v0.17.0

Highlights

• mx.einsum: PR
• Big speedups in reductions: benchmarks
• 2x faster model loading: PR
• mx.fast.metal_kernel for custom GPU kernels: docs

Core

• Faster program exits
• Laplace sampling
• mx.nan_to_num
• nn.tanh gelu approximation
• Fused GPU quantization ops
• Faster group norm
• bf16 winograd conv
• vmap support for mx.scatter
• mx.pad "edge" padding
• More numerically stable mx.var
• mx.linalg.cholesky_inv/mx.linalg.tri_inv
• mx.isfinite
• Complex mx.sign now mirrors NumPy 2.0 behaviour
• More flexible mx.fast.rope
• Update to nanobind 2.1

Bug Fixes

• gguf zero initialization
• expm1f overflow handling
• bfloat16 hadamard
• large arrays for various ops
• rope fix
• bf16 array creation
• preserve dtype in nn.Dropout
• nn.TransformerEncoder with norm_first=False
• excess copies from contiguity bug