Who contributed to Google on June 28, 2026?

2 developers shipped this update, including mattjj and copybara-service[bot].

What were the notable Google updates?

support checkpoint_name in custom_vjp fwd if custom_vjp3=1, Fix `lax.special.gammainc` and `lax.special.gammaincc` for a = infinity, and Fix `lax.special.igamma` and `lax.special.igammac` for `a = inf` & `x` finite.

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The Wire · Showcase

JAX TIGHTENS GRADIENT CHECKPOINTING, FIXES SCIPY PARITY BUGS

By RepoJournal · Filed 06:02 UTC on June 28, 2026 · About Google

2 people shipped this

mattjj @mattjj 2 cited

copybara-service[bot] @copybara-service[bot] 1 cited

JAX's custom_vjp3 primitive now supports checkpoint_name in forward passes, unlocking memory-efficient gradient computation for complex AD workflows.

The big move is giving custom_vjp3 a remat rule that applies JAX's remat_transform to primal functions [1]. This means you can now checkpoint intermediate values in custom VJP forward passes without breaking the AD chain, which matters for training large models where memory is the bottleneck. Alongside this, JAX made primal_left_tangent_right a hijax primitive so it lowers away in lojax, letting the compiler dead-code-eliminate unused gradients [1].

The team also shipped fixes to scipy.special parity bugs that have been lingering [2] [3]. lax.special.gammainc and lax.special.gammaincc now return 0.0 and 1.0 respectively when a=infinity instead of NaN, matching scipy's behavior. Same fix went into igamma and igammac for a=inf with finite x. These are edge cases but they matter if you're doing numerical computation or porting scipy code to JAX.

Test coverage for remat3 got a refresh to close gaps [4], so expect fewer surprises in production rematerialization rules. Custom AD primitives and scipy compatibility are both stability plays, not headline features, but both are the kind of fixes that prevent silent correctness bugs.

Action items

→ Review custom_vjp forward passes for checkpoint_name opportunities if you're memory-constrained on large models google/jax [plan]
→ Test scipy.special edge cases (gammainc, gammaincc, igamma, igammac) if you rely on infinity bounds google/jax [monitor]

References

[1] support checkpoint_name in custom_vjp fwd if custom_vjp3=1 ↗ google/jax
[2] Fix `lax.special.gammainc` and `lax.special.gammaincc` for a = infinity ↗ google/jax
[3] Fix `lax.special.igamma` and `lax.special.igammac` for `a = inf` & `x` finite. google/jax
[4] [remat3] update tests to finish coverage of remat3 ↗ google/jax

Quick answers

What shipped in Google on June 28, 2026?: JAX's custom_vjp3 primitive now supports checkpoint_name in forward passes, unlocking memory-efficient gradient computation for complex AD workflows. In total, 6 commits and 4 pull requests landed.
Who contributed to Google on June 28, 2026?: 2 developers shipped this update, including mattjj and copybara-service[bot].
What were the notable Google updates?: support checkpoint_name in custom_vjp fwd if custom_vjp3=1, Fix `lax.special.gammainc` and `lax.special.gammaincc` for a = infinity, and Fix `lax.special.igamma` and `lax.special.igammac` for `a = inf` & `x` finite.

JAX SYNCS XLA COMPILER STACK

JAX updated its XLA dependency to pull in the latest compiler improvements and optimizations.

ai 1 shipped 1-min read

Google 2 days ago

JAX OVERHAULS AUTODIFF INTERNALS WITH CUSTOM_VJP3, EXPANDS MESH API

JAX shipped a major redesign of custom differentiation rules that simplifies how you define vector-Jacobian products, while simultaneously opening up mesh operations to the public API.

ai 24 shipped 1-min read

Google 3 days ago

JAX FIXES REMAT3 CONSTANT HANDLING CRASH, GOOGLE CLOUD PYTHON CENTRALIZES REST TRANSCODING

Matthew Johnson patched a critical remat3 regression where closed-over constants were silently dropped, causing immediate crashes in production rematerialization pipelines [ref:1].

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ai 54 shipped 1-min read

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