Files
2019-02-06 13:36:48 -05:00

17 lines
389 B
Python

import torch
import torch.nn as nn
class LockedDropout(nn.Module):
def __init__(self):
super().__init__()
def forward(self, x, dropout=0.5):
if not self.training or not dropout:
return x
m = x.data.new(1, x.size(1), x.size(2)).bernoulli_(1 - dropout)
mask = m / (1 - dropout)
mask = mask.expand_as(x)
return mask * x