code: def testSampleFromDatasetsRerandomizeEachIterationEpochs(
      self, rerandomize
  ):
      if rerandomize is not None and not tf_compat.forward_compatible(
          2022, 12, 17
      ):
          self.skipTest(
              "target functionality not available due to forward compatibility"
          )
      dataset1 = dataset_ops.Dataset.range(0, 10)
      dataset2 = dataset_ops.Dataset.range(100, 110)
      sample_dataset = dataset_ops.Dataset.sample_from_datasets(
          [dataset1, dataset2],
          seed=42,
          weights=[0.5, 0.5],
          stop_on_empty_dataset=True,
          rerandomize_each_iteration=rerandomize,
      )
      first_epoch = self.getDatasetOutput(sample_dataset)
      second_epoch = self.getDatasetOutput(sample_dataset)
  
      if rerandomize:
          self.assertNotEqual(first_epoch, second_epoch)
      else:
          self.assertEqual(first_epoch, second_epoch)
  
imports: from absl.testing import parameterized
  import numpy
  from tensorflow.python.compat import compat
  from tensorflow.python.data.kernel_tests import checkpoint_test_base
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.data.ops import options
  from tensorflow.python.eager import def_function
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import errors
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import random_seed
  from tensorflow.python.platform import test
label_desc: Use image node_id 12 for calling the SampleFromDatasetsTest obj's underlying member method code with example usage: obj.testSampleFromDatasetsRerandomizeEachIterationEpochs(rerandomize) without return types