code: def testUpdate(self, tau, sort_variables_by_name):
      source_policy = TfPolicyHoldsVariables(
          init_var_value=1.0, var_scope="source"
      )
      target_policy = TfPolicyHoldsVariables(
          init_var_value=0.0, var_scope="target"
      )
  
      self.evaluate(tf.compat.v1.global_variables_initializer())
      for var in self.evaluate(target_policy.variables()):
          self.assertAllEqual(var, np.zeros(var.shape))
  
      update_op = target_policy.update(
          source_policy,
          tau=tau,
          sort_variables_by_name=sort_variables_by_name,
      )
      self.evaluate(update_op)
      for var in self.evaluate(target_policy.variables()):
          self.assertAllEqual(var, np.ones(var.shape) * tau)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from typing import cast
  from absl.testing import parameterized
  import numpy
  import tensorflow
  import tensorflow_probability
  from tf_agents.policies import tf_policy
  from tf_agents.specs import tensor_spec
  from tf_agents.trajectories import policy_step
  from tf_agents.trajectories import time_step
  from tf_agents.utils import common
  from tf_agents.utils import test_utils
label_desc: Use image node_id 1 for calling the TfPolicyTest obj's underlying member method code with example usage: obj.testUpdate(tau, sort_variables_by_name) without return types