src/transformers/models/mobilevit/modeling_mobilevit.py/MobileViTLayer/forward
class MobileViTLayer:    def forward(self, features: torch.Tensor) -> torch.Tensor:
        # reduce spatial dimensions if needed
        if self.downsampling_layer:
            features = self.downsampling_layer(features)

        residual = features

        # local representation
        features = self.conv_kxk(features)
        features = self.conv_1x1(features)

        # convert feature map to patches
        patches, info_dict = self.unfolding(features)

        # learn global representations
        patches = self.transformer(patches)
        patches = self.layernorm(patches)

        # convert patches back to feature maps
        features = self.folding(patches, info_dict)

        features = self.conv_projection(features)
        features = self.fusion(torch.cat((residual, features), dim=1))
        return features