class_docstr: Benchmark the optimizers with smooth, unbounded, functions
class_docstr_tok: ["Benchmark","the","optimizers","with","smooth",",","unbounded",",","functions"]
code: def run_asymmetric_quadratic(self, methods=None):
      s = funcs.AsymmetricQuadratic()
      #    print "checking gradient",
      #    scipy.optimize.check_grad(s.fun, s.der, np.array([1.1, -2.3]))
      b = _BenchOptimizers(
          "function sum(x**2) + x[0]", fun=s.fun, der=s.der, hess=s.hess
      )
      for i in range(10):
          b.bench_run(np.random.uniform(-2, 2, 3), methods=methods)
      return b
  
imports: import os
  import time
  import inspect
  import json
  import traceback
  from collections import defaultdict
  import numpy
  from .None import test_functions
  from .None import go_benchmark_functions
  from .common import Benchmark, is_xslow, safe_import
  from .lsq_problems import extract_lsq_problems
label_desc: Use image node_id 8 for calling the BenchSmoothUnbounded obj's underlying member method code with example usage: obj.run_asymmetric_quadratic(methods) and returns: b