class_docstr: Rosenbrock function.
  
  The following optimization problem:
      minimize sum(100.0*(x[1:] - x[:-1]**2.0)**2.0 + (1 - x[:-1])**2.0)
code: def fun(self, x):
      x = np.asarray(x)
      r = np.sum(
          100.0 * (x[1:] - x[:-1] ** 2.0) ** 2.0 + (1 - x[:-1]) ** 2.0,
          axis=0,
      )
      return r
  
file_path: catboost/contrib/python/scipy/py3/scipy/optimize/tests/test_hessian_update_strategy.py
imports: import numpy
  from copy import deepcopy
  from numpy.linalg import norm
  from numpy.testing import TestCase, assert_array_almost_equal, assert_array_equal, assert_array_less
  from scipy.optimize import BFGS, SR1
label_desc: Use image node_id 2 for calling the Rosenbrock obj's underlying member method code with example usage: obj.fun(x) and returns: r