class_docstr: Base class that tests mirrored variable creator.
  
  Currently it assumes all strategy objects have two replicas.
code: def testVariableWithTensorInitialValueInFunction(self, distribution):
      if not context.executing_eagerly():
          self.skipTest("`tf.function` is an eager-only feature")
  
      v = [None]
  
      def model_fn():
          if v[0] is None:
              init_val = array_ops.zeros([])
              v[0] = variables.Variable(init_val)
          distribute_lib.get_replica_context().merge_call(lambda _: _)
          return v[0]
  
      @def_function.function(autograph=False)
      def make_v1():
          return distribution.experimental_local_results(
              distribution.extended.call_for_each_replica(model_fn)
          )
  
      self.assertAllEqual([0, 0], make_v1())
  
imports: from tensorflow.python.checkpoint import checkpoint
  from tensorflow.python.distribute import collective_all_reduce_strategy
  from tensorflow.python.distribute import combinations
  from tensorflow.python.distribute import distribute_lib
  from tensorflow.python.distribute import distribute_utils
  from tensorflow.python.distribute import strategy_combinations
  from tensorflow.python.distribute import values
  from tensorflow.python.eager import backprop
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.eager import test
  from tensorflow.python.framework import config
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import func_graph
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import rnn
  from tensorflow.python.ops import rnn_cell_impl
  from tensorflow.python.ops import state_ops
  from tensorflow.python.ops import variable_scope
  from tensorflow.python.ops import variable_v1
  from tensorflow.python.ops import variables
  from tensorflow.python.saved_model import load
  from tensorflow.python.saved_model import save
label_desc: Use image node_id 5 for calling the MirroredVariableCreationTest obj's underlying member method code with example usage: obj.testVariableWithTensorInitialValueInFunction(distribution) and returns: v, distribution