class AddGNoise(torch.nn.Module):
def __init__(self, mean=0, stddev=1):
super(AddGNoise, self).__init__()
self.mean = mean
self.stddev = stddev
def forward(self, X):
if self.training:
return X + torch.empty(X.shape).normal_(mean=self.mean,std=self.stddev)
return X
We can use self.training in pytorch, how to do this in mxnet?