[dependabot]

Updates the requirements on lazymatrix to permit the latest version.

Release notes

Sourced from lazymatrix's releases.

v0.11.0

Features

• add row and chain product workspace (#28) (4f3718a)
• add fused row and pipeline products (df88d1b)

Performance Improvements

• vectorize contiguous ndarray column updates (94e7c1c)
• reduce reversed columns in memory order (d551db8)
• reuse contiguous kernels for vector reductions (fe41613)

Changelog

Sourced from lazymatrix's changelog.

0.11.0 (2026-11-06)

Features

• add row and chain product workspace (#28) (4f3718a)
• add fused row and pipeline products (df88d1b)

Performance Improvements

• vectorize contiguous ndarray column updates (94e7c1c)
• reduce reversed columns in memory order (d551db8)
• reuse contiguous kernels for vector reductions (fe41613)

0.10.0 (2026-11-04)

This version introduces row normalization for dense and sparse matrices, along with ordered normalization recipes. To support both axes consistently, I have reworked the API and taken the opportunity to simplify how matrices store and expose fitted parameters. This brings several breaking changes to the Rust API:

• Normalization, NormalizationParams, and NormalizationStats are renamed ColumnNormalization, ColumnNormalizationParams, and ColumnNormalizationStats. The name NormalizationParams now denotes a trait shared by fitted column, row, and chain parameters.
• LazyMatrix<M, F> and EagerMatrix<M, F> now take a fitted parameter type as their second generic argument. For example, use LazyMatrix<M, ColumnNormalizationParams<F>> for column normalization or LazyMatrix<M, RowNormalizationParams<F>> for row normalization.
• LazyMatrix::from_normalization(data, params) becomes LazyMatrix::from_parts(data, params). The old from_parts(data, centers, scales) becomes from_column_parts(...), with from_row_parts(...) available for rows. The with_centers and with_scales shortcuts are removed.
• Both matrix wrappers expose fitted centers and scales through normalization().centers() and normalization().scales() instead of matrix-level accessors.
• Both wrappers now return (data, params) from into_parts() instead of (data, centers, scales).
• Column and row parameter into_parts() methods now return (dimension, centers, scales), preserving the dimension even when both vectors are absent.
• Submatrix<'a, O> now borrows a logical parent operator instead of storing column normalization separately. Read the parent through as_inner() and selection bounds through row_range() and column_range(). The submatrix's centers() and scales() accessors are removed; inspect the parent's normalization() instead.
• ColumnNormalization and RowNormalization are non-exhaustive. Construct custom recipes with new(center, scale) instead of struct literals.
• Chain fitting now uses public recipe and fitted-parameter bounds, with fit::<M, P>() and fit_apply::<M, P>() replacing scalar generic arguments.

... (truncated)

Commits

• 725eccf chore(release): v0.11.0 (+1 more) (#27)
• 4f3718a feat: add row and chain product workspace (#28)
• df88d1b feat: add fused row and pipeline products
• 9a08493 docs: split todo
• 1b891d7 test: investigate cached dot gap against faer
• 73b5d21 test: evaluate fused uncached column dots
• 94e7c1c perf: vectorize contiguous ndarray column updates
• d551db8 perf: reduce reversed columns in memory order
• fe41613 perf: reuse contiguous kernels for vector reductions
• 8750c46 docs: list outstanding performance opportunities
• Additional commits viewable in compare view

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[Mec-iS]

@jolars please take a look

[jolars]

Yes, @Mec-iS - there were breaking changes in 0.10. I'd be happy to file a PR to update the implementation. Want me to?

[jolars]

I opened #530 with the update, including the updated adapter.

[dependabot]

OK, I won't notify you again about this release, but will get in touch when a new version is available. If you'd rather skip all updates until the next major or minor version, let me know by commenting @dependabot ignore this major version or @dependabot ignore this minor version. You can also ignore all major, minor, or patch releases for a dependency by adding an ignore condition with the desired update_types to your config file.

If you change your mind, just re-open this PR and I'll resolve any conflicts on it.