code: def scale_for_robust_loss_function(J, f, rho):
      """Scale Jacobian and residuals for a robust loss function.
  
      Arrays are modified in place.
      """
      J_scale = rho[1] + 2 * rho[2] * f**2
      J_scale[J_scale < EPS] = EPS
      J_scale **= 0.5
  
      f *= rho[1] / J_scale
  
      return left_multiply(J, J_scale, copy=False), f
  
imports: from __future__ import division, print_function, absolute_import
  from math import copysign
  import numpy
  from numpy.linalg import norm
  from scipy.linalg import cho_factor, cho_solve, LinAlgError
  from scipy.sparse import issparse
  from scipy.sparse.linalg import LinearOperator, aslinearoperator
label_desc: Use image node_id 26 for calling a global function with example usage: scale_for_robust_loss_function(J, f, rho) and returns: left_multiply,  f