content: import torch
  import torch.nn as nn
  from . import SparseTensor
  
  __all__ = [
      'SparseLinear'
  ]
  
  
  class SparseLinear(nn.Linear):
      def __init__(self, in_features, out_features, bias=True):
          super(SparseLinear, self).__init__(in_features, out_features, bias)
  
      def forward(self, input: SparseTensor) -> SparseTensor:
          return input.replace(super().forward(input.feats))
  