def forward(self, x: torch.Tensor) -> List[torch.Tensor]:
        r"""
        This method processes the input tensor `x` through the FullAdapter model and performs operations including
        pixel unshuffling, convolution, and a stack of AdapterBlocks. It returns a list of feature tensors, each
        capturing information at a different stage of processing within the FullAdapter model. The number of feature
        tensors in the list is determined by the number of downsample blocks specified during initialization.
        """
        x = self.unshuffle(x)
        x = self.conv_in(x)

        features = []

        for block in self.body:
            x = block(x)
            features.append(x)

        return features

        This method processes the input tensor `x` through the FullAdapter model and performs operations including
        pixel unshuffling, convolution, and a stack of AdapterBlocks. It returns a list of feature tensors, each
        capturing information at a different stage of processing within the FullAdapter model. The number of feature
        tensors in the list is determined by the number of downsample blocks specified during initialization.
        
src/diffusers/models/adapter.py