class_docstr: Help lazily evaluate a matrix exponential.
  
  The idea is to not do more work than we need for high expm precision,
  so we lazily compute matrix powers and store or precompute
  other properties of the matrix.
class_docstr_tok: ["Help","lazily","evaluate","a","matrix","exponential",".","The","idea","is","to","not","do","more","work","than","we","need","for","high","expm","precision",",","so","we","lazily","compute","matrix","powers","and","store","or","precompute","other","properties","of","the","matrix","."]
code: def A10(self):
      if self._A10 is None:
          self._A10 = _smart_matrix_product(
              self.A4, self.A6, structure=self.structure
          )
      return self._A10
  
imports: import numpy
  from scipy.linalg._basic import solve, solve_triangular
  from scipy.sparse._base import issparse
  from scipy.sparse.linalg import spsolve
  from scipy.sparse._sputils import is_pydata_spmatrix, isintlike
  import scipy.sparse
  import scipy.sparse.linalg
  from scipy.sparse.linalg._interface import LinearOperator
  from scipy.sparse._construct import eye
  from ._expm_multiply import _ident_like, _exact_1_norm
label_desc: Use image node_id 6 for calling the _ExpmPadeHelper obj's underlying member method code with example usage: obj.A10() and returns: self