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import sys, onnx
from tinygrad import Tensor, fetch, GlobalCounters
from tinygrad.uop.ops import UOp
from tinygrad.frontend.onnx import OnnxRunner
from tinygrad.engine.grouper import get_kernelize_map
from tinygrad.engine.schedule import create_schedule_with_vars
from tinygrad.engine.realize import run_schedule
# NOLOCALS=1 GPU=1 IMAGE=2 FLOAT16=1 VIZ=1 DEBUG=2 python3 examples/openpilot/compile4.py
OPENPILOT_MODEL = sys.argv[1] if len(sys.argv) > 1 else "https://github.com/commaai/openpilot/raw/v0.9.7/selfdrive/modeld/models/supercombo.onnx"
OUTPUT = sys.argv[2] if len(sys.argv) > 2 else "/tmp/openpilot.pkl"
if __name__ == "__main__":
fn = fetch(OPENPILOT_MODEL)
onnx_file = fetch(OPENPILOT_MODEL)
onnx_model = onnx.load(onnx_file)
run_onnx = OnnxRunner(onnx_model)
inputs = run_onnx.get_empty_input_data("npy")
out: Tensor = next(iter(run_onnx({k:v.to(None) for k,v in inputs.items()}).values())).to('cpu')
root = out.uop
targets = [x.uop for x in inputs.values()]
print(targets)
# TODO: abstract this from gradient?
# compute the target path (top down)
in_target_path: dict[UOp, bool] = {}
for u in root.toposort(): in_target_path[u] = any(x in targets or in_target_path[x] for x in u.src)
independent_set = {}
for u in root.toposort():
if in_target_path[u]:
for s in u.src:
if not in_target_path[s]:
independent_set[s] = None
independent = UOp.sink(*independent_set.keys())
kernelized = get_kernelize_map(independent)
independent = independent.substitute(kernelized)
schedule, var_vals = create_schedule_with_vars(independent)
run_schedule(schedule)
print("**** real ****")
GlobalCounters.reset()
out.uop = root.substitute(kernelized)
out.kernelize()
# realize
out.realize()