models.py 文件源码

def forward(self, embeddings, return_v_adv=False):
        def act(x):
            return F.leaky_relu(x, negative_slope=0.2, inplace=True)

        B, _ = embeddings.size()

        x = act(self.fc1_bn(self.fc1(embeddings)))
        x = add_white_noise(x, 0.005, self.training)
        x = F.dropout(x, p=0.1, training=self.training)

        x_v = self.fc_v(x)
        x_v_expanded = x_v.expand(B, 9)

        x_adv = self.fc_advantage(x)
        x_adv_mean = x_adv.mean(dim=1)
        x_adv_mean = x_adv_mean.expand(B, 9)
        x_adv = x_adv - x_adv_mean

        x = x_v_expanded + x_adv

        if return_v_adv:
            return x, (x_v, x_adv)
        else:
            return x