Bump the all-julia-packages group across 1 directory with 5 updates

[dependabot]

Updates the requirements on CUDA, ChainRulesCore, Mooncake, AMDGPU and Enzyme to permit the latest version.
Updates CUDA to 6.2.1

Release notes

Sourced from CUDA's releases.

v6.2.1

CUDA v6.2.1

Diff since v6.2.0

Merged pull requests:

• Update CI (#3175) (@​maleadt)
• Ignore patch in llvm and ptxas compat helpers (#3176) (@​AntonOresten)
• Bump GPUToolbox and remove the ability to reset devices (#3178) (@​maleadt)
• Add narrow-precision floats to cudaDataType (#3180) (@​AntonOresten)
• Bump actions/checkout from 6 to 7 (#3182) (@​dependabot[bot])
• Update to GPUToolbox v3. (#3183) (@​maleadt)
• Skip device-to-device copies of zero-byte arrays. (#3184) (@​maleadt)
• don't promote to i64 unnecessarily in unsafe_cached_load (#3186) (@​simeonschaub)
• Fix cluster barriers silently trapping on Julia <= 1.11 (#3188) (@​AntonOresten)
• Implementing specialized coo_type for CuSparseCOO (#3190) (@​alonsoC1s)

Closed issues:

• rCuFFTPlan not defined (#2509)
• Julia 1.12: Switch to Once (#2544)
• Norm of Hermitian matrices trigger scalar indexing error (#2965)
• LLVM 18 / Julia 1.12: Invalid vectorization leads to ptxas error (#3036)
• LLVM 20 / Julia 1.13: Back-end crash during texture tests (#3037)
• CUDACore - warning during precompilation (#3177)
• Error on CUDA.rand(RGB{Float32}, ...) in CUDA.jl 6.1 and 6.2 (#3179)
• deepcopy fails for CuArray with zero-size element type (#3181)
• Calling findnz(A) with a COO-formatted argument causes a stack overflow (#3189)

Commits

• 2816631 Bump version.
• 1b62bc2 Fix cluster barriers silently trapping on Julia <= 1.11 (#3188)
• 5886f9d Implementing specialized coo_type for CuSparseCOO (#3190)
• 8c6af3b Add narrow-precision floats to cudaDataType (#3180)
• ae647ae Don't promote to i64 unnecessarily in unsafe_cached_load (#3186)
• fbb9098 Skip device-to-device copies of zero-byte arrays. (#3184)
• 9dc5657 Update to GPUToolbox v3. (#3183)
• f4a33a2 Bump actions/checkout from 6 to 7 (#3182)
• bc81d40 Bump GPUToolbox and remove the ability to reset devices (#3178)
• f36a98c Ignore patch versions in LLVM and ptxas compatibility queries (#3176)
• Additional commits viewable in compare view

Updates ChainRulesCore to 1.26.1

Release notes

Sourced from ChainRulesCore's releases.

v1.26.1

What's Changed

• Bump actions/checkout from 4 to 5 by @​dependabot[bot] in JuliaDiff/ChainRulesCore.jl#699
• Bump actions/checkout from 5 to 6 by @​dependabot[bot] in JuliaDiff/ChainRulesCore.jl#700
• Bump codecov/codecov-action from 5 to 6 by @​dependabot[bot] in JuliaDiff/ChainRulesCore.jl#705
• Fix some tests and bump version by @​JamesWrigley in JuliaDiff/ChainRulesCore.jl#706

New Contributors

• @​JamesWrigley made their first contribution in JuliaDiff/ChainRulesCore.jl#706

Full Changelog: JuliaDiff/ChainRulesCore.jl@v1.26.0...v1.26.1

Commits

• 4253bff Fix some tests and bump version (#706)
• dad0d24 Bump codecov/codecov-action from 5 to 6 (#705)
• 004e43e Bump actions/checkout from 5 to 6 (#700)
• 115c282 Bump actions/checkout from 4 to 5 (#699)
• 414b660 Update Project.toml
• 124e0cb Merge pull request #698 from ChrisRackauckas-Claude/update-compat-bounds-2025
• 1d5c651 Update Downgrade.yml
• 6facda3 Create Downgrade.yml
• 632c0dc Update compat bounds to exclude releases >1 year old
• f396d36 Merge pull request #697 from ChrisRackauckas-Claude/bump-julia-v1.10
• Additional commits viewable in compare view

Updates Mooncake to 0.5.41

Release notes

Sourced from Mooncake's releases.

v0.5.41

Mooncake v0.5.41

Diff since v0.5.40

Merged pull requests:

• Enable Flux BatchNorm GPU test (#1255) (@​AstitvaAggarwal)
• Fix wrong gradient through NNlib.sigmoid at exactly zero (#1258) (@​yebai)

Closed issues:

• TagBot: Manual intervention needed for releases (#1254)
• Incorrect gradient through NNlib.sigmoid / sigmoid_fast in a two-layer composition (#1257)

Changelog

Sourced from Mooncake's changelog.

0.5.32

• Fix forward-over-reverse Hessian-vector products on closures that capture a Ref wrapped in a NoTangent-typed aggregate, which previously threw UndefRefError. prepare_hvp_cache now eagerly compiles the inner rrule!! together with its forward-mode dual callables and routes the outer forward pass through a new DerivedFoRRule, so the inner IdDict constructor is no longer inlined past Mooncake's rule (#1193, #1202).
• Fix the gradient of copysign(x, y) with respect to x: the derivative is sign(x) * sign(y), and the missing sign(x) factor previously gave the wrong gradient sign when x < 0 (#1196).
• Handle mutation of non-const globals (setglobal!) in forward mode on Julia 1.12+ (#1194).
• Version-bound the Core._call_latest(CoreLogging.handle_message, ...) rule (and its keyword-argument variant) to Julia below 1.12 (#1200).

0.5.31

• Guard codual_type / fcodual_type against unbound TypeVars (#1191, #1192).

0.5.30

• Bump the LogExpFunctions compat bound to 1 (#1186).

0.5.29

• Add a max_fd_step keyword to TestUtils.test_rule that caps the finite-difference step sizes, keeping perturbations of domain-restricted functions (log, sqrt, cholesky) inside their domains (#1173).
• Pre-allocate and reuse the Hessian, gradient, and basis-direction buffers in the Hessian cache so that repeated value_gradient_and_hessian!! calls avoid allocation (#1178).
• Add consistency checks for rule reuse (#1172).
• Mark CUDACore.cudaError_enum as having no tangent (#1175).

0.5.28

• Throw a clear UnhandledLanguageFeatureException for try / catch blocks in reverse-mode AD instead of an opaque IR-verification failure (#1161).
• Import the ChainRules svd rule via @from_rrule (#1163, closes #670).
• Guard the friendly_tangent_cache array branch against NoTangent element types (e.g. SparseMatrixCSC{Int}) (#1150).

0.5.27

• Add a cached value_and_jacobian!! interface for both forward-mode (chunked) and reverse-mode (row-by-row) caches (#1153).
• Fix tangent_type for Union{NoRData, RData{...}} (#1133).
• Add foreigncall zero-derivative rules for jl_get_world_counter and jl_matching_methods, supporting forward-over-reverse over those calls (#1143).
• Handle Ptr in zero_tangent by delegating to uninit_tangent (#1139).
• Update the CUDA extension for CUDA + cuDNN 6 (#1148).

0.5.26

• Add Config(empty_cache=true) to free internal caches before rebuilding rules.

config = Mooncake.Config(empty_cache=true)
cache = Mooncake.prepare_gradient_cache(sin, 1.0; config)

0.5.25

• Add nfwd: a new N-wide forward-mode implementation built around NDual, with Nfwd / NfwdMooncake internals and broad tests for scalar, array, and rule-building paths.
• Expand Mooncake's forward-mode interface and caching around nfwd, including prepared derivative/gradient cache improvements and lower-allocation hot paths for repeated calls.
• Route a broader scalar-math set through nfwd-backed direct primitive frule!! / rrule!! wrappers, reducing dependence on imported ChainRules rules for these cases.

... (truncated)

Commits

• 5e77308 Fix wrong gradient through NNlib.sigmoid at exactly zero (#1258)
• 8177e9e enable batchnorm GPU test (#1255)
• 4a74c5c Update README.md
• eda3655 Update README.md
• dec260b State plainly that spam or abusive accounts will be blocked and reported,
• 2c50c7a Update TagBot.yml
• 1c26d03 Add rrule!! for NNlib.gather (#1252)
• a592e9f CUDA Statistics.mean, Statistics.varm rules (#1228)
• 049f5a8 CUDA HVP/Hessian: work for non-kernel ops, fail clearly on kernel ops (#1248)
• 4ed91a0 Preserve the copy rule boundary in the trtrs! pullback (#1247)
• Additional commits viewable in compare view

Updates AMDGPU to 2.7.0

Release notes

Sourced from AMDGPU's releases.

v2.7.0

AMDGPU v2.7.0

Diff since v2.6.0

Merged pull requests:

• Improve discovery robustness (#934) (@​luraess)
• Add eigensolver support for Hermitian and Symmetric (#945) (@​luraess)
• Fix scalar multiplication for ROCSparseMatrix adjoint/transpose wrappers. (#946) (@​luraess)
• Add mixed real/complex sparse-dense matrix multiplication (#947) (@​luraess)
• Improve CSCS CI (#956) (@​luraess)
• Improve documentation (#959) (@​luraess)
• Add svd/svdvals support for ROCArray (#960) (@​luraess)

Closed issues:

• SVD not consistently working with ROCArrays (#837)
• Scalar indexing with multiplication between a scalar and the adjoint of ROC sparse matrices (#854)
• Generalized eigensolver for Hermitian matrices fails (#903)
• ROCSparseMatrxCSC{<:Complex}*ROCMatrix{<:Real} triggers allowscalar error (#904)
• Improve MI300 CI (#948)

Commits

• e73cebd Bump minor version
• 6794de3 Merge pull request #959
• 71739ff Merge pull request #960
• 50588f3 Improve doc
• 868b495 Format
• 5c078b9 Merge branch 'lr/up-doc' of https://github.com/JuliaGPU/AMDGPU.jl into lr/up-doc
• f1f934c Typos
• 444d40b Add svd
• 4120708 svd alg
• b3a1941 Fixup 1.12
• Additional commits viewable in compare view

Updates Enzyme to 0.13.195

Release notes

Sourced from Enzyme's releases.

v0.13.195

Enzyme v0.13.195

Diff since v0.13.194

Merged pull requests:

• Mark 1.13 test as more aggressive (#3395) (@​wsmoses)
• Mark ordered collection hash as non differentiable (#3397) (@​wsmoses)
• Pretty print mi errors (#3398) (@​wsmoses)

Closed issues:

• Illegal type analysis when trying to differentiate a GraphDynamics ODE (#3396)

Commits

• ded9341 Update OrderedCollections UUID in Project.toml
• 26b29d6 Update OrderedCollections UUID in Project.toml
• 1165ea8 Pretty print mi errors (#3398)
• f233beb Bump version from 0.13.194 to 0.13.195
• 498f9fc Mark ordered collection hash as non differentiable (#3397)
• afe4f64 Mark 1.13 test as more aggressive (#3395)
• 0ec46c2 Update version to 0.13.194
• 96c2975 Cache rule existance queries (#3393)
• f6ed50c Bump version from 0.13.192 to 0.13.193
• 80915d3 Resolve mismatched root calling conv on 1.12 via rta (#3391)
• Additional commits viewable in compare view

[lkdvos]

Hmmm, I'm slightly confused by this PR as this should not be happening (this compat is already specified in the root Project.toml, and the workspaces keep us from needing to duplicate this). I'll investigate.

[lkdvos]

@dependabot recreate

[lkdvos]

@dependabot recreate

[dependabot]

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[dependabot]

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[codecov]

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