def forward(self, x: torch.Tensor, mask=None) -> torch.Tensor:
        r"""The forward method of the `MaskConditionEncoder` class."""
        out = {}
        for l in range(len(self.layers)):
            layer = self.layers[l]
            x = layer(x)
            out[str(tuple(x.shape))] = x
            x = torch.relu(x)
        return out
The forward method of the `MaskConditionEncoder` class.
src/diffusers/models/autoencoders/vae.py