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manual seed , reuse memory buffers across runs

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discountchubbs
2026-08-10 14:06:39 -07:00
parent 8fa6067c9a
commit f5d5a8a329
1 changed files with 6 additions and 3 deletions
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openpilot/sunnypilot/modeld_v2/compile_modeld.py
+6 -3
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@@ -213,9 +213,11 @@ def compile_and_warmup(nv12: NV12Frame, model_size: tuple[int, int], prepare_onl
is_supercombo = vision_runner is None
run_func = create_jit_runner(vision_runner, policy_runners, nv12, model_size, features_slice, frame_skip, all_shapes, prepare_only)
run_jit = TinyJit(run_func, prune=True)
def run_once(seed):
queues, npy = generate_queues_and_npy(all_shapes, frame_skip, Device.DEFAULT, is_supercombo=is_supercombo)
def run_once(seed, queues=None, npy=None):
if queues is None or npy is None:
queues, npy = generate_queues_and_npy(all_shapes, frame_skip, Device.DEFAULT, is_supercombo=is_supercombo)
rng = np.random.default_rng(seed)
Tensor.manual_seed(seed)
frame = Tensor.randint(nv12.size, low=0, high=256, dtype=dtypes.uint8, device=WARP_DEV).realize()
big_frame = Tensor.randint(nv12.size, low=0, high=256, dtype=dtypes.uint8, device=WARP_DEV).realize()
for value in npy.values():
@@ -225,8 +227,9 @@ def compile_and_warmup(nv12: NV12Frame, model_size: tuple[int, int], prepare_onl
Device.default.synchronize()
return [np.copy(value.numpy()) for value in (outs if isinstance(outs, tuple) else [outs])] if outs is not None else []
warmup_queues, warmup_npy = generate_queues_and_npy(all_shapes, frame_skip, Device.DEFAULT, is_supercombo=is_supercombo)
for i in range(3):
run_once(42 + i)
run_once(42 + i, warmup_queues, warmup_npy)
if not prepare_only:
baseline = run_once(42)