def forward(self, batch: torch.Tensor) -> torch.Tensor:
        """Encode input images to the salient space.

        Args:
            batch (torch.Tensor): Input batch of images of shape
                ``(batch_size, channels, height, width)``

        Returns:
            torch.Tensor: Feature maps from the bottleneck layer
        """
        act1 = self.block1(batch)
        mp1 = self.mp1(act1)
        act2 = self.block2(mp1)
        mp2 = self.mp3(act2)
        act3 = self.block3(mp2)
        mp3 = self.mp3(act3)
        act4 = self.block4(mp3)
        mp4 = self.mp4(act4)
        return self.block5(mp4)
Encode input images to the salient space.

        Args:
            batch (torch.Tensor): Input batch of images of shape
                ``(batch_size, channels, height, width)``

        Returns:
            torch.Tensor: Feature maps from the bottleneck layer
        
src/anomalib/models/image/draem/torch_model.py