If I run

```
model = models.googlenet(pretrained=False)
params_count = sum(p.numel() for p in model.parameters() if p.requires_grad)
print("GoogLeNet number of trainable parameters: {}".format(params_count))
```

I get

GoogLeNet number of trainable parameters: 13004888

But, from the original paper, the number of parameters should be 6.7977 millions.

What I’m missing? is TorchVision implementing a different version of GoogLeNet respect to the original paper?

Thanks,

Mario