Custom Op Registration

Key Insight

Registering a custom Triton kernel as a custom op allows PyTorch's compiler, torch.compile, to trace and optimize it within a larger neural network model graph. By defining schema, validation rules, and derivative mappings, we bridge the gap between low-level hardware kernels and high-level graph execution. This integration ensures that custom optimizations do not break auto-differentiation or graph capture, making custom acceleration safe for production training and inference.