makepad/libs/ai/hub/examples/pixal_naf_check.rs
Admin 60615db4ed libs: ai hub/models/cuda, speech, chat_ui
Squash of 54 work commits (Sep 1–12):
  6251f7c  ai-hub: body domain — live pose packets ride the realtime session
  ea50c77  chat_ui: the feed's session gets its profile brief back
  f51b5f3  ai-body: the crate for the native SAM 3D Body port, with its weights reader
  8211ae6  ai-body: the MHR rig and the pose head's parameter decoding, oracle-exact
  9e343a8  ai-body: the DINOv3 ViT-H+/16 backbone, crop and ray conditioning; Metal gains rope-half and affine layer norm
  69d842c  ai-body: the promptable pose decoder and its refinement loop, oracle-matched on Metal
  66e5e2f  ai-hub: SAM 3D Body runs natively — `sam3dbody` on the body domain, oracle-matched end to end
  a634198  ai-hub: the body-native commit carried a peer's in-flight hub hunks; put them back where they were
  9ff44e8  ai-hub: the body-native wiring, this time only the lane's hunks
  6a1c16b  ai-body: third-party notices — what the port is implemented after, and what it is not
  d78411a  ai-body: the per-step work moves to the GPU
  b22259b  ai-body: the context stays on the GPU; only the pose token leaves the loop
  346f31f  ai-body: flash attention for the head-dim-64 blocks
  45b5b98  ai-body: the crop size is a runtime knob, and the loop reports where its time goes
  4be6d19  ai-body: the test modules import the grid constants they still use
  7598346  ai-body: tensor-core GEMMs for the backbone, and the rig's correctives only where they count
  a9ce596  ai-body: the crop warp runs across cores
  8964ba6  ai-body: an FP8 backbone mode, off by default, measured against the oracle
  a2aaa8f  ai-body: the FP8 bias rides a column-broadcast add on the device
  d53c77d  metal: a device-resident ViT stack, and the body backbone rides it
  d006d0a  metal: resident f32 linears keep their weight on the device
  525ba1c  metal: a device-resident two-way decoder layer, and the body decoder rides it
  c9e6d88  ai-body: the hands pass — hand crops, the hand decoder, the hand-mode rig and the wrist fusion
  62dff26  ai-body: the mask prompt — a person's segmentation mask conditions the body pass
  a648cf8  ai-hub: body session options — hands, detect, persons=N
  8c568df  ai-hub: drop the SAM 3D Body reference worker backend
  7ff875a  ai-hub: keep a peer's in-flight beats/notes/local work out of the body commits
  31e5faa  ai-hub: local model runner, licence acknowledgements, a shared install panel; Beat This!, Basic Pitch and the Salamander drum-kit entries
  b94bc58  ai-services: the wire, the app port and the panel state — one conversation, many apps
  2acb798  ai-services: wire v2 — endpoints, receiver-side caps, result disposition
  8ae0ffb  ai-services: the engine core — registry, router and conversation, tested against a scripted model
  2308736  ai-services: the real models behind the engine feature — local through the hub, Claude, and none
  c3f631d  livepipe: one reusable pipe from a camera to a fleet node and back
  ff62db3  ai libs: the runtime env-var cleanup — precision is a per-caller policy, not an environment side channel
  04a94ef  realtime: one service-log line when a live session opens and one when it closes
  0ecb81c  ai models: the model-crates env-var cleanup — 172 research knobs gone, the unset default is the code
  4ca36c1  ai hub + services: the assistant's model comes from wherever it is resident — the fleet chat box, with tools, then the local weights
  432121e  aichat engine + wm: launch, then use — the assistant continues in the same turn once the app it started is on the bus
  7a5bf69  ai-hub registry: the Salamander drumkit samples come from the makepad.nl mirror — the GitHub repo only carries the .sfz files
  102ffc5  ai-services: messages on the bus — a manifest declares topics, the engine subscribes on a tool's behalf or by ToolResult.subscribe, a service publishes Message frames, an idle conversation wakes on a message as an event turn under rate laws; the WM bus forwards the new frames; every app that matches the wire gets its arm
  a837792  hub + flow: a whitespace-only chat completion is retried once and then fails instead of passing as an answer; a flow's model is a fleet model id unless it names a weight file on disk; chat models show under the text domain in /v1/models
  bc6c620  hub + flow: what the chat review found — the in-process route retries an empty completion too, a node says whether its prefill opened thinking so a brief-mode answer is never discarded, a preferred model falls back to normal election when no node has it, discovery keeps looking for the preferred model until patience runs out
  75c3441  hub: the PRO 6000 serves image as well as chat and text
  ad5e98b  hub registry: flux2-dev's VRAM estimate is its measured peak, 30 GB
  c7241e0  hub: a node that evicted every resident releases its cached allocator pool before refusing a load or publishing usable VRAM
  30575f0  flow: route generation by request workload
  1be1e21  ai-hub: gate downloads by disk capacity and recover fleet admission
  df6b394  filesystem_watcher, bounded_http, ai services: live and tool prerequisites
  79ebdb9  ai-hub: add a native Pixal3D image-to-3D backend
  0ba0d74  ai-hub: propagate typed refusals under reject queue policy
  cc6c872  Speed up H3 conditioning and video decoding
  e512059  Fix Qwen vision residency and generated material colors
  2864f68  ai-hub http client: bound every plain TCP connect to 3 s per address
  3d93229  ai: CUDA is a Linux/Windows-only dependency; the hub library defaults to llm + stt

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
2026-09-15 13:40:31 +02:00

56 lines
2 KiB
Rust

//! Offline native encoder + sparse NAF oracle fixture. See trellis/tests.
#[cfg(feature = "mesh")]
fn main() -> Result<(), Box<dyn std::error::Error>> {
use makepad_ai_trellis::{
backend::{gpu_download, gpu_upload},
pixal_naf::PixalNaf,
trellis::TrellisWeights,
trellis_image::T2Image,
};
let args: Vec<_> = std::env::args().collect();
if args.len() != 3 {
return Err("usage: pixal_naf_check DINO_NAF.safetensors OUTPUT.f32".into());
}
let weights = TrellisWeights::load(&args[1])?;
let naf = PixalNaf::prepare(&weights)?;
let image = T2Image {
width: 32,
height: 32,
channels: 3,
data: (0..3 * 32 * 32)
.map(|i| ((i * 13) % 257) as f32 / 256.0)
.collect(),
};
let values: Vec<f32> = (0..4 * 4 * 1024)
.map(|i| ((i * 17) % 101) as f32 / 50.0 - 1.0)
.collect();
let values = gpu_upload(&values, 16, 1024)?;
let mut uv = vec![[0.0, 0.0], [1.0, 1.0], [0.5, 0.5], [-1.0, 2.0]];
uv.extend((0..29).map(|i| [i as f32 / 28.0, ((i * 7) % 29) as f32 / 28.0]));
let encoded = naf.encode(&image)?;
let mut bytes = Vec::new();
for target in [16, 32] {
let guide = naf.guide_from_features(&encoded, target, 4)?;
let output = gpu_download(&guide.sample(&values, &uv)?)?;
let direct = gpu_download(&naf.guide(&image, target, 4)?.sample(&values, &uv)?)?;
let error = output
.iter()
.zip(&direct)
.map(|(a, b)| (a - b).abs())
.fold(0.0_f32, f32::max);
if error > 1e-6 {
return Err(format!("cached guide disagrees: {error}").into());
}
eprintln!("guide {target}: cached/direct max error {error}");
for value in output {
bytes.extend_from_slice(&value.to_le_bytes());
}
}
std::fs::write(&args[2], bytes)?;
Ok(())
}
#[cfg(not(feature = "mesh"))]
fn main() {
eprintln!("build with --features mesh");
std::process::exit(1);
}