code: def _weighted_std(a, axis, weights):
      average = np.average(a, axis, weights)
      variance = np.average((a - average) ** 2, axis, weights)
      return np.sqrt(variance)
  
imports: from math import ceil, isnan, isinf, exp, log
  from ...utils._native import Native
  from ._tensor import restore_missing_value_zeros
  import numpy
  import warnings
  from itertools import islice
  import logging
label_desc: Use image node_id 1 for calling a global function with example usage: _weighted_std(a, axis, weights) and returns: np