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ponder-lab / Hybridize-Functions-Refactoring / #2047 / 1
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main: 79%

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Ran 22 Jun 2026 07:21PM UTC
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22 Jun 2026 07:17PM UTC coverage: 80.01%. Remained the same
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Bump Ariadne to 0.51.0; pin the sparse parameter type divergence (#643)

Bump the Ariadne dependency from 0.50.0 to 0.51.0 (`hybridize.target`),
which ships the sparse-tensor type API (`SparseTensorType`, `isSparse()`,
`layout()`, `asSparse()`) that #533 needs.

0.51.0 now types `SparseTensor` parameters as sparse, which surfaces a
divergence the dense-only pins did not show: the nine `testHasLikelyTensor
Parameter*` sparse-fixture audits asserted dense types for both the raw
Ariadne result (Layer 1) and the Hybridize-inferred signature (Layer 2).
Re-pin Layer 1 to the sparse type (`.asSparse()`) while keeping Layer 2
dense, since `inferInputSignature` still drops sparseness to a dense
`TensorSpec`. The Layer 2 expectation flips to sparse when `SparseTensorSpec`
emission lands (#533).

No code references the removed 3-arg `TensorType(dtype, dims, sparse)`
constructor or `sparse` field, so the bump needs no production-code change.

Closes #636.

Co-authored-by: Claude Opus 4.8 <noreply@anthropic.com>

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