def forward(
        self,
        batch: torch.Tensor,
    ) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
        """Convert inputs to salient space through encoder network.

        Args:
            batch (torch.Tensor): Input batch of concatenated original and
                reconstructed images

        Returns:
            tuple: Contains 6 activation tensors from each encoder block
        """
        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)
        act5 = self.block5(mp4)
        mp5 = self.mp5(act5)
        act6 = self.block6(mp5)
        return act1, act2, act3, act4, act5, act6
Convert inputs to salient space through encoder network.

        Args:
            batch (torch.Tensor): Input batch of concatenated original and
                reconstructed images

        Returns:
            tuple: Contains 6 activation tensors from each encoder block
        
src/anomalib/models/image/draem/torch_model.py