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car-detection-bayes
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FLOPS report

This commit is contained in:
Glenn Jocher 2020-04-01 14:05:41 -07:00
parent ea80ba65af
commit 4ac60018f6
1 changed files with 8 additions and 5 deletions
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13
utils/torch_utils.py
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@ -87,12 +87,15 @@ def model_info(model, verbose=False):
name = name.replace('module_list.', '') name = name.replace('module_list.', '')
print('%5g %40s %9s %12g %20s %10.3g %10.3g' % print('%5g %40s %9s %12g %20s %10.3g %10.3g' %
(i, name, p.requires_grad, p.numel(), list(p.shape), p.mean(), p.std())) (i, name, p.requires_grad, p.numel(), list(p.shape), p.mean(), p.std()))
print('Model Summary: %g layers, %g parameters, %g gradients' % (len(list(model.parameters())), n_p, n_g))
# FLOPs try: # FLOPS
# from thop import profile from thop import profile
# macs, params = profile(model, inputs=(torch.zeros(1, 3, 640, 640),)) macs, _ = profile(model, inputs=(torch.zeros(1, 3, 640, 640),))
# print('%.3f GFLOPs' % (macs / 1E9 * 2)) fs = ', %.1f GFLOPS' % (macs / 1E9 * 2)
except:
fs = ''
print('Model Summary: %g layers, %g parameters, %g gradients%s' % (len(list(model.parameters())), n_p, n_g, fs))
def load_classifier(name='resnet101', n=2): def load_classifier(name='resnet101', n=2):