Add _vectorize_node dispatchers for sparse ops#2190
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The default Blockwise-based fallback in pytensor/graph/replace.py wraps ops in Blockwise and rebuilds their make_node with dense dummy core inputs, which contradicts the sparse-input contract enforced by as_sparse_variable. As a result, vectorize_graph crashes with "Variable type field must be a SparseTensorType" the moment it encounters any sparse op — pmx-extras pathfinder hits this whenever a PyMC model uses a sparse projection (e.g. a sum-to-zero constraint encoded as pt.dot(flat, as_sparse_variable(csr))). This patch: - Registers an explicit dispatcher for StructuredDot that batches the dense (right) input via a moveaxis+reshape trick while keeping the sparse (left) input unbatched (scipy has no batched-sparse type). Raises NotImplementedError with a clear message if the caller tries to batch the sparse input. - Registers NotImplementedError stubs for the other sparse ops likely to appear in user graphs (TrueDot, AddSS, AddSSData, AddSD, SparseSparseMultiply, SparseDenseMultiply) so callers see a descriptive error instead of the cryptic as_sparse_variable TypeError from the Blockwise fallback.
Add TestVectorizeSparse covering the StructuredDot dispatcher (batched dense input, no-batch no-op, batched-sparse error) and the AddSD / SparseDenseMultiply NotImplementedError stubs. The structured_dot test reproduces the original "Variable type field must be a SparseTensorType" crash without the dispatcher (issue pymc-devs#2189). Drop the NotImplementedError stubs for the all-sparse-input ops (TrueDot, AddSS, AddSSData, SparseSparseMultiply): a sparse input can never become batched, so vectorize_graph never dispatches to them. Keep only the reachable AddSD / SparseDenseMultiply, and reword the error since AddSD's output is dense, not sparse. Move the _vectorize_node import to the top of the module (no circular import) to satisfy ruff E402. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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ricardoV94
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May 29, 2026
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please remove these global comments/separators
ricardoV94
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May 29, 2026
| # That contradicts the sparse-input contract enforced by as_sparse_variable, | ||
| # so every sparse op needs a custom dispatcher (or a clear NotImplementedError). | ||
| @_vectorize_node.register(StructuredDot) | ||
| def _vectorize_structured_dot(op, node, batch_a, batch_b): |
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looks good, just need style cleanup |
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