feat(types): add i8/i16/u8 element types, storage only

[Ravenwater]

Phase 1 of #88. 1389 passed, 3 skipped (from 1374).

i8, i16 and u8 are the operand types of MTL5 v5.11.0's widening dot and integer GEMM — the accumulator stays int32, which is what vpdpbusd / vpmaddwd / SDOT take. Registering the containers is the prerequisite that makes those kernels reachable at all.

>>> v = mtl5.vector(np.arange(4, dtype=np.int8))
>>> type(v).__name__
'DenseVector_i8'

Built and tested against the current v5.10.0 pin — this phase does not need v5.11.0, so it does not disturb the 5.10.0 soak.

Fixes a silent wrong-dtype bug

Found while checking the dispatch. The native factories take nb::ndarray<T> without .noconvert(), so nanobind's converting second pass handed an int8 array to the float overload, registered first:

>>> mtl5.vector(np.arange(4, dtype=np.int8))     # before
DenseVector_f32   is_view=True   # ...but writes through the NumPy array were invisible

A view of the converted temporary — wrong dtype, and a false zero-copy claim. This is precisely the failure mtl5_ndarray.cpp:460 documents at its .noconvert(), which the native factories never got. An exact match now resolves in the first pass, before conversion is considered.

The dtypes still unregistered (f16, uint16, uint32, uint64) keep the old behaviour. Worth a follow-up decision on .noconvert(); I left it out here because it changes behaviour for currently-working callers and is separable from this phase.

dot and norm are deliberately not registered

This is the phase-1 checklist item that said to confirm what register_native pulls in rather than assume it. The answer is that its norm and dot are not usable on these types. Both default to accumulating in the element type, so 8- and 16-bit operands overflow almost immediately — six-element vectors of 100 (exact dot 80000, exact two_norm 244.9490):

	i8	i16	u8
dot	−128	14464	128
two_norm	9.798	nan	9.798

The dot values are MTL5's documented two's-complement wrapping, and become correct the moment an int32 accumulator is supplied — that is phase 2. two_norm is worse than wrapping: it takes sqrt of a sum that has wrapped, and of a negative one for i16.

i32 has the same failure, but only past ~46341 — where an 8-bit sum of squares overflows at two elements of 12. An edge case there; essentially every input here.

Exposing an operation that is wrong for almost all inputs is worse than not exposing it, so mtl5.dot(i8_vec, i8_vec) raises TypeError rather than returning a wrapped number. register_native is split into register_native_storage (containers and factories) plus the norm/dot overloads, so the existing types are registered exactly as before.

Tests

15 new, in two classes:

• TestNarrowIntegerStorage — dispatch, matrix round-trip, and zero-copy asserted by writing through the NumPy array. is_view alone would not have caught the old bug, since the view of the converted temporary reported True.
• TestNarrowIntegerHasNoArithmetic — pins the TypeError, with the measured overflow table in the docstring and a note that if it starts failing because someone registered the generic overloads, the fix is the accumulator, not deleting the test.

Next

Phase 2 (AccKind::I32, integer dtypes in dtypes()/accumulators(), the overflow contract in the docstrings) is what makes these types compute, and it does need the v5.11.0 pin — that is where wrapping_arithmetic.hpp lands, and where the generic integer loops stop being UB on overflow.

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Summary by CodeRabbit

• New Features

  • Added dense vector and matrix support for int8, int16, and uint8 data types.
  • Added zero-copy NumPy factories with dtype preservation and buffer sharing.
  • Added matching package-level exports for the new types.

• Bug Fixes

  • Corrected exact data-type overload selection.

• Known Limitations

  • dot and norm are unavailable for these narrow integer types and raise TypeError.

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📒 Files selected for processing (3)

• CHANGELOG.md
• python/src/mtl5_module.cpp
• tests/test_vector.py

📝 Walkthrough

Walkthrough

Adds i8, i16, and u8 vector and matrix bindings with zero-copy NumPy factories. These types use storage-only registration, preserve exact dtypes, and raise TypeError for dot and norm.

Changes

Narrow integer bindings

Layer / File(s)	Summary
Storage registration and dtype mapping python/src/mtl5_types.hpp, python/src/mtl5_module.cpp	Adds suffix mappings for narrow integer types and separates storage registration from arithmetic registration.
Narrow type bindings and package exports python/src/mtl5_module.cpp, mtl5/__init__.py	Registers i8, i16, and u8 vector and matrix containers. Adds the bindings to package imports and __all__.
Narrow integer behavior validation tests/test_vector.py, CHANGELOG.md	Tests zero-copy aliasing, dtype preservation, matrix round trips, and TypeError results for dot and norm. Documents the supported behavior.

Estimated code review effort: 3 (Moderate) | ~20 minutes

Merge Risk: 🟡 Moderate · up to 02de0

The PR adds narrow integer storage types but currently also exposes matrix multiplication for them, allowing results to be narrowed into i8, i16, or u8 and silently overflow. This can return incorrect results for affected callers, so merge should wait for the registration split; minor documentation inconsistencies also need follow-up.

Sequence Diagram(s)

sequenceDiagram
  participant PythonCaller
  participant mtl5_module
  participant NumPy
  participant NarrowIntegerContainer
  PythonCaller->>mtl5_module: create i8, i16, or u8 vector/matrix
  mtl5_module->>NumPy: resolve exact input dtype
  NumPy-->>mtl5_module: provide typed buffer
  mtl5_module->>NarrowIntegerContainer: construct storage binding
  NarrowIntegerContainer-->>PythonCaller: return typed container
  PythonCaller->>mtl5_module: call dot or norm
  mtl5_module-->>PythonCaller: raise TypeError

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🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 21.05% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 19 functions across 4 files. (1 skipped: …	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly and concisely describes the main change: adding storage-only support for the i8, i16, and u8 element types.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.

Full details: Docstring Coverage

Explanation

Docstring coverage is 21.05% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 19 functions across 4 files. (1 skipped: 1 unsupported.)

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Actionable comments posted: 3

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Inline comments:
In `@CHANGELOG.md`:
- Around line 20-24: Align the MTL5 dependency declaration with the changelog’s
v5.11.0 kernel claims: update the fallback dependency from v5.10.0 to v5.11.0,
or revise the changelog to mark those kernels as requiring a future dependency
upgrade.

In `@python/src/mtl5_module.cpp`:
- Around line 1016-1020: Split register_native_matrix so storage binding and
arithmetic binding are separate; keep register_native_storage<T> limited to
storage registration and exclude both __matmul__ overloads for narrow integer
types. Ensure existing native-type registration still invokes the arithmetic
registration while DenseMatrix_i8, DenseMatrix_i16, and DenseMatrix_u8 do not
expose matrix multiplication.

In `@tests/test_vector.py`:
- Around line 144-155: Recompute the overflow example so the dot and two_norm
tables use one consistent vector length and input; for six elements of 100, use
the corresponding exact dot product and measured results. Update the explanation
in tests/test_vector.py lines 144-155 and CHANGELOG.md lines 36-52, or
explicitly document separate inputs if the values intentionally differ.

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Configuration used: defaults

Review profile: CHILL

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Run ID: 949b7056-1772-4040-826a-909c813559b2

📥 Commits

Reviewing files that changed from the base of the PR and between d12cb73 and 02de048.

📒 Files selected for processing (5)

• CHANGELOG.md
• mtl5/__init__.py
• python/src/mtl5_module.cpp
• python/src/mtl5_types.hpp
• tests/test_vector.py

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