class_docstr: Tests for sharing datasets across jobs using a cross-trainer cache.
code: def testDisableCrossTrainerCacheByDefault(self):
      cluster = self._create_cluster(num_workers=1)
      dataset = dataset_ops.Dataset.range(10000000).repeat()
      dataset1 = self.make_distributed_dataset(
          dataset, cluster, job_name="job"
      )
      self.assertDatasetProduces(dataset1.take(10), list(range(10)))
  
      # The two clients use the same job. The second client can't read the data
      # already read by the first client.
      dataset2 = self.make_distributed_dataset(
          dataset, cluster, job_name="job"
      )
      output = self.getDatasetOutput(dataset2.take(10))
      self.assertGreaterEqual(output[0], 10)
  
imports: import multiprocessing
  from absl.testing import parameterized
  from tensorflow.python.data.experimental.kernel_tests.service import test_base
  from tensorflow.python.data.experimental.ops import data_service_ops
  from tensorflow.python.data.kernel_tests import test_base
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.framework import combinations
  from tensorflow.python.framework import errors
  from tensorflow.python.platform import test
label_desc: Use image node_id 3 for calling the CrossTrainerCacheTest obj's underlying member method code with example usage: obj.testDisableCrossTrainerCacheByDefault() without return types