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Published December 15, 2025 | Version rel-2.36.0
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pymc-devs/pytensor: rel-2.36.0

Description

<!-- Release notes generated using configuration in .github/release.yml at main -->

What's Changed

Major Changes 🛠

  • Support Python 3.14 by @Armavica in https://github.com/pymc-devs/pytensor/pull/1661
  • Numba full backend support and required dependency by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/811
  • Start deprecating shared updates functionality in Scan by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1704
  • Reorganize the sparse module by @jessegrabowski in https://github.com/pymc-devs/pytensor/pull/1674
  • Remove tensor/io.py by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1766
  • Remove InRange scalar Op by @Copilot in https://github.com/pymc-devs/pytensor/pull/1699

New Features 🎉

  • Add more MLX dispatches by @jessegrabowski in https://github.com/pymc-devs/pytensor/pull/1684
  • Add linalg Ops to MLX backend by @cetagostini in https://github.com/pymc-devs/pytensor/pull/1700
  • Reliable caching of Graphs and individual Ops in numba backend by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1637
  • Support TypedList on Numba backend by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1745
  • Implement numba dispatch for ScalarLoop by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1445
  • Implement Convolve2D Op by @jessegrabowski in https://github.com/pymc-devs/pytensor/pull/1397
  • Numba AdvancedIndexing: Complete support for integer advanced indexing by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1778
  • Implement Scan based filter helper by @emekaokoli19 in https://github.com/pymc-devs/pytensor/pull/1717
  • Support Scan with MIT-MOT in JAX backend by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1651

Bugfixes 🐛

  • Ignore axis argument in numba CumOp when input is 1d by @jessegrabowski in https://github.com/pymc-devs/pytensor/pull/1691
  • Fix pytensor_cache clear by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1694
  • Fix 0-sized CGemV with unitialized memory by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1719
  • Handle non-constant NoneTypeT variables by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1728
  • Fix numba cache bugs and suppress noisy warnings by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1731
  • Fix shape error formatting in C impl of Elemwise by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1749
  • Numba Pow: Fix failure with discrete integer exponents by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1758
  • Handle upcasting of scalar to vector arrays by scipy vector optimizers by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1768
  • Validate compatible linker in Scan Python/C backend by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1757
  • Numba and JAX Scan fixes by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1754
  • Handle F-order and arbitrary index ndim in numba UnravelIndex and RavelMultiIndex by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1770
  • Misc numba fixes by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1771
  • Numba Dot: Handle complex inputs by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1776
  • Numba RavelMultiIndex: Fix scalars with clip mode by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1775
  • Fix Elemwise inside OpFromGraph in numba mode by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1774
  • Avoid runtime broadcast error due to dot_to_mul rewrite by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1783
  • Optimize: Handle gradient wrt scalar inputs and guard against unsupported types by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1784
  • Numba CAReduce: respect acc_dtype by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1773
  • Fix wrap_jax when there is a mix of statically known and unknown shapes by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1722

Documentation 📖

  • Fix latex formatting in VJP autodiff example by @williambdean in https://github.com/pymc-devs/pytensor/pull/1726

Maintenance 🔧

  • Rename sparse functions to match numpy array API by @jessegrabowski in https://github.com/pymc-devs/pytensor/pull/1663
  • Remove scalar_ prefix from several Ops by @Copilot in https://github.com/pymc-devs/pytensor/pull/1683
  • Add __rtruediv__ and __rfloordiv__ to Scalar variables by @Copilot in https://github.com/pymc-devs/pytensor/pull/1701
  • Fix Blockwise vmap dispatch for no batch dimensions by @cetagostini in https://github.com/pymc-devs/pytensor/pull/1705
  • JITLinker improvements by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1746
  • Numba fallback to object mode in more cases by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1747
  • Remove transfer_type and default inplace Elemwise Ops by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1752
  • Speedup RNG copy in non-mutable RVs by @emekaokoli19 in https://github.com/pymc-devs/pytensor/pull/1721
  • Sort and Argsort: Check axis are integers by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1769
  • Numba do not cache inplace list ops by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1767
  • Handle mixed input dtypes and empty size in numba lapack functions by @ricardoV94 in https://github.com/pymc-devs/pytensor/pull/1764
  • Rewrite concatenate([x, x]) as tile by @tchan102 in https://github.com/pymc-devs/pytensor/pull/1714

New Contributors

  • @cetagostini made their first contribution in https://github.com/pymc-devs/pytensor/pull/1700
  • @tchan102 made their first contribution in https://github.com/pymc-devs/pytensor/pull/1714
  • @emekaokoli19 made their first contribution in https://github.com/pymc-devs/pytensor/pull/1717
  • @Mr-Imperium made their first contribution in https://github.com/pymc-devs/pytensor/pull/1748

Full Changelog: https://github.com/pymc-devs/pytensor/compare/rel-2.35.1...rel-2.36.0

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