code: def parse_weights(weights_path, move_rules=None):
      data = np.load(weights_path, encoding="bytes", allow_pickle=True)
  
      if isinstance(data, np.lib.npyio.NpzFile) or isinstance(
          data, dict
      ):
          values = data["values"]
  
          if tf_later_than("1.4"):
              for i, name in enumerate(data["names"]):
                  if "/beta" in str(
                      data["names"][i - 1]
                  ) and "/gamma" in str(name):
                      values[i], values[i - 1] = (
                          values[i - 1],
                          values[i],
                      )
      else:
          values = data
  
      return values
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  import tensorflow
  import warnings
  from contextlib import contextmanager
  from .version_utils import tf_later_than
label_desc: Use image node_id 24 for calling a global function with example usage: parse_weights(weights_path, move_rules) and returns: values