[dependabot]

Updates the requirements on AbstractNeuralNetworks to permit the latest version.

Release notes

Sourced from AbstractNeuralNetworks's releases.

v0.9.1

AbstractNeuralNetworks v0.9.1

Diff since v0.9.0

Changed

• CI uploads coverage from the Julia 1 - ubuntu-latest job instead of Julia min, and a test job saves the Julia cache only when it succeeds.

• Pkg.test() no longer runs the doctests. test/quality/doctests.jl is now the group doctests, which an empty ARGS does not run; Pkg.test(test_args = ["doctests"]) runs it. In CI the Doctests job stays their runner, so the test matrix no longer runs them a second time.

• test/neural_network_constructors.jl moves to test/integration/neural_network_constructors.jl. The test convention keeps a test file at the top level of test/ only where it mirrors src/<name>.jl, and there is no src/neural_network_constructors.jl. The file tests the NeuralNetwork constructors of src/neural_network.jl, whose mirror test/neural_network.jl already exists, so it goes to test/integration/.

Dependencies and tests

• Admits NeuralNetworkParameters 0.5 alongside 0.4.2 (compat only; no change to this package's own behaviour). The downstream packages move to NNP 0.5, and they can resolve only if this package admits it. NNP 0.5 gives an untouched leaf a zero gradient instead of nothing, gives a leaf's gradient the leaf's element type, rejects a NetworkParameters with two numeric element types, and makes + add storage leaf by leaf. The test suite passes against both 0.4.2 and 0.5.

Merged pull requests:

• CI: coverage from Julia 1 on ubuntu, save the cache only from a job that succeeds (#54) (@​michakraus)
• Move the doctests into their own test group (#55) (@​michakraus)
• Move the top-level test files that mirror no source file (#56) (@​michakraus)
• Admit NeuralNetworkParameters 0.5 in compat (#57) (@​michakraus)

Changelog

Sourced from AbstractNeuralNetworks's changelog.

[0.9.1] — 2026-10-11

Changed

• CI uploads coverage from the Julia 1 - ubuntu-latest job instead of Julia min, and a test job saves the Julia cache only when it succeeds.

• Pkg.test() no longer runs the doctests. test/quality/doctests.jl is now the group doctests, which an empty ARGS does not run; Pkg.test(test_args = ["doctests"]) runs it. In CI the Doctests job stays their runner, so the test matrix no longer runs them a second time.

• test/neural_network_constructors.jl moves to test/integration/neural_network_constructors.jl. The test convention keeps a test file at the top level of test/ only where it mirrors src/<name>.jl, and there is no src/neural_network_constructors.jl. The file tests the NeuralNetwork constructors of src/neural_network.jl, whose mirror test/neural_network.jl already exists, so it goes to test/integration/.

Dependencies and tests

• Admits NeuralNetworkParameters 0.5 alongside 0.4.2 (compat only; no change to this package's own behaviour). The downstream packages move to NNP 0.5, and they can resolve only if this package admits it. NNP 0.5 gives an untouched leaf a zero gradient instead of nothing, gives a leaf's gradient the leaf's element type, rejects a NetworkParameters with two numeric element types, and makes + add storage leaf by leaf. The test suite passes against both 0.4.2 and 0.5.

[0.9.0] — 2026-10-02

Methods that GeometricMachineLearning (GML) defined on this package's types move here. A method on Dense, Linear or NeuralNetwork is type piracy wherever it is written outside this package. GML defined three such methods, the 3-tensor methods on Dense and Linear, and the save/load methods for NeuralNetwork in its HDF5 extension.

Breaking Changes

• A GML that still defines the three 3-tensor methods fails to precompile against this release, with "Method overwriting is not permitted during Module precompilation". GML has to delete them in the same change that raises its AbstractNeuralNetworks bound.

• The backend keyword of load(NeuralNetwork, …) is removed; the network loads on the CPU and changebackend(backend, nn) moves it to a device with parameters included.

New Features

• Dense, Linear and Affine accept inputs of rank 3 or more. Each layer applies its weight matrix to the first dimension, preserving the remaining dimensions. The implementation uses only reshape and matrix multiplication, so it runs on any array type that supports both — including device-backed arrays.

• A new weak extension, HDF5Ext, provides save and load for NeuralNetwork. The

... (truncated)

Commits

• dfbd3aa Release 0.9.1
• f910cb7 Admit NeuralNetworkParameters 0.5 in compat (#57)
• da7271c Sync the shared git hooks
• ad32d33 Move the top-level test files that mirror no source file (#56)
• 7ff1daf Move the doctests into their own test group (#55)
• 05d4c17 CI: coverage from Julia 1 on ubuntu, save the cache only from a job that succ...
• b52245e Sync the shared git hooks
• 8bd7539 Sync the shared hooks and workflows from the harness
• 87c3801 Sync the shared git hooks
• af6c6b7 Sync the shared pre-commit hook
• Additional commits viewable in compare view

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[codecov]

Codecov Report

✅ All modified and coverable lines are covered by tests.
✅ Project coverage is 49.83%. Comparing base (e111300) to head (1628374).

Additional details and impacted files

@@           Coverage Diff           @@
##             main      #57   +/-   ##
=======================================
  Coverage   49.83%   49.83%           
=======================================
  Files          13       13           
  Lines         616      616           
=======================================
  Hits          307      307           
  Misses        309      309           

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