viable/strict/1776922694: Fix UnaryUfuncInfo ref lambda syntax (#181003)

The PyTorch development team has resolved a subtle but important bug in their core mathematical operations library. The issue was in the `UnaryUfuncInfo` reference implementation for two special mathematical functions: `special.spherical_bessel_j0` and `special.airy_ai`. When SciPy (a scientific computing library) wasn't installed on a system, these operations were incorrectly configured with `ref=lambda x: None` instead of the proper `ref=None` value. This syntax error caused specific CUDA test cases to fail unexpectedly.

The bug was particularly problematic because it only manifested in specific testing scenarios—specifically the `TestUnaryUfuncsCUDA::test_reference_numerics_large*` test suite—when SciPy was unavailable. This made it a conditional failure that could slip through standard testing pipelines. The fix ensures that PyTorch's mathematical operations behave consistently regardless of whether users have SciPy installed, maintaining reliability for GPU-accelerated computations that depend on these special functions.

While this might seem like a minor technical fix, it's actually crucial for maintaining PyTorch's reputation for robust numerical computing. Special functions like spherical Bessel functions and Airy functions are essential in physics simulations, signal processing, and quantum computing applications. Ensuring they work correctly on CUDA (NVIDIA's GPU computing platform) is vital for researchers and engineers who rely on PyTorch for high-performance scientific computing.