blob: 804eb9a24567a9aafdf93cf69ea2b224a2aa19a5 [file] [log] [blame]
import argparse
import torch
class Module(torch.nn.Module):
def __init__(self):
super(Module, self).__init__()
self.conv = torch.nn.Conv2d(1, 10, 5, 1)
def forward(self, x):
y = self.conv(x)
return y
def run_model(level):
m = Module().eval()
d = torch.rand(1, 1, 112, 112)
with torch.backends.mkldnn.verbose(level):
m(d)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument("--verbose-level", default=0, type=int)
args = parser.parse_args()
try:
run_model(args.verbose_level)
except Exception as e:
print(e)