class Dropout(Module):
def __init__(self, p=0.5):
self.p=p
self.prob_matrix=None
def forward(self,x):
self.prob_matrix=Tensor(x.size())
# build bernoulli matrix according to probability, only activate pass through the matrix
self.prob_matrix=self.prob_matrix.bernoulli_(1.-self.p).div_(1.-self.p)
return x * self.prob_matrix
def backward(self,gradwrtoutput):
# use the same matrix in forward pass
return gradwrtoutput*self.prob_matrix.t()
def param(self):
return []
