parameters: (t)
return_statement: return csr_matrix((arrs[2], arrs[1], arrs[0]), shape=t.shape)
docstring: Converts a taco tensor to a scipy csr_matrix.
  
      Takes a matrix from taco in any format and converts the matrix to a scipy sparse csr matrix. This method removes
      explicit zeros from the original taco tensor during the conversion.
  
      Parameters
      -----------
      t: tensor
          A taco tensor to convert to a scipy.csr_matrix array. The tensor must be of order 2 (i.e it must be a matrix).
          If the order of the tensor is not equal to 2, a value error is thrown.
  
  
      Notes
      -------
      The data and index values are always copied when making the scipy sparse array
  
  
      Returns
      ---------
      matrix: scipy.sparse.csr_matrix
          A matrix containing a copy of the data from the original order 2 tensor t.
function: def to_sp_csr(t):
      """
  
      Converts a taco tensor to a scipy csr_matrix.
  
      Takes a matrix from taco in any format and converts the matrix to a scipy sparse csr matrix. This method removes
      explicit zeros from the original taco tensor during the conversion.
  
      Parameters
      -----------
      t: tensor
          A taco tensor to convert to a scipy.csr_matrix array. The tensor must be of order 2 (i.e it must be a matrix).
          If the order of the tensor is not equal to 2, a value error is thrown.
  
  
      Notes
      -------
      The data and index values are always copied when making the scipy sparse array
  
  
      Returns
      ---------
      matrix: scipy.sparse.csr_matrix
          A matrix containing a copy of the data from the original order 2 tensor t.
  
      """
      arrs = _cm.to_sp_matrix(t._tensor, True)
      return csr_matrix((arrs[2], arrs[1], arrs[0]), shape=t.shape)
function_tokens: def to_sp_csr ( t ) : arrs = _cm . to_sp_matrix ( t . _tensor , True ) return csr_matrix ( ( arrs [ 2 ] , arrs [ 1 ] , arrs [ 0 ] ) , shape = t . shape )