dcgan_w.py 文件源码

def forward(self, prior):
        prior = prior.cuda()
        fc_layer = leaky_relu(self.linear1(prior).view(-1, 512, 4, 4), negative_slope = 0.2)
        deconv_layer1 = self.bn1(leaky_relu(self.deconv1(fc_layer), negative_slope = 0.2))
        deconv_layer2 = self.bn2(leaky_relu(self.deconv2(deconv_layer1), negative_slope = 0.2))
        deconv_layer3 = tanh(self.deconv3(deconv_layer2))
        return deconv_layer3

#    Infer without batch normalization cannot improve image quality
#    def infer(self, prior):
#        prior = prior.cuda()
#        fc_layer = leaky_relu(self.linear1(prior).view(-1, 512, 4, 4), negative_slope = 0.2)
#        deconv_layer1 = leaky_relu(self.deconv1(fc_layer), negative_slope = 0.2)
#        deconv_layer2 = leaky_relu(self.deconv2(deconv_layer1), negative_slope = 0.2)
#        deconv_layer3 = tanh(self.deconv3(deconv_layer2))
#        return deconv_layer3