def forward(self, x: torch.Tensor) -> torch.Tensor:
        """Forward pass.

        Args:
            x (torch.Tensor): Input Tensor.
        Returns:
            torch.Tensor: Output Tensor.
        """
        latents = self.latents.repeat(x.size(0), 1, 1)

        x = self.proj_in(x)

        for block in self.layers:
            residual = latents
            latents = block(x, latents, residual)

        latents = self.proj_out(latents)
        return self.norm_out(latents)
Forward pass.

        Args:
            x (torch.Tensor): Input Tensor.
        Returns:
            torch.Tensor: Output Tensor.
        
src/diffusers/models/embeddings.py