code: def variables_load(filename, variables):
      """Assigns values to structure of `tf.Variable`s from `filename`."""
      if not tf.executing_eagerly():
          raise ValueError(
              "Can only load variables while in eager mode."
          )
      with np.load(filename) as data:
          vars_ = tf.nest.flatten(variables)
          if len(vars_) != len(data):
              raise ValueError(
                  'File "{}" has incorrect number of variables '
                  "(saw: {}, expected: {}).".format(
                      filename, len(data), len(vars_)
                  )
              )
          return tf.group(
              [
                  v.assign(x)
                  for v, (_, x) in zip(vars_, list(data.items()))
              ]
          )
  
imports: import collections
  import contextlib
  import functools
  import sys
  import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.internal import tensorshape_util
label_desc: Use image node_id 11 for calling a global function with example usage: variables_load(filename, variables) and returns: tf