forked from IQ.Lvbs/IQ.Pilot
120 lines
5.3 KiB
Python
120 lines
5.3 KiB
Python
#!/usr/bin/env python3
|
|
"""
|
|
Copyright © IQ.Lvbs, apart of Project Teal Lvbs, All Rights Reserved, licensed under https://konn3kt.com/tos/
|
|
|
|
Compile the backend-neutral warp-only artifact: NV12 camera frames + 3x3
|
|
transforms -> (2, 6, model_h/2, model_w/2) uint8 warped tensor, on the device
|
|
GPU (QCOM). maciqmodeld runs this locally
|
|
and feed the output to their backend, so the big model's image pipeline is
|
|
bit-identical to comma's fused pkl warp stage.
|
|
|
|
Run ON the device (needs the QCOM backend):
|
|
cd /data/openpilot && DEV=QCOM WARP_DEV=QCOM IMAGE=1 FLOAT16=1 NOLOCALS=1 JIT_BATCH_SIZE=0 \
|
|
python3 iqpilot/selfdrive/iqmodeld/tools/compile_warp.py \
|
|
--camera-resolutions 1928x1208 --output /data/models/emac_warp.pkl
|
|
The artifact is then split per-resolution into Paths.model_root().
|
|
"""
|
|
from __future__ import annotations
|
|
|
|
import argparse
|
|
import hashlib
|
|
import os
|
|
import pickle
|
|
from functools import partial
|
|
|
|
import numpy as np
|
|
|
|
SELFTEST_SEED = 20260817
|
|
|
|
from iqpilot.selfdrive.iqmodeld.temporal_state import DEFAULT_FRAME_SKIP, MODEL_INPUT_SPEC
|
|
from iqpilot.selfdrive.iqmodeld.tools.compile_supercombo import (
|
|
NV12Frame, WARP_INPUTS, compile_jit, make_random_images, make_warp, make_warp_input_queues,
|
|
)
|
|
|
|
MODEL_SIZE = (MODEL_INPUT_SPEC["img"][0][3] * 2, MODEL_INPUT_SPEC["img"][0][2] * 2) # (512, 256)
|
|
|
|
|
|
def _parse_size(s: str) -> tuple[int, int]:
|
|
w, h = s.lower().split("x")
|
|
return int(w), int(h)
|
|
|
|
|
|
def compile_warp(cam_w: int, cam_h: int, out_path: str | None = None,
|
|
frame_skip: int = DEFAULT_FRAME_SKIP) -> str:
|
|
"""Compile the warp-only QCOM JIT for one camera resolution and write the pkl.
|
|
Returns the artifact path. Callable from the workers so a fresh device
|
|
self-provisions the warp instead of erroring — needs the QCOM backend."""
|
|
# the QCOM warp env must be set before tinygrad is imported here
|
|
os.environ.setdefault("DEV", "QCOM")
|
|
os.environ.setdefault("WARP_DEV", "QCOM")
|
|
os.environ.setdefault("IMAGE", "1")
|
|
os.environ.setdefault("FLOAT16", "1")
|
|
os.environ.setdefault("NOLOCALS", "1")
|
|
os.environ.setdefault("JIT_BATCH_SIZE", "0")
|
|
from tinygrad.engine.jit import TinyJit
|
|
from iqpilot.system.camerad.cameras.nv12_info import get_nv12_info
|
|
from iqpilot.system.hardware.hw import Paths
|
|
|
|
model_w, model_h = MODEL_SIZE
|
|
input_shapes = {name: shape for name, (shape, _) in MODEL_INPUT_SPEC.items()}
|
|
nv12 = NV12Frame(cam_w, cam_h, *get_nv12_info(cam_w, cam_h))
|
|
make_random_warp_inputs = partial(make_random_images, keys=["frame", "big_frame"],
|
|
shape=nv12.size, device=os.getenv("WARP_DEV"))
|
|
warp_jit = TinyJit(make_warp(nv12, model_w, model_h, frame_skip), prune=True)
|
|
make_warp_queues = partial(make_warp_input_queues, input_shapes, frame_skip)
|
|
compiled = compile_jit(warp_jit, make_random_warp_inputs, WARP_INPUTS, make_warp_queues)
|
|
|
|
# historical artifact name: already-provisioned devices keep their warp
|
|
out_path = out_path or os.path.join(Paths.model_root(), f"emac_warp_{cam_w}x{cam_h}_tinygrad.pkl")
|
|
os.makedirs(os.path.dirname(out_path), exist_ok=True)
|
|
tmp = out_path + ".part"
|
|
bundle = {(cam_w, cam_h): compiled, "frame_skip": frame_skip, "model_size": MODEL_SIZE}
|
|
bundle["selftest"] = selftest_digest(compiled, cam_w, cam_h, nv12.size)
|
|
with open(tmp, "wb") as f:
|
|
pickle.dump(bundle, f)
|
|
os.replace(tmp, out_path) # atomic: a reader never sees a half-written pkl
|
|
return out_path
|
|
|
|
|
|
def main() -> None:
|
|
p = argparse.ArgumentParser()
|
|
p.add_argument("--camera-resolutions", type=_parse_size, nargs="+", default=[(1928, 1208)])
|
|
p.add_argument("--output", default=None)
|
|
p.add_argument("--frame-skip", type=int, default=DEFAULT_FRAME_SKIP)
|
|
args = p.parse_args()
|
|
for cam_w, cam_h in args.camera_resolutions:
|
|
out = compile_warp(cam_w, cam_h, args.output, frame_skip=args.frame_skip)
|
|
print(f"saved warp JIT to {out} ({os.path.getsize(out) / 1e6:.2f} MB)")
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|
|
|
|
|
|
def selftest_inputs(cam_w: int, cam_h: int, nv12_size: int):
|
|
"""A fixed synthetic frame pair and pair of matrices. Deterministic so the
|
|
digest is reproducible on the device that compiled the artifact."""
|
|
rng = np.random.default_rng(SELFTEST_SEED)
|
|
frame = rng.integers(0, 256, nv12_size, dtype=np.uint8)
|
|
big_frame = rng.integers(0, 256, nv12_size, dtype=np.uint8)
|
|
tfm = np.array([[0.7, 0.02, 300.0], [0.01, 0.7, 240.0], [0.0, 0.0, 1.0]], dtype=np.float32)
|
|
big_tfm = np.array([[0.5, 0.01, 380.0], [0.02, 0.5, 300.0], [0.0, 0.0, 1.0]], dtype=np.float32)
|
|
return frame, big_frame, tfm, big_tfm
|
|
|
|
|
|
def selftest_digest(compiled, cam_w: int, cam_h: int, nv12_size: int) -> str:
|
|
"""Hash the warp's output for a fixed input.
|
|
|
|
A warp artifact pinned to one tinygrad can still unpickle under another and
|
|
then compute silently wrong, which reaches the model as a garbage image and
|
|
looks like a bad model rather than a stale artifact. A version string cannot
|
|
see that; running it can."""
|
|
from tinygrad.tensor import Tensor
|
|
frame, big_frame, tfm, big_tfm = selftest_inputs(cam_w, cam_h, nv12_size)
|
|
dev = os.getenv("WARP_DEV") or "QCOM"
|
|
out = compiled(tfm=Tensor(tfm, device="NPY").realize(),
|
|
big_tfm=Tensor(big_tfm, device="NPY").realize(),
|
|
frame=Tensor(frame, device=dev).realize(),
|
|
big_frame=Tensor(big_frame, device=dev).realize())
|
|
return hashlib.sha256(out.numpy().astype(np.uint8).tobytes()).hexdigest()
|