape, x)
(34.0, [6.0, 10.0])

Related:

• perf: avoid double function call in ReverseDiff value_and_gradient DifferentiationInterface.jl#729

(jl_gKdWaj) pkg> st
Status `/private/var/folders/pt/myrxq2gs5hzcp79v5475_dh40000gp/T/jl_gKdWaj/Project.toml`
  [163ba53b] DiffResults v1.1.0
  [37e2e3b7] ReverseDiff v1.15.3

julia> versioninfo()
Julia Version 1.11.3
Commit d63adeda50d (2025-01-21 19:42 UTC)
Build Info:
  Official https://julialang.org/ release
Platform Info:
  OS: macOS (arm64-apple-darwin24.0.0)
  CPU: 11 × Apple M3 Pro
  WORD_SIZE: 64
  LLVM: libLLVM-16.0.6 (ORCJIT, apple-m2)
Threads: 5 default, 0 interactive, 2 GC (on 5 virtual cores)
Environment:
  JULIA_EDITOR = code

[nsajko]

This doesn't reproduce on nightly Julia.

[nsajko]

BTW, as mentioned on Slack, --compile=min is a good way to check if a bug is a miscompilation.

[gdalle]

You're right, with --compile=min it disappears as well. Not sure what to do about it then.

[nsajko]

Not sure what to do about it then.

Create a MWE and report an issue to JuliaLang/julia.

Create the MWE by:

1. starting from the reproducer above
2. inlining the contents of the two packages and all dependencies
3. delete irrelevant code manually
4. optionally (I think it's slightly demanding to set up), use https://github.com/maleadt/creduce_julia to further reduce the MWE

Another thing to do is bisect the fix (given that the bug is perhaps fixed on nightly), and see if it's backportable.

[gdalle]

Unfortunately I wouldn't even know where to begin to inline ReverseDiff. I tried removing it entirely and the effect disappeared.