code: def t(src: SparseTensor) -> SparseTensor:
      csr2csc = src.storage.csr2csc()
  
      row, col, value = src.coo()
  
      if value is not None:
          value = value[csr2csc]
  
      sparse_sizes = src.storage.sparse_sizes()
  
      storage = SparseStorage(
          row=col[csr2csc],
          rowptr=src.storage._colptr,
          col=row[csr2csc],
          value=value,
          sparse_sizes=(sparse_sizes[1], sparse_sizes[0]),
          rowcount=src.storage._colcount,
          colptr=src.storage._rowptr,
          colcount=src.storage._rowcount,
          csr2csc=src.storage._csc2csr,
          csc2csr=csr2csc,
          is_sorted=True,
      )
  
      return src.from_storage(storage)
  
imports: import torch
  from torch_sparse.storage import SparseStorage
  from torch_sparse.tensor import SparseTensor
label_desc: Use image node_id 1 for calling a global function with example usage: t(src) and returns: src