def output_controller(self, x):
# soft decision
if self.soft_decision:
return self.sigmoid(x)
# stochastic hard decision:
if self.stochastic:
x = self.sigmoid(x)
return ops.ST_StochasticIndicator()(x)
else:
x = self.sigmoid(x)
return ops.ST_Indicator()(x)
def forward(self, x):
# convolution
x = self.conv1(x)
# spatial averaging and fully connected layer
if self.ngf == 1:
x = x.mean(dim=-1).mean(dim=-1).squeeze()
else:
x = F.relu(x)
x = x.mean(dim=-1).mean(dim=-1).squeeze() # global average pooling
x = self.linear1(x).squeeze()
# get probability of "left" or "right"
output = self.sigmoid(x)
if self.soft_decision:
return output
if self.stochastic:
return ops.ST_StochasticIndicator()(output)
else:
return ops.ST_Indicator()(output)
