code: def test_kafka_group_io_dataset_resume_primary_cg():
      """Test the functionality of the KafkaGroupIODataset when the
      consumer group is yet to catch up with the newly added messages only
      (Instead of reading from the beginning).
      """
      import tensorflow_io.kafka as kafka_io
  
      # Write new messages to the topic
      for i in range(10, 100):
          message = f"D{i}"
          kafka_io.write_kafka(
              message=message, topic="key-partition-test"
          )
      # Read only the newly sent 90 messages
      dataset = tfio.experimental.streaming.KafkaGroupIODataset(
          topics=["key-partition-test"],
          group_id="cgtestprimary",
          servers="localhost:9092",
          configuration=[
              "session.timeout.ms=7000",
              "max.poll.interval.ms=8000",
          ],
      )
      assert np.all(
          sorted(k.numpy() for (k, _) in dataset)
          == sorted(("D" + str(i)).encode() for i in range(10, 100))
      )
  
imports: import sys
  import time
  import pytest
  import numpy
  import threading
  import tensorflow
  import tensorflow_io
label_desc: Use image node_id 10 for calling a global function with example usage: test_kafka_group_io_dataset_resume_primary_cg() without return types