nx_nn.nx
buildroot/runtime/nx_nn.nx
about
nx_nn.nx -- sovereign FIXED-POINT NEURAL INFERENCE substrate, the foundation under the neural-audio moonshot. The
research established that neural audio is phone-CPU-viable BECAUSE it runs INT-quantised (DeepFilterNet RTF 0.04, Lyra
0.57ms/frame on a Pixel 6) -- not float, not GPU. So the sovereign path is integer matmul + bias + activation in a
Q-scale, which is exactly what a learned PLC / RVQ-codebook net needs for its forward pass. This rung is the inference
machinery (a linear layer + ReLU/tanh); the LEARNED weights come from the training pipeline (the next moonshot rung).
Pure integer, no FPU, no syscalls -> phone-friendly + wasm-friendly. license_tier: ORIGINAL
dependencies 0 imports · 1 importers
imports: none
imported by: nx_nn_gate.nx
structs
| none |
consts
| none |
functions
| 10 | func nn_linear(inp: *i64, I: i64, W: *i64, b: *i64, O: i64, Qshift: i64, out: *i64) -> i64 called by 1: main |
| 22 | func nn_relu(x: *i64, n: i64) -> i64 { var i: i64 = 0; while i < n { if x[i] < 0 { x[i] = 0 } i = i + 1 } return 0 } called by 1: main |
| 24 | func nn_clamp(x: *i64, n: i64, one: i64) -> i64 |