code: def test_with_large_counts(self):
      # Check for accumulating floating point errors with large counts (> 2^24).
      # See https://github.com/tensorflow/tensorflow/issues/51419 for details.
      if os.environ.get("TEST_SIZE", "small") != "large":
          self.skipTest("Not enough RAM to run this test.")
      large_count = 20_000_000
      data = [0] + [1] * large_count
      pb = self.histogram("large_count", data=data, buckets=2)
      buckets = tensor_util.make_ndarray(pb.value[0].tensor)
      self.assertEqual(buckets[0][2], 1)
      self.assertEqual(buckets[1][2], large_count)
  
imports: import glob
  import os
  import numpy
  import tensorflow
  from tensorboard.compat import tf2
  from tensorboard.compat.proto import summary_pb2
  from tensorboard.plugins.histogram import metadata
  from tensorboard.plugins.histogram import summary
  from tensorboard.util import tensor_util
label_desc: Use image node_id 12 for calling the SummaryBaseTest obj's underlying member method code with example usage: obj.test_with_large_counts() without return types