9def main(nnpackage_path, backends="cpu"):
10
11 session = infer.session(nnpackage_path, backends)
12
13
14 input_infos = session.get_inputs_tensorinfo()
15
16
17 for i in range(10):
18 dummy_inputs = []
19 for info in input_infos:
20
21 dims = list(info.dims)
22
23 dims = [random.randint(1, 10) if d == -1 else d for d in dims]
24
25 shape = tuple(dims[:info.rank])
26
27 dummy_inputs.append(
28 np.random.uniform(low=0.0, high=1.0, size=shape).astype(info.dtype))
29
30 outputs = session.infer(dummy_inputs)
31 print(f"Inference run {i+1}/10 completed.")
32
33 print(f"nnpackage {nnpackage_path.split('/')[-1]} runs successfully.")
34 return
35
36