class_docstr: Tests for sharing datasets across jobs using a cross-trainer cache.
code: def testConcurrentReaders(self):
      # Fetching an element from the dataset will trigger prefetches of more
      # elements, one per CPU core which will be placed in the cache.
      # However if the number of prefetches exceeds the space available in
      # the cache then the sliding window will be moved forward away from
      # the element just read thus negating the use of the cache as other
      # trainers will not get the correct element.
      # Hence the need to calculate the size of the cache based on the
      # number of CPU cores and the element size of 423. The extra 8
      # entries are simply a bit of margin.
      num_cpus = multiprocessing.cpu_count()
      cluster = self._create_cluster(
          num_workers=1,
          cross_trainer_cache_size_bytes=(num_cpus + 8) * 423,
      )
      num_readers = 20
      num_elements = 50
      dataset = dataset_ops.Dataset.range(10000000).repeat()
  
      datasets = []
      iterators = []
      for i in range(num_readers):
          distributed_dataset = self.make_distributed_dataset(
              dataset,
              cluster,
              job_name="job",
              cross_trainer_cache=data_service_ops.CrossTrainerCache(
                  trainer_id=f"Trainer {i}"
              ),
              max_outstanding_requests=1,
          )
          iterator = self.getNext(distributed_dataset)
          datasets.append(distributed_dataset)
          iterators.append(iterator)
  
      for i in range(num_elements):
          # All the readers read the same element in one step.
          for j in range(num_readers):
              self.assertEqual(self.evaluate(iterators[j]()), i)
  
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 4 for calling the CrossTrainerCacheTest obj's underlying member method code with example usage: obj.testConcurrentReaders() without return types