class_docstr: Barrier optimization problem:
      minimize fun(x) - barrier_parameter*sum(log(s))
      subject to: constr_eq(x)     = 0
                constr_ineq(x) + s = 0
code: def _compute_gradient(self, g):
      return np.hstack(
          (g, -self.barrier_parameter * np.ones(self.n_ineq))
      )
  
imports: import scipy.sparse
  import numpy
  from .equality_constrained_sqp import equality_constrained_sqp
  from scipy.sparse.linalg import LinearOperator
label_desc: Use image node_id 10 for calling the BarrierSubproblem obj's underlying member method code with example usage: obj._compute_gradient(g) and returns: np