code: def prepare_bounds(bounds, n):
      lb, ub = [np.asarray(b, dtype=float) for b in bounds]
  
      if lb.ndim == 0:
          lb = np.resize(lb, n)
  
      if ub.ndim == 0:
          ub = np.resize(ub, n)
  
      return lb, ub
  
file_path: catboost/contrib/python/scipy/py2/scipy/optimize/_lsq/lsq_linear.py
imports: from __future__ import division, print_function, absolute_import
  import numpy
  from numpy.linalg import norm
  from scipy.sparse import issparse, csr_matrix
  from scipy.sparse.linalg import LinearOperator, lsmr
  from scipy.optimize import OptimizeResult
  from .common import in_bounds, compute_grad
  from .trf_linear import trf_linear
  from .bvls import bvls
label_desc: Use image node_id 1 for calling a global function with example usage: prepare_bounds(bounds, n) and returns: lb,  ub