code: def solver(A, config):
      
      # Convert A to acceptable format
      A = make_csr(A)
  
      # Generate smoothed aggregation solver
      try:
          return \
              smoothed_aggregation_solver(A,
                                          B=config['B'],
                                          BH=config['BH'],
                                          smooth=config['smooth'],
                                          strength=config['strength'],
                                          max_levels=config['max_levels'],
                                          max_coarse=config['max_coarse'],
                                          coarse_solver=config['coarse_solver'],
                                          symmetry=config['symmetry'],
                                          aggregate=config['aggregate'],
                                          presmoother=config['presmoother'],
                                          postsmoother=config['postsmoother'],
                                          keep=config['keep'])
      except BaseException:
          raise TypeError('Failed generating smoothed_aggregation_solver')
docs: Generate an SA solver given matrix A and a configuration.
  
      Parameters
      ----------
      A : array, matrix, csr_matrix, bsr_matrix
          Matrix to invert, CSR or BSR format preferred for efficiency
      config : dict
          A dictionary of solver configuration parameters that is used to
          generate a smoothed aggregation solver
  
      Returns
      -------
      ml : smoothed_aggregation_solver
          smoothed aggregation hierarchy
  
      Notes
      -----
      config must contain the following parameter entries for
      smoothed_aggregation_solver: symmetry, smooth, presmoother, postsmoother,
      B, strength, max_levels, max_coarse, coarse_solver, aggregate, keep
  
      Examples
      --------
      >>> from pyamg.gallery import poisson
      >>> from pyamg import solver_configuration,solver
      >>> A = poisson((40,40),format='csr')
      >>> config = solver_configuration(A,verb=False)
      >>> ml = solver(A,config)