class_docstr: Class for sparse matrix.
class_docstr_tok: ["Class","for","sparse","matrix","."]
docstr: Returns the transpose of this sparse matrix.
  
  Returns
  -------
  SparseMatrix
      The transpose of this sparse matrix.
  
  Examples
  --------
  
  >>> indices = torch.tensor([[1, 1, 3], [2, 1, 3]])
  >>> val = torch.tensor([1, 1, 2])
  >>> A = dglsp.spmatrix(indices, val)
  >>> A = A.transpose()
  SparseMatrix(indices=tensor([[2, 1, 3],
                               [1, 1, 3]]),
               values=tensor([1, 1, 2]),
               shape=(4, 4), nnz=3)
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code: def transpose(self):
      """Returns the transpose of this sparse matrix.
  
      Returns
      -------
      SparseMatrix
          The transpose of this sparse matrix.
  
      Examples
      --------
  
      >>> indices = torch.tensor([[1, 1, 3], [2, 1, 3]])
      >>> val = torch.tensor([1, 1, 2])
      >>> A = dglsp.spmatrix(indices, val)
      >>> A = A.transpose()
      SparseMatrix(indices=tensor([[2, 1, 3],
                                   [1, 1, 3]]),
                   values=tensor([1, 1, 2]),
                   shape=(4, 4), nnz=3)
      """
      return SparseMatrix(self.c_sparse_matrix.transpose())
  
imports: from typing import Optional, Tuple
  import torch
label_desc: Use image node_id 17 for calling the SparseMatrix obj's underlying member method code with example usage: obj.transpose() and returns: SparseMatrix