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Add cho_factor and cho_solve to dpnp.scipy.linalg - #3116
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antonwolfy wants to merge 7 commits into
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antonwolfy wants to merge 7 commits into
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Implement SciPy-compatible `dpnp.scipy.linalg.cho_factor` and `dpnp.scipy.linalg.cho_solve` with batched input support (gh-3096). - `cho_factor` uses the existing `potrf` / `potrf_batch` bindings. Only the referenced triangle is copied into a zeroed C-order buffer, which matches the SciPy 1.18 output in a single pass. The input is factorized in place for `overwrite_a=True` when it is 2-D, writable, of the result dtype, and C- or F-contiguous. - `cho_solve` uses a new LAPACK `potrs` binding for 2-D input and a new BLAS `trsm_batch` binding (two triangular solves) for batched input, since oneMKL `potrs_batch` is much slower. Batch dimensions are broadcast as in `lu_solve`. - Add tests and API reference entries.
A C-order factor is passed to oneMKL transposed, so the solves are with conj(A), and `b` and the solution are conjugated to compensate. This is only needed for a complex factor. Decide it from the dtype of `c` rather than the result dtype, so a real factor with a complex right-hand side no longer conjugates `b` and the solution. Add a test for a real factor with complex right-hand sides.
Add `tests/cupyx_tests/linalg_tests/test_solve.py` from CuPy as `dpnp/tests/third_party/cupyx/linalg_tests/test_solve.py`, with `TestChosolve` adapted to `dpnp.scipy.linalg.cho_solve`: - pass `check_finite=False`, since dpnp checks the whole factor for infs and NaNs, as SciPy does, and the tests put NaNs in the unused triangle; - pass a batch of vectors with a trailing axis, since dpnp follows SciPy's `(..., n, k)` rule for a batched right-hand side. The `invh` tests are skipped, as `invh` is not supported.
Contributor
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View rendered docs @ https://intelpython.github.io/dpnp/pull/3116/index.html |
Contributor
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Array API standard conformance tests for dpnp=0.21.0dev15=np2py314h8d9cdd5_15 ran successfully. |
Collaborator
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coverage: 82.5% (-0.1%) from 82.615% — cho-factor-cho-solve into master |
- Add See Also link from dpnp.linalg.cholesky to dpnp.scipy.linalg.cho_factor - Fix the upper-triangular example output in dpnp.linalg.cholesky - Remove stale linalg.lu_factor and linalg.lu_solve entries from linalg.rst - Look up the order manager in _copy_rhs and _cho_solve_trsm instead of passing it
- Do not broadcast a 2-D factor `c` over a batched right-hand side: fold the batch into the RHS columns for one `potrs` call, or, for a real type on GPU with a small batch (batch * nrhs > 16, batch <= 32), where oneMKL potrs slows down above 16 columns, share the factor by all batch elements in `trsm_batch` - Let `_trsm_batch` take a 2-D triangular matrix shared by the batch (stride 0) - Submit both `check_finite` reductions before waiting for the first result - Accept the batch-shaped `lower` array returned by SciPy >= 1.18 in `cho_solve`, if all its values are equal
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Implement SciPy-compatible
dpnp.scipy.linalg.cho_factoranddpnp.scipy.linalg.cho_solvewith batched input support (#3096).