code: def test_value_error_low_with_syncs(self):
      min_error = np.inf
      for _ in range(5):
          train_model = self._model_fn(mode="train")
          eval_model = self._model_fn(mode="eval")
          train_task = value_tasks.ValueTrainTask(
              self._trajectory_batch_stream,
              optimizer=opt.Adam(),
              lr_schedule=lr_schedules.constant(1e-3),
              advantage_estimator=advantages.td_k(
                  gamma=self._task.gamma, margin=1
              ),
              model=train_model,
              target_model=eval_model,
              # Synchronize often throughout training.
              sync_at=(lambda step: step % 10 == 0),
          )
          loop = training.Loop(
              model=train_model,
              eval_model=eval_model,
              tasks=[train_task],
          )
  
          # Assert that before training, the error is high.
          error_before = self._value_error(train_task.value)
          self.assertGreater(error_before, 2.0)
  
          loop.run(n_steps=100)
  
          # Assert that after training, the error is small.
          error_after = self._value_error(train_task.value)
  
          if error_after < 0.8:
              return
  
          min_error = min(min_error, error_after)
  
      self.fail(
          f"Even after 5 trials, min error_after({min_error}) is not < 0.8"
      )
  
file_path: trax/trax/rl/value_tasks_test.py
imports: from absl.testing import absltest
  import numpy
  from trax import layers
  from trax import models
  from trax import optimizers
  from trax.rl import advantages
  from trax.rl import distributions
  from trax.rl import policy_tasks
  from trax.rl import task
  from trax.rl import value_tasks
  from trax.supervised import lr_schedules
  from trax.supervised import training
label_desc: Use image node_id 5 for calling the ValueTasksTest obj's underlying member method code with example usage: obj.test_value_error_low_with_syncs() without return types