code: def build(self):
      self.w = variables.Variable(
          initial_value=random_ops.random_uniform((10, 10)),
          dtype=dtypes.float32,
      )
      self.iterations = variables.Variable(
          initial_value=0, dtype=dtypes.int32
      )
      # Allow external control to make the model run its train_fn in an infinite
      # loop. This allows us to reliably test worker preemption in the middle of
      # function execution.
      self.do_infinite_step = variables.Variable(False)
  
      self.rebuild_iterators()
  
imports: import gc
  import os
  import sys
  import threading
  import time
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.distribute import multi_worker_test_base
  from tensorflow.python.distribute import parameter_server_strategy_v2
  from tensorflow.python.distribute import test_util
  from tensorflow.python.distribute.cluster_resolver.cluster_resolver import SimpleClusterResolver
  from tensorflow.python.distribute.coordinator import cluster_coordinator
  from tensorflow.python.eager import context
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import random_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.platform import tf_logging
  from tensorflow.python.training import coordinator
  from tensorflow.python.training import server_lib
label_desc: Use image node_id 2 for calling the Model obj's underlying member method code with example usage: obj.build() without return types