From 21093c8b46412a13f43e5e3d98128c6f5cc1cadf Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?David=20M=C3=BCller-Widmann?=
 <devmotion@users.noreply.github.com>
Date: Sat, 7 Nov 2026 03:16:30 +0100
Subject: [PATCH] Restore non-differentiable `rand!(::AbstractRNG,
 ::AbstractArray)`

GPUArrays and CUDA implement `rand!(rng, A)` directly, without a sampler,
and forward their out-of-place `rand(rng, ...)` methods to it. Since #855
removed this rule, Zygote differentiates into their kernels and errors.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
---
 Project.toml                   |  2 +-
 src/rulesets/Random/random.jl  |  2 ++
 test/rulesets/Random/random.jl | 21 ++++++++++++++++++++-
 3 files changed, 23 insertions(+), 2 deletions(-)

diff --git a/Project.toml b/Project.toml
index 65c7177b9..277f12aeb 100644
--- a/Project.toml
+++ b/Project.toml
@@ -1,6 +1,6 @@
 name = "ChainRules"
 uuid = "082447d4-558c-5d27-93f4-14fc19e9eca2"
-version = "1.74.11"
+version = "1.74.12"
 
 [deps]
 Adapt = "79e6a3ab-5dfb-504d-930d-738a2a938a0e"
diff --git a/src/rulesets/Random/random.jl b/src/rulesets/Random/random.jl
index ef9f67b0d..1fe4dd803 100644
--- a/src/rulesets/Random/random.jl
+++ b/src/rulesets/Random/random.jl
@@ -26,6 +26,8 @@ const NonDifferentiableSampler = Union{
 }
 @non_differentiable rand(::AbstractRNG, ::NonDifferentiableSampler)
 @non_differentiable rand!(::AbstractRNG, ::AbstractArray, ::NonDifferentiableSampler)
+# GPUArrays and CUDA implement this directly, without a sampler
+@non_differentiable rand!(::AbstractRNG, ::AbstractArray)
 
 @non_differentiable randexp(::Any...)
 
diff --git a/test/rulesets/Random/random.jl b/test/rulesets/Random/random.jl
index dbff1c824..49cb707d7 100644
--- a/test/rulesets/Random/random.jl
+++ b/test/rulesets/Random/random.jl
@@ -1,4 +1,4 @@
-using ChainRules, ChainRulesCore, Random, Test
+using ChainRules, ChainRulesCore, JLArrays, Random, Test
 
 # Simple Distributions like object for testing purposes
 struct NormalDistribution
@@ -7,6 +7,10 @@ struct NormalDistribution
 end
 Random.rand(d::NormalDistribution) = d.μ + d.σ*randn()
 
+# RNG that, like GPUArrays and CUDA, implements `rand!(rng, A)` without a sampler
+struct DirectRNG <: AbstractRNG end
+Random.rand!(::DirectRNG, A::Array) = fill!(A, 0.5)
+
 @testset "Random" begin
     rng_types = [MersenneTwister, Xoshiro]
     
@@ -121,4 +125,19 @@ Random.rand(d::NormalDistribution) = d.μ + d.σ*randn()
         end
         @test rrule(rand, rng, Random.SamplerRangeNDL(1.5, UInt64(4))) === nothing
     end
+
+    @testset "rand!(rng, A)" begin
+        for (rng, A) in (
+            (Xoshiro(123), zeros(3)),
+            (Xoshiro(123), JLArray(zeros(Float32, 3))),  # GPUArrays: no sampler
+            (DirectRNG(), zeros(3)),
+        )
+            Ω, dΩ = frule((NoTangent(), NoTangent(), NoTangent()), rand!, rng, A)
+            @test Ω === A
+            @test dΩ isa NoTangent
+            Ω, pb! = rrule(rand!, rng, A)
+            @test Ω === A
+            @test all(darg isa NoTangent for darg in pb!(ones(3)))
+        end
+    end
 end