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IQ.Pilot Release Commit @ f2a861c

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IQ.Lvbs CI [bot]
2026-09-02 15:07:09 -05:00
parent b42569dbca
commit e8748fd704
5497 changed files with 316070 additions and 179848 deletions
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17
iqpilot/selfdrive/iqmodeld/models/runners/tinygrad/supercombo_runner.py
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@@ -12,11 +12,11 @@ from typing import Any
import numpy as np
from openpilot.common.params import Params
from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.model_runner import CUSTOM_MODEL_PATH, NumpyDict, ShapeDict, SliceDict
from openpilot.iqpilot.selfdrive.iqmodeld.models.runners.model_runner import ModelRunner
from openpilot.iqpilot.selfdrive.iqmodeld.models.split_model_constants import SplitModelConstants
from openpilot.iqpilot.selfdrive.iqmodeld.parser import PhaseParser
from iqpilot.common.params import Params
from iqpilot.selfdrive.iqmodeld.models.runners.model_runner import CUSTOM_MODEL_PATH, NumpyDict, ShapeDict, SliceDict
from iqpilot.selfdrive.iqmodeld.models.runners.model_runner import ModelRunner
from iqpilot.selfdrive.iqmodeld.models.split_model_constants import SplitModelConstants
from iqpilot.selfdrive.iqmodeld.parser import PhaseParser
def _tinygrad_imports():
@@ -68,8 +68,6 @@ def _is_jit_arg_mismatch(err: BaseException) -> bool:
class TinygradSupercomboRunner(ModelRunner):
"""Runs a single combined supercombo pkl. Bundle ships one `driving_supercombo_*` artifact."""
uses_opencl_warp: bool = False
def __init__(self):
@@ -282,7 +280,6 @@ class TinygradSupercomboRunner(ModelRunner):
zeros_u8 = lambda s: Tensor(np.zeros(s, dtype=np.uint8), device=Device.DEFAULT).contiguous().realize()
zeros_f32 = lambda s: Tensor(np.zeros(s, dtype=np.float32), device=Device.DEFAULT).contiguous().realize()
# packed npy block (single NPY tensor, mutated in place via views): order matches run_policy.split
shapes = {'desire': (dp[2],), 'traffic_convention': tuple(tc), 'action_t': tuple(at), 'prev_feat': (fb[0], fb[2])}
sizes = [math.prod(s) for s in shapes.values()]
packed = np.zeros(sum(sizes), dtype=np.float32)
@@ -318,7 +315,6 @@ class TinygradSupercomboRunner(ModelRunner):
self._npy['traffic_convention'][:] = numpy_inputs['traffic_convention']
if 'action_t' in numpy_inputs:
self._npy['action_t'][:] = numpy_inputs['action_t']
# self._npy['prev_feat'] holds last frame's hidden_state (zeros on the first frame)
frame = self._frame_tensor('img', bufs['img'])
big_frame = self._frame_tensor('big_img', bufs['big_img'])
@@ -334,11 +330,10 @@ class TinygradSupercomboRunner(ModelRunner):
raise
flat = out.numpy().flatten()
# feed hidden_state back as prev_feat for the next frame
self._npy['prev_feat'][:] = flat[self._hidden_slice].reshape(self._npy['prev_feat'].shape)
sliced = {k: flat[np.newaxis, sl] for k, sl in self._slices.items()}
return self._parser.parse_vision_outputs(sliced) # single-pass; parse_outputs double-parses a combined dict
return self._parser.parse_vision_outputs(sliced)
def _run_model(self) -> NumpyDict:
raise RuntimeError("supercombo path goes through run_fused(), not _run_model()")