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modeld: no runtime compile (#38060)

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This commit is contained in:
Armand du Parc Locmaria
2026-05-18 15:54:18 -07:00
committed by GitHub
parent 46e3c907f6
commit 2920503f94
2 changed files with 6 additions and 6 deletions
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selfdrive/modeld/compile_modeld.py
+4 -4
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@@ -103,10 +103,10 @@ def make_input_queues(vision_input_shapes, policy_input_shapes, frame_skip, devi
'big_tfm': np.zeros((3, 3), dtype=np.float32),
}
input_queues = {
'img_q': Tensor.zeros(img_buf_shape, dtype='uint8', device=device).contiguous().realize(),
'big_img_q': Tensor.zeros(img_buf_shape, dtype='uint8', device=device).contiguous().realize(),
'feat_q': Tensor.zeros(frame_skip * (fb[1] - 1) + 1, fb[0], fb[2], device=device).contiguous().realize(),
'desire_q': Tensor.zeros(frame_skip * dp[1], dp[0], dp[2], device=device).contiguous().realize(),
'img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
'big_img_q': Tensor(np.zeros(img_buf_shape, dtype=np.uint8), device=device).contiguous().realize(),
'feat_q': Tensor(np.zeros((frame_skip * (fb[1] - 1) + 1, fb[0], fb[2]), dtype=np.float32), device=device).contiguous().realize(),
'desire_q': Tensor(np.zeros((frame_skip * dp[1], dp[0], dp[2]), dtype=np.float32), device=device).contiguous().realize(),
**{k: Tensor(v, device='NPY').realize() for k, v in npy.items()},
}
return input_queues, npy
selfdrive/modeld/modeld.py
+2 -2
View File
@@ -95,8 +95,8 @@ class ModelState:
self.warp_enqueue = jits[(cam_w,cam_h)]['warp_enqueue']
self.warp_enqueue(
**self.input_queues,
frame=Tensor.zeros(self.frame_buf_params['img'][3], dtype='uint8', device=self.DEV).contiguous().realize(),
big_frame=Tensor.zeros(self.frame_buf_params['big_img'][3], dtype='uint8', device=self.DEV).contiguous().realize())
frame=Tensor(np.zeros(self.frame_buf_params['img'][3], dtype=np.uint8), device=self.DEV).contiguous().realize(),
big_frame=Tensor(np.zeros(self.frame_buf_params['big_img'][3], dtype=np.uint8), device=self.DEV).contiguous().realize())
def slice_outputs(self, model_outputs: np.ndarray, output_slices: dict[str, slice]) -> dict[str, np.ndarray]:
parsed_model_outputs = {k: model_outputs[np.newaxis, v] for k,v in output_slices.items()}