benchmark on different inputs
@@ -25,7 +25,8 @@ class TestOnnxModel(unittest.TestCase):
dat = fetch(OPENPILOT_MODEL)
onnx_model = onnx.load(io.BytesIO(dat))
run_onnx = get_run_onnx(onnx_model)
- inputs = {
+ def get_inputs():
+ np_inputs = {
"input_imgs": np.random.randn(*(1, 12, 128, 256)),
"big_input_imgs": np.random.randn(*(1, 12, 128, 256)),
"desire": np.zeros((1, 8)),
@@ -33,9 +34,12 @@ class TestOnnxModel(unittest.TestCase):
"initial_state": np.zeros((1, 512))
#"initial_state": np.zeros((1, 768))
}
- inputs = {k:Tensor(v.astype(np.float32), requires_grad=False) for k,v in inputs.items()}
+ inputs = {k:Tensor(v.astype(np.float32), requires_grad=False) for k,v in np_inputs.items()}
for _,v in inputs.items(): v.realize()
+ return inputs
+
for _ in range(7):
+ inputs = get_inputs()
st = time.monotonic()
tinygrad_out = run_onnx(inputs)['outputs']
mt = time.monotonic()
@@ -47,6 +51,7 @@ class TestOnnxModel(unittest.TestCase):
import cProfile
import pstats
+ inputs = get_inputs()
pr = cProfile.Profile(timer=time.perf_counter_ns, timeunit=1e-6)
pr.enable()
tinygrad_out = run_onnx(inputs)['outputs']
