This is a packed redesign! Let's start with what's cool about it and later cover the mechanics.
1. Extends dot products covering the entire matrix:
- all IEEE 754 floating-point formats (f16, f32, f64)
- real, complex, complex-conjugate dot-products
- Arm NEON & SVE, x86 Haswell, Skylake, Ice Lake, Sapphire Rapids
2. Add support for `complex32` Python type ... that:
- [NumPy doesn't support](https://github.com/numpy/numpy/issues/14753),
- [but CuPy wants](https://github.com/cupy/cupy/pull/4454).
SimSIMD is now the fastest and most popular library for computing half-precision products/similarities for Fourier Series and other complex data 🥳
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What breaks:
- Return types are now 64-bit floats, up from 32.
- Inner products are now defined as `AB`, instead of `1 - AB` for broader applicability.