(self, x)
return output
r"""
        Feedforwards a batch of real/fake images and produces a batch of GAN logits.

        Args:
            x (Tensor): A batch of images of shape (N, C, H, W).

        Returns:
            Tensor: A batch of GAN logits of shape (N, 1).
r"""
        Feedforwards a batch of real/fake images and produces a batch of GAN logits.
r Feedforwards a batch of real / fake images and produces a batch of GAN logits .
def forward(self, x):
        r"""
        Feedforwards a batch of real/fake images and produces a batch of GAN logits.

        Args:
            x (Tensor): A batch of images of shape (N, C, H, W).

        Returns:
            Tensor: A batch of GAN logits of shape (N, 1).
        """
        h = x
        h = self.block1(h)
        h = self.block2(h)
        h = self.block3(h)
        h = self.block4(h)
        h = self.activation(h)

        # Global average pooling
        h = h.mean(3).mean(2)

        output = self.l5(h)

        return output
def forward ( self , x ) : h = x h = self . block1 ( h ) h = self . block2 ( h ) h = self . block3 ( h ) h = self . block4 ( h ) h = self . activation ( h ) # Global average pooling h = h . mean ( 3 ) . mean ( 2 ) output = self . l5 ( h ) return output