Add triangular solve function for sparse CSR tensors in XPU by tszulist-hbn · Pull Request #3261 · intel/torch-xpu-ops

tszulist-hbn · 2026-04-02T15:59:36Z

Resolves: #3167

This PR adds the SparseCsrXPU dispatch for triangular_solve by converting the sparse matrix to dense and delegating to the existing dense XPU triangular_solve implementation. This follows the same pattern used by other XPU sparse ops (addmm, baddbmm, etc.).

Changes:

yaml/native/native_functions.yaml — Register SparseCsrXPU: triangular_solve_out_sparse_csr_xpu dispatch for both triangular_solve.X (structured out variant) and triangular_solve (structured delegate).
src/ATen/native/sparse/xpu/SparseCsrTensorMath.cpp — Implement triangular_solve_out_sparse_csr_xpu() which handles the zero-nnz edge case (fills X with NaN, matching CUDA behavior) and otherwise converts sparse A to dense before calling at::triangular_solve.

Tests verified:

test_block_triangular_solve — 64/64 variants pass (block_size 2/3, int32/int64, contiguous/noncontiguous, float32/float64/complex64/complex128)
test_sparse_triangular_solve_xpu — 4/4 variants pass (float32/float64/complex64/complex128)

Created test_triangular_solve_sparse.py with test cases covering:

Upper/lower triangular sparse CSR matrices
Multiple right-hand sides (multi-column B)
Transpose mode
Unit-triangular mode
float32 precision (with relaxed tolerances)
Empty RHS (exercises the numel() == 0 early-exit path that fills with NaN)

Each test constructs a non-singular triangular matrix in CSR format, solves on XPU, and compares against the dense CPU result. The style follows the existing test_linalg.py pattern in the same directory.

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Pull request overview

Adds SparseCsrXPU support for triangular_solve by wiring a SparseCsrXPU dispatch and implementing an XPU sparse CSR fallback that densifies A and calls the existing dense XPU solve.

Changes:

Register SparseCsrXPU dispatch for triangular_solve.X (and delegate triangular_solve to it).
Implement triangular_solve_out_sparse_csr_xpu in the XPU sparse CSR math file using A.to_dense() + at::triangular_solve.
Add an _nnz()==0 fast-path intended to match CUDA behavior (fills X with NaNs).

Reviewed changes

Copilot reviewed 2 out of 2 changed files in this pull request and generated 4 comments.

File	Description
yaml/native/native_functions.yaml	Adds SparseCsrXPU dispatch registration for `triangular_solve.X` and structured delegate entry for `triangular_solve`.
src/ATen/native/sparse/xpu/SparseCsrTensorMath.cpp	Implements SparseCsrXPU out-kernel that densifies `A` and delegates to dense `at::triangular_solve`, with an `_nnz()==0` special-case.

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guangyey

Overall LGTM. Could you please add a test case? Maybe test/regressions is a good place.
Defer to @CuiYifeng

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CuiYifeng

LGTM, but I noticed that test_block_triangular_solve_block_size like cases are still failed in CI https://github.com/intel/torch-xpu-ops/actions/runs/24331820702/job/71154120366?pr=3261. Please check, thanks.

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Copilot AI review requested due to automatic review settings April 2, 2026 15:59

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Add triangular solve function for sparse CSR tensors in XPU

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