compare-pytorch-and-torch-grads.py 文件源码

def printM(mods):
    for m in mods:
        if isinstance(m, legacy.nn.SpatialConvolution):
            print('Conv2d norm: {}'.format(torch.norm(m.output)))
        elif isinstance(m, legacy.nn.Linear):
            pass
        elif isinstance(m, legacy.nn.Concat) or \
             isinstance(m, legacy.nn.Sequential):
            printM(m.modules)

# printM(net_th.modules)