class_docstr: Dimensionality reduction of node features via Singular Value
  Decomposition (SVD) (functional name: :obj:`svd_feature_reduction`).
  
  Args:
      out_channels (int): The dimensionlity of node features after
          reduction.
code: def forward(self, data: Data) -> Data:
      assert data.x is not None
  
      if data.x.size(-1) > self.out_channels:
          U, S, _ = torch.linalg.svd(data.x)
          data.x = torch.mm(
              U[:, : self.out_channels],
              torch.diag(S[: self.out_channels]),
          )
      return data
  
file_path: pytorch_geometric/torch_geometric/transforms/svd_feature_reduction.py
imports: import torch
  from torch_geometric.data import Data
  from torch_geometric.data.datapipes import functional_transform
  from torch_geometric.transforms import BaseTransform
label_desc: Use image node_id 2 for calling the SVDFeatureReduction obj's underlying member method code with example usage: obj.forward(data) and returns: data