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Bump the julia-deps group across 1 directory with 2 updates#14

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Bump the julia-deps group across 1 directory with 2 updates#14
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Updates the requirements on TypeUtils and AppleAccelerate to permit the latest version.
Updates TypeUtils to 2.0.0

Release notes

Sourced from TypeUtils's releases.

v2.0.0

Version 2.0.0 of TypeUtils (2026-06-12)

Breaking changes

  • By default, adapt_precision only converts non-integer numbers. The former behavior wasto convert all numbers which is not desirable as a general rule for integers (which include Booleans). The fixed behavior is that an integer or complex number with integer real and imaginary parts is left unchanged by adapt_precision while a rational number is converted to floating-point. It is still possible to overcome this behavior for a custom type by specializing adapt_precision.

Changed

  • get_precision can work on any types and instances.

  • Minimal Julia version is 1.0, this bound is imposed by the InverseFunctions package.

Added

  • Function adapt_multiplier_precision(α, x) to adapt the precision of a scalar numerical multiplier α to that of the other operand x (an array).

  • is_unitless(x) returns whether number x (a numeric value or type) is a unitless number.

  • is_static_number(x) returns whether number x (a numeric value or type) is a static number, i.e. a number whose value is known considering its type.

Changelog

Sourced from TypeUtils's changelog.

Version 2.0.0 (2026-06-12)

Breaking changes

  • By default, adapt_precision only converts non-integer numbers. The former behavior was to convert all numbers which is not desirable as a general rule for integers (which include Booleans). The fixed behavior is that an integer or complex number with integer real and imaginary parts is left unchanged by adapt_precision while a rational number is converted to floating-point. It is still possible to overcome this behavior for a custom type by specializing adapt_precision.

Changed

  • get_precision can work on any types and instances.

  • Minimal Julia version is 1.0, this bound is imposed by the InverseFunctions package.

Added

  • Function adapt_multiplier_precision(α, x) to adapt the precision of a scalar numerical multiplier α to that of the other operand x (an array).

  • is_unitless(x) returns whether number x (a numeric value or type) is a unitless number.

  • is_static_number(x) returns whether number x (a numeric value or type) is a static number, i.e. a number whose value is known considering its type.

Version 1.14.0 (2026-01-06)

This new minor version essentially provides lazymap (see below).

Added

  • B = lazymap([T::Type,], f, A[, f_inv]) yields an object B that lazily maps function f to array or iterator A. Optional argument T is the element-type of B which is automatically inferred if not specified. If A is an (abstract) array, f_inv may be provided to specify the inverse of f. Related type alias LazyMap{T,N,F,typeof(A)} can be used to specialize on the type B with N = ndims(A) and F = typeof(f).

Changed

  • The former function as_eltype(T,A) is now a shortcut for lazymap(T,identity,A) unless T == eltype(A) holds in which case A is returned.

  • Private type TypeUtils.AsEltype (formerly used by as_eltytpe) no longer exists.

Version 1.13.0 (2025-12-19)

Added

... (truncated)

Commits

Updates AppleAccelerate to 0.7.0

Release notes

Sourced from AppleAccelerate's releases.

v0.7.0

AppleAccelerate v0.7.0

Diff since v0.6.1

AppleAccelerate v0.7.0

A large feature release. The minor-version bump (0.6 → 0.7) signals breaking changes under Julia's pre-1.0 semver — see below.

⚠️ Breaking changes

  • Complex dot(x, y) is now conjugated, matching LinearAlgebra.dot (sum(conj(x) .* y)). Previously it computed the unconjugated (bilinear) product. Code relying on the old behavior should switch to the new dotu (unconjugated) function.
  • Sparse getindex on symmetric/Hermitian AASparseMatrix now reads from the mirror entry when only one triangle is stored (conjugating for Hermitian), instead of returning zero. Element access into the empty triangle therefore returns the symmetric/Hermitian value rather than 0.
  • AASparseMatrix no longer auto-tags unit-triangular matrices. A triangular SparseMatrixCSC with an all-ones diagonal is no longer automatically flagged ATT_UNIT_TRIANGULAR; the stored diagonal is used as-is. Pass the attribute explicitly to recover the previous optimization.

New: generated raw ABI layer (two-layer architecture)

  • AppleAccelerate.LibAccelerate — a committed, Clang.jl-generated raw @ccall layer covering the in-scope Accelerate headers (vDSP, vForce, vBasicOps/vBigNum, vectorOps, Sparse/Solve.h, BNNS, Quadrature). Idiomatic wrappers are written on top; any unwrapped symbol is reachable directly via the submodule.

New capabilities

  • BNNS neural-network primitives: BNNSArray, bnns_matmul/bnns_matmul!, bnns_activation/bnns_activation!, plus an NNlib package extension (batched_mul! and activations) that loads when NNlib is present.
  • Sparse: in-place refactor! (recompute the numeric factorization reusing the existing symbolic one); the LinearAlgebra-style reuse spellings lu!/cholesky!/ldlt!(F, A); factorization conveniences lu/cholesky/qr/ldlt(::AASparseMatrix); and a SparseMatrixCSC(::AASparseMatrix) round-trip. (These dispatch on AppleAccelerate's own types and do not override Julia's built-in sparse factorizations.)
  • vForce: additional element-wise functions (cbrt, nextafter, remainder, pows, …).
  • dotu: unconjugated (bilinear) complex dot product.
  • Internal array/DSP wrappers migrated onto the generated raw layer (complex ops now operate zero-alloc on interleaved Vector{Complex} storage; same public signatures).

Fixes

  • Numerous correctness and memory-safety fixes: sparse unit-triangular multiply/solve, symmetric/Hermitian getindex, convolution out-of-bounds guards, vDSP length validation, GC-safety in complex/split-complex ops, set_num_threads argument validation, and a generated double-precision-complex typedef correction.

Requirements

  • Julia 1.10+, macOS 13.4+.

Merged pull requests:

... (truncated)

Commits
  • f388d9f Remove the binding-coverage report (#174)
  • 9fde5b0 docs: refresh capabilities (BNNS, Quadrature, extensions, sparse #161) (#173)
  • 971d539 test(bnns): strengthen BNNS + NNlib ext cross-validation coverage (#171)
  • 9aed9c0 Test: drive src/dsp.jl and FFT extension to 100% coverage (#169)
  • 096ae3a Test: cover successful ldiv!(x, f, b) body in sparse.jl (98.21% -> 100%) (#166)
  • 1aa8594 test: raise coverage of BLAS/LAPACK forwarding spine (#170)
  • 05f49fc test(complexarray): cover all ops + numeric cross-validation vs Base/LinearAl...
  • c060e37 Test: cross-validate array.jl ops against Base/Statistics references (#167)
  • 023f528 codecov: ignore generated raw layer and gen/ scripts (#172)
  • 371bddc test(quadrature): cross-validate every path against analytic integrals (#165)
  • Additional commits viewable in compare view

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@dependabot
Bump the julia-deps group across 1 directory with 2 updates
622df70 
Updates the requirements on [TypeUtils](https://github.com/emmt/TypeUtils.jl) and [AppleAccelerate](https://github.com/JuliaLinearAlgebra/AppleAccelerate.jl) to permit the latest version.

Updates `TypeUtils` to 2.0.0
- [Release notes](https://github.com/emmt/TypeUtils.jl/releases)
- [Changelog](https://github.com/emmt/TypeUtils.jl/blob/main/NEWS.md)
- [Commits](emmt/TypeUtils.jl@v1.14.0...v2.0.0)

Updates `AppleAccelerate` to 0.7.0
- [Release notes](https://github.com/JuliaLinearAlgebra/AppleAccelerate.jl/releases)
- [Commits](JuliaLinearAlgebra/AppleAccelerate.jl@v0.6.0...v0.7.0)

---
updated-dependencies:
- dependency-name: TypeUtils
  dependency-version: 2.0.0
  dependency-type: direct:production
  dependency-group: julia-deps
- dependency-name: AppleAccelerate
  dependency-version: 0.7.0
  dependency-type: direct:production
  dependency-group: julia-deps
...

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@dependabot dependabot Bot added dependencies Pull requests that update a dependency file julia Pull requests that update julia code labels Jun 30, 2026
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