code: def test_normal_distribution_input(self):
      bucket_count = 44
      pb = self.histogram(
          "normal",
          data=self.gaussian.reshape((5, -1)),
          buckets=bucket_count,
      )
      buckets = tensor_util.make_ndarray(pb.value[0].tensor)
      self.assertEqual(buckets[:, 0].min(), self.gaussian.min())
      # Assert near, not equal, since TF's linspace op introduces floating point
      # error in the upper bound of the result.
      self.assertNear(
          buckets[:, 1].max(), self.gaussian.max(), 1.0**-10
      )
      self.assertEqual(buckets[:, 2].sum(), self.gaussian.size)
      np.testing.assert_allclose(buckets[1:, 0], buckets[:-1, 1])
  
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 9 for calling the SummaryBaseTest obj's underlying member method code with example usage: obj.test_normal_distribution_input() without return types